Artist.update has return valueLegend initializers gain edgecolor and facecolor kwargsdraw_image backend APImatplotlib.ticker.LinearLocator algorithm updatematplotlib.ticker.LogLocator gains numticks kwargmatplotlib.cbook.ls_mapper, added ls_mapper_rAxes.get_childrenNone as x or y value in ax.plotargs and kwargs from MicrosecondLocator.__call__ValueError for the MicrosecondLocator and YearLocatorImage from main namespacelod from ArtistLena images from sample_data'faceted' as a valid value for shading in tri.tripcolorfaceted kwarg from scatterset_colorbar method from ScalarMappabletesting.image_util.pymlab.FIFOBuffermlab.prepcaNavigationToolbar2QTAggLog of changes to matplotlib that affect the outward-facing API. If updating matplotlib breaks your scripts, this list may help you figure out what caused the breakage and how to fix it by updating your code.
For new features that were added to matplotlib, please see What’s new in matplotlib.
The axisbg and axis_bgcolor properties on Axes have been
deprecated in favor of facecolor.
The GDK and GTK backends have been deprecated. These obsolete backends
allow figures to be rendered via the GDK API to files and GTK2 figures.
They are untested and known to be broken, and their use has been
discouraged for some time. Instead, use the GTKAgg and GTKCairo
backends for rendering to GTK2 windows.
The WX backend has been deprecated. It is untested, and its
use has been discouraged for some time. Instead, use the WXAgg
backend for rendering figures to WX windows.
The deprecated and not fully functional CocoaAgg backend has been removed.
Artist.update has return value¶The methods matplotlib.artist.Artist.set,
matplotlib.Artist.update, and the function matplotlib.artist.setp
now use a common codepath to look up how to update the given artist
properties (either using the setter methods or an attribute/property).
The behavior of matplotlib.Artist.update is slightly changed to
return a list of the values returned from the setter methods to avoid
changing the API of matplotlib.Artist.set and
matplotlib.artist.setp.
The keys passed into matplotlib.Artist.update are now converted to
lower case before being processed, to match the behavior of
matplotlib.Artist.set and matplotlib.artist.setp. This should not
break any user code because there are no set methods with capitals in
their names, but this puts a constraint on naming properties in the future.
Legend initializers gain edgecolor and facecolor kwargs¶The Legend background patch (or ‘frame’)
can have its edgecolor and facecolor determined by the
corresponding keyword arguments to the matplotlib.legend.Legend
initializer, or to any of the methods or functions that call that
initializer. If left to their default values of None, their values
will be taken from matplotlib.rcParams. The previously-existing
framealpha kwarg still controls the alpha transparency of the
patch.
Colorbrewer’s qualitative/discrete colormaps (“Accent”, “Dark2”, “Paired”,
“Pastel1”, “Pastel2”, “Set1”, “Set2”, “Set3”) are now implemented as
ListedColormap instead of LinearSegmentedColormap.
To use these for images where categories are specified as integers, for instance, use:
plt.imshow(x, cmap='Dark2', norm=colors.NoNorm())
draw_image backend API¶The draw_image method implemented by backends has changed its interface.
This change is only relevant if the backend declares that it is able
to transform images by returning True from option_scale_image.
See the draw_image docstring for more information.
matplotlib.ticker.LinearLocator algorithm update¶The matplotlib.ticker.LinearLocator is used to define the range and
location of axis ticks when the user wants an exact number of ticks.
LinearLocator thus differs from the default locator MaxNLocator,
for which the user specifies a maximum number of intervals rather than
a precise number of ticks.
The view range algorithm in matplotlib.ticker.LinearLocator has been
changed so that more convenient tick locations are chosen. The new algorithm
returns a plot view range that is a multiple of the user-requested number of
ticks. This ensures tick marks will be located at whole integers more
consistently. For example, when both y-axes of a``twinx`` plot use
matplotlib.ticker.LinearLocator with the same number of ticks,
their y-tick locations and grid lines will coincide.
matplotlib.ticker.LogLocator gains numticks kwarg¶The maximum number of ticks generated by the
LogLocator can now be controlled explicitly
via setting the new ‘numticks’ kwarg to an integer. By default
the kwarg is None which internally sets it to the ‘auto’ string,
triggering a new algorithm for adjusting the maximum according
to the axis length relative to the ticklabel font size.
Matplotlib has both a 2D and a 3D quiver function. These changes
affect only the 3D function and make the default behavior of the 3D
function match the 2D version. There are two changes:
normalize keyword, which defaults to False.pivot keyword now defaults to tail instead of
tip. This was done in order to match the default behavior of
the 2D quiver function.To obtain the previous behavior with the 3D quiver function, one can call the function with
ax.quiver(x, y, z, u, v, w, normalize=True, pivot='tip')
where “ax” is an Axes3d object created with something like
import mpl_toolkits.mplot3d.axes3d
ax = plt.sublot(111, projection='3d')
autorange behavior in boxplots¶Prior to v1.5.2, the whiskers of boxplots would extend to the mininum and maximum values if the quartiles were all equal (i.e., Q1 = median = Q3). This behavior has been disabled by default to restore consistency with other plotting packages.
To restore the old behavior, simply set autorange=True when
calling plt.boxplot.
matplotlib.cbook.ls_mapper, added ls_mapper_r¶Formerly, matplotlib.cbook.ls_mapper was a dictionary with
the long-form line-style names ("solid") as keys and the short
forms ("-") as values. This long-to-short mapping is now done
by ls_mapper_r, and the short-to-long mapping is done by the
ls_mapper.
This was done to prevent an Artist that is already associated with an Axes from being moved/added to a different Axes. This was never supported as it causes havoc with the transform stack. The apparent support for this (as it did not raise an exception) was the source of multiple bug reports and questions on SO.
For almost all use-cases, the assignment of the axes to an artist should be
taken care of by the axes as part of the Axes.add_* method, hence the
deprecation of {get,set}_axes.
Removing the set_axes method will also remove the ‘axes’ line from
the ACCEPTS kwarg tables (assuming that the removal date gets here
before that gets overhauled).
Tightened validation so that only {‘tip’, ‘tail’, ‘mid’, and ‘middle’}
(but any capitalization) are valid values for the ‘pivot’ kwarg in
the Quiver.__init__ (and hence Axes.quiver and
plt.quiver which both fully delegate to Quiver). Previously any
input matching ‘mid.*’ would be interpreted as ‘middle’, ‘tip.*’ as
‘tip’ and any string not matching one of those patterns as ‘tail’.
The value of Quiver.pivot is normalized to be in the set {‘tip’,
‘tail’, ‘middle’} in Quiver.__init__.
Axes.get_children¶The artist order returned by Axes.get_children did not
match the one used by Axes.draw. They now use the same
order, as Axes.draw now calls Axes.get_children.
The default behaviour of contour() and
contourf() when using a masked array is now determined
by the new keyword argument corner_mask, or if this is not specified then
the new rcParam contour.corner_mask instead. The new default behaviour is
equivalent to using corner_mask=True; the previous behaviour can be obtained
using corner_mask=False or by changing the rcParam. The example
http://matplotlib.org/examples/pylab_examples/contour_corner_mask.html
demonstrates the difference. Use of the old contouring algorithm, which is
obtained with corner_mask='legacy', is now deprecated.
Contour labels may now appear in different places than in earlier versions of matplotlib.
In addition, the keyword argument nchunk now applies to
contour() as well as
contourf(), and it subdivides the domain into
subdomains of exactly nchunk by nchunk quads, whereas previously it was
only roughly nchunk by nchunk quads.
The C/C++ object that performs contour calculations used to be stored in the public attribute QuadContourSet.Cntr, but is now stored in a private attribute and should not be accessed by end users.
This was a bug fix targeted at making the api for Locators more consistent.
In the old behavior, only locators of type MaxNLocator have set_params() defined, causing its use on any other Locator to raise an AttributeError ( aside: set_params(args) is a function that sets the parameters of a Locator instance to be as specified within args). The fix involves moving set_params() to the Locator class such that all subtypes will have this function defined.
Since each of the Locator subtypes have their own modifiable parameters, a universal set_params() in Locator isn’t ideal. Instead, a default no-operation function that raises a warning is implemented in Locator. Subtypes extending Locator will then override with their own implementations. Subtypes that do not have a need for set_params() will fall back onto their parent’s implementation, which raises a warning as intended.
In the new behavior, Locator instances will not raise an AttributeError when set_params() is called. For Locators that do not implement set_params(), the default implementation in Locator is used.
None as x or y value in ax.plot¶Do not allow None as a valid input for the x or y args in
ax.plot. This may break some user code, but this was never officially
supported (ex documented) and allowing None objects through can lead
to confusing exceptions downstream.
To create an empty line use
ln1, = ax.plot([], [], ...)
ln2, = ax.plot([], ...)
In either case to update the data in the Line2D object you must update
both the x and y data.
args and kwargs from MicrosecondLocator.__call__¶The call signature of __call__()
has changed from __call__(self, *args, **kwargs) to __call__(self).
This is consistent with the superclass Locator
and also all the other Locators derived from this superclass.
ValueError for the MicrosecondLocator and YearLocator¶The MicrosecondLocator and
YearLocator objects when called will return
an empty list if the axes have no data or the view has no interval.
Previously, they raised a ValueError. This is consistent with all
the Date Locators.
The call signature was OffsetBox.DrawingArea(..., clip=True) but nothing
was done with the clip argument. The object did not do any clipping
regardless of that parameter. Now the object can and does clip the
child Artists if they are set to be clipped.
You can turn off the clipping on a per-child basis using
child.set_clip_on(False).
Add salt to the hash used to determine the id of the clipPath
nodes. This is to avoid conflicts when two svg documents with the same
clip path are included in the same document (see
https://github.com/ipython/ipython/issues/8133 and
https://github.com/matplotlib/matplotlib/issues/4349 ), however this
means that the svg output is no longer deterministic if the same
figure is saved twice. It is not expected that this will affect any
users as the current ids are generated from an md5 hash of properties
of the clip path and any user would have a very difficult time
anticipating the value of the id.
When drawing circle markers above some marker size (previously 6.0) the path used to generate the marker was snapped to pixel centers. However, this ends up distorting the marker away from a circle. By setting the snap threshold to inf snapping is never done on circles.
This change broke several tests, but is an improvement.
Previously the ‘get_position’ method on Text would strip away unit information even though the units were still present. There was no inherent need to do this, so it has been changed so that unit data (if present) will be preserved. Essentially a call to ‘get_position’ will return the exact value from a call to ‘set_position’.
If you wish to get the old behaviour, then you can use the new method called ‘get_unitless_position’.
Interactive pan and zoom were previously implemented using a Cartesian-specific
algorithm that was not necessarily applicable to custom Axes. Three new private
methods, _get_view(),
_set_view(), and
_set_view_from_bbox(), allow for custom
Axes classes to override the pan and zoom algorithms. Implementors of
custom Axes who override these methods may provide suitable behaviour for
both pan and zoom as well as the view navigation buttons on the interactive
toolbars.
The spacing commands in mathtext have been changed to more closely match vanilla TeX.
The extra space that appeared after subscripts and superscripts has been removed.
In #2351 for 1.4.0 the behavior of [‘axes points’, ‘axes pixel’, ‘figure points’, ‘figure pixel’] as coordinates was change to no longer wrap for negative values. In 1.4.3 this change was reverted for ‘axes points’ and ‘axes pixel’ and in addition caused ‘axes fraction’ to wrap. For 1.5 the behavior has been reverted to as it was in 1.4.0-1.4.2, no wrapping for any type of coordinate.
GraphicsContextBase.set_graylevel¶The GraphicsContextBase.set_graylevel function has been deprecated in 1.5 and
will be removed in 1.6. It has been unused. The
GraphicsContextBase.set_foreground could be used instead.
The idle_event was broken or missing in most backends and causes spurious
warnings in some cases, and its use in creating animations is now obsolete due
to the animations module. Therefore code involving it has been removed from all
but the wx backend (where it partially works), and its use is deprecated. The
animations module may be used instead to create animations.
color_cycle deprecated¶In light of the new property cycling feature, the Axes method set_color_cycle is now deprecated. Calling this method will replace the current property cycle with one that cycles just the given colors.
Similarly, the rc parameter axes.color_cycle is also deprecated in lieu of the new axes.prop_cycle parameter. Having both parameters in the same rc file is not recommended as the result cannot be predicted. For compatibility, setting axes.color_cycle will replace the cycler in axes.prop_cycle with a color cycle. Accessing axes.color_cycle will return just the color portion of the property cycle, if it exists.
Timeline for removal has not been set.
The version of jquery bundled with the webagg backend has been upgraded from 1.7.1 to 1.11.3. If you are using the version of jquery bundled with webagg you will need to update your html files as such
- <script src="_static/jquery/js/jquery-1.7.1.min.js"></script>
+ <script src="_static/jquery/js/jquery-1.11.3.min.js"></script>
Image from main namespace¶Image was imported from PIL/pillow to test if PIL is available, but
there is no reason to keep Image in the namespace once the availability
has been determined.
lod from Artist¶Removed the method set_lod and all references to the attribute _lod as the are not used anywhere else in the code base. It appears to be a feature stub that was never built out.
Lena images from sample_data¶The lena.png and lena.jpg images have been removed from
matplotlib’s sample_data directory. The images are also no longer
available from matplotlib.cbook.get_sample_data. We suggest using
matplotlib.cbook.get_sample_data('grace_hopper.png') or
matplotlib.cbook.get_sample_data('grace_hopper.jpg') instead.
Removed handling of loc as a positional argument to Legend
Remove code to allow legend handlers to be callable. They must now
implement a method legend_artist.
Removed method set_scale. This is now handled via a private method which
should not be used directly by users. It is called via Axes.set_{x,y}scale
which takes care of ensuring the related changes are also made to the Axes
object.
Removed functions with ambiguous argument order from finance.py
Removed textcoords and xytext proprieties from Annotation objects.
Both ipython_console_highlighting and ipython_directive have been
moved to IPython.
Change your import from ‘matplotlib.sphinxext.ipython_directive’ to ‘IPython.sphinxext.ipython_directive’ and from ‘matplotlib.sphinxext.ipython_directive’ to ‘IPython.sphinxext.ipython_directive’
Deprecated in 2005, use set_color
'faceted' as a valid value for shading in tri.tripcolor¶Use edgecolor instead. Added validation on shading to
only be valid values.
faceted kwarg from scatter¶Remove support for the faceted kwarg. This was deprecated in
d48b34288e9651ff95c3b8a071ef5ac5cf50bae7 (2008-04-18!) and replaced by
edgecolor.
set_colorbar method from ScalarMappable¶Remove set_colorbar method, use colorbar attribute directly.
- remove
get_proxy_renderermethod fromAbstarctPathEffectclass- remove
patch_alphaandoffset_xyfromSimplePatchShadow
testing.image_util.py¶Contained only a no-longer used port of functionality from PIL
mlab.FIFOBuffer¶Not used internally and not part of core mission of mpl.
mlab.prepca¶Deprecated in 2009.
Remove the module matplotlib.mpl. Deprecated in 1.3 by
PR #1670 and commit 78ce67d161625833cacff23cfe5d74920248c5b2
A major refactoring of the axes module was made. The axes module has been split into smaller modules:
- the
_basemodule, which contains a new private _AxesBase class. This class contains all methods except plotting and labelling methods.- the
axesmodule, which contains the Axes class. This class inherits from _AxesBase, and contains all plotting and labelling methods.- the
_subplotmodule, with all the classes concerning subplotting.
There are a couple of things that do not exists in the axes module’s
namespace anymore. If you use them, you need to import them from their
original location:
- math ->
import math- ma ->
from numpy import ma- cbook ->
from matplotlib import cbook- docstring ->
from matplotlib import docstring- is_sequence_of_strings ->
from matplotlib.cbook import is_sequence_of_strings- is_string_like ->
from matplotlib.cbook import is_string_like- iterable ->
from matplotlib.cbook import iterable- itertools ->
import itertools- martist ->
from matplotlib import artist as martist- matplotlib ->
import matplotlib- mcoll ->
from matplotlib import collections as mcoll- mcolors ->
from matplotlib import colors as mcolors- mcontour ->
from matplotlib import contour as mcontour- mpatches ->
from matplotlib import patches as mpatches- mpath ->
from matplotlib import path as mpath- mquiver ->
from matplotlib import quiver as mquiver- mstack ->
from matplotlib import stack as mstack- mstream ->
from matplotlib import stream as mstream- mtable ->
from matplotlib import table as mtable
As part of the refactoring to enable Qt5 support, the module
matplotlib.backends.qt4_compat was renamed to
matplotlib.qt_compat. qt4_compat is deprecated in 1.4 and
will be removed in 1.5.
The errorbar() method has been changed such that
the upper and lower limits (lolims, uplims, xlolims, xuplims) now
point in the correct direction.
The fmt kwarg for plot() defaults.
A bug has been fixed in the path effects rendering of fonts, which now means that the font size is consistent with non-path effect fonts. See https://github.com/matplotlib/matplotlib/issues/2889 for more detail.
The Sphinx extensions ipython_directive and
ipython_console_highlighting have been moved to the IPython
project itself. While they remain in matplotlib for this release,
they have been deprecated. Update your extensions in conf.py to
point to IPython.sphinxext.ipython_directive instead of
matplotlib.sphinxext.ipython_directive.
In finance, almost all functions have been deprecated
and replaced with a pair of functions name *_ochl and *_ohlc.
The former is the ‘open-close-high-low’ order of quotes used
previously in this module, and the latter is the
‘open-high-low-close’ order that is standard in finance.
For consistency the face_alpha keyword to
matplotlib.patheffects.SimplePatchShadow has been deprecated in
favour of the alpha keyword. Similarly, the keyword offset_xy is now
named offset across all _Base` has
been renamed to matplotlib.patheffects.AbstractPathEffect.
matplotlib.patheffect.ProxyRenderer has been renamed to
matplotlib.patheffects.PathEffectRenderer and is now a full
RendererBase subclass.
The artist used to draw the outline of a colorbar has been changed
from a matplotlib.lines.Line2D to matplotlib.patches.Polygon,
thus colorbar.ColorbarBase.outline is now a
matplotlib.patches.Polygon object.
The legend handler interface has changed from a callable, to any object
which implements the legend_artists method (a deprecation phase will
see this interface be maintained for v1.4). See
Legend guide for further details. Further legend changes
include:
matplotlib.axes.Axes._get_legend_handles()now returns a generator of handles, rather than a list.- The
legend()function’s “loc” positional argument has been deprecated. Use the “loc” keyword instead.
The rcParams savefig.transparent has been added to control
default transparency when saving figures.
Slightly refactored the Annotation family. The text location in
Annotation is now handled entirely handled by the underlying Text
object so set_position works as expected. The attributes xytext and
textcoords have been deprecated in favor of xyann and anncoords so
that Annotation and AnnotaionBbox can share a common sensibly named
api for getting/setting the location of the text or box.
xyann-> set the location of the annotationxy-> set where the arrow points toanncoords-> set the units of the annotation locationxycoords-> set the units of the point locationset_position()->Annotationonly set location of annotation
matplotlib.mlab.specgram, matplotlib.mlab.psd, matplotlib.mlab.csd,
matplotlib.mlab.cohere, matplotlib.mlab.cohere_pairs,
matplotlib.pyplot.specgram, matplotlib.pyplot.psd,
matplotlib.pyplot.csd, and matplotlib.pyplot.cohere now raise
ValueError where they previously raised AssertionError.
For matplotlib.mlab.psd, matplotlib.mlab.csd,
matplotlib.mlab.cohere, matplotlib.mlab.cohere_pairs,
matplotlib.pyplot.specgram, matplotlib.pyplot.psd,
matplotlib.pyplot.csd, and matplotlib.pyplot.cohere, in cases
where a shape (n, 1) array is returned, this is now converted to a (n, )
array. Previously, (n, m) arrays were averaged to an (n, ) array, but
(n, 1) arrays were returend unchanged. This change makes the dimensions
consistent in both cases.
Added the rcParam axes.fromatter.useoffset to control the default value
of useOffset in ticker.ScalarFormatter
Added Formatter sub-class StrMethodFormatter which
does the exact same thing as FormatStrFormatter, but for new-style
formatting strings.
Deprecated matplotlib.testing.image_util and the only function within,
matplotlib.testing.image_util.autocontrast. These will be removed
completely in v1.5.0.
The fmt argument of plot_date() has been
changed from bo to just o, so color cycling can happen by default.
Removed the class FigureManagerQTAgg and deprecated NavigationToolbar2QTAgg
which will be removed in 1.5.
Removed formerly public (non-prefixed) attributes rect and
drawRect from FigureCanvasQTAgg; they were always an
implementation detail of the (preserved) drawRectangle() function.
The function signatures of tight_bbox.adjust_bbox and
tight_bbox.process_figure_for_rasterizing have been changed. A new
fixed_dpi parameter allows for overriding the figure.dpi setting
instead of trying to deduce the intended behaviour from the file format.
Added support for horizontal/vertical axes padding to
mpl_toolkits.axes_grid1.ImageGrid — argument axes_pad can now be
tuple-like if separate axis padding is required.
The original behavior is preserved.
Added support for skewed transforms to matplotlib.transforms.Affine2D,
which can be created using the skew and skew_deg methods.
Added clockwise parameter to control sectors direction in axes.pie
In matplotlib.lines.Line2D the markevery functionality has been extended.
Previously an integer start-index and stride-length could be specified using
either a two-element-list or a two-element-tuple. Now this can only be done
using a two-element-tuple. If a two-element-list is used then it will be
treated as numpy fancy indexing and only the two markers corresponding to the
given indexes will be shown.
removed prop kwarg from mpl_toolkits.axes_grid1.anchored_artists.AnchoredSizeBar
call. It was passed through to the base-class __init__ and is only used for
setting padding. Now fontproperties (which is what is really used to set
the font properties of AnchoredSizeBar) is passed through in place of prop.
If fontpropreties is not passed in, but prop is, then prop is used inplace
of fontpropreties. If both are passed in, prop is silently ignored.
The use of the index 0 in plt.subplot and related commands is
deprecated. Due to a lack of validation calling plt.subplots(2, 2,
0) does not raise an exception, but puts an axes in the _last_
position. This is due to the indexing in subplot being 1-based (to
mirror MATLAB) so before indexing into the GridSpec object used to
determine where the axes should go, 1 is subtracted off. Passing in
0 results in passing -1 to GridSpec which results in getting the
last position back. Even though this behavior is clearly wrong and
not intended, we are going through a deprecation cycle in an
abundance of caution that any users are exploiting this ‘feature’.
The use of 0 as an index will raise a warning in 1.4 and an
exception in 1.5.
Clipping is now off by default on offset boxes.
matplotlib now uses a less-aggressive call to gc.collect(1) when
closing figures to avoid major delays with large numbers of user objects
in memory.
The default clip value of all pie artists now defaults to False.
mlab.levypdf. The code raised a numpy error (and has for
a long time) and was not the standard form of the Levy distribution.
scipy.stats.levy should be used insteadIt is rare that we make an API change in a bugfix release, however, for 1.3.1 since 1.3.0 the following change was made:
text.Text.cached (used to cache font objects) has been made into a
private variable. Among the obvious encapsulation benefit, this
removes this confusing-looking member from the documentation.hist() now always returns bin
occupancies as an array of type float. Previously, it was sometimes
an array of type int, depending on the call.The following items that were deprecated in version 1.2 or earlier have now been removed completely.
The Qt 3.x backends (
qtandqtagg) have been removed in favor of the Qt 4.x backends (qt4andqt4agg).The FltkAgg and Emf backends have been removed.
The
matplotlib.nxutilsmodule has been removed. Use the functionality onmatplotlib.path.Path.contains_pointand friends instead.Instead of
axes.Axes.get_frame, useaxes.Axes.patch.The following
kwargsto thelegendfunction have been renamed:
pad->borderpadlabelsep->labelspacinghandlelen->handlelengthhandletextsep->handletextpadaxespad->borderaxespadRelated to this, the following rcParams have been removed:
legend.pad,legend.labelsep,legend.handlelen,legend.handletextsepandlegend.axespadFor the
histfunction, instead ofwidth, userwidth(relative width).On
patches.Circle, theresolutionkwarg has been removed. For a circle made up of line segments, usepatches.CirclePolygon.The printing functions in the Wx backend have been removed due to the burden of keeping them up-to-date.
mlab.liaupunovhas been removed.
mlab.save,mlab.load,pylab.saveandpylab.loadhave been removed. We recommend usingnumpy.savetxtandnumpy.loadtxtinstead.
widgets.HorizontalSpanSelectorhas been removed. Usewidgets.SpanSelectorinstead.
The CocoaAgg backend has been deprecated, with the possibility for deletion or resurrection in a future release.
The top-level functions in matplotlib.path that are implemented in
C++ were never meant to be public. Instead, users should use the
Pythonic wrappers for them in the path.Path and
collections.Collection classes. Use the following mapping to update
your code:
point_in_path->path.Path.contains_pointget_path_extents->path.Path.get_extentspoint_in_path_collection->collection.Collection.containspath_in_path->path.Path.contains_pathpath_intersects_path->path.Path.intersects_pathconvert_path_to_polygons->path.Path.to_polygonscleanup_path->path.Path.cleanedpoints_in_path->path.Path.contains_pointsclip_path_to_rect->path.Path.clip_to_bbox
matplotlib.colors.normalize and matplotlib.colors.no_norm have
been deprecated in favour of matplotlib.colors.Normalize and
matplotlib.colors.NoNorm respectively.
The ScalarMappable class’ set_colorbar is now
deprecated. Instead, the
matplotlib.cm.ScalarMappable.colorbar attribute should be
used. In previous matplotlib versions this attribute was an
undocumented tuple of (colorbar_instance, colorbar_axes) but is
now just colorbar_instance. To get the colorbar axes it is
possible to just use the
ax attribute on a colorbar
instance.
The mpl module is now deprecated. Those who relied on this
module should transition to simply using import matplotlib as mpl.
Patch now fully supports using RGBA values for
its facecolor and edgecolor attributes, which enables faces and
edges to have different alpha values. If the
Patch object’s alpha attribute is set to
anything other than None, that value will override any alpha-channel
value in both the face and edge colors. Previously, if
Patch had alpha=None, the alpha component
of edgecolor would be applied to both the edge and face.
The optional isRGB argument to
set_foreground() (and
the other GraphicsContext classes that descend from it) has been renamed to
isRGBA, and should now only be set to True if the fg color
argument is known to be an RGBA tuple.
For Patch, the capstyle used is now
butt, to be consistent with the default for most other objects, and to
avoid problems with non-solid linestyle appearing solid when using a
large linewidth. Previously, Patch used
capstyle='projecting'.
Path objects can now be marked as readonly by passing
readonly=True to its constructor. The built-in path singletons,
obtained through Path.unit* class methods return readonly paths.
If you have code that modified these, you will need to make a
deepcopy first, using either:
import copy
path = copy.deepcopy(Path.unit_circle())
# or
path = Path.unit_circle().deepcopy()
Deep copying a Path always creates an editable (i.e. non-readonly)
Path.
The list at Path.NUM_VERTICES was replaced by a dictionary mapping
Path codes to the number of expected vertices at
NUM_VERTICES_FOR_CODE.
To support XKCD style plots, the matplotlib.path.cleanup_path()
method’s signature was updated to require a sketch argument. Users of
matplotlib.path.cleanup_path() are encouraged to use the new
cleaned() Path method.
Data limits on a plot now start from a state of having “null”
limits, rather than limits in the range (0, 1). This has an effect
on artists that only control limits in one direction, such as
axvline and axhline, since their limits will not longer also
include the range (0, 1). This fixes some problems where the
computed limits would be dependent on the order in which artists
were added to the axes.
Fixed a bug in setting the position for the right/top spine with data position type. Previously, it would draw the right or top spine at +1 data offset.
In FancyArrow, the default arrow head
width, head_width, has been made larger to produce a visible
arrow head. The new value of this kwarg is head_width = 20 *
width.
It is now possible to provide number of levels + 1 colors in the case of
extend='both' for contourf (or just number of levels colors for an
extend value min or max) such that the resulting colormap’s
set_under and set_over are defined appropriately. Any other number
of colors will continue to behave as before (if more colors are provided
than levels, the colors will be unused). A similar change has been applied
to contour, where extend='both' would expect number of levels + 2
colors.
A new keyword extendrect in colorbar() and
ColorbarBase allows one to control the shape
of colorbar extensions.
The extension of MultiCursor to both vertical
(default) and/or horizontal cursor implied that self.line is replaced
by self.vline for vertical cursors lines and self.hline is added
for the horizontal cursors lines.
On POSIX platforms, the report_memory() function
raises NotImplementedError instead of OSError if the
ps command cannot be run.
The matplotlib.cbook.check_output() function has been moved to
matplotlib.compat.subprocess().
matplotlibrc configuration file is now
located in config/matplotlib/matplotlibrc to conform to the
XDG Base Directory Specification.font.* rcParams now affect only text objects created after the
rcParam has been set, and will not retroactively affect already
existing text objects. This brings their behavior in line with most
other rcParams.grid() in
plotfile(). To draw the axes grid, set the
axes.grid rcParam to True, or explicitly call
grid().The classic option of the rc parameter toolbar is deprecated
and will be removed in the next release.
The isvector() method has been removed since it
is no longer functional.
The rasterization_zorder property on Axes a
zorder below which artists are rasterized. This has defaulted to
-30000.0, but it now defaults to None, meaning no artists will be
rasterized. In order to rasterize artists below a given zorder
value, set_rasterization_zorder must be explicitly called.
In scatter(), and scatter,
when specifying a marker using a tuple, the angle is now specified
in degrees, not radians.
Using twinx() or
twiny() no longer overrides the current locaters
and formatters on the axes.
In contourf(), the handling of the extend
kwarg has changed. Formerly, the extended ranges were mapped
after to 0, 1 after being normed, so that they always corresponded
to the extreme values of the colormap. Now they are mapped
outside this range so that they correspond to the special
colormap values determined by the
set_under() and
set_over() methods, which
default to the colormap end points.
The new rc parameter savefig.format replaces cairo.format and
savefig.extension, and sets the default file format used by
matplotlib.figure.Figure.savefig().
In pie() and pie(), one can
now set the radius of the pie; setting the radius to ‘None’ (the default
value), will result in a pie with a radius of 1 as before.
Use of projection_factory() is now deprecated
in favour of axes class identification using
process_projection_requirements() followed by
direct axes class invocation (at the time of writing, functions which do this
are: add_axes(),
add_subplot() and
gca()). Therefore:
key = figure._make_key(*args, **kwargs)
ispolar = kwargs.pop('polar', False)
projection = kwargs.pop('projection', None)
if ispolar:
if projection is not None and projection != 'polar':
raise ValueError('polar and projection args are inconsistent')
projection = 'polar'
ax = projection_factory(projection, self, rect, **kwargs)
key = self._make_key(*args, **kwargs)
# is now
projection_class, kwargs, key = \
process_projection_requirements(self, *args, **kwargs)
ax = projection_class(self, rect, **kwargs)
This change means that third party objects can expose themselves as
matplotlib axes by providing a _as_mpl_axes method. See
Developer’s guide for creating scales and transformation for more detail.
A new keyword extendfrac in colorbar() and
ColorbarBase allows one to control the size of
the triangular minimum and maximum extensions on colorbars.
A new keyword capthick in errorbar() has been
added as an intuitive alias to the markeredgewidth and mew keyword
arguments, which indirectly controlled the thickness of the caps on
the errorbars. For backwards compatibility, specifying either of the
original keyword arguments will override any value provided by
capthick.
Transform subclassing behaviour is now subtly changed. If your transform
implements a non-affine transformation, then it should override the
transform_non_affine method, rather than the generic transform method.
Previously transforms would define transform and then copy the
method into transform_non_affine:
class MyTransform(mtrans.Transform):
def transform(self, xy):
...
transform_non_affine = transform
This approach will no longer function correctly and should be changed to:
class MyTransform(mtrans.Transform):
def transform_non_affine(self, xy):
...
Artists no longer have x_isdata or y_isdata attributes; instead
any artist’s transform can be interrogated with
artist_instance.get_transform().contains_branch(ax.transData)
Lines added to an axes now take into account their transform when updating the data and view limits. This means transforms can now be used as a pre-transform. For instance:
>>> import matplotlib.pyplot as plt
>>> import matplotlib.transforms as mtrans
>>> ax = plt.axes()
>>> ax.plot(range(10), transform=mtrans.Affine2D().scale(10) + ax.transData)
>>> print(ax.viewLim)
Bbox('array([[ 0., 0.],\n [ 90., 90.]])')
One can now easily get a transform which goes from one transform’s coordinate system to another, in an optimized way, using the new subtract method on a transform. For instance, to go from data coordinates to axes coordinates:
>>> import matplotlib.pyplot as plt
>>> ax = plt.axes()
>>> data2ax = ax.transData - ax.transAxes
>>> print(ax.transData.depth, ax.transAxes.depth)
3, 1
>>> print(data2ax.depth)
2
for versions before 1.2 this could only be achieved in a sub-optimal way,
using ax.transData + ax.transAxes.inverted() (depth is a new concept,
but had it existed it would return 4 for this example).
twinx and twiny now returns an instance of SubplotBase if
parent axes is an instance of SubplotBase.
All Qt3-based backends are now deprecated due to the lack of py3k bindings. Qt and QtAgg backends will continue to work in v1.2.x for py2.6 and py2.7. It is anticipated that the Qt3 support will be completely removed for the next release.
ColorConverter,
Colormap and
Normalize now subclasses object
ContourSet instances no longer have a transform attribute. Instead,
access the transform with the get_transform method.
matplotlib.sankey.Sankey for generating Sankey diagrams.imshow(), setting interpolation to ‘nearest’
will now always mean that the nearest-neighbor interpolation is performed.
If you want the no-op interpolation to be performed, choose ‘none’.scatter() or just for
plot(). This is now no longer the case. This merge
did result in a conflict. The string ‘d’ now means “thin diamond” while
‘D’ will mean “regular diamond”.matplotlib.axes.Axes.set_xlim(),
matplotlib.axes.Axes.set_ylim(), and
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.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.viewLim based on
the matplotlib.axes.Axes.dataLim.matplotlib.axes.Axes.locator_params() allows one to
adjust axes locator parameters such as nbins.matplotlib.axes.Axes.ticklabel_format() is a convenience
method for controlling the matplotlib.ticker.ScalarFormatter
that is used by default with linear axes.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.EllipseCollection has been
changed in two ways:Ellipse, and to better match
their names; previously they specified the half-height and
half-width.axes.color_cycle, and the color
cycle is now independent of the rc parameter lines.color.
matplotlib.Axes.set_default_color_cycle() is deprecated.matplotlib.backends.backend_pdf.PdfPages for
more information.The new rc parameter savefig.extension sets 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.matplotlib.cm.get_cmap(). Colormaps can be made the
default and applied to the current image using
matplotlib.pyplot.set_cmap().psd(), csd(), and cohere() will now automatically wrap negative frequency components to the beginning of the returned arrays. This is much more sensible behavior and makes them consistent with specgram(). The previous behavior was more of an oversight than a design decision.
Added new keyword parameters nonposx, nonposy to
matplotlib.axes.Axes methods that set log scale
parameters. The default is still to mask out non-positive
values, but the kwargs accept ‘clip’, which causes non-positive
values to be replaced with a very small positive value.
Added new matplotlib.pyplot.fignum_exists() and
matplotlib.pyplot.get_fignums(); they merely expose
information that had been hidden in matplotlib._pylab_helpers.
Deprecated numerix package.
Added new matplotlib.image.imsave() and exposed it to the
matplotlib.pyplot interface.
Remove support for pyExcelerator in exceltools – use xlwt instead
Changed the defaults of acorr and xcorr to use usevlines=True, maxlags=10 and normed=True since these are the best defaults
Following keyword parameters for matplotlib.label.Label are now
deprecated and new set of parameters are introduced. The new parameters
are given as a fraction of the font-size. Also, scatteryoffsets,
fancybox and columnspacing are added as keyword parameters.
Deprecated New pad borderpad labelsep labelspacing handlelen handlelength handlestextsep handletextpad axespad borderaxespad
Removed the configobj and experimental traits rc support
Modified matplotlib.mlab.psd(), matplotlib.mlab.csd(),
matplotlib.mlab.cohere(), and matplotlib.mlab.specgram()
to scale one-sided densities by a factor of 2. Also, optionally
scale the densities by the sampling frequency, which gives true values
of densities that can be integrated by the returned frequency values.
This also gives better MATLAB compatibility. The corresponding
matplotlib.axes.Axes methods and matplotlib.pyplot
functions were updated as well.
Font lookup now uses a nearest-neighbor approach rather than an exact match. Some fonts may be different in plots, but should be closer to what was requested.
matplotlib.axes.Axes.set_xlim(),
matplotlib.axes.Axes.set_ylim() now return a copy of the
viewlim array to avoid modify-in-place surprises.
matplotlib.afm.AFM.get_fullname() and
matplotlib.afm.AFM.get_familyname() no longer raise an
exception if the AFM file does not specify these optional
attributes, but returns a guess based on the required FontName
attribute.
Changed precision kwarg in matplotlib.pyplot.spy(); default is
0, and the string value ‘present’ is used for sparse arrays only to
show filled locations.
Added angles kwarg to matplotlib.pyplot.quiver() for more
flexible specification of the arrow angles.
Deprecated (raise NotImplementedError) all the mlab2 functions from
matplotlib.mlab out of concern that some of them were not
clean room implementations.
Methods matplotlib.collections.Collection.get_offsets() and
matplotlib.collections.Collection.set_offsets() added to
Collection base class.
matplotlib.figure.Figure.figurePatch renamed
matplotlib.figure.Figure.patch;
matplotlib.axes.Axes.axesPatch renamed
matplotlib.axes.Axes.patch;
matplotlib.axes.Axes.axesFrame renamed
matplotlib.axes.Axes.frame.
matplotlib.axes.Axes.get_frame(), which returns
matplotlib.axes.Axes.patch, is deprecated.
Changes in the matplotlib.contour.ContourLabeler attributes
(matplotlib.pyplot.clabel() function) so that they all have a
form like .labelAttribute. The three attributes that are most
likely to be used by end users, .cl, .cl_xy and
.cl_cvalues have been maintained for the moment (in addition to
their renamed versions), but they are deprecated and will eventually
be removed.
Moved several functions in matplotlib.mlab and
matplotlib.cbook into a separate module
matplotlib.numerical_methods because they were unrelated to
the initial purpose of mlab or cbook and appeared more coherent
elsewhere.
matplotlib.axes3d support and replaced it with
a non-implemented error pointing to 0.91.xmatplotlib.image.imread() now no longer always returns RGBA data—if
the image is luminance or RGB, it will return a MxN or MxNx3 array
if possible. Also uint8 is no longer always forced to float.matplotlib.cm.ScalarMappable callback
infrastructure to use matplotlib.cbook.CallbackRegistry
rather than custom callback handling. Any users of
matplotlib.cm.ScalarMappable.add_observer() of the
ScalarMappable should use the
matplotlib.cm.ScalarMappable.callbacks
CallbackRegistry instead.matplotlib.axes.set_default_color_cycle() and
matplotlib.axes.Axes.set_color_cycle().matplotlib.cbook will
no longer provide set, enumerate(), reversed()
or izip() compatibility functions.matplotlib.axes.Axes.hist() now uses future Numpy 1.3
semantics for histograms. Providing binedges, the last value gives
the upper-right edge now, which was implicitly set to +infinity in
Numpy 1.0. This also means that the last bin doesn’t contain upper
outliers any more by default.hexbin(), is an alternative to
scatter() for large datasets. It makes
something like a pcolor() of a 2-D
histogram, but uses hexagonal bins.symmetric, in matplotlib.ticker.MaxNLocator
allows one require an axis to be centered around zero.mpl_toolkits (not matplotlib.toolkits)A major new feature of the 0.98 series is a more flexible and extensible transformation infrastructure, written in Python/Numpy rather than a custom C extension.
The primary goal of this refactoring was to make it easier to extend matplotlib to support new kinds of projections. This is mostly an internal improvement, and the possible user-visible changes it allows are yet to come.
See matplotlib.transforms for a description of the design of
the new transformation framework.
For efficiency, many of these functions return views into Numpy arrays. This means that if you hold on to a reference to them, their contents may change. If you want to store a snapshot of their current values, use the Numpy array method copy().
The view intervals are now stored only in one place – in the
matplotlib.axes.Axes instance, not in the locator instances
as well. This means locators must get their limits from their
matplotlib.axis.Axis, which in turn looks up its limits from
the Axes. If a locator is used temporarily
and not assigned to an Axis or Axes, (e.g., in
matplotlib.contour), a dummy axis must be created to store its
bounds. Call matplotlib.ticker.Locator.create_dummy_axis() to
do so.
The functionality of Pbox has been merged with
Bbox. Its methods now all return
copies rather than modifying in place.
The following lists many of the simple changes necessary to update code from the old transformation framework to the new one. In particular, methods that return a copy are named with a verb in the past tense, whereas methods that alter an object in place are named with a verb in the present tense.
matplotlib.transforms¶| Old method | New method |
|---|---|
Bbox.get_bounds() |
transforms.Bbox.bounds |
Bbox.width() |
transforms.Bbox.width |
Bbox.height() |
transforms.Bbox.height |
Bbox.intervalx().get_bounds() |
transforms.Bbox.intervalx |
Bbox.intervalx().set_bounds() |
[Bbox.intervalx is now a property.] |
Bbox.intervaly().get_bounds() |
transforms.Bbox.intervaly |
Bbox.intervaly().set_bounds() |
[Bbox.intervaly is now a property.] |
Bbox.xmin() |
transforms.Bbox.x0 or
transforms.Bbox.xmin [1] |
Bbox.ymin() |
transforms.Bbox.y0 or
transforms.Bbox.ymin [1] |
Bbox.xmax() |
transforms.Bbox.x1 or
transforms.Bbox.xmax [1] |
Bbox.ymax() |
transforms.Bbox.y1 or
transforms.Bbox.ymax [1] |
Bbox.overlaps(bboxes) |
Bbox.count_overlaps(bboxes) |
bbox_all(bboxes) |
Bbox.union(bboxes)
[transforms.Bbox.union() is a staticmethod.] |
lbwh_to_bbox(l, b, w, h) |
Bbox.from_bounds(x0, y0, w, h)
[transforms.Bbox.from_bounds() is a staticmethod.] |
inverse_transform_bbox(trans, bbox) |
Bbox.inverse_transformed(trans) |
Interval.contains_open(v) |
interval_contains_open(tuple, v) |
Interval.contains(v) |
interval_contains(tuple, v) |
identity_transform() |
matplotlib.transforms.IdentityTransform |
blend_xy_sep_transform(xtrans, ytrans) |
blended_transform_factory(xtrans, ytrans) |
scale_transform(xs, ys) |
Affine2D().scale(xs[, ys]) |
get_bbox_transform(boxin, boxout) |
BboxTransform(boxin, boxout) or
BboxTransformFrom(boxin) or
BboxTransformTo(boxout) |
Transform.seq_xy_tup(points) |
Transform.transform(points) |
Transform.inverse_xy_tup(points) |
Transform.inverted().transform(points) |
| [1] | (1, 2, 3, 4) The Bbox is bound by the points
(x0, y0) to (x1, y1) and there is no defined order to these points,
that is, x0 is not necessarily the left edge of the box. To get
the left edge of the Bbox, use the read-only property
xmin. |
matplotlib.axes¶| Old method | New method |
|---|---|
Axes.get_position() |
matplotlib.axes.Axes.get_position() [2] |
Axes.set_position() |
matplotlib.axes.Axes.set_position() [3] |
Axes.toggle_log_lineary() |
matplotlib.axes.Axes.set_yscale() [4] |
Subplot class |
removed. |
The Polar class has moved to matplotlib.projections.polar.
| [2] | matplotlib.axes.Axes.get_position() used to return a list
of points, now it returns a matplotlib.transforms.Bbox
instance. |
| [3] | matplotlib.axes.Axes.set_position() now accepts either
four scalars or a matplotlib.transforms.Bbox instance. |
| [4] | Since the recfactoring allows for more than two scale types
(‘log’ or ‘linear’), it no longer makes sense to have a toggle.
Axes.toggle_log_lineary() has been removed. |
matplotlib.artist¶| Old method | New method |
|---|---|
Artist.set_clip_path(path) |
Artist.set_clip_path(path, transform) [5] |
| [5] | matplotlib.artist.Artist.set_clip_path() now accepts a
matplotlib.path.Path instance and a
matplotlib.transforms.Transform that will be applied to
the path immediately before clipping. |
matplotlib.collections¶| Old method | New method |
|---|---|
linestyle |
linestyles [6] |
| [6] | Linestyles are now treated like all other collection attributes, i.e. a single value or multiple values may be provided. |
matplotlib.colors¶| Old method | New method |
|---|---|
ColorConvertor.to_rgba_list(c) |
ColorConvertor.to_rgba_array(c)
[matplotlib.colors.ColorConvertor.to_rgba_array()
returns an Nx4 Numpy array of RGBA color quadruples.] |
matplotlib.contour¶| Old method | New method |
|---|---|
Contour._segments |
matplotlib.contour.Contour.get_paths`() [Returns a
list of matplotlib.path.Path instances.] |
matplotlib.figure¶| Old method | New method |
|---|---|
Figure.dpi.get() / Figure.dpi.set() |
matplotlib.figure.Figure.dpi (a property) |
matplotlib.patches¶| Old method | New method |
|---|---|
Patch.get_verts() |
matplotlib.patches.Patch.get_path() [Returns a
matplotlib.path.Path instance] |
matplotlib.backend_bases¶| Old method | New method |
|---|---|
GraphicsContext.set_clip_rectangle(tuple) |
GraphicsContext.set_clip_rectangle(bbox) |
GraphicsContext.get_clip_path() |
GraphicsContext.get_clip_path() [7] |
GraphicsContext.set_clip_path() |
GraphicsContext.set_clip_path() [8] |
RendererBase¶New methods:
draw_path(self, gc, path, transform, rgbFace)draw_markers(self, gc, marker_path, marker_trans, path, trans, rgbFace)draw_path_collection(self, master_transform, cliprect, clippath, clippath_trans, paths, all_transforms, offsets, offsetTrans, facecolors, edgecolors, linewidths, linestyles, antialiaseds)[optional]
Changed methods:
draw_image(self, x, y, im, bbox)is nowdraw_image(self, x, y, im, bbox, clippath, clippath_trans)
Removed methods:
draw_arcdraw_line_collectiondraw_linedraw_linesdraw_pointdraw_quad_meshdraw_poly_collectiondraw_polygondraw_rectangledraw_regpoly_collection
| [7] | matplotlib.backend_bases.GraphicsContext.get_clip_path()
returns a tuple of the form (path, affine_transform), where
path is a matplotlib.path.Path instance and
affine_transform is a matplotlib.transforms.Affine2D
instance. |
| [8] | matplotlib.backend_bases.GraphicsContext.set_clip_path()
now only accepts a matplotlib.transforms.TransformedPath
instance. |
csv2rec(), checkrows=0 is the new default indicating all rows
will be checked for type inferencerec2gtk() to matplotlib.toolkits.gtktoolsrec2excel() to matplotlib.toolkits.exceltoolsmatplotlib.__init__cbook.is_file_like() to
cbook.is_writable_file_like() and corrected behavior.pyplot.colorbar() and
Figure.colorbar() so that one can specify the axes object from
which space for the colorbar is to be taken, if one does not want to
make the colorbar axes manually.cbook.reversed() so it yields a tuple rather than a
(index, tuple). This agrees with the python reversed builtin,
and cbook only defines reversed if python doesn’t provide the
builtin.csv2rec()matplotlib.dviread file now has a parser for files like
psfonts.map and pdftex.map, to map TeX font names to external files.matplotlib.type1font contains a new class for Type 1
fonts. Currently it simply reads pfa and pfb format files and
stores the data in a way that is suitable for embedding in pdf
files. In the future the class might actually parse the font to
allow e.g., subsetting.matplotlib.FT2Font now supports FT_Attach_File(). In
practice this can be used to read an afm file in addition to a
pfa/pfb file, to get metrics and kerning information for a Type 1
font.AFM class now supports querying CapHeight and stem
widths. The get_name_char method now has an isord kwarg like
get_width_char.pcolor() default to shading=’flat’; but as noted now in the
docstring, it is preferable to simply use the edgecolor kwarg.\cal, \rm, \it, \tt) now
behave as TeX does: they are in effect until the next font change
command or the end of the grouping. Therefore uses of $\cal{R}$
should be changed to ${\cal R}$. Alternatively, you may use the
new LaTeX-style font commands (\mathcal, \mathrm,
\mathit, \mathtt) which do affect the following group,
e.g., $\mathcal{R}$.linespacing kwarg, which is a multiple of the maximum vertical
extent of a line of ordinary text. The default is 1.2;
linespacing=2 would be like ordinary double spacing, for example.matplotlib.colors.Normalize.__init__`() to clip=False;
clipping silently defeats the purpose of the special over, under,
and bad values in the colormap, thereby leading to unexpected
behavior. The new default should reduce such surprises.set_xlim() and
set_ylim() True by default; removed
the Axes custom callback handling into a ‘callbacks’ attribute which
is a CallbackRegistry instance. This now
supports the ‘xlim_changed’ and ‘ylim_changed’ Axes events.The file dviread.py has a (very limited and fragile) dvi reader
for usetex support. The API might change in the future so don't
depend on it yet.
Removed deprecated support for a float value as a gray-scale;
now it must be a string, like '0.5'. Added alpha kwarg to
ColorConverter.to_rgba_list.
New method set_bounds(vmin, vmax) for formatters, locators sets
the viewInterval and dataInterval from floats.
Removed deprecated colorbar_classic.
Line2D.get_xdata and get_ydata valid_only=False kwarg is replaced
by orig=True. When True, it returns the original data, otherwise
the processed data (masked, converted)
Some modifications to the units interface.
units.ConversionInterface.tickers renamed to
units.ConversionInterface.axisinfo and it now returns a
units.AxisInfo object rather than a tuple. This will make it
easier to add axis info functionality (e.g., I added a default label
on this iteration) w/o having to change the tuple length and hence
the API of the client code every time new functionality is added.
Also, units.ConversionInterface.convert_to_value is now simply
named units.ConversionInterface.convert.
Axes.errorbar uses Axes.vlines and Axes.hlines to draw its error
limits int he vertical and horizontal direction. As you'll see
in the changes below, these functions now return a LineCollection
rather than a list of lines. The new return signature for
errorbar is ylins, caplines, errorcollections where
errorcollections is a xerrcollection, yerrcollection
Axes.vlines and Axes.hlines now create and returns a LineCollection, not a list
of lines. This is much faster. The kwarg signature has changed,
so consult the docs
MaxNLocator accepts a new Boolean kwarg ('integer') to force
ticks to integer locations.
Commands that pass an argument to the Text constructor or to
Text.set_text() now accept any object that can be converted
with '%s'. This affects xlabel(), title(), etc.
Barh now takes a **kwargs dict instead of most of the old
arguments. This helps ensure that bar and barh are kept in sync,
but as a side effect you can no longer pass e.g., color as a
positional argument.
ft2font.get_charmap() now returns a dict that maps character codes
to glyph indices (until now it was reversed)
Moved data files into lib/matplotlib so that setuptools' develop
mode works. Re-organized the mpl-data layout so that this source
structure is maintained in the installation. (i.e., the 'fonts' and
'images' sub-directories are maintained in site-packages.).
Suggest removing site-packages/matplotlib/mpl-data and
~/.matplotlib/ttffont.cache before installing
All artists now implement a "pick" method which users should not
call. Rather, set the "picker" property of any artist you want to
pick on (the epsilon distance in points for a hit test) and
register with the "pick_event" callback. See
examples/pick_event_demo.py for details
Bar, barh, and hist have "log" binary kwarg: log=True
sets the ordinate to a log scale.
Boxplot can handle a list of vectors instead of just
an array, so vectors can have different lengths.
Plot can handle 2-D x and/or y; it plots the columns.
Added linewidth kwarg to bar and barh.
Made the default Artist._transform None (rather than invoking
identity_transform for each artist only to have it overridden
later). Use artist.get_transform() rather than artist._transform,
even in derived classes, so that the default transform will be
created lazily as needed
New LogNorm subclass of Normalize added to colors.py.
All Normalize subclasses have new inverse() method, and
the __call__() method has a new clip kwarg.
Changed class names in colors.py to match convention:
normalize -> Normalize, no_norm -> NoNorm. Old names
are still available for now.
Removed obsolete pcolor_classic command and method.
Removed lineprops and markerprops from the Annotation code and
replaced them with an arrow configurable with kwarg arrowprops.
See examples/annotation_demo.py - JDH
Completely reworked the annotations API because I found the old
API cumbersome. The new design is much more legible and easy to
read. See matplotlib.text.Annotation and
examples/annotation_demo.py
markeredgecolor and markerfacecolor cannot be configured in
matplotlibrc any more. Instead, markers are generally colored
automatically based on the color of the line, unless marker colors
are explicitly set as kwargs - NN
Changed default comment character for load to '#' - JDH
math_parse_s_ft2font_svg from mathtext.py & mathtext2.py now returns
width, height, svg_elements. svg_elements is an instance of Bunch (
cmbook.py) and has the attributes svg_glyphs and svg_lines, which are both
lists.
Renderer.draw_arc now takes an additional parameter, rotation.
It specifies to draw the artist rotated in degrees anti-
clockwise. It was added for rotated ellipses.
Renamed Figure.set_figsize_inches to Figure.set_size_inches to
better match the get method, Figure.get_size_inches.
Removed the copy_bbox_transform from transforms.py; added
shallowcopy methods to all transforms. All transforms already
had deepcopy methods.
FigureManager.resize(width, height): resize the window
specified in pixels
barh: x and y args have been renamed to width and bottom
respectively, and their order has been swapped to maintain
a (position, value) order.
bar and barh: now accept kwarg 'edgecolor'.
bar and barh: The left, height, width and bottom args can
now all be scalars or sequences; see docstring.
barh: now defaults to edge aligned instead of center
aligned bars
bar, barh and hist: Added a keyword arg 'align' that
controls between edge or center bar alignment.
Collections: PolyCollection and LineCollection now accept
vertices or segments either in the original form [(x,y),
(x,y), ...] or as a 2D numerix array, with X as the first column
and Y as the second. Contour and quiver output the numerix
form. The transforms methods Bbox.update() and
Transformation.seq_xy_tups() now accept either form.
Collections: LineCollection is now a ScalarMappable like
PolyCollection, etc.
Specifying a grayscale color as a float is deprecated; use
a string instead, e.g., 0.75 -> '0.75'.
Collections: initializers now accept any mpl color arg, or
sequence of such args; previously only a sequence of rgba
tuples was accepted.
Colorbar: completely new version and api; see docstring. The
original version is still accessible as colorbar_classic, but
is deprecated.
Contourf: "extend" kwarg replaces "clip_ends"; see docstring.
Masked array support added to pcolormesh.
Modified aspect-ratio handling:
Removed aspect kwarg from imshow
Axes methods:
set_aspect(self, aspect, adjustable=None, anchor=None)
set_adjustable(self, adjustable)
set_anchor(self, anchor)
Pylab interface:
axis('image')
Backend developers: ft2font's load_char now takes a flags
argument, which you can OR together from the LOAD_XXX
constants.
Matplotlib data is installed into the matplotlib module.
This is similar to package_data. This should get rid of
having to check for many possibilities in _get_data_path().
The MATPLOTLIBDATA env key is still checked first to allow
for flexibility.
1) Separated the color table data from cm.py out into
a new file, _cm.py, to make it easier to find the actual
code in cm.py and to add new colormaps. Everything
from _cm.py is imported by cm.py, so the split should be
transparent.
2) Enabled automatic generation of a colormap from
a list of colors in contour; see modified
examples/contour_demo.py.
3) Support for imshow of a masked array, with the
ability to specify colors (or no color at all) for
masked regions, and for regions that are above or
below the normally mapped region. See
examples/image_masked.py.
4) In support of the above, added two new classes,
ListedColormap, and no_norm, to colors.py, and modified
the Colormap class to include common functionality. Added
a clip kwarg to the normalize class.
Made xtick and ytick separate props in rc
made pos=None the default for tick formatters rather than 0 to
indicate "not supplied"
Removed "feature" of minor ticks which prevents them from
overlapping major ticks. Often you want major and minor ticks at
the same place, and can offset the major ticks with the pad. This
could be made configurable
Changed the internal structure of contour.py to a more OO style.
Calls to contour or contourf in axes.py or pylab.py now return
a ContourSet object which contains references to the
LineCollections or PolyCollections created by the call,
as well as the configuration variables that were used.
The ContourSet object is a "mappable" if a colormap was used.
Added a clip_ends kwarg to contourf. From the docstring:
* clip_ends = True
If False, the limits for color scaling are set to the
minimum and maximum contour levels.
True (default) clips the scaling limits. Example:
if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100],
then the scaling limits will be [-100, 100] if clip_ends
is False, and [-3, 3] if clip_ends is True.
Added kwargs linewidths, antialiased, and nchunk to contourf. These
are experimental; see the docstring.
Changed Figure.colorbar():
kw argument order changed;
if mappable arg is a non-filled ContourSet, colorbar() shows
lines instead hof polygons.
if mappable arg is a filled ContourSet with clip_ends=True,
the endpoints are not labelled, so as to give the
correct impression of open-endedness.
Changed LineCollection.get_linewidths to get_linewidth, for
consistency.
Unified argument handling between hlines and vlines. Both now
take optionally a fmt argument (as in plot) and a keyword args
that can be passed onto Line2D.
Removed all references to "data clipping" in rc and lines.py since
these were not used and not optimized. I'm sure they'll be
resurrected later with a better implementation when needed.
'set' removed - no more deprecation warnings. Use 'setp' instead.
Backend developers: Added flipud method to image and removed it
from to_str. Removed origin kwarg from backend.draw_image.
origin is handled entirely by the frontend now.
- Made HOME/.matplotlib the new config dir where the matplotlibrc
file, the ttf.cache, and the tex.cache live. The new default
filenames in .matplotlib have no leading dot and are not hidden.
e.g., the new names are matplotlibrc, tex.cache, and ttffont.cache.
This is how ipython does it so it must be right.
If old files are found, a warning is issued and they are moved to
the new location.
- backends/__init__.py no longer imports new_figure_manager,
draw_if_interactive and show from the default backend, but puts
these imports into a call to pylab_setup. Also, the Toolbar is no
longer imported from WX/WXAgg. New usage:
from backends import pylab_setup
new_figure_manager, draw_if_interactive, show = pylab_setup()
- Moved Figure.get_width_height() to FigureCanvasBase. It now
returns int instead of float.
- toolbar import change in GTKAgg, GTKCairo and WXAgg
- Added subplot config tool to GTK* backends -- note you must now
import the NavigationToolbar2 from your backend of choice rather
than from backend_gtk because it needs to know about the backend
specific canvas -- see examples/embedding_in_gtk2.py. Ditto for
wx backend -- see examples/embedding_in_wxagg.py
- hist bin change
Sean Richards notes there was a problem in the way we created
the binning for histogram, which made the last bin
underrepresented. From his post:
I see that hist uses the linspace function to create the bins
and then uses searchsorted to put the values in their correct
bin. That's all good but I am confused over the use of linspace
for the bin creation. I wouldn't have thought that it does
what is needed, to quote the docstring it creates a "Linear
spaced array from min to max". For it to work correctly
shouldn't the values in the bins array be the same bound for
each bin? (i.e. each value should be the lower bound of a
bin). To provide the correct bins for hist would it not be
something like
def bins(xmin, xmax, N):
if N==1: return xmax
dx = (xmax-xmin)/N # instead of N-1
return xmin + dx*arange(N)
This suggestion is implemented in 0.81. My test script with these
changes does not reveal any bias in the binning
from matplotlib.numerix.mlab import randn, rand, zeros, Float
from matplotlib.mlab import hist, mean
Nbins = 50
Ntests = 200
results = zeros((Ntests,Nbins), typecode=Float)
for i in range(Ntests):
print 'computing', i
x = rand(10000)
n, bins = hist(x, Nbins)
results[i] = n
print mean(results)
- pylab and artist "set" functions renamed to setp to avoid clash
with python2.4 built-in set. Current version will issue a
deprecation warning which will be removed in future versions
- imshow interpolation arguments changes for advanced interpolation
schemes. See help imshow, particularly the interpolation,
filternorm and filterrad kwargs
- Support for masked arrays has been added to the plot command and
to the Line2D object. Only the valid points are plotted. A
"valid_only" kwarg was added to the get_xdata() and get_ydata()
methods of Line2D; by default it is False, so that the original
data arrays are returned. Setting it to True returns the plottable
points.
- contour changes:
Masked arrays: contour and contourf now accept masked arrays as
the variable to be contoured. Masking works correctly for
contour, but a bug remains to be fixed before it will work for
contourf. The "badmask" kwarg has been removed from both
functions.
Level argument changes:
Old version: a list of levels as one of the positional
arguments specified the lower bound of each filled region; the
upper bound of the last region was taken as a very large
number. Hence, it was not possible to specify that z values
between 0 and 1, for example, be filled, and that values
outside that range remain unfilled.
New version: a list of N levels is taken as specifying the
boundaries of N-1 z ranges. Now the user has more control over
what is colored and what is not. Repeated calls to contourf
(with different colormaps or color specifications, for example)
can be used to color different ranges of z. Values of z
outside an expected range are left uncolored.
Example:
Old: contourf(z, [0, 1, 2]) would yield 3 regions: 0-1, 1-2, and >2.
New: it would yield 2 regions: 0-1, 1-2. If the same 3 regions were
desired, the equivalent list of levels would be [0, 1, 2,
1e38].
- xlim/ylim/axis always return the new limits regardless of
arguments. They now take kwargs which allow you to selectively
change the upper or lower limits while leaving unnamed limits
unchanged. See help(xlim) for example
- Removed deprecated ColormapJet and friends
- Removed all error handling from the verbose object
- figure num of zero is now allowed
- Line2D, Text, and Patch copy_properties renamed update_from and
moved into artist base class
- LineCollecitons.color renamed to LineCollections.set_color for
consistency with set/get introspection mechanism,
- pylab figure now defaults to num=None, which creates a new figure
with a guaranteed unique number
- contour method syntax changed - now it is MATLAB compatible
unchanged: contour(Z)
old: contour(Z, x=Y, y=Y)
new: contour(X, Y, Z)
see http://matplotlib.sf.net/matplotlib.pylab.html#-contour
- Increased the default resolution for save command.
- Renamed the base attribute of the ticker classes to _base to avoid conflict
with the base method. Sitt for subs
- subs=none now does autosubbing in the tick locator.
- New subplots that overlap old will delete the old axes. If you
do not want this behavior, use fig.add_subplot or the axes
command
Significant numerix namespace changes, introduced to resolve
namespace clashes between python built-ins and mlab names.
Refactored numerix to maintain separate modules, rather than
folding all these names into a single namespace. See the following
mailing list threads for more information and background
http://sourceforge.net/mailarchive/forum.php?thread_id=6398890&forum_id=36187
http://sourceforge.net/mailarchive/forum.php?thread_id=6323208&forum_id=36187
OLD usage
from matplotlib.numerix import array, mean, fft
NEW usage
from matplotlib.numerix import array
from matplotlib.numerix.mlab import mean
from matplotlib.numerix.fft import fft
numerix dir structure mirrors numarray (though it is an incomplete
implementation)
numerix
numerix/mlab
numerix/linear_algebra
numerix/fft
numerix/random_array
but of course you can use 'numerix : Numeric' and still get the
symbols.
pylab still imports most of the symbols from Numerix, MLab, fft,
etc, but is more cautious. For names that clash with python names
(min, max, sum), pylab keeps the builtins and provides the numeric
versions with an a* prefix, e.g., (amin, amax, asum)
MplEvent factored into a base class Event and derived classes
MouseEvent and KeyEvent
Removed definct set_measurement in wx toolbar
removed add_axes and add_subplot from backend_bases. Use
figure.add_axes and add_subplot instead. The figure now manages the
current axes with gca and sca for get and set current axes. If you
have code you are porting which called, e.g., figmanager.add_axes, you
can now simply do figmanager.canvas.figure.add_axes.
mpl_connect and mpl_disconnect in the MATLAB interface renamed to
connect and disconnect
Did away with the text methods for angle since they were ambiguous.
fontangle could mean fontstyle (obligue, etc) or the rotation of the
text. Use style and rotation instead.
Dates are now represented internally as float days since 0001-01-01,
UTC.
All date tickers and formatters are now in matplotlib.dates, rather
than matplotlib.tickers
converters have been abolished from all functions and classes.
num2date and date2num are now the converter functions for all date
plots
Most of the date tick locators have a different meaning in their
constructors. In the prior implementation, the first argument was a
base and multiples of the base were ticked. e.g.,
HourLocator(5) # old: tick every 5 minutes
In the new implementation, the explicit points you want to tick are
provided as a number or sequence
HourLocator(range(0,5,61)) # new: tick every 5 minutes
This gives much greater flexibility. I have tried to make the
default constructors (no args) behave similarly, where possible.
Note that YearLocator still works under the base/multiple scheme.
The difference between the YearLocator and the other locators is
that years are not recurrent.
Financial functions:
matplotlib.finance.quotes_historical_yahoo(ticker, date1, date2)
date1, date2 are now datetime instances. Return value is a list
of quotes where the quote time is a float - days since gregorian
start, as returned by date2num
See examples/finance_demo.py for example usage of new API
canvas.connect is now deprecated for event handling. use
mpl_connect and mpl_disconnect instead. The callback signature is
func(event) rather than func(widget, event)
ColormapJet and Grayscale are deprecated. For backwards
compatibility, they can be obtained either by doing
from matplotlib.cm import ColormapJet
or
from matplotlib.matlab import *
They are replaced by cm.jet and cm.grey
removed the set_default_font / get_default_font scheme from the
font_manager to unify customization of font defaults with the rest of
the rc scheme. See examples/font_properties_demo.py and help(rc) in
matplotlib.matlab.
Several of the backends used a PIXELS_PER_INCH hack that I added to try and make images render consistently across backends. This just complicated matters. So you may find that some font sizes and line widths appear different than before. Apologies for the inconvenience. You should set the dpi to an accurate value for your screen to get true sizes.
There are two changes to the MATLAB interface API, both involving the patch drawing commands. For efficiency, pcolor and scatter have been rewritten to use polygon collections, which are a new set of objects from matplotlib.collections designed to enable efficient handling of large collections of objects. These new collections make it possible to build large scatter plots or pcolor plots with no loops at the python level, and are significantly faster than their predecessors. The original pcolor and scatter functions are retained as pcolor_classic and scatter_classic.
The return value from pcolor is a PolyCollection. Most of the propertes that are available on rectangles or other patches are also available on PolyCollections, e.g., you can say:
c = scatter(blah, blah)
c.set_linewidth(1.0)
c.set_facecolor('r')
c.set_alpha(0.5)
or:
c = scatter(blah, blah)
set(c, 'linewidth', 1.0, 'facecolor', 'r', 'alpha', 0.5)
Because the collection is a single object, you no longer need to loop over the return value of scatter or pcolor to set properties for the entire list.
If you want the different elements of a collection to vary on a property, e.g., to have different line widths, see matplotlib.collections for a discussion on how to set the properties as a sequence.
For scatter, the size argument is now in points^2 (the area of the symbol in points) as in MATLAB and is not in data coords as before. Using sizes in data coords caused several problems. So you will need to adjust your size arguments accordingly or use scatter_classic.
For reasons not clear to me (and which I’ll eventually fix) spacing no longer works in font groups. However, I added three new spacing commands which compensate for this ‘’ (regular space), ‘/’ (small space) and ‘hspace{frac}’ where frac is a fraction of fontsize in points. You will need to quote spaces in font strings, is:
title(r'$\rm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$')
The x and y axis instances no longer have autoscale view. These are handled by axes.autoscale_view
You should not instantiate your own Axes any more using the OO API. Rather, create a Figure as before and in place of:
f = Figure(figsize=(5,4), dpi=100) a = Subplot(f, 111) f.add_axis(a)use:
f = Figure(figsize=(5,4), dpi=100) a = f.add_subplot(111)That is, add_axis no longer exists and is replaced by:
add_axes(rect, axisbg=defaultcolor, frameon=True) add_subplot(num, axisbg=defaultcolor, frameon=True)
If you define your own Artists, you need to rename the _draw method to draw
matplotlib.transforms.Bound2D is replaced by matplotlib.transforms.Bbox. If you want to construct a bbox from left, bottom, width, height (the signature for Bound2D), use matplotlib.transforms.lbwh_to_bbox, as in
bbox = clickBBox = lbwh_to_bbox(left, bottom, width, height)The Bbox has a different API than the Bound2D. e.g., if you want to get the width and height of the bbox
- OLD::
- width = fig.bbox.x.interval() height = fig.bbox.y.interval()
- New::
- width = fig.bbox.width() height = fig.bbox.height()
You no longer pass the bbox, dpi, or transforms to the various Artist constructors. The old way or creating lines and rectangles was cumbersome because you had to pass so many attributes to the Line2D and Rectangle classes not related directly to the geometry and properties of the object. Now default values are added to the object when you call axes.add_line or axes.add_patch, so they are hidden from the user.
If you want to define a custom transformation on these objects, call o.set_transform(trans) where trans is a Transformation instance.
In prior versions of you wanted to add a custom line in data coords, you would have to do
- l = Line2D(dpi, bbox, x, y,
- color = color, transx = transx, transy = transy, )
now all you need is
l = Line2D(x, y, color=color)and the axes will set the transformation for you (unless you have set your own already, in which case it will eave it unchanged)
The entire transformation architecture has been rewritten. Previously the x and y transformations where stored in the xaxis and yaxis instances. The problem with this approach is it only allows for separable transforms (where the x and y transformations don’t depend on one another). But for cases like polar, they do. Now transformations operate on x,y together. There is a new base class matplotlib.transforms.Transformation and two concrete implementations, matplotlib.transforms.SeparableTransformation and matplotlib.transforms.Affine. The SeparableTransformation is constructed with the bounding box of the input (this determines the rectangular coordinate system of the input, i.e., the x and y view limits), the bounding box of the display, and possibly nonlinear transformations of x and y. The 2 most frequently used transformations, data coordinates -> display and axes coordinates -> display are available as ax.transData and ax.transAxes. See alignment_demo.py which uses axes coords.
Also, the transformations should be much faster now, for two reasons
they are written entirely in extension code
because they operate on x and y together, they can do the entire transformation in one loop. Earlier I did something along the lines of:
xt = sx*func(x) + tx yt = sy*func(y) + tyAlthough this was done in numerix, it still involves 6 length(x) for-loops (the multiply, add, and function evaluation each for x and y). Now all of that is done in a single pass.
If you are using transformations and bounding boxes to get the cursor position in data coordinates, the method calls are a little different now. See the updated examples/coords_demo.py which shows you how to do this.
Likewise, if you are using the artist bounding boxes to pick items on the canvas with the GUI, the bbox methods are somewhat different. You will need to see the updated examples/object_picker.py.
See unit/transforms_unit.py for many examples using the new transformations.
* refactored Figure class so it is no longer backend dependent.
FigureCanvasBackend takes over the backend specific duties of the
Figure. matplotlib.backend_bases.FigureBase moved to
matplotlib.figure.Figure.
* backends must implement FigureCanvasBackend (the thing that
controls the figure and handles the events if any) and
FigureManagerBackend (wraps the canvas and the window for MATLAB
interface). FigureCanvasBase implements a backend switching
mechanism
* Figure is now an Artist (like everything else in the figure) and
is totally backend independent
* GDFONTPATH renamed to TTFPATH
* backend faceColor argument changed to rgbFace
* colormap stuff moved to colors.py
* arg_to_rgb in backend_bases moved to class ColorConverter in
colors.py
* GD users must upgrade to gd-2.0.22 and gdmodule-0.52 since new gd
features (clipping, antialiased lines) are now used.
* Renderer must implement points_to_pixels
Migrating code:
MATLAB interface:
The only API change for those using the MATLAB interface is in how
you call figure redraws for dynamically updating figures. In the
old API, you did
fig.draw()
In the new API, you do
manager = get_current_fig_manager()
manager.canvas.draw()
See the examples system_monitor.py, dynamic_demo.py, and anim.py
API
There is one important API change for application developers.
Figure instances used subclass GUI widgets that enabled them to be
placed directly into figures. e.g., FigureGTK subclassed
gtk.DrawingArea. Now the Figure class is independent of the
backend, and FigureCanvas takes over the functionality formerly
handled by Figure. In order to include figures into your apps,
you now need to do, for example
# gtk example
fig = Figure(figsize=(5,4), dpi=100)
canvas = FigureCanvasGTK(fig) # a gtk.DrawingArea
canvas.show()
vbox.pack_start(canvas)
If you use the NavigationToolbar, this in now intialized with a
FigureCanvas, not a Figure. The examples embedding_in_gtk.py,
embedding_in_gtk2.py, and mpl_with_glade.py all reflect the new
API so use these as a guide.
All prior calls to
figure.draw() and
figure.print_figure(args)
should now be
canvas.draw() and
canvas.print_figure(args)
Apologies for the inconvenience. This refactorization brings
significant more freedom in developing matplotlib and should bring
better plotting capabilities, so I hope the inconvenience is worth
it.
* Refactoring AxisText to be backend independent. Text drawing and
get_window_extent functionality will be moved to the Renderer.
* backend_bases.AxisTextBase is now text.Text module
* All the erase and reset functionality removed from AxisText - not
needed with double buffered drawing. Ditto with state change.
Text instances have a get_prop_tup method that returns a hashable
tuple of text properties which you can use to see if text props
have changed, e.g., by caching a font or layout instance in a dict
with the prop tup as a key -- see RendererGTK.get_pango_layout in
backend_gtk for an example.
* Text._get_xy_display renamed Text.get_xy_display
* Artist set_renderer and wash_brushes methods removed
* Moved Legend class from matplotlib.axes into matplotlib.legend
* Moved Tick, XTick, YTick, Axis, XAxis, YAxis from matplotlib.axes
to matplotlib.axis
* moved process_text_args to matplotlib.text
* After getting Text handled in a backend independent fashion, the
import process is much cleaner since there are no longer cyclic
dependencies
* matplotlib.matlab._get_current_fig_manager renamed to
matplotlib.matlab.get_current_fig_manager to allow user access to
the GUI window attribute, e.g., figManager.window for GTK and
figManager.frame for wx
- Artist
* __init__ takes a DPI instance and a Bound2D instance which is
the bounding box of the artist in display coords
* get_window_extent returns a Bound2D instance
* set_size is removed; replaced by bbox and dpi
* the clip_gc method is removed. Artists now clip themselves with
their box
* added _clipOn boolean attribute. If True, gc clip to bbox.
- AxisTextBase
* Initialized with a transx, transy which are Transform instances
* set_drawing_area removed
* get_left_right and get_top_bottom are replaced by get_window_extent
- Line2D Patches now take transx, transy
* Initialized with a transx, transy which are Transform instances
- Patches
* Initialized with a transx, transy which are Transform instances
- FigureBase attributes dpi is a DPI intance rather than scalar and
new attribute bbox is a Bound2D in display coords, and I got rid
of the left, width, height, etc... attributes. These are now
accessible as, for example, bbox.x.min is left, bbox.x.interval()
is width, bbox.y.max is top, etc...
- GcfBase attribute pagesize renamed to figsize
- Axes
* removed figbg attribute
* added fig instance to __init__
* resizing is handled by figure call to resize.
- Subplot
* added fig instance to __init__
- Renderer methods for patches now take gcEdge and gcFace instances.
gcFace=None takes the place of filled=False
- True and False symbols provided by cbook in a python2.3 compatible
way
- new module transforms supplies Bound1D, Bound2D and Transform
instances and more
- Changes to the MATLAB helpers API
* _matlab_helpers.GcfBase is renamed by Gcf. Backends no longer
need to derive from this class. Instead, they provide a factory
function new_figure_manager(num, figsize, dpi). The destroy
method of the GcfDerived from the backends is moved to the derived
FigureManager.
* FigureManagerBase moved to backend_bases
* Gcf.get_all_figwins renamed to Gcf.get_all_fig_managers
Jeremy:
Make sure to self._reset = False in AxisTextWX._set_font. This was
something missing in my backend code.