widgets matplotlib.widgets GUI neutral widgets Widgets that are designed to work for any of the GUI backends. All of these widgets require you to predefine a matplotlib.axes.Axes instance and pass that as the first arg. matplotlib doesn?t try to be too smart with respect to layout ? you will have to figure out how wide and tall you want your Axes to be to accommodate your widget. class matplotlib.widgets.AxesWidget(ax) Bases: matplotlib.widgets.Widget Widget that is connected to a single A


units matplotlib.units The classes here provide support for using custom classes with matplotlib, e.g., those that do not expose the array interface but know how to converter themselves to arrays. It also supoprts classes with units and units conversion. Use cases include converters for custom objects, e.g., a list of datetime objects, as well as for objects that are unit aware. We don?t assume any particular units implementation, rather a units implementation must provide a ConversionInterfac


type1font matplotlib.type1font This module contains a class representing a Type 1 font. This version reads pfa and pfb files and splits them for embedding in pdf files. It also supports SlantFont and ExtendFont transformations, similarly to pdfTeX and friends. There is no support yet for subsetting. Usage: >>> font = Type1Font(filename) >>> clear_part, encrypted_part, finale = font.parts >>> slanted_font = font.transform({'slant': 0.167}) >>> extended_font =


triangular grids matplotlib.tri Unstructured triangular grid functions. class matplotlib.tri.Triangulation(x, y, triangles=None, mask=None) An unstructured triangular grid consisting of npoints points and ntri triangles. The triangles can either be specified by the user or automatically generated using a Delaunay triangulation. Parameters: x, y : array_like of shape (npoints) Coordinates of grid points. triangles : integer array_like of shape (ntri, 3), optional For each triangle, the i


tight_layout matplotlib.tight_layout This module provides routines to adjust subplot params so that subplots are nicely fit in the figure. In doing so, only axis labels, tick labels, axes titles and offsetboxes that are anchored to axes are currently considered. Internally, it assumes that the margins (left_margin, etc.) which are differences between ax.get_tightbbox and ax.bbox are independent of axes position. This may fail if Axes.adjustable is datalim. Also, This will fail for some cases (


ticker matplotlib.ticker Tick locating and formatting This module contains classes to support completely configurable tick locating and formatting. Although the locators know nothing about major or minor ticks, they are used by the Axis class to support major and minor tick locating and formatting. Generic tick locators and formatters are provided, as well as domain specific custom ones.. Default Formatter The default formatter identifies when the x-data being plotted is a small range on top


text matplotlib.text Classes for including text in a figure. class matplotlib.text.Annotation(s, xy, xytext=None, xycoords='data', textcoords=None, arrowprops=None, annotation_clip=None, **kwargs) Bases: matplotlib.text.Text, matplotlib.text._AnnotationBase Annotate the point xy with text s. Additional kwargs are passed to Text. Parameters: s : str The text of the annotation xy : iterable Length 2 sequence specifying the (x,y) point to annotate xytext : iterable, optional Length 2 seq


style matplotlib.style matplotlib.style.context(style, after_reset=False) Context manager for using style settings temporarily. Parameters: style : str, dict, or list A style specification. Valid options are: str The name of a style or a path/URL to a style file. For a list of available style names, see style.available. dict Dictionary with valid key/value pairs for matplotlib.rcParams. list A list of style specifiers (str or dict) applied from first to last in the list. after_reset : boo


spines matplotlib.spines class matplotlib.spines.Spine(axes, spine_type, path, **kwargs) Bases: matplotlib.patches.Patch an axis spine ? the line noting the data area boundaries Spines are the lines connecting the axis tick marks and noting the boundaries of the data area. They can be placed at arbitrary positions. See function:set_position for more information. The default position is ('outward',0). Spines are subclasses of class:Patch, and inherit much of their behavior. Spines draw a lin


scale matplotlib.scale class matplotlib.scale.InvertedLog10Transform(shorthand_name=None) Bases: matplotlib.transforms.Transform Creates a new TransformNode. shorthand_name - a string representing the ?name? of this transform. The name carries no significance other than to improve the readability of str(transform) when DEBUG=True. base = 10.0 has_inverse = True input_dims = 1 inverted() is_separable = True output_dims = 1 transform_non_affine(a) class matplotlib.sc