Changes beyond 0.99.x#
The default behavior of
matplotlib.axes.Axes.axis(), and their corresponding pyplot functions, has been changed: when view limits are set explicitly with one of these methods, autoscaling is turned off for the matching axis. A new auto kwarg is available to control this behavior. The limit kwargs have been renamed to left and right instead of xmin and xmax, and bottom and top instead of ymin and ymax. The old names may still be used, however.
There are five new Axes methods with corresponding pyplot functions to facilitate autoscaling, tick location, and tick label formatting, and the general appearance of ticks and tick labels:
matplotlib.axes.Axes.autoscale()turns autoscaling on or off, and applies it.
matplotlib.axes.Axes.margins()sets margins used to autoscale the
matplotlib.axes.Axes.viewLimbased on the
matplotlib.axes.Axes.locator_params()allows one to adjust axes locator parameters such as nbins.
matplotlib.axes.Axes.tick_params()controls direction, size, visibility, and color of ticks and their labels.
matplotlib.axes.Axes.bar()method accepts a error_kw kwarg; it is a dictionary of kwargs to be passed to the errorbar function.
matplotlib.axes.Axes.hist()color kwarg now accepts a sequence of color specs to match a sequence of datasets.
EllipseCollectionhas been changed in two ways:
There is a new units option, 'xy', that scales the ellipse with the data units. This matches the :class:'~matplotlib.patches.Ellipse` scaling.
The height and width kwargs have been changed to specify the height and width, again for consistency with
Ellipse, and to better match their names; previously they specified the half-height and half-width.
There is a new rc parameter
axes.color_cycle, and the color cycle is now independent of the rc parameter
You can now print several figures to one pdf file and modify the document information dictionary of a pdf file. See the docstrings of the class
matplotlib.backends.backend_pdf.PdfPagesfor more information.
The new rc parameter
savefig.extensionsets the filename extension that is used by
matplotlib.figure.Figure.savefig()if its fname argument lacks an extension.
In an effort to simplify the backend API, all clipping rectangles and paths are now passed in using GraphicsContext objects, even on collections and images. Therefore:
draw_path_collection(self, master_transform, cliprect, clippath, clippath_trans, paths, all_transforms, offsets, offsetTrans, facecolors, edgecolors, linewidths, linestyles, antialiaseds, urls) # is now draw_path_collection(self, gc, master_transform, paths, all_transforms, offsets, offsetTrans, facecolors, edgecolors, linewidths, linestyles, antialiaseds, urls) draw_quad_mesh(self, master_transform, cliprect, clippath, clippath_trans, meshWidth, meshHeight, coordinates, offsets, offsetTrans, facecolors, antialiased, showedges) # is now draw_quad_mesh(self, gc, master_transform, meshWidth, meshHeight, coordinates, offsets, offsetTrans, facecolors, antialiased, showedges) draw_image(self, x, y, im, bbox, clippath=None, clippath_trans=None) # is now draw_image(self, gc, x, y, im)
There are four new Axes methods with corresponding pyplot functions that deal with unstructured triangular grids:
matplotlib.axes.Axes.tricontour()draws contour lines on a triangular grid.
matplotlib.axes.Axes.tricontourf()draws filled contours on a triangular grid.
matplotlib.axes.Axes.tripcolor()draws a pseudocolor plot on a triangular grid.
matplotlib.axes.Axes.triplot()draws a triangular grid as lines and/or markers.