matplotlib 3.5.1

BackRef

The underlying storage is made up of two parallel numpy arrays:

These two arrays always have the same length in the first dimension. For example, to represent a cubic curve, you must provide three vertices and three CURVE4 codes.

The code types are:

If codes is None, it is interpreted as a MOVETO followed by a series of LINETO .

Users of Path objects should not access the vertices and codes arrays directly. Instead, they should use iter_segments or cleaned to get the vertex/code pairs. This helps, in particular, to consistently handle the case of codes being None.

Some behavior of Path objects can be controlled by rcParams. See the rcParams whose keys start with 'path.'.

note

The vertices and codes arrays should be treated as immutable -- there are a number of optimizations and assumptions made up front in the constructor that will not change when the data changes.

A series of possibly disconnected, possibly closed, line and curve segments.

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

matplotlib

66 Elements
matplotlib.patches.Polygon.set_xy
matplotlib.patches.BoxStyle
matplotlib.transforms.Transform
matplotlib.lines.Line2D.__init__
matplotlib.axes._axes.Axes.cohere
matplotlib.spines.Spine.__init__
matplotlib.lines.Line2D.get_path
matplotlib.pyplot.plot_date
matplotlib.pyplot.spy
matplotlib.pyplot.plot
matplotlib.path.Path.__deepcopy__
matplotlib.pyplot.psd
matplotlib.pyplot.errorbar
matplotlib.pyplot.axline
matplotlib.path.Path.iter_segments
matplotlib.pyplot.angle_spectrum
matplotlib.patches.Polygon.get_path
matplotlib.axes._axes.Axes.magnitude_spectrum
matplotlib.contour.ContourSet.find_nearest_contour
matplotlib.pyplot.grid
matplotlib.transforms.Transform.transform_path
matplotlib.artist.Line2D.set
matplotlib._enums.JoinStyle
matplotlib.pyplot.cohere
matplotlib.backend_bases.RendererBase.draw_path
matplotlib.path.get_path_collection_extents
matplotlib.pyplot.axvline
matplotlib.artist.Artist.set_clip_path
matplotlib.axes._axes.Axes.plot
matplotlib.markers.MarkerStyle.get_alt_transform
matplotlib.axes._axes.Axes.axhline
matplotlib.pyplot.magnitude_spectrum
matplotlib.patches.PathPatch.__init__
matplotlib.markers.MarkerStyle.get_path
matplotlib.legend.Legend._auto_legend_data
matplotlib.axes._base._AxesBase.grid
matplotlib.transforms.Transform.transform_path_affine
matplotlib.pyplot.phase_spectrum
matplotlib.pyplot.csd
matplotlib.backend_bases.GraphicsContextBase.get_clip_path
matplotlib.axes._axes.Axes.psd
matplotlib.axes._axes.Axes.csd
matplotlib.transforms.Transform.transform_path_non_affine
matplotlib.axes._axes.Axes.plot_date
matplotlib.collections.PathCollection.__init__
matplotlib.path.Path.copy
matplotlib.artist._AxLine.set
matplotlib.axes._axes.Axes.spy
matplotlib.patches.ArrowStyle
matplotlib.patches.ConnectionStyle
matplotlib.axes._axes.Axes.phase_spectrum
matplotlib.axes._axes.Axes.axline
matplotlib.axes._axes.Axes.angle_spectrum
matplotlib.markers
matplotlib.axes._axes.Axes.axvline
matplotlib.patches.BoxStyle._Base
matplotlib.pyplot.axhline
matplotlib.table.Cell.get_path
matplotlib.transforms.TransformedPath
matplotlib.axes._axes.Axes.errorbar
matplotlib.backend_bases.GraphicsContextBase.get_hatch_path
matplotlib.markers.MarkerStyle.get_transform
matplotlib.collections.PathCollection
matplotlib.patches.BoxStyle._Base.transmute
matplotlib.path
matplotlib.markers.MarkerStyle.get_alt_path

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


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