remove venv
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from matplotlib import cbook
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from matplotlib.artist import Artist
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class Container(tuple):
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"""
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Base class for containers.
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Containers are classes that collect semantically related Artists such as
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the bars of a bar plot.
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"""
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def __repr__(self):
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return f"<{type(self).__name__} object of {len(self)} artists>"
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def __new__(cls, *args, **kwargs):
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return tuple.__new__(cls, args[0])
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def __init__(self, kl, label=None):
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self._callbacks = cbook.CallbackRegistry(signals=["pchanged"])
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self._remove_method = None
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self._label = str(label) if label is not None else None
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def remove(self):
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for c in cbook.flatten(
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self, scalarp=lambda x: isinstance(x, Artist)):
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if c is not None:
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c.remove()
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if self._remove_method:
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self._remove_method(self)
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def get_children(self):
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return [child for child in cbook.flatten(self) if child is not None]
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get_label = Artist.get_label
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set_label = Artist.set_label
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add_callback = Artist.add_callback
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remove_callback = Artist.remove_callback
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pchanged = Artist.pchanged
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class BarContainer(Container):
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"""
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Container for the artists of bar plots (e.g. created by `.Axes.bar`).
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The container can be treated as a tuple of the *patches* themselves.
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Additionally, you can access these and further parameters by the
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attributes.
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Attributes
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----------
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patches : list of :class:`~matplotlib.patches.Rectangle`
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The artists of the bars.
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errorbar : None or :class:`~matplotlib.container.ErrorbarContainer`
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A container for the error bar artists if error bars are present.
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*None* otherwise.
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datavalues : None or array-like
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The underlying data values corresponding to the bars.
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orientation : {'vertical', 'horizontal'}, default: None
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If 'vertical', the bars are assumed to be vertical.
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If 'horizontal', the bars are assumed to be horizontal.
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"""
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def __init__(self, patches, errorbar=None, *, datavalues=None,
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orientation=None, **kwargs):
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self.patches = patches
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self.errorbar = errorbar
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self.datavalues = datavalues
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self.orientation = orientation
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super().__init__(patches, **kwargs)
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class ErrorbarContainer(Container):
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"""
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Container for the artists of error bars (e.g. created by `.Axes.errorbar`).
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The container can be treated as the *lines* tuple itself.
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Additionally, you can access these and further parameters by the
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attributes.
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Attributes
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----------
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lines : tuple
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Tuple of ``(data_line, caplines, barlinecols)``.
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- data_line : A `~matplotlib.lines.Line2D` instance of x, y plot markers
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and/or line.
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- caplines : A tuple of `~matplotlib.lines.Line2D` instances of the error
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bar caps.
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- barlinecols : A tuple of `~matplotlib.collections.LineCollection` with the
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horizontal and vertical error ranges.
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has_xerr, has_yerr : bool
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``True`` if the errorbar has x/y errors.
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"""
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def __init__(self, lines, has_xerr=False, has_yerr=False, **kwargs):
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self.lines = lines
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self.has_xerr = has_xerr
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self.has_yerr = has_yerr
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super().__init__(lines, **kwargs)
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class StemContainer(Container):
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"""
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Container for the artists created in a :meth:`.Axes.stem` plot.
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The container can be treated like a namedtuple ``(markerline, stemlines,
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baseline)``.
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Attributes
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----------
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markerline : `~matplotlib.lines.Line2D`
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The artist of the markers at the stem heads.
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stemlines : `~matplotlib.collections.LineCollection`
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The artists of the vertical lines for all stems.
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baseline : `~matplotlib.lines.Line2D`
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The artist of the horizontal baseline.
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"""
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def __init__(self, markerline_stemlines_baseline, **kwargs):
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"""
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Parameters
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----------
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markerline_stemlines_baseline : tuple
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Tuple of ``(markerline, stemlines, baseline)``.
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``markerline`` contains the `.Line2D` of the markers,
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``stemlines`` is a `.LineCollection` of the main lines,
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``baseline`` is the `.Line2D` of the baseline.
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"""
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markerline, stemlines, baseline = markerline_stemlines_baseline
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self.markerline = markerline
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self.stemlines = stemlines
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self.baseline = baseline
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super().__init__(markerline_stemlines_baseline, **kwargs)
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