The 2019 SciPy John Hunter Excellence in Plotting Contest is accepting submissions!
Apply by June 8th

Version 3.1.0
Fork me on GitHub

Source code for matplotlib.container

import matplotlib.cbook as cbook
import matplotlib.artist as martist

[docs]class Container(tuple): """ Base class for containers. Containers are classes that collect semantically related Artists such as the bars of a bar plot. """ def __repr__(self): return ("<{} object of {} artists>" .format(type(self).__name__, len(self))) def __new__(cls, *args, **kwargs): return tuple.__new__(cls, args[0]) def __init__(self, kl, label=None): self.eventson = False # fire events only if eventson self._oid = 0 # an observer id self._propobservers = {} # a dict from oids to funcs self._remove_method = None self.set_label(label)
[docs] @cbook.deprecated("3.0") def set_remove_method(self, f): self._remove_method = f
[docs] def remove(self): for c in cbook.flatten( self, scalarp=lambda x: isinstance(x, martist.Artist)): if c is not None: c.remove() if self._remove_method: self._remove_method(self)
[docs] def get_label(self): """ Get the label used for this artist in the legend. """ return self._label
[docs] def set_label(self, s): """ Set the label to *s* for auto legend. Parameters ---------- s : object Any object other than None gets converted to its `str`. """ if s is not None: self._label = str(s) else: self._label = None self.pchanged()
[docs] def add_callback(self, func): """ Adds a callback function that will be called whenever one of the :class:`Artist`'s properties changes. Returns an *id* that is useful for removing the callback with :meth:`remove_callback` later. """ oid = self._oid self._propobservers[oid] = func self._oid += 1 return oid
[docs] def remove_callback(self, oid): """ Remove a callback based on its *id*. .. seealso:: :meth:`add_callback` For adding callbacks """ try: del self._propobservers[oid] except KeyError: pass
[docs] def pchanged(self): """ Fire an event when property changed, calling all of the registered callbacks. """ for oid, func in list(self._propobservers.items()): func(self)
[docs] def get_children(self): return [child for child in cbook.flatten(self) if child is not None]
[docs]class BarContainer(Container): """ Container for the artists of bar plots (e.g. created by ``). The container can be treated as a tuple of the *patches* themselves. Additionally, you can access these and further parameters by the attributes. Attributes ---------- patches : list of :class:`~matplotlib.patches.Rectangle` The artists of the bars. errorbar : None or :class:`~matplotlib.container.ErrorbarContainer` A container for the error bar artists if error bars are present. *None* otherwise. """ def __init__(self, patches, errorbar=None, **kwargs): self.patches = patches self.errorbar = errorbar Container.__init__(self, patches, **kwargs)
[docs]class ErrorbarContainer(Container): """ Container for the artists of error bars (e.g. created by `.Axes.errorbar`). The container can be treated as the *lines* tuple itself. Additionally, you can access these and further parameters by the attributes. Attributes ---------- lines : tuple Tuple of ``(data_line, caplines, barlinecols)``. - data_line : :class:`~matplotlib.lines.Line2D` instance of x, y plot markers and/or line. - caplines : tuple of :class:`~matplotlib.lines.Line2D` instances of the error bar caps. - barlinecols : list of :class:`~matplotlib.collections.LineCollection` with the horizontal and vertical error ranges. has_xerr, has_yerr : bool ``True`` if the errorbar has x/y errors. """ def __init__(self, lines, has_xerr=False, has_yerr=False, **kwargs): self.lines = lines self.has_xerr = has_xerr self.has_yerr = has_yerr Container.__init__(self, lines, **kwargs)
[docs]class StemContainer(Container): """ Container for the artists created in a :meth:`.Axes.stem` plot. The container can be treated like a namedtuple ``(markerline, stemlines, baseline)``. Attributes ---------- markerline : :class:`~matplotlib.lines.Line2D` The artist of the markers at the stem heads. stemlines : list of :class:`~matplotlib.lines.Line2D` The artists of the vertical lines for all stems. baseline : :class:`~matplotlib.lines.Line2D` The artist of the horizontal baseline. """ def __init__(self, markerline_stemlines_baseline, **kwargs): """ Parameters ---------- markerline_stemlines_baseline : tuple Tuple of ``(markerline, stemlines, baseline)``. ``markerline`` contains the `LineCollection` of the markers, ``stemlines`` is a `LineCollection` of the main lines, ``baseline`` is the `Line2D` of the baseline. """ markerline, stemlines, baseline = markerline_stemlines_baseline self.markerline = markerline self.stemlines = stemlines self.baseline = baseline Container.__init__(self, markerline_stemlines_baseline, **kwargs)