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

cm (colormap) matplotlib.cm This module provides a large set of colormaps, functions for registering new colormaps and for getting a colormap by name, and a mixin class for adding color mapping functionality. class matplotlib.cm.ScalarMappable(norm=None, cmap=None) Bases: object This is a mixin class to support scalar data to RGBA mapping. The ScalarMappable makes use of data normalization before returning RGBA colors from the given colormap. Parameters: norm : matplotlib.colors.Normalize

The top level matplotlib module matplotlib.use(arg, warn=True, force=False) Set the matplotlib backend to one of the known backends. The argument is case-insensitive. warn specifies whether a warning should be issued if a backend has already been set up. force is an experimental flag that tells matplotlib to attempt to initialize a new backend by reloading the backend module. Note This function must be called before importing pyplot for the first time; or, if you are not using pyplot, it mu

gridspec matplotlib.gridspec gridspec is a module which specifies the location of the subplot in the figure. GridSpec specifies the geometry of the grid that a subplot will be placed. The number of rows and number of columns of the grid need to be set. Optionally, the subplot layout parameters (e.g., left, right, etc.) can be tuned. SubplotSpec specifies the location of the subplot in the given GridSpec. class matplotlib.gridspec.GridSpec(nrows, ncols, left=None, bottom=None, right=Non

mathtext matplotlib.mathtext mathtext is a module for parsing a subset of the TeX math syntax and drawing them to a matplotlib backend. For a tutorial of its usage see Writing mathematical expressions. This document is primarily concerned with implementation details. The module uses pyparsing to parse the TeX expression. The Bakoma distribution of the TeX Computer Modern fonts, and STIX fonts are supported. There is experimental support for using arbitrary fonts, but results may vary withou

font_manager matplotlib.font_manager A module for finding, managing, and using fonts across platforms. This module provides a single FontManager instance that can be shared across backends and platforms. The findfont() function returns the best TrueType (TTF) font file in the local or system font path that matches the specified FontProperties instance. The FontManager also handles Adobe Font Metrics (AFM) font files for use by the PostScript backend. The design is based on the W3C Cascading St

legend and legend_handler matplotlib.legend The legend module defines the Legend class, which is responsible for drawing legends associated with axes and/or figures. Important It is unlikely that you would ever create a Legend instance manually. Most users would normally create a legend via the legend() function. For more details on legends there is also a legend guide. The Legend class can be considered as a container of legend handles and legend texts. Creation of corresponding legend hand

mlab matplotlib.mlab Numerical python functions written for compatability with MATLAB commands with the same names. MATLAB compatible functions cohere() Coherence (normalized cross spectral density) csd() Cross spectral density uing Welch?s average periodogram detrend() Remove the mean or best fit line from an array find() Return the indices where some condition is true; numpy.nonzero is similar but more general. griddata() Interpolate irregularly distributed data to a regular

colorbar matplotlib.colorbar Colorbar toolkit with two classes and a function: ColorbarBase the base class with full colorbar drawing functionality. It can be used as-is to make a colorbar for a given colormap; a mappable object (e.g., image) is not needed. Colorbar the derived class for use with images or contour plots. make_axes() a function for resizing an axes and adding a second axes suitable for a colorbar The colorbar() method uses make_axes() and Colorbar; the colorbar() fu

axis matplotlib.axis Classes for the ticks and x and y axis class matplotlib.axis.Axis(axes, pickradius=15) Bases: matplotlib.artist.Artist Public attributes axes.transData - transform data coords to display coords axes.transAxes - transform axis coords to display coords labelpad - number of points between the axis and its label Init the axis with the parent Axes instance OFFSETTEXTPAD = 3 axis_date(tz=None) Sets up x-axis ticks and labels that treat the x data as dates. tz is a tz