"""
Classes for the efficient drawing of large collections of objects that
share most properties, e.g., a large number of line segments or
polygons.
The classes are not meant to be as flexible as their single element
counterparts (e.g., you may not be able to select all line styles) but
they are meant to be fast for common use cases (e.g., a large set of solid
line segments).
"""
import itertools
import math
from numbers import Number, Real
import warnings
import numpy as np
import matplotlib as mpl
from . import (_api, _path, artist, cbook, cm, colors as mcolors, _docstring,
hatch as mhatch, lines as mlines, path as mpath, transforms)
from ._enums import JoinStyle, CapStyle
# "color" is excluded; it is a compound setter, and its docstring differs
# in LineCollection.
@_api.define_aliases({
"antialiased": ["antialiaseds", "aa"],
"edgecolor": ["edgecolors", "ec"],
"facecolor": ["facecolors", "fc"],
"linestyle": ["linestyles", "dashes", "ls"],
"linewidth": ["linewidths", "lw"],
"offset_transform": ["transOffset"],
})
class Collection(artist.Artist, cm.ScalarMappable):
r"""
Base class for Collections. Must be subclassed to be usable.
A Collection represents a sequence of `.Patch`\es that can be drawn
more efficiently together than individually. For example, when a single
path is being drawn repeatedly at different offsets, the renderer can
typically execute a ``draw_marker()`` call much more efficiently than a
series of repeated calls to ``draw_path()`` with the offsets put in
one-by-one.
Most properties of a collection can be configured per-element. Therefore,
Collections have "plural" versions of many of the properties of a `.Patch`
(e.g. `.Collection.get_paths` instead of `.Patch.get_path`). Exceptions are
the *zorder*, *hatch*, *pickradius*, *capstyle* and *joinstyle* properties,
which can only be set globally for the whole collection.
Besides these exceptions, all properties can be specified as single values
(applying to all elements) or sequences of values. The property of the
``i``\th element of the collection is::
prop[i % len(prop)]
Each Collection can optionally be used as its own `.ScalarMappable` by
passing the *norm* and *cmap* parameters to its constructor. If the
Collection's `.ScalarMappable` matrix ``_A`` has been set (via a call
to `.Collection.set_array`), then at draw time this internal scalar
mappable will be used to set the ``facecolors`` and ``edgecolors``,
ignoring those that were manually passed in.
"""
#: Either a list of 3x3 arrays or an Nx3x3 array (representing N
#: transforms), suitable for the `all_transforms` argument to
#: `~matplotlib.backend_bases.RendererBase.draw_path_collection`;
#: each 3x3 array is used to initialize an
#: `~matplotlib.transforms.Affine2D` object.
#: Each kind of collection defines this based on its arguments.
_transforms = np.empty((0, 3, 3))
# Whether to draw an edge by default. Set on a
# subclass-by-subclass basis.
_edge_default = False
@_docstring.interpd
def __init__(self, *,
edgecolors=None,
facecolors=None,
linewidths=None,
linestyles='solid',
capstyle=None,
joinstyle=None,
antialiaseds=None,
offsets=None,
offset_transform=None,
norm=None, # optional for ScalarMappable
cmap=None, # ditto
pickradius=5.0,
hatch=None,
urls=None,
zorder=1,
**kwargs
):
"""
Parameters
----------
edgecolors : color or list of colors, default: :rc:`patch.edgecolor`
Edge color for each patch making up the collection. The special
value 'face' can be passed to make the edgecolor match the
facecolor.
facecolors : color or list of colors, default: :rc:`patch.facecolor`
Face color for each patch making up the collection.
linewidths : float or list of floats, default: :rc:`patch.linewidth`
Line width for each patch making up the collection.
linestyles : str or tuple or list thereof, 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 lengths
in points. For examples, see
:doc:`/gallery/lines_bars_and_markers/linestyles`.
capstyle : `.CapStyle`-like, default: :rc:`patch.capstyle`
Style to use for capping lines for all paths in the collection.
Allowed values are %(CapStyle)s.
joinstyle : `.JoinStyle`-like, default: :rc:`patch.joinstyle`
Style to use for joining lines for all paths in the collection.
Allowed values are %(JoinStyle)s.
antialiaseds : bool or list of bool, default: :rc:`patch.antialiased`
Whether each patch in the collection should be drawn with
antialiasing.
offsets : (float, float) or list thereof, default: (0, 0)
A vector by which to translate each patch after rendering (default
is no translation). The translation is performed in screen (pixel)
coordinates (i.e. after the Artist's transform is applied).
offset_transform : `~.Transform`, default: `.IdentityTransform`
A single transform which will be applied to each *offsets* vector
before it is used.
cmap, norm
Data normalization and colormapping parameters. See
`.ScalarMappable` for a detailed description.
hatch : str, optional
Hatching pattern to use in filled paths, if any. Valid strings are
['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']. See
:doc:`/gallery/shapes_and_collections/hatch_style_reference` for
the meaning of each hatch type.
pickradius : float, default: 5.0
If ``pickradius <= 0``, then `.Collection.contains` will return
``True`` whenever the test point is inside of one of the polygons
formed by the control points of a Path in the Collection. On the
other hand, if it is greater than 0, then we instead check if the
test point is contained in a stroke of width ``2*pickradius``
following any of the Paths in the Collection.
urls : list of str, default: None
A URL for each patch to link to once drawn. Currently only works
for the SVG backend. See :doc:`/gallery/misc/hyperlinks_sgskip` for
examples.
zorder : float, default: 1
The drawing order, shared by all Patches in the Collection. See
:doc:`/gallery/misc/zorder_demo` for all defaults and examples.
"""
artist.Artist.__init__(self)
cm.ScalarMappable.__init__(self, norm, cmap)
# list of un-scaled dash patterns
# this is needed scaling the dash pattern by linewidth
self._us_linestyles = [(0, None)]
# list of dash patterns
self._linestyles = [(0, None)]
# list of unbroadcast/scaled linewidths
self._us_lw = [0]
self._linewidths = [0]
self._gapcolor = None # Currently only used by LineCollection.
# Flags set by _set_mappable_flags: are colors from mapping an array?
self._face_is_mapped = None
self._edge_is_mapped = None
self._mapped_colors = None # calculated in update_scalarmappable
self._hatch_color = mcolors.to_rgba(mpl.rcParams['hatch.color'])
self.set_facecolor(facecolors)
self.set_edgecolor(edgecolors)
self.set_linewidth(linewidths)
self.set_linestyle(linestyles)
self.set_antialiased(antialiaseds)
self.set_pickradius(pickradius)
self.set_urls(urls)
self.set_hatch(hatch)
self.set_zorder(zorder)
if capstyle:
self.set_capstyle(capstyle)
else:
self._capstyle = None
if joinstyle:
self.set_joinstyle(joinstyle)
else:
self._joinstyle = None
if offsets is not None:
offsets = np.asanyarray(offsets, float)
# Broadcast (2,) -> (1, 2) but nothing else.
if offsets.shape == (2,):
offsets = offsets[None, :]
self._offsets = offsets
self._offset_transform = offset_transform
self._path_effects = None
self._internal_update(kwargs)
self._paths = None
def get_paths(self):
return self._paths
def set_paths(self, paths):
self._paths = paths
self.stale = True
def get_transforms(self):
return self._transforms
def get_offset_transform(self):
"""Return the `.Transform` instance used by this artist offset."""
if self._offset_transform is None:
self._offset_transform = transforms.IdentityTransform()
elif (not isinstance(self._offset_transform, transforms.Transform)
and hasattr(self._offset_transform, '_as_mpl_transform')):
self._offset_transform = \
self._offset_transform._as_mpl_transform(self.axes)
return self._offset_transform
def set_offset_transform(self, offset_transform):
"""
Set the artist offset transform.
Parameters
----------
offset_transform : `.Transform`
"""
self._offset_transform = offset_transform
def get_datalim(self, transData):
# Calculate the data limits and return them as a `.Bbox`.
#
# This operation depends on the transforms for the data in the
# collection and whether the collection has offsets:
#
# 1. offsets = None, transform child of transData: use the paths for
# the automatic limits (i.e. for LineCollection in streamline).
# 2. offsets != None: offset_transform is child of transData:
#
# a. transform is child of transData: use the path + offset for
# limits (i.e for bar).
# b. transform is not a child of transData: just use the offsets
# for the limits (i.e. for scatter)
#
# 3. otherwise return a null Bbox.
transform = self.get_transform()
offset_trf = self.get_offset_transform()
if not (isinstance(offset_trf, transforms.IdentityTransform)
or offset_trf.contains_branch(transData)):
# if the offsets are in some coords other than data,
# then don't use them for autoscaling.
return transforms.Bbox.null()
paths = self.get_paths()
if not len(paths):
# No paths to transform
return transforms.Bbox.null()
if not transform.is_affine:
paths = [transform.transform_path_non_affine(p) for p in paths]
# Don't convert transform to transform.get_affine() here because
# we may have transform.contains_branch(transData) but not
# transforms.get_affine().contains_branch(transData). But later,
# be careful to only apply the affine part that remains.
offsets = self.get_offsets()
if any(transform.contains_branch_seperately(transData)):
# collections that are just in data units (like quiver)
# can properly have the axes limits set by their shape +
# offset. LineCollections that have no offsets can
# also use this algorithm (like streamplot).
if isinstance(offsets, np.ma.MaskedArray):
offsets = offsets.filled(np.nan)
# get_path_collection_extents handles nan but not masked arrays
return mpath.get_path_collection_extents(
transform.get_affine() - transData, paths,
self.get_transforms(),
offset_trf.transform_non_affine(offsets),
offset_trf.get_affine().frozen())
# NOTE: None is the default case where no offsets were passed in
if self._offsets is not None:
# this is for collections that have their paths (shapes)
# in physical, axes-relative, or figure-relative units
# (i.e. like scatter). We can't uniquely set limits based on
# those shapes, so we just set the limits based on their
# location.
offsets = (offset_trf - transData).transform(offsets)
# note A-B means A B^{-1}
offsets = np.ma.masked_invalid(offsets)
if not offsets.mask.all():
bbox = transforms.Bbox.null()
bbox.update_from_data_xy(offsets)
return bbox
return transforms.Bbox.null()
def get_window_extent(self, renderer=None):
# TODO: check to ensure that this does not fail for
# cases other than scatter plot legend
return self.get_datalim(transforms.IdentityTransform())
def _prepare_points(self):
# Helper for drawing and hit testing.
transform = self.get_transform()
offset_trf = self.get_offset_transform()
offsets = self.get_offsets()
paths = self.get_paths()
if self.have_units():
paths = []
for path in self.get_paths():
vertices = path.vertices
xs, ys = vertices[:, 0], vertices[:, 1]
xs = self.convert_xunits(xs)
ys = self.convert_yunits(ys)
paths.append(mpath.Path(np.column_stack([xs, ys]), path.codes))
xs = self.convert_xunits(offsets[:, 0])
ys = self.convert_yunits(offsets[:, 1])
offsets = np.ma.column_stack([xs, ys])
if not transform.is_affine:
paths = [transform.transform_path_non_affine(path)
for path in paths]
transform = transform.get_affine()
if not offset_trf.is_affine:
offsets = offset_trf.transform_non_affine(offsets)
# This might have changed an ndarray into a masked array.
offset_trf = offset_trf.get_affine()
if isinstance(offsets, np.ma.MaskedArray):
offsets = offsets.filled(np.nan)
# Changing from a masked array to nan-filled ndarray
# is probably most efficient at this point.
return transform, offset_trf, offsets, paths
@artist.allow_rasterization
def draw(self, renderer):
if not self.get_visible():
return
renderer.open_group(self.__class__.__name__, self.get_gid())
self.update_scalarmappable()
transform, offset_trf, offsets, paths = self._prepare_points()
gc = renderer.new_gc()
self._set_gc_clip(gc)
gc.set_snap(self.get_snap())
if self._hatch:
gc.set_hatch(self._hatch)
gc.set_hatch_color(self._hatch_color)
if self.get_sketch_params() is not None:
gc.set_sketch_params(*self.get_sketch_params())
if self.get_path_effects():
from matplotlib.patheffects import PathEffectRenderer
renderer = PathEffectRenderer(self.get_path_effects(), renderer)
# If the collection is made up of a single shape/color/stroke,
# it can be rendered once and blitted multiple times, using
# `draw_markers` rather than `draw_path_collection`. This is
# *much* faster for Agg, and results in smaller file sizes in
# PDF/SVG/PS.
trans = self.get_transforms()
facecolors = self.get_facecolor()
edgecolors = self.get_edgecolor()
do_single_path_optimization = False
if (len(paths) == 1 and len(trans) <= 1 and
len(facecolors) == 1 and len(edgecolors) == 1 and
len(self._linewidths) == 1 and
all(ls[1] is None for ls in self._linestyles) and
len(self._antialiaseds) == 1 and len(self._urls) == 1 and
self.get_hatch() is None):
if len(trans):
combined_transform = transforms.Affine2D(trans[0]) + transform
else:
combined_transform = transform
extents = paths[0].get_extents(combined_transform)
if (extents.width < self.figure.bbox.width
and extents.height < self.figure.bbox.height):
do_single_path_optimization = True
if self._joinstyle:
gc.set_joinstyle(self._joinstyle)
if self._capstyle:
gc.set_capstyle(self._capstyle)
if do_single_path_optimization:
gc.set_foreground(tuple(edgecolors[0]))
gc.set_linewidth(self._linewidths[0])
gc.set_dashes(*self._linestyles[0])
gc.set_antialiased(self._antialiaseds[0])
gc.set_url(self._urls[0])
renderer.draw_markers(
gc, paths[0], combined_transform.frozen(),
mpath.Path(offsets), offset_trf, tuple(facecolors[0]))
else:
if self._gapcolor is not None:
# First draw paths within the gaps.
ipaths, ilinestyles = self._get_inverse_paths_linestyles()
renderer.draw_path_collection(
gc, transform.frozen(), ipaths,
self.get_transforms(), offsets, offset_trf,
[mcolors.to_rgba("none")], self._gapcolor,
self._linewidths, ilinestyles,
self._antialiaseds, self._urls,
"screen")
renderer.draw_path_collection(
gc, transform.frozen(), paths,
self.get_transforms(), offsets, offset_trf,
self.get_facecolor(), self.get_edgecolor(),
self._linewidths, self._linestyles,
self._antialiaseds, self._urls,
"screen") # offset_position, kept for backcompat.
gc.restore()
renderer.close_group(self.__class__.__name__)
self.stale = False
def set_pickradius(self, pickradius):
"""
Set the pick radius used for containment tests.
Parameters
----------
pickradius : float
Pick radius, in points.
"""
if not isinstance(pickradius, Real):
raise ValueError(
f"pickradius must be a real-valued number, not {pickradius!r}")
self._pickradius = pickradius
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.
"""
if self._different_canvas(mouseevent) or 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:
self.axes._unstale_viewLim()
transform, offset_trf, offsets, paths = self._prepare_points()
# Tests if the point is contained on one of the polygons formed
# by the control points of each of the paths. A point is considered
# "on" a path if it would lie within a stroke of width 2*pickradius
# following the path. If pickradius <= 0, then we instead simply check
# if the point is *inside* of the path instead.
ind = _path.point_in_path_collection(
mouseevent.x, mouseevent.y, pickradius,
transform.frozen(), paths, self.get_transforms(),
offsets, offset_trf, pickradius <= 0)
return len(ind) > 0, dict(ind=ind)
def set_urls(self, urls):
"""
Parameters
----------
urls : list of str or None
Notes
-----
URLs are currently only implemented by the SVG backend. They are
ignored by all other backends.
"""
self._urls = urls if urls is not None else [None]
self.stale = True
def get_urls(self):
"""
Return a list of URLs, one for each element of the collection.
The list contains *None* for elements without a URL. See
:doc:`/gallery/misc/hyperlinks_sgskip` for an example.
"""
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', '.', '*'}
"""
# Use validate_hatch(list) after deprecation.
mhatch._validate_hatch_pattern(hatch)
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 : (N, 2) or (2,) array-like
"""
offsets = np.asanyarray(offsets)
if offsets.shape == (2,): # Broadcast (2,) -> (1, 2) but nothing else.
offsets = offsets[None, :]
cstack = (np.ma.column_stack if isinstance(offsets, np.ma.MaskedArray)
else np.column_stack)
self._offsets = cstack(
(np.asanyarray(self.convert_xunits(offsets[:, 0]), float),
np.asanyarray(self.convert_yunits(offsets[:, 1]), float)))
self.stale = True
def get_offsets(self):
"""Return the offsets for the collection."""
# Default to zeros in the no-offset (None) case
return np.zeros((1, 2)) if self._offsets is None else self._offsets
def _get_default_linewidth(self):
# This may be overridden in a subclass.
return mpl.rcParams['patch.linewidth'] # validated as float
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 list of floats
"""
if lw is None:
lw = self._get_default_linewidth()
# get the un-scaled/broadcast lw
self._us_lw = np.atleast_1d(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 : str or tuple or list thereof
Valid values for individual linestyles include {'-', '--', '-.',
':', '', (offset, on-off-seq)}. See `.Line2D.set_linestyle` for a
complete description.
"""
try:
dashes = [mlines._get_dash_pattern(ls)]
except ValueError:
try:
dashes = [mlines._get_dash_pattern(x) for x in ls]
except ValueError as err:
emsg = f'Do not know how to convert {ls!r} to dashes'
raise ValueError(emsg) from err
# 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)
@_docstring.interpd
def set_capstyle(self, cs):
"""
Set the `.CapStyle` for the collection (for all its elements).
Parameters
----------
cs : `.CapStyle` or %(CapStyle)s
"""
self._capstyle = CapStyle(cs)
@_docstring.interpd
def get_capstyle(self):
"""
Return the cap style for the collection (for all its elements).
Returns
-------
%(CapStyle)s or None
"""
return self._capstyle.name if self._capstyle else None
@_docstring.interpd
def set_joinstyle(self, js):
"""
Set the `.JoinStyle` for the collection (for all its elements).
Parameters
----------
js : `.JoinStyle` or %(JoinStyle)s
"""
self._joinstyle = JoinStyle(js)
@_docstring.interpd
def get_joinstyle(self):
"""
Return the join style for the collection (for all its elements).
Returns
-------
%(JoinStyle)s or None
"""
return self._joinstyle.name if self._joinstyle else None
@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 patterns
dashes = [mlines._scale_dashes(o, d, lw)
for (o, d), lw in zip(dashes, linewidths)]
return linewidths, dashes
def get_antialiased(self):
"""
Get the antialiasing state for rendering.
Returns
-------
array of bools
"""
return self._antialiaseds
def set_antialiased(self, aa):
"""
Set the antialiasing state for rendering.
Parameters
----------
aa : bool or list of bools
"""
if aa is None:
aa = self._get_default_antialiased()
self._antialiaseds = np.atleast_1d(np.asarray(aa, bool))
self.stale = True
def _get_default_antialiased(self):
# This may be overridden in a subclass.
return mpl.rcParams['patch.antialiased']
def set_color(self, c):
"""
Set both the edgecolor and the facecolor.
Parameters
----------
c : color or list 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 _get_default_facecolor(self):
# This may be overridden in a subclass.
return mpl.rcParams['patch.facecolor']
def _set_facecolor(self, c):
if c is None:
c = self._get_default_facecolor()
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 list of colors
"""
if isinstance(c, str) and c.lower() in ("none", "face"):
c = c.lower()
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 _get_default_edgecolor(self):
# This may be overridden in a subclass.
return mpl.rcParams['patch.edgecolor']
def _set_edgecolor(self, c):
set_hatch_color = True
if c is None:
if (mpl.rcParams['patch.force_edgecolor']
or self._edge_default
or cbook._str_equal(self._original_facecolor, 'none')):
c = self._get_default_edgecolor()
else:
c = 'none'
set_hatch_color = False
if cbook._str_lower_equal(c, 'face'):
self._edgecolors = 'face'
self.stale = True
return
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 list of colors or 'face'
The collection edgecolor(s). If a sequence, the patches cycle
through it. If 'face', match the facecolor.
"""
# We pass through a default value for use in LineCollection.
# This allows us to maintain None as the default indicator in
# _original_edgecolor.
if isinstance(c, str) and c.lower() in ("none", "face"):
c = c.lower()
self._original_edgecolor = c
self._set_edgecolor(c)
def set_alpha(self, alpha):
"""
Set the transparency of the collection.
Parameters
----------
alpha : float or array of float or None
If not None, *alpha* values must be between 0 and 1, inclusive.
If an array is provided, its length must match the number of
elements in the collection. Masked values and nans are not
supported.
"""
artist.Artist._set_alpha_for_array(self, alpha)
self._set_facecolor(self._original_facecolor)
self._set_edgecolor(self._original_edgecolor)
set_alpha.__doc__ = artist.Artist._set_alpha_for_array.__doc__
def get_linewidth(self):
return self._linewidths
def get_linestyle(self):
return self._linestyles
def _set_mappable_flags(self):
"""
Determine whether edges and/or faces are color-mapped.
This is a helper for update_scalarmappable.
It sets Boolean flags '_edge_is_mapped' and '_face_is_mapped'.
Returns
-------
mapping_change : bool
True if either flag is True, or if a flag has changed.
"""
# The flags are initialized to None to ensure this returns True
# the first time it is called.
edge0 = self._edge_is_mapped
face0 = self._face_is_mapped
# After returning, the flags must be Booleans, not None.
self._edge_is_mapped = False
self._face_is_mapped = False
if self._A is not None:
if not cbook._str_equal(self._original_facecolor, 'none'):
self._face_is_mapped = True
if cbook._str_equal(self._original_edgecolor, 'face'):
self._edge_is_mapped = True
else:
if self._original_edgecolor is None:
self._edge_is_mapped = True
mapped = self._face_is_mapped or self._edge_is_mapped
changed = (edge0 is None or face0 is None
or self._edge_is_mapped != edge0
or self._face_is_mapped != face0)
return mapped or changed
def update_scalarmappable(self):
"""
Update colors from the scalar mappable array, if any.
Assign colors to edges and faces based on the array and/or
colors that were directly set, as appropriate.
"""
if not self._set_mappable_flags():
return
# Allow possibility to call 'self.set_array(None)'.
if self._A is not None:
# QuadMesh can map 2d arrays (but pcolormesh supplies 1d array)
if self._A.ndim > 1 and not isinstance(self, _MeshData):
raise ValueError('Collections can only map rank 1 arrays')
if np.iterable(self._alpha):
if self._alpha.size != self._A.size:
raise ValueError(
f'Data array shape, {self._A.shape} '
'is incompatible with alpha array shape, '
f'{self._alpha.shape}. '
'This can occur with the deprecated '
'behavior of the "flat" shading option, '
'in which a row and/or column of the data '
'array is dropped.')
# pcolormesh, scatter, maybe others flatten their _A
self._alpha = self._alpha.reshape(self._A.shape)
self._mapped_colors = self.to_rgba(self._A, self._alpha)
if self._face_is_mapped:
self._facecolors = self._mapped_colors
else:
self._set_facecolor(self._original_facecolor)
if self._edge_is_mapped:
self._edgecolors = self._mapped_colors
else:
self._set_edgecolor(self._original_edgecolor)
self.stale = True
def get_fill(self):
"""Return whether face is colored."""
return not cbook._str_lower_equal(self._original_facecolor, "none")
def update_from(self, other):
"""Copy properties from other to self."""
artist.Artist.update_from(self, other)
self._antialiaseds = other._antialiaseds
self._mapped_colors = other._mapped_colors
self._edge_is_mapped = other._edge_is_mapped
self._original_edgecolor = other._original_edgecolor
self._edgecolors = other._edgecolors
self._face_is_mapped = other._face_is_mapped
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.stale = True
class _CollectionWithSizes(Collection):
"""
Base class for collections that have an array of sizes.
"""
_factor = 1.0
def get_sizes(self):
"""
Return the sizes ('areas') of the elements in the collection.
Returns
-------
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 : `numpy.ndarray` or None
The size to set for each element of the collection. The
value is the 'area' of the element.
dpi : float, default: 72
The dpi of the canvas.
"""
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)
super().draw(renderer)
class PathCollection(_CollectionWithSizes):
r"""
A collection of `~.path.Path`\s, as created by e.g. `~.Axes.scatter`.
"""
def __init__(self, paths, sizes=None, **kwargs):
"""
Parameters
----------
paths : list of `.path.Path`
The paths that will make up the `.Collection`.
sizes : array-like
The factor by which to scale each drawn `~.path.Path`. One unit
squared in the Path's data space is scaled to be ``sizes**2``
points when rendered.
**kwargs
Forwarded to `.Collection`.
"""
super().__init__(**kwargs)
self.set_paths(paths)
self.set_sizes(sizes)
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):
"""
Create legend handles and labels for a PathCollection.
Each legend handle is a `.Line2D` representing the Path that was drawn,
and each label is a string that represents the Path.
This is useful for obtaining a legend for a `~.Axes.scatter` plot;
e.g.::
scatter = plt.scatter([1, 2, 3], [4, 5, 6], c=[7, 2, 3], num=None)
plt.legend(*scatter.legend_elements())
creates three legend elements, one for each color with the numerical
values passed to *c* as the labels.
Also see the :ref:`automatedlegendcreation` example.
Parameters
----------
prop : {"colors", "sizes"}, default: "colors"
If "colors", the legend handles will show the different colors of
the collection. If "sizes", the legend will show the different
sizes. To set both, use *kwargs* to directly edit the `.Line2D`
properties.
num : int, None, "auto" (default), array-like, or `~.ticker.Locator`
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 `~.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 = lambda
x: 10**x``.
**kwargs
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
-------
handles : list of `.Line2D`
Visual representation of each element of the legend.
labels : list of str
The string labels for elements of the legend.
"""
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.")
fu = func(u)
fmt.axis.set_view_interval(fu.min(), fu.max())
fmt.axis.set_data_interval(fu.min(), fu.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]
yarr = np.linspace(arr.min(), arr.max(), 256)
xarr = func(yarr)
ix = np.argsort(xarr)
values = np.interp(label_values, xarr[ix], yarr[ix])
kw = {"markeredgewidth": self.get_linewidths()[0],
"alpha": self.get_alpha(),
**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):
def __init__(self, verts, sizes=None, *, closed=True, **kwargs):
"""
Parameters
----------
verts : list of array-like
The sequence of polygons [*verts0*, *verts1*, ...] where each
element *verts_i* defines the vertices of polygon *i* as a 2D
array-like of shape (M, 2).
sizes : array-like, default: None
Squared scaling factors for the polygons. The coordinates of each
polygon *verts_i* are multiplied by the square-root of the
corresponding entry in *sizes* (i.e., *sizes* specify the scaling
of areas). The scaling is applied before the Artist master
transform.
closed : bool, default: True
Whether the polygon should be closed by adding a CLOSEPOLY
connection at the end.
**kwargs
Forwarded to `.Collection`.
"""
super().__init__(**kwargs)
self.set_sizes(sizes)
self.set_verts(verts, closed)
self.stale = True
def set_verts(self, verts, closed=True):
"""
Set the vertices of the polygons.
Parameters
----------
verts : list of array-like
The sequence of polygons [*verts0*, *verts1*, ...] where each
element *verts_i* defines the vertices of polygon *i* as a 2D
array-like of shape (M, 2).
closed : bool, default: True
Whether the polygon should be closed by adding a CLOSEPOLY
connection at the end.
"""
self.stale = True
if isinstance(verts, np.ma.MaskedArray):
verts = verts.astype(float).filled(np.nan)
# No need to do anything fancy if the path isn't closed.
if not closed:
self._paths = [mpath.Path(xy) for xy in verts]
return
# Fast path for arrays
if isinstance(verts, np.ndarray) and len(verts.shape) == 3:
verts_pad = np.concatenate((verts, verts[:, :1]), axis=1)
# Creating the codes once is much faster than having Path do it
# separately each time by passing closed=True.
codes = np.empty(verts_pad.shape[1], dtype=mpath.Path.code_type)
codes[:] = mpath.Path.LINETO
codes[0] = mpath.Path.MOVETO
codes[-1] = mpath.Path.CLOSEPOLY
self._paths = [mpath.Path(xy, codes) for xy in verts_pad]
return
self._paths = []
for xy in verts:
if len(xy):
self._paths.append(mpath.Path._create_closed(xy))
else:
self._paths.append(mpath.Path(xy))
set_paths = set_verts
def set_verts_and_codes(self, verts, codes):
"""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 = [mpath.Path(xy, cds) if len(xy) else mpath.Path(xy)
for xy, cds in zip(verts, codes)]
self.stale = True
@classmethod
@_api.deprecated("3.7", alternative="fill_between")
def span_where(cls, x, ymin, ymax, where, **kwargs):
"""
Return a `.BrokenBarHCollection` that plots horizontal bars from
over the regions in *x* where *where* is True. The bars range
on the y-axis from *ymin* to *ymax*
*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]))
return BrokenBarHCollection(xranges, [ymin, ymax - ymin], **kwargs)
@_api.deprecated("3.7")
class BrokenBarHCollection(PolyCollection):
"""
A collection of horizontal bars spanning *yrange* with a sequence of
*xranges*.
"""
def __init__(self, xranges, yrange, **kwargs):
"""
Parameters
----------
xranges : list of (float, float)
The sequence of (left-edge-position, width) pairs for each bar.
yrange : (float, float)
The (lower-edge, height) common to all bars.
**kwargs
Forwarded to `.Collection`.
"""
ymin, ywidth = yrange
ymax = ymin + ywidth
verts = [[(xmin, ymin),
(xmin, ymax),
(xmin + xwidth, ymax),
(xmin + xwidth, ymin),
(xmin, ymin)] for xmin, xwidth in xranges]
super().__init__(verts, **kwargs)
class RegularPolyCollection(_CollectionWithSizes):
"""A collection of n-sided regular polygons."""
_path_generator = mpath.Path.unit_regular_polygon
_factor = np.pi ** (-1/2)
def __init__(self,
numsides,
*,
rotation=0,
sizes=(1,),
**kwargs):
"""
Parameters
----------
numsides : int
The number of sides of the polygon.
rotation : float
The rotation of the polygon in radians.
sizes : tuple of float
The area of the circle circumscribing the polygon in points^2.
**kwargs
Forwarded to `.Collection`.
Examples
--------
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,
offset_transform=ax.transData,
)
"""
super().__init__(**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
]
# Explicitly not super().draw, because set_sizes must be called before
# updating 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):
r"""
Represents a sequence of `.Line2D`\s that should be drawn together.
This class extends `.Collection` to represent a sequence of
`.Line2D`\s instead of just a sequence of `.Patch`\s.
Just as in `.Collection`, each property of a *LineCollection* may be either
a single value or a list of values. This list is then used cyclically for
each element of the LineCollection, so the property of the ``i``\th element
of the collection is::
prop[i % len(prop)]
The properties of each member of a *LineCollection* default to their values
in :rc:`lines.*` instead of :rc:`patch.*`, and the property *colors* is
added in place of *edgecolors*.
"""
_edge_default = True
def __init__(self, segments, # Can be None.
*,
zorder=2, # Collection.zorder is 1
**kwargs
):
"""
Parameters
----------
segments : list of array-like
A sequence (*line0*, *line1*, *line2*) of lines, where each line is a list
of points::
lineN = [(x0, y0), (x1, y1), ... (xm, ym)]
or the equivalent Mx2 numpy array with two columns. Each line
can have a different number of segments.
linewidths : float or list of float, default: :rc:`lines.linewidth`
The width of each line in points.
colors : color or list of color, default: :rc:`lines.color`
A sequence of RGBA tuples (e.g., arbitrary color strings, etc, not
allowed).
antialiaseds : bool or list of bool, default: :rc:`lines.antialiased`
Whether to use antialiasing for each line.
zorder : float, default: 2
zorder of the lines once drawn.
facecolors : color or list of color, default: 'none'
When setting *facecolors*, each line is interpreted as a boundary
for an area, implicitly closing the path from the last point to the
first point. The enclosed area is filled with *facecolor*.
In order to manually specify what should count as the "interior" of
each line, please use `.PathCollection` instead, where the
"interior" can be specified by appropriate usage of
`~.path.Path.CLOSEPOLY`.
**kwargs
Forwarded to `.Collection`.
"""
# Unfortunately, mplot3d needs this explicit setting of 'facecolors'.
kwargs.setdefault('facecolors', 'none')
super().__init__(
zorder=zorder,
**kwargs)
self.set_segments(segments)
def set_segments(self, segments):
if segments is None:
return
self._paths = [mpath.Path(seg) if isinstance(seg, np.ma.MaskedArray)
else mpath.Path(np.asarray(seg, float))
for seg in segments]
self.stale = True
set_verts = set_segments # for compatibility with PolyCollection
set_paths = set_segments
def get_segments(self):
"""
Returns
-------
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, _
# Never simplify here, we want to get the data-space values
# back and there in no way to know the "right" simplification
# threshold so never try.
in path.iter_segments(simplify=False)
]
vertices = np.asarray(vertices)
segments.append(vertices)
return segments
def _get_default_linewidth(self):
return mpl.rcParams['lines.linewidth']
def _get_default_antialiased(self):
return mpl.rcParams['lines.antialiased']
def _get_default_edgecolor(self):
return mpl.rcParams['lines.color']
def _get_default_facecolor(self):
return 'none'
def set_alpha(self, alpha):
# docstring inherited
super().set_alpha(alpha)
if self._gapcolor is not None:
self.set_gapcolor(self._original_gapcolor)
def set_color(self, c):
"""
Set the edgecolor(s) of the LineCollection.
Parameters
----------
c : color or list of colors
Single color (all lines have same color), or a
sequence of RGBA tuples; if it is a sequence the lines will
cycle through the sequence.
"""
self.set_edgecolor(c)
set_colors = set_color
def get_color(self):
return self._edgecolors
get_colors = get_color # for compatibility with old versions
def set_gapcolor(self, gapcolor):
"""
Set a color to fill the gaps in the dashed line style.
.. note::
Striped lines are created by drawing two interleaved dashed lines.
There can be overlaps between those two, which may result in
artifacts when using transparency.
This functionality is experimental and may change.
Parameters
----------
gapcolor : color or list of colors or None
The color with which to fill the gaps. If None, the gaps are
unfilled.
"""
self._original_gapcolor = gapcolor
self._set_gapcolor(gapcolor)
def _set_gapcolor(self, gapcolor):
if gapcolor is not None:
gapcolor = mcolors.to_rgba_array(gapcolor, self._alpha)
self._gapcolor = gapcolor
self.stale = True
def get_gapcolor(self):
return self._gapcolor
def _get_inverse_paths_linestyles(self):
"""
Returns the path and pattern for the gaps in the non-solid lines.
This path and pattern is the inverse of the path and pattern used to
construct the non-solid lines. For solid lines, we set the inverse path
to nans to prevent drawing an inverse line.
"""
path_patterns = [
(mpath.Path(np.full((1, 2), np.nan)), ls)
if ls == (0, None) else
(path, mlines._get_inverse_dash_pattern(*ls))
for (path, ls) in
zip(self._paths, itertools.cycle(self._linestyles))]
return zip(*path_patterns)
class EventCollection(LineCollection):
"""
A collection of locations along a single axis at which an "event" occurred.
The events are given by a 1-dimensional array. They do not have an
amplitude and are displayed as parallel lines.
"""
_edge_default = True
def __init__(self,
positions, # Cannot be None.
orientation='horizontal',
*,
lineoffset=0,
linelength=1,
linewidth=None,
color=None,
linestyle='solid',
antialiased=None,
**kwargs
):
"""
Parameters
----------
positions : 1D array-like
Each value is an event.
orientation : {'horizontal', 'vertical'}, default: 'horizontal'
The sequence of events is plotted along this direction.
The marker lines of the single events are along the orthogonal
direction.
lineoffset : float, default: 0
The offset of the center of the markers from the origin, in the
direction orthogonal to *orientation*.
linelength : float, default: 1
The total height of the marker (i.e. the marker stretches from
``lineoffset - linelength/2`` to ``lineoffset + linelength/2``).
linewidth : float or list thereof, default: :rc:`lines.linewidth`
The line width of the event lines, in points.
color : color or list of colors, default: :rc:`lines.color`
The color of the event lines.
linestyle : str or tuple or list thereof, 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 : bool or list thereof, default: :rc:`lines.antialiased`
Whether to use antialiasing for drawing the lines.
**kwargs
Forwarded to `.LineCollection`.
Examples
--------
.. plot:: gallery/lines_bars_and_markers/eventcollection_demo.py
"""
super().__init__([],
linewidths=linewidth, linestyles=linestyle,
colors=color, antialiaseds=antialiased,
**kwargs)
self._is_horizontal = True # Initial value, may be switched below.
self._linelength = linelength
self._lineoffset = lineoffset
self.set_orientation(orientation)
self.set_positions(positions)
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."""
if positions is None:
positions = []
if np.ndim(positions) != 1:
raise ValueError('positions must be one-dimensional')
lineoffset = self.get_lineoffset()
linelength = self.get_linelength()
pos_idx = 0 if self.is_horizontal() else 1
segments = np.empty((len(positions), 2, 2))
segments[:, :, pos_idx] = np.sort(positions)[:, None]
segments[:, 0, 1 - pos_idx] = lineoffset + linelength / 2
segments[:, 1, 1 - pos_idx] = lineoffset - linelength / 2
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):
"""
Set the orientation of the event line.
Parameters
----------
orientation : {'horizontal', 'vertical'}
"""
is_horizontal = _api.check_getitem(
{"horizontal": True, "vertical": False},
orientation=orientation)
if is_horizontal == self.is_horizontal():
return
self.switch_orientation()
def get_linelength(self):
"""Return 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):
"""Return 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().get_linewidth()[0]
def get_linewidths(self):
return super().get_linewidth()
def get_color(self):
"""Return 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)
def __init__(self, sizes, **kwargs):
"""
Parameters
----------
sizes : float or array-like
The area of each circle in points^2.
**kwargs
Forwarded to `.Collection`.
"""
super().__init__(**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."""
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 `~.patches.Ellipse` with
``axes.transData`` as its transform.
**kwargs
Forwarded to `Collection`.
"""
super().__init__(**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(f'Unrecognized units: {self._units!r}')
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()
super().draw(renderer)
class PatchCollection(Collection):
"""
A generic collection of patches.
PatchCollection draws faster than a large number of equivalent individual
Patches. It also makes it easier to assign a colormap to a heterogeneous
collection of patches.
"""
def __init__(self, patches, *, match_original=False, **kwargs):
"""
Parameters
----------
patches : list of `.Patch`
A sequence of Patch objects. This list may include
a heterogeneous assortment of different patch types.
match_original : bool, default: False
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.
**kwargs
All other parameters are forwarded to `.Collection`.
If any of *edgecolors*, *facecolors*, *linewidths*, *antialiaseds*
are None, they default to their `.rcParams` patch setting, in
sequence form.
Notes
-----
The use of `~matplotlib.cm.ScalarMappable` functionality is optional.
If the `~matplotlib.cm.ScalarMappable` matrix ``_A`` has been set (via
a call to `~.ScalarMappable.set_array`), 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]
super().__init__(**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):
super().__init__(**kwargs)
self._triangulation = triangulation
self._shading = 'gouraud'
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):
"""
Convert 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 _MeshData:
r"""
Class for managing the two dimensional coordinates of Quadrilateral meshes
and the associated data with them. This class is a mixin and is intended to
be used with another collection that will implement the draw separately.
A quadrilateral mesh is a grid of M by N adjacent quadrilaterals that are
defined via a (M+1, N+1) grid of vertices. The quadrilateral (m, n) is
defined by the vertices ::
(m+1, n) ----------- (m+1, n+1)
/ /
/ /
/ /
(m, n) -------- (m, n+1)
The mesh need not be regular and the polygons need not be convex.
Parameters
----------
coordinates : (M+1, N+1, 2) array-like
The vertices. ``coordinates[m, n]`` specifies the (x, y) coordinates
of vertex (m, n).
shading : {'flat', 'gouraud'}, default: 'flat'
"""
def __init__(self, coordinates, *, shading='flat'):
_api.check_shape((None, None, 2), coordinates=coordinates)
self._coordinates = coordinates
self._shading = shading
def set_array(self, A):
"""
Set the data values.
Parameters
----------
A : array-like
The mesh data. Supported array shapes are:
- (M, N) or (M*N,): a mesh with scalar data. The values are mapped
to colors using normalization and a colormap. See parameters
*norm*, *cmap*, *vmin*, *vmax*.
- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),
i.e. including transparency.
If the values are provided as a 2D grid, the shape must match the
coordinates grid. If the values are 1D, they are reshaped to 2D.
M, N follow from the coordinates grid, where the coordinates grid
shape is (M, N) for 'gouraud' *shading* and (M+1, N+1) for 'flat'
shading.
"""
height, width = self._coordinates.shape[0:-1]
if self._shading == 'flat':
h, w = height - 1, width - 1
else:
h, w = height, width
ok_shapes = [(h, w, 3), (h, w, 4), (h, w), (h * w,)]
if A is not None:
shape = np.shape(A)
if shape not in ok_shapes:
raise ValueError(
f"For X ({width}) and Y ({height}) with {self._shading} "
f"shading, A should have shape "
f"{' or '.join(map(str, ok_shapes))}, not {A.shape}")
return super().set_array(A)
def get_coordinates(self):
"""
Return the vertices of the mesh as an (M+1, N+1, 2) array.
M, N are the number of quadrilaterals in the rows / columns of the
mesh, corresponding to (M+1, N+1) vertices.
The last dimension specifies the components (x, y).
"""
return self._coordinates
def get_edgecolor(self):
# docstring inherited
# Note that we want to return an array of shape (N*M, 4)
# a flattened RGBA collection
return super().get_edgecolor().reshape(-1, 4)
def get_facecolor(self):
# docstring inherited
# Note that we want to return an array of shape (N*M, 4)
# a flattened RGBA collection
return super().get_facecolor().reshape(-1, 4)
@staticmethod
def _convert_mesh_to_paths(coordinates):
"""
Convert 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).reshape((-1, 5, 2))
return [mpath.Path(x) for x in points]
def _convert_mesh_to_triangles(self, coordinates):
"""
Convert a given mesh into a sequence of triangles, each point
with its own color. The result can be used to construct a call to
`~.RendererBase.draw_gouraud_triangles`.
"""
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).reshape((-1, 3, 2))
c = self.get_facecolor().reshape((*coordinates.shape[:2], 4))
z = self.get_array()
mask = z.mask if np.ma.is_masked(z) else None
if mask is not None:
c[mask, 3] = np.nan
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).reshape((-1, 3, 4))
tmask = np.isnan(colors[..., 2, 3])
return triangles[~tmask], colors[~tmask]
class QuadMesh(_MeshData, Collection):
r"""
Class for the efficient drawing of a quadrilateral mesh.
A quadrilateral mesh is a grid of M by N adjacent quadrilaterals that are
defined via a (M+1, N+1) grid of vertices. The quadrilateral (m, n) is
defined by the vertices ::
(m+1, n) ----------- (m+1, n+1)
/ /
/ /
/ /
(m, n) -------- (m, n+1)
The mesh need not be regular and the polygons need not be convex.
Parameters
----------
coordinates : (M+1, N+1, 2) array-like
The vertices. ``coordinates[m, n]`` specifies the (x, y) coordinates
of vertex (m, n).
antialiased : bool, default: True
shading : {'flat', 'gouraud'}, default: 'flat'
Notes
-----
Unlike other `.Collection`\s, the default *pickradius* of `.QuadMesh` is 0,
i.e. `~.Artist.contains` checks whether the test point is within any of the
mesh quadrilaterals.
"""
def __init__(self, coordinates, *, antialiased=True, shading='flat',
**kwargs):
kwargs.setdefault("pickradius", 0)
super().__init__(coordinates=coordinates, shading=shading)
Collection.__init__(self, **kwargs)
self._antialiased = antialiased
self._bbox = transforms.Bbox.unit()
self._bbox.update_from_data_xy(self._coordinates.reshape(-1, 2))
self.set_mouseover(False)
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._coordinates)
self.stale = True
def get_datalim(self, transData):
return (self.get_transform() - transData).transform_bbox(self._bbox)
@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()
offset_trf = self.get_offset_transform()
offsets = self.get_offsets()
if self.have_units():
xs = self.convert_xunits(offsets[:, 0])
ys = self.convert_yunits(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 offset_trf.is_affine:
offsets = offset_trf.transform_non_affine(offsets)
offset_trf = offset_trf.get_affine()
gc = renderer.new_gc()
gc.set_snap(self.get_snap())
self._set_gc_clip(gc)
gc.set_linewidth(self.get_linewidth()[0])
if self._shading == 'gouraud':
triangles, colors = self._convert_mesh_to_triangles(coordinates)
renderer.draw_gouraud_triangles(
gc, triangles, colors, transform.frozen())
else:
renderer.draw_quad_mesh(
gc, transform.frozen(),
coordinates.shape[1] - 1, coordinates.shape[0] - 1,
coordinates, offsets, offset_trf,
# Backends expect flattened rgba arrays (n*m, 4) for fc and ec
self.get_facecolor().reshape((-1, 4)),
self._antialiased, self.get_edgecolors().reshape((-1, 4)))
gc.restore()
renderer.close_group(self.__class__.__name__)
self.stale = False
def get_cursor_data(self, event):
contained, info = self.contains(event)
if contained and self.get_array() is not None:
return self.get_array().ravel()[info["ind"]]
return None
class PolyQuadMesh(_MeshData, PolyCollection):
"""
Class for drawing a quadrilateral mesh as individual Polygons.
A quadrilateral mesh is a grid of M by N adjacent quadrilaterals that are
defined via a (M+1, N+1) grid of vertices. The quadrilateral (m, n) is
defined by the vertices ::
(m+1, n) ----------- (m+1, n+1)
/ /
/ /
/ /
(m, n) -------- (m, n+1)
The mesh need not be regular and the polygons need not be convex.
Parameters
----------
coordinates : (M+1, N+1, 2) array-like
The vertices. ``coordinates[m, n]`` specifies the (x, y) coordinates
of vertex (m, n).
Notes
-----
Unlike `.QuadMesh`, this class will draw each cell as an individual Polygon.
This is significantly slower, but allows for more flexibility when wanting
to add additional properties to the cells, such as hatching.
Another difference from `.QuadMesh` is that if any of the vertices or data
of a cell are masked, that Polygon will **not** be drawn and it won't be in
the list of paths returned.
"""
def __init__(self, coordinates, **kwargs):
# We need to keep track of whether we are using deprecated compression
# Update it after the initializers
self._deprecated_compression = False
super().__init__(coordinates=coordinates)
PolyCollection.__init__(self, verts=[], **kwargs)
# Store this during the compression deprecation period
self._original_mask = ~self._get_unmasked_polys()
self._deprecated_compression = np.any(self._original_mask)
# Setting the verts updates the paths of the PolyCollection
# This is called after the initializers to make sure the kwargs
# have all been processed and available for the masking calculations
self._set_unmasked_verts()
def _get_unmasked_polys(self):
"""Get the unmasked regions using the coordinates and array"""
# mask(X) | mask(Y)
mask = np.any(np.ma.getmaskarray(self._coordinates), axis=-1)
# We want the shape of the polygon, which is the corner of each X/Y array
mask = (mask[0:-1, 0:-1] | mask[1:, 1:] | mask[0:-1, 1:] | mask[1:, 0:-1])
if (getattr(self, "_deprecated_compression", False) and
np.any(self._original_mask)):
return ~(mask | self._original_mask)
# Take account of the array data too, temporarily avoiding
# the compression warning and resetting the variable after the call
with cbook._setattr_cm(self, _deprecated_compression=False):
arr = self.get_array()
if arr is not None:
arr = np.ma.getmaskarray(arr)
if arr.ndim == 3:
# RGB(A) case
mask |= np.any(arr, axis=-1)
elif arr.ndim == 2:
mask |= arr
else:
mask |= arr.reshape(self._coordinates[:-1, :-1, :].shape[:2])
return ~mask
def _set_unmasked_verts(self):
X = self._coordinates[..., 0]
Y = self._coordinates[..., 1]
unmask = self._get_unmasked_polys()
X1 = np.ma.filled(X[:-1, :-1])[unmask]
Y1 = np.ma.filled(Y[:-1, :-1])[unmask]
X2 = np.ma.filled(X[1:, :-1])[unmask]
Y2 = np.ma.filled(Y[1:, :-1])[unmask]
X3 = np.ma.filled(X[1:, 1:])[unmask]
Y3 = np.ma.filled(Y[1:, 1:])[unmask]
X4 = np.ma.filled(X[:-1, 1:])[unmask]
Y4 = np.ma.filled(Y[:-1, 1:])[unmask]
npoly = len(X1)
xy = np.ma.stack([X1, Y1, X2, Y2, X3, Y3, X4, Y4, X1, Y1], axis=-1)
verts = xy.reshape((npoly, 5, 2))
self.set_verts(verts)
def get_edgecolor(self):
# docstring inherited
# We only want to return the facecolors of the polygons
# that were drawn.
ec = super().get_edgecolor()
unmasked_polys = self._get_unmasked_polys().ravel()
if len(ec) != len(unmasked_polys):
# Mapping is off
return ec
return ec[unmasked_polys, :]
def get_facecolor(self):
# docstring inherited
# We only want to return the facecolors of the polygons
# that were drawn.
fc = super().get_facecolor()
unmasked_polys = self._get_unmasked_polys().ravel()
if len(fc) != len(unmasked_polys):
# Mapping is off
return fc
return fc[unmasked_polys, :]
def set_array(self, A):
# docstring inherited
prev_unmask = self._get_unmasked_polys()
# MPL <3.8 compressed the mask, so we need to handle flattened 1d input
# until the deprecation expires, also only warning when there are masked
# elements and thus compression occurring.
if self._deprecated_compression and np.ndim(A) == 1:
_api.warn_deprecated("3.8", message="Setting a PolyQuadMesh array using "
"the compressed values is deprecated. "
"Pass the full 2D shape of the original array "
f"{prev_unmask.shape} including the masked elements.")
Afull = np.empty(self._original_mask.shape)
Afull[~self._original_mask] = A
# We also want to update the mask with any potential
# new masked elements that came in. But, we don't want
# to update any of the compression from the original
mask = self._original_mask.copy()
mask[~self._original_mask] |= np.ma.getmask(A)
A = np.ma.array(Afull, mask=mask)
return super().set_array(A)
self._deprecated_compression = False
super().set_array(A)
# If the mask has changed at all we need to update
# the set of Polys that we are drawing
if not np.array_equal(prev_unmask, self._get_unmasked_polys()):
self._set_unmasked_verts()
def get_array(self):
# docstring inherited
# Can remove this entire function once the deprecation period ends
A = super().get_array()
if A is None:
return
if self._deprecated_compression and np.any(np.ma.getmask(A)):
_api.warn_deprecated("3.8", message=(
"Getting the array from a PolyQuadMesh will return the full "
"array in the future (uncompressed). To get this behavior now "
"set the PolyQuadMesh with a 2D array .set_array(data2d)."))
# Setting an array of a polycollection required
# compressing the array
return np.ma.compressed(A)
return A