Source code for matplotlib.collections

Classes for the efficient drawing of large collections of objects that
share most properties, e.g., a large number of line segments or

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 math
from numbers import Number
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
import warnings

# "color" is excluded; it is a compound setter, and its docstring differs
# in LineCollection.
[docs]@cbook._define_aliases({ "antialiased": ["antialiaseds", "aa"], "edgecolor": ["edgecolors", "ec"], "facecolor": ["facecolors", "fc"], "linestyle": ["linestyles", "dashes", "ls"], "linewidth": ["linewidths", "lw"], }) 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. """ _offsets = np.zeros((0, 2)) _transOffset = transforms.IdentityTransform() #: 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 @_api.delete_parameter("3.3", "offset_position") @docstring.interpd def __init__(self, edgecolors=None, facecolors=None, linewidths=None, linestyles='solid', capstyle=None, joinstyle=None, antialiaseds=None, offsets=None, transOffset=None, norm=None, # optional for ScalarMappable cmap=None, # ditto pickradius=5.0, hatch=None, urls=None, offset_position='screen', 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). transOffset : `~.transforms.Transform`, default: `.IdentityTransform` A single transform which will be applied to each *offsets* vector before it is used. offset_position : {{'screen' (default), 'data' (deprecated)}} If set to 'data' (deprecated), *offsets* will be treated as if it is in data coordinates instead of in screen coordinates. norm : `~.colors.Normalize`, optional Forwarded to `.ScalarMappable`. The default of ``None`` means that the first draw call will set ``vmin`` and ``vmax`` using the minimum and maximum values of the data. cmap : `~.colors.Colormap`, optional Forwarded to `.ScalarMappable`. The default of ``None`` will result in :rc:`image.cmap` being used. 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] # 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._offset_position = "screen" if offset_position != "screen": self.set_offset_position(offset_position) # emit deprecation. self.set_zorder(zorder) if capstyle: self.set_capstyle(capstyle) else: self._capstyle = None if joinstyle: self.set_joinstyle(joinstyle) else: self._joinstyle = None self._offsets = np.zeros((1, 2)) # save if offsets passed in were none... self._offsetsNone = offsets is None self._uniform_offsets = 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, :] if transOffset is not None: self._offsets = offsets self._transOffset = transOffset else: self._uniform_offsets = offsets self._path_effects = None self.update(kwargs) self._paths = None
[docs] def get_paths(self): return self._paths
[docs] def set_paths(self): raise NotImplementedError
[docs] def get_transforms(self): return self._transforms
[docs] def get_offset_transform(self): t = self._transOffset if (not isinstance(t, transforms.Transform) and hasattr(t, '_as_mpl_transform')): t = t._as_mpl_transform(self.axes) return t
[docs] 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() transOffset = self.get_offset_transform() if (not self._offsetsNone and not transOffset.contains_branch(transData)): # if there are offsets but in some coords other than data, # then don't use them for autoscaling. return transforms.Bbox.null() offsets = self._offsets paths = self.get_paths() 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. if isinstance(offsets, offsets = offsets.filled(np.nan) # get_path_collection_extents handles nan but not masked arrays if len(paths) and len(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). return mpath.get_path_collection_extents( transform.get_affine() - transData, paths, self.get_transforms(), transOffset.transform_non_affine(offsets), transOffset.get_affine().frozen()) if not self._offsetsNone: # 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 = (transOffset - transData).transform(offsets) # note A-B means A B^{-1} offsets = if not offsets.mask.all(): bbox = transforms.Bbox.null() bbox.update_from_data_xy(offsets) return bbox return transforms.Bbox.null()
[docs] def get_window_extent(self, renderer): # 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() transOffset = self.get_offset_transform() offsets = self._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]), if offsets.size: xs = self.convert_xunits(offsets[:, 0]) ys = self.convert_yunits(offsets[:, 1]) offsets = np.column_stack([xs, ys]) if not transform.is_affine: paths = [transform.transform_path_non_affine(path) for path in paths] transform = transform.get_affine() if not transOffset.is_affine: offsets = transOffset.transform_non_affine(offsets) # This might have changed an ndarray into a masked array. transOffset = transOffset.get_affine() if isinstance(offsets, offsets = offsets.filled(np.nan) # Changing from a masked array to nan-filled ndarray # is probably most efficient at this point. return transform, transOffset, offsets, paths
[docs] @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, transOffset, 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), 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
[docs] def set_pickradius(self, pr): """ Set the pick radius used for containment tests. Parameters ---------- pr : float Pick radius, in points. """ self._pickradius = pr
[docs] def get_pickradius(self): return self._pickradius
[docs] 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: self.axes._unstale_viewLim() transform, transOffset, 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, transOffset, pickradius <= 0, self._offset_position) return len(ind) > 0, dict(ind=ind)
[docs] 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
[docs] 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
[docs] 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
[docs] def get_hatch(self): """Return the current hatching pattern.""" return self._hatch
[docs] def set_offsets(self, offsets): """ Set the offsets for the collection. Parameters ---------- offsets : (N, 2) or (2,) array-like """ 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
[docs] 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
[docs] @_api.deprecated("3.3") 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'} """ _api.check_in_list(['screen', 'data'], offset_position=offset_position) self._offset_position = offset_position self.stale = True
[docs] @_api.deprecated("3.3") def get_offset_position(self): """ Return 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 _get_default_linewidth(self): # This may be overridden in a subclass. return mpl.rcParams['patch.linewidth'] # validated as float
[docs] 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(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
[docs] 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: 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 as err: raise ValueError('Do not know how to convert {!r} to ' 'dashes'.format(ls)) 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)
[docs] @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)
[docs] def get_capstyle(self): return
[docs] @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)
[docs] def get_joinstyle(self): return
@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
[docs] 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']
[docs] 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
[docs] 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)
[docs] def get_facecolor(self): return self._facecolors
[docs] 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
[docs] 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)
[docs] 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._update_dict['array'] = True self._set_facecolor(self._original_facecolor) self._set_edgecolor(self._original_edgecolor)
set_alpha.__doc__ = artist.Artist._set_alpha_for_array.__doc__
[docs] def get_linewidth(self): return self._linewidths
[docs] 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
[docs] 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._check_update("array") and self._A is not None: # QuadMesh can map 2d arrays (but pcolormesh supplies 1d array) if self._A.ndim > 1 and not isinstance(self, QuadMesh): 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
[docs] def get_fill(self): """Return whether face is colored.""" return not cbook._str_lower_equal(self._original_facecolor, "none")
[docs] 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._update_dict = other._update_dict.copy() 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 : 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)
[docs]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
[docs] def set_paths(self, paths): self._paths = paths self.stale = True
[docs] def get_paths(self): return self._paths
[docs] 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 what each Path represents. 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]) 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.") 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] 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 = 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
[docs]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
[docs] 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, 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): if isinstance(xy, xy =[xy, xy[:1]]) else: xy = np.concatenate([xy, xy[:1]]) self._paths.append(mpath.Path(xy, closed=True)) else: self._paths.append(mpath.Path(xy))
set_paths = set_verts
[docs] 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 = [] 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
[docs]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)
[docs] @classmethod 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 cls(xranges, [ymin, ymax - ymin], **kwargs)
[docs]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, transOffset=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())
[docs] def get_numsides(self): return self._numsides
[docs] def get_rotation(self): return self._rotation
[docs] @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)
[docs]class StarPolygonCollection(RegularPolyCollection): """Draw a collection of regular stars with *numsides* points.""" _path_generator = mpath.Path.unit_regular_star
[docs]class AsteriskPolygonCollection(RegularPolyCollection): """Draw a collection of regular asterisks with *numsides* points.""" _path_generator = mpath.Path.unit_regular_asterisk
[docs]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. *args, # Deprecated. zorder=2, # Collection.zorder is 1 **kwargs ): """ Parameters ---------- segments : list of array-like 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 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 : int, 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`. """ argnames = ["linewidths", "colors", "antialiaseds", "linestyles", "offsets", "transOffset", "norm", "cmap", "pickradius", "zorder", "facecolors"] if args: argkw = {name: val for name, val in zip(argnames, args)} kwargs.update(argkw) cbook.warn_deprecated( "3.4", message="Since %(since)s, passing LineCollection " "arguments other than the first, 'segments', as positional " "arguments is deprecated, and they will become keyword-only " "arguments %(removal)s." ) # Unfortunately, mplot3d needs this explicit setting of 'facecolors'. kwargs.setdefault('facecolors', 'none') super().__init__( zorder=zorder, **kwargs) self.set_segments(segments)
[docs] def set_segments(self, segments): if segments is None: return _segments = [] for seg in segments: if not isinstance(seg, 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
[docs] 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 _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 _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'
[docs] 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
[docs] def get_color(self): return self._edgecolors
get_colors = get_color # for compatibility with old versions
[docs]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/ """ 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)
[docs] 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()]
[docs] 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)
[docs] 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
[docs] def is_horizontal(self): """True if the eventcollection is horizontal, False if vertical.""" return self._is_horizontal
[docs] def get_orientation(self): """ Return the orientation of the event line ('horizontal' or 'vertical'). """ return 'horizontal' if self.is_horizontal() else 'vertical'
[docs] 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
[docs] def set_orientation(self, orientation=None): """ Set the orientation of the event line. Parameters ---------- orientation : {'horizontal', 'vertical'} """ try: is_horizontal = _api.check_getitem( {"horizontal": True, "vertical": False}, orientation=orientation) except ValueError: if (orientation is None or orientation.lower() == "none" or orientation.lower() == "horizontal"): is_horizontal = True elif orientation.lower() == "vertical": is_horizontal = False else: raise normalized = "horizontal" if is_horizontal else "vertical" _api.warn_deprecated( "3.3", message="Support for setting the orientation of " f"EventCollection to {orientation!r} is deprecated since " f"%(since)s and will be removed %(removal)s; please set it to " f"{normalized!r} instead.") if is_horizontal == self.is_horizontal(): return self.switch_orientation()
[docs] def get_linelength(self): """Return the length of the lines used to mark each event.""" return self._linelength
[docs] 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
[docs] def get_lineoffset(self): """Return the offset of the lines used to mark each event.""" return self._lineoffset
[docs] 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
[docs] def get_linewidth(self): """Get the width of the lines used to mark each event.""" return super().get_linewidth()[0]
[docs] def get_linewidths(self): return super().get_linewidth()
[docs] def get_color(self): """Return the color of the lines used to mark each event.""" return self.get_colors()[0]
[docs]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()]
[docs]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('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))
[docs] @artist.allow_rasterization def draw(self, renderer): self._set_transforms() super().draw(renderer)
[docs]class PatchCollection(Collection): """ A generic collection of patches. This makes it easier to assign a colormap 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 `.rcParams` patch setting, in sequence form. The use of `` functionality is optional. If the `` 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)
[docs] def set_paths(self, patches): paths = [p.get_transform().transform_path(p.get_path()) for p in patches] self._paths = paths
[docs]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)
[docs] def get_paths(self): if self._paths is None: self.set_paths() return self._paths
[docs] def set_paths(self): self._paths = self.convert_mesh_to_paths(self._triangulation)
[docs] @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]
[docs] @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__)
[docs]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): super().__init__(**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)))
[docs] def get_paths(self): if self._paths is None: self.set_paths() return self._paths
[docs] def set_paths(self): self._paths = self.convert_mesh_to_paths( self._meshWidth, self._meshHeight, self._coordinates) self.stale = True
[docs] def get_datalim(self, transData): return (self.get_transform() - transData).transform_bbox(self._bbox)
[docs] @staticmethod def convert_mesh_to_paths(meshWidth, meshHeight, 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, c = 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]
[docs] def convert_mesh_to_triangles(self, meshWidth, meshHeight, coordinates): """ Convert a given mesh into a sequence of triangles, each point with its own color. This is useful for experiments using `~.RendererBase.draw_gouraud_triangle`. """ if isinstance(coordinates, p = 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
[docs] @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() 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( 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, # 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
_artist_kwdoc = artist.kwdoc(Collection) for k in ('QuadMesh', 'TriMesh', 'PolyCollection', 'BrokenBarHCollection', 'RegularPolyCollection', 'PathCollection', 'StarPolygonCollection', 'PatchCollection', 'CircleCollection', 'Collection',): docstring.interpd.update({f'{k}_kwdoc': _artist_kwdoc}) docstring.interpd.update(LineCollection_kwdoc=artist.kwdoc(LineCollection))