dviread matplotlib.dviread An experimental module for reading dvi files output by TeX. Several limitations make this not (currently) useful as a general-purpose dvi preprocessor, but it is currently used by the pdf backend for processing usetex text. Interface: dvi = Dvi(filename, 72) # iterate over pages (but only one page is supported for now): for page in dvi: w, h, d = page.width, page.height, page.descent for x,y,font,glyph,width in page.text: fontname = font.texname

dates matplotlib.dates Matplotlib provides sophisticated date plotting capabilities, standing on the shoulders of python datetime, the add-on modules pytz and dateutil. datetime objects are converted to floating point numbers which represent time in days since 0001-01-01 UTC, plus 1. For example, 0001-01-01, 06:00 is 1.25, not 0.25. The helper functions date2num(), num2date() and drange() are used to facilitate easy conversion to and from datetime and numeric ranges. Note Like Python?s dat

colors For a visual representation of the matplotlib colormaps, see the ?Color? section in the gallery. matplotlib.colors A module for converting numbers or color arguments to RGB or RGBA RGB and RGBA are sequences of, respectively, 3 or 4 floats in the range 0-1. This module includes functions and classes for color specification conversions, and for mapping numbers to colors in a 1-D array of colors called a colormap. Colormapping typically involves two steps: a data array is first mapped ont

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

collections matplotlib.collections Classes for the efficient drawing of large collections of objects that share most properties, e.g., a large number of line segments or polygons. The classes are not meant to be as flexible as their single element counterparts (e.g., you may not be able to select all line styles) but they are meant to be fast for common use cases (e.g., a large set of solid line segemnts) class matplotlib.collections.AsteriskPolygonCollection(numsides, rotation=0, sizes=(1

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

cbook matplotlib.cbook A collection of utility functions and classes. Originally, many (but not all) were from the Python Cookbook ? hence the name cbook. This module is safe to import from anywhere within matplotlib; it imports matplotlib only at runtime. class matplotlib.cbook.Bunch(**kwds) Bases: object Often we want to just collect a bunch of stuff together, naming each item of the bunch; a dictionary?s OK for that, but a small do- nothing class is even handier, and prettier to use. Whe

matplotlib.backend_tools Abstract base classes define the primitives for Tools. These tools are used by matplotlib.backend_managers.ToolManager ToolBase Simple stateless tool ToolToggleBase Tool that has two states, only one Toggle tool can be active at any given time for the same matplotlib.backend_managers.ToolManager class matplotlib.backend_tools.AxisScaleBase(*args, **kwargs) Bases: matplotlib.backend_tools.ToolToggleBase Base Tool to toggle between linear and logarithmic disa

matplotlib.backend_managers ToolManager Class that makes the bridge between user interaction (key press, toolbar clicks, ..) and the actions in response to the user inputs. class matplotlib.backend_managers.ToolEvent(name, sender, tool, data=None) Bases: object Event for tool manipulation (add/remove) class matplotlib.backend_managers.ToolManager(canvas) Bases: object Helper class that groups all the user interactions for a FigureManager Attributes manager: FigureManager keypre

matplotlib.backend_bases Abstract base classes define the primitives that renderers and graphics contexts must implement to serve as a matplotlib backend RendererBase An abstract base class to handle drawing/rendering operations. FigureCanvasBase The abstraction layer that separates the matplotlib.figure.Figure from the backend specific details like a user interface drawing area GraphicsContextBase An abstract base class that provides color, line styles, etc... Event The base class