Behavior changes¶
Reduced default value of rcParams["axes.formatter.limits"]
(default: [-5, 6])¶
Changed the default value of rcParams["axes.formatter.limits"]
(default: [-5, 6]) from -7, 7 to
-5, 6 for better readability.
(Source code, png, pdf)

matplotlib.colorbar.Colorbar
uses un-normalized axes for all mappables¶
Before 3.0, matplotlib.colorbar.Colorbar
(colorbar
) normalized
all axes limits between 0 and 1 and had custom tickers to handle the
labelling of the colorbar ticks. After 3.0, colorbars constructed from
mappables that were not contours were constructed with axes that had
limits between vmin
and vmax
of the mappable's norm, and the tickers
were made children of the normal axes tickers.
This version of Matplotlib extends that to mappables made by contours, and allows the axes to run between the lowest boundary in the contour and the highest.
Code that worked around the normalization between 0 and 1 will need to be modified.
MovieWriterRegistry
¶
MovieWriterRegistry
now always checks the availability of the writer classes
before returning them. If one wishes, for example, to get the first available
writer, without performing the availability check on subsequent writers, it is
now possible to iterate over the registry, which will yield the names of the
available classes.
Autoscaling¶
Matplotlib used to recompute autoscaled limits after every plotting
(plot()
, bar()
, etc.) call. It now only does so when actually
rendering the canvas, or when the user queries the Axes limits. This is a
major performance improvement for plots with a large number of artists.
In particular, this means that artists added manually with Axes.add_line
,
Axes.add_patch
, etc. will be taken into account by the autoscale, even
without an explicit call to Axes.autoscale_view
.
In some cases, this can result in different limits being reported. If this is
an issue, consider triggering a draw with fig.canvas.draw
.
Autoscaling has also changed for artists that are based on the Collection
class. Previously, the method that calculates the automatic limits
Collection.get_datalim
tried to take into account the size of objects
in the collection and make the limits large enough to not clip any of the
object, i.e., for Axes.scatter
it would make the limits large enough to not
clip any markers in the scatter. This is problematic when the object size is
specified in physical space, or figure-relative space, because the transform
from physical units to data limits requires knowing the data limits, and
becomes invalid when the new limits are applied. This is an inverse
problem that is theoretically solvable (if the object is physically smaller
than the axes), but the extra complexity was not deemed worth it, particularly
as the most common use case is for markers in scatter that are usually small
enough to be accommodated by the default data limit margins.
While the new behavior is algorithmically simpler, it is conditional on
properties of the Collection
object:
offsets = None
,transform
is a child ofAxes.transData
: use the paths for the automatic limits (i.e. forLineCollection
inAxes.streamplot
).offsets != None
, andoffset_transform
is child ofAxes.transData
:
transform
is child ofAxes.transData
: use thepath + offset
for- limits (i.e., for
Axes.bar
).
transform
is not a child ofAxes.transData
: just use the offsets- for the limits (i.e. for scatter)
- otherwise return a null
Bbox
.
While this seems complicated, the logic is simply to use the information from the object that are in data space for the limits, but not information that is in physical units.
log-scale bar() / hist() autolimits¶
The autolimits computation in bar
and hist
when the axes
already uses log-scale has changed to match the computation when the axes is
switched to log-scale after the call to bar
and hist
, and
when calling bar(..., log=True)
/ hist(..., log=True)
: if there are
at least two different bar heights, add the normal axes margins to them (in
log-scale); if there is only a single bar height, expand the axes limits by one
order of magnitude around it and then apply axes margins.
Axes labels spanning multiple rows/columns¶
Axes.label_outer
now correctly keep the x labels and tick labels visible
for Axes spanning multiple rows, as long as they cover the last row of the Axes
grid. (This is consistent with keeping the y labels and tick labels visible
for Axes spanning multiple columns as long as they cover the first column of
the Axes grid.)
The Axes.is_last_row
and Axes.is_last_col
methods now correctly return
True for Axes spanning multiple rows, as long as they cover the last row or
column respectively. Again this is consistent with the behavior for axes
covering the first row or column.
The Axes.rowNum
and Axes.colNum
attributes are deprecated, as they only
refer to the first grid cell covered by the Axes. Instead, use the new
ax.get_subplotspec().rowspan
and ax.get_subplotspec().colspan
properties, which are range
objects indicating the whole span of rows and
columns covered by the subplot.
(Note that all methods and attributes mentioned here actually only exist on
the Subplot
subclass of Axes
, which is used for grid-positioned Axes but
not for Axes positioned directly in absolute coordinates.)
The GridSpec
class gained the nrows
and ncols
properties as more
explicit synonyms for the parameters returned by GridSpec.get_geometry
.
Locators¶
When more than Locator.MAXTICKS
ticks are generated, the behavior of
Locator.raise_if_exceeds
changed from raising a RuntimeError to emitting a
log at WARNING level.
nonsingular Locators¶
Locator.nonsingular
(introduced in mpl 3.1), DateLocator.nonsingular
, and
AutoDateLocator.nonsingular
now returns a range v0, v1
with v0 <= v1
.
This behavior is consistent with the implementation of nonsingular
by the
LogLocator
and LogitLocator
subclasses.
get_data_ratio
¶
Axes.get_data_ratio
now takes the axes scale into account (linear, log,
logit, etc.) before computing the y-to-x ratio. This change allows fixed
aspects to be applied to any combination of x and y scales.
Artist sticky edges¶
Previously, the sticky_edges
attribute of artists was a list of values such
that if an axis limit coincides with a sticky edge, it would not be expanded by
the axes margins (this is the mechanism that e.g. prevents margins from being
added around images).
sticky_edges
now have an additional effect on margins application: even if
an axis limit did not coincide with a sticky edge, it cannot cross a sticky
edge through margin application -- instead, the margins will only expand the
axis limit until it bumps against the sticky edge.
This change improves the margins of axes displaying a streamplot
:
- if the streamplot goes all the way to the edges of the vector field, then the axis limits are set to match exactly the vector field limits (whereas they would sometimes be off by a small floating point error previously).
- if the streamplot does not reach the edges of the vector field (e.g., due to
the use of
start_points
andmaxlength
), then margins expansion will not cross the vector field limits anymore.
This change is also used internally to ensure that polar plots don't display negative r values unless the user really passes in a negative value.
gid
in svg output¶
Previously, if a figure, axis, legend or some other artists had a custom
gid
set (e.g. via .set_gid()
), this would not be reflected in
the svg output. Instead a default gid, like figure_1
would be shown.
This is now fixed, such that e.g. fig.set_gid("myfigure")
correctly
shows up as <g id="myfigure">
in the svg file. If you relied on the
gid having the default format, you now need to make sure not to set the
gid
parameter of the artists.
Fonts¶
Font weight guessing now first checks for the presence of the FT_STYLE_BOLD_FLAG before trying to match substrings in the font name. In particular, this means that Times New Roman Bold is now correctly detected as bold, not normal weight.
Color-like checking¶
matplotlib.color.is_colorlike()
used to return True for all string
representations of floats. However, only those with values in 0-1 are valid
colors (representing grayscale values). is_colorlike()
now returns False
for string representations of floats outside 0-1.
Default image interpolation¶
Images displayed in Matplotlib previously used nearest-neighbor interpolation, leading to aliasing effects for downscaling and non-integer upscaling.
New default for rcParams["image.interpolation"]
(default: 'antialiased') is the new option "antialiased".
imshow(A, interpolation='antialiased')
will apply a Hanning filter when
resampling the data in A for display (or saving to file) if the upsample
rate is less than a factor of three, and not an integer; downsampled data is
always smoothed at resampling.
To get the old behavior, set rcParams["image.interpolation"]
(default: 'antialiased') to the old default "nearest"
(or specify the interpolation
kwarg of Axes.imshow
)
To always get the anti-aliasing behavior, no matter what the up/down sample
rate, set rcParams["image.interpolation"]
(default: 'antialiased') to "hanning" (or one of the other filters
available).
Note that the "hanning" filter was chosen because it has only a modest performance penalty. Anti-aliasing can be improved with other filters.
rcParams¶
When using RendererSVG
with rcParams["svg.image_inline"] ==
True
, externally written images now use a single counter even if the
renderer.basename
attribute is overwritten, rather than a counter per
basename.
This change will only affect you if you used rcParams["svg.image_inline"] = True
(the default is False) and manually modified renderer.basename
.
Changed the default value of rcParams["axes.formatter.limits"]
(default: [-5, 6]) from -7, 7 to -5, 6
for better readability.
add_subplot()
¶
Figure.add_subplot()
and pyplot.subplot()
do not accept a figure
keyword argument anymore. It only used to work anyway if the passed figure
was self
or the current figure, respectively.
indicate_inset()
¶
In <= 3.1.0, indicate_inset
and
indicate_inset_zoom
were documented as returning
a 4-tuple of ConnectionPatch
, where in fact they
returned a 4-length list.
They now correctly return a 4-tuple.
indicate_inset
would previously raise an error if
the optional inset_ax was not supplied; it now completes successfully,
and returns None instead of the tuple of ConnectionPatch
.
PGF backend¶
The pgf backend's get_canvas_width_height now returns the canvas size in
display units rather than in inches, which it previously did.
The new behavior is the correct one given the uses of get_canvas_width_height
in the rest of the codebase.
The pgf backend now includes images using \includegraphics
instead of
\pgfimage
if the version of graphicx
is recent enough to support the
interpolate
option (this is detected automatically).
cbook
¶
The default value of the "obj_type" parameter to cbook.warn_deprecated
has
been changed from "attribute" (a default that was never used internally) to the
empty string.
Testing¶
The test suite no longer turns on the Python fault handler by default.
Set the standard PYTHONFAULTHANDLER
environment variable to do so.
Backend supports_blit
¶
Backends do not need to explicitly define the flag supports_blit
anymore.
This is only relevant for backend developers. Backends had to define the flag
supports_blit
. This is not needed anymore because the blitting capability
is now automatically detected.
Exception changes¶
Various APIs that raised a ValueError
for incorrectly typed inputs now raise
TypeError
instead: backend_bases.GraphicsContextBase.set_clip_path
,
blocking_input.BlockingInput.__call__
, cm.register_cmap
, dviread.DviFont
,
rcsetup.validate_hatch
, rcsetup.validate_animation_writer_path
, spines.Spine
,
many classes in the matplotlib.transforms
module and matplotlib.tri
package, and Axes methods that take a norm
parameter.
If extra kwargs are passed to LogScale
, TypeError
will now be
raised instead of ValueError
.
mplot3d auto-registration¶
mpl_toolkits.mplot3d
is always registered by default now. It is no
longer necessary to import mplot3d to create 3d axes with
ax = fig.add_subplot(111, projection="3d")
SymLogNorm
now has a base parameter¶
Previously, SymLogNorm
had no base keyword argument and the base was
hard-coded to base=np.e
. This was inconsistent with the default behavior of
SymmetricalLogScale
(which defaults to base=10
) and the use of the word
"decade" in the documentation.
In preparation for changing the default base to 10, calling SymLogNorm
without the new base keyword argument emits a deprecation warning.