"""
`matplotlib.figure` implements the following classes:
`Figure`
Top level `~matplotlib.artist.Artist`, which holds all plot elements.
Many methods are implemented in `FigureBase`.
`SubFigure`
A logical figure inside a figure, usually added to a figure (or parent
`SubFigure`) with `Figure.add_subfigure` or `Figure.subfigures` methods
(provisional API v3.4).
`SubplotParams`
Control the default spacing between subplots.
Figures are typically created using pyplot methods `~.pyplot.figure`,
`~.pyplot.subplots`, and `~.pyplot.subplot_mosaic`.
.. plot::
:include-source:
fig, ax = plt.subplots(figsize=(2, 2), facecolor='lightskyblue',
layout='constrained')
fig.suptitle('Figure')
ax.set_title('Axes', loc='left', fontstyle='oblique', fontsize='medium')
Some situations call for directly instantiating a `~.figure.Figure` class,
usually inside an application of some sort (see :ref:`user_interfaces` for a
list of examples) . More information about Figures can be found at
:ref:`figure-intro`.
"""
from contextlib import ExitStack
import inspect
import itertools
import logging
from numbers import Integral
import threading
import numpy as np
import matplotlib as mpl
from matplotlib import _blocking_input, backend_bases, _docstring, projections
from matplotlib.artist import (
Artist, allow_rasterization, _finalize_rasterization)
from matplotlib.backend_bases import (
DrawEvent, FigureCanvasBase, NonGuiException, MouseButton, _get_renderer)
import matplotlib._api as _api
import matplotlib.cbook as cbook
import matplotlib.colorbar as cbar
import matplotlib.image as mimage
from matplotlib.axes import Axes
from matplotlib.gridspec import GridSpec
from matplotlib.layout_engine import (
ConstrainedLayoutEngine, TightLayoutEngine, LayoutEngine,
PlaceHolderLayoutEngine
)
import matplotlib.legend as mlegend
from matplotlib.patches import Rectangle
from matplotlib.text import Text
from matplotlib.transforms import (Affine2D, Bbox, BboxTransformTo,
TransformedBbox)
_log = logging.getLogger(__name__)
def _stale_figure_callback(self, val):
if self.figure:
self.figure.stale = val
class _AxesStack:
"""
Helper class to track axes in a figure.
Axes are tracked both in the order in which they have been added
(``self._axes`` insertion/iteration order) and in the separate "gca" stack
(which is the index to which they map in the ``self._axes`` dict).
"""
def __init__(self):
self._axes = {} # Mapping of axes to "gca" order.
self._counter = itertools.count()
def as_list(self):
"""List the axes that have been added to the figure."""
return [*self._axes] # This relies on dict preserving order.
def remove(self, a):
"""Remove the axes from the stack."""
self._axes.pop(a)
def bubble(self, a):
"""Move an axes, which must already exist in the stack, to the top."""
if a not in self._axes:
raise ValueError("Axes has not been added yet")
self._axes[a] = next(self._counter)
def add(self, a):
"""Add an axes to the stack, ignoring it if already present."""
if a not in self._axes:
self._axes[a] = next(self._counter)
def current(self):
"""Return the active axes, or None if the stack is empty."""
return max(self._axes, key=self._axes.__getitem__, default=None)
def __getstate__(self):
return {
**vars(self),
"_counter": max(self._axes.values(), default=0)
}
def __setstate__(self, state):
next_counter = state.pop('_counter')
vars(self).update(state)
self._counter = itertools.count(next_counter)
class SubplotParams:
"""
A class to hold the parameters for a subplot.
"""
def __init__(self, left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None):
"""
Defaults are given by :rc:`figure.subplot.[name]`.
Parameters
----------
left : float
The position of the left edge of the subplots,
as a fraction of the figure width.
right : float
The position of the right edge of the subplots,
as a fraction of the figure width.
bottom : float
The position of the bottom edge of the subplots,
as a fraction of the figure height.
top : float
The position of the top edge of the subplots,
as a fraction of the figure height.
wspace : float
The width of the padding between subplots,
as a fraction of the average Axes width.
hspace : float
The height of the padding between subplots,
as a fraction of the average Axes height.
"""
for key in ["left", "bottom", "right", "top", "wspace", "hspace"]:
setattr(self, key, mpl.rcParams[f"figure.subplot.{key}"])
self.update(left, bottom, right, top, wspace, hspace)
def update(self, left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None):
"""
Update the dimensions of the passed parameters. *None* means unchanged.
"""
if ((left if left is not None else self.left)
>= (right if right is not None else self.right)):
raise ValueError('left cannot be >= right')
if ((bottom if bottom is not None else self.bottom)
>= (top if top is not None else self.top)):
raise ValueError('bottom cannot be >= top')
if left is not None:
self.left = left
if right is not None:
self.right = right
if bottom is not None:
self.bottom = bottom
if top is not None:
self.top = top
if wspace is not None:
self.wspace = wspace
if hspace is not None:
self.hspace = hspace
class FigureBase(Artist):
"""
Base class for `.Figure` and `.SubFigure` containing the methods that add
artists to the figure or subfigure, create Axes, etc.
"""
def __init__(self, **kwargs):
super().__init__()
# remove the non-figure artist _axes property
# as it makes no sense for a figure to be _in_ an Axes
# this is used by the property methods in the artist base class
# which are over-ridden in this class
del self._axes
self._suptitle = None
self._supxlabel = None
self._supylabel = None
# groupers to keep track of x and y labels we want to align.
# see self.align_xlabels and self.align_ylabels and
# axis._get_tick_boxes_siblings
self._align_label_groups = {"x": cbook.Grouper(), "y": cbook.Grouper()}
self._localaxes = [] # track all axes
self.artists = []
self.lines = []
self.patches = []
self.texts = []
self.images = []
self.legends = []
self.subfigs = []
self.stale = True
self.suppressComposite = None
self.set(**kwargs)
def _get_draw_artists(self, renderer):
"""Also runs apply_aspect"""
artists = self.get_children()
for sfig in self.subfigs:
artists.remove(sfig)
childa = sfig.get_children()
for child in childa:
if child in artists:
artists.remove(child)
artists.remove(self.patch)
artists = sorted(
(artist for artist in artists if not artist.get_animated()),
key=lambda artist: artist.get_zorder())
for ax in self._localaxes:
locator = ax.get_axes_locator()
ax.apply_aspect(locator(ax, renderer) if locator else None)
for child in ax.get_children():
if hasattr(child, 'apply_aspect'):
locator = child.get_axes_locator()
child.apply_aspect(
locator(child, renderer) if locator else None)
return artists
def autofmt_xdate(
self, bottom=0.2, rotation=30, ha='right', which='major'):
"""
Date ticklabels often overlap, so it is useful to rotate them
and right align them. Also, a common use case is a number of
subplots with shared x-axis where the x-axis is date data. The
ticklabels are often long, and it helps to rotate them on the
bottom subplot and turn them off on other subplots, as well as
turn off xlabels.
Parameters
----------
bottom : float, default: 0.2
The bottom of the subplots for `subplots_adjust`.
rotation : float, default: 30 degrees
The rotation angle of the xtick labels in degrees.
ha : {'left', 'center', 'right'}, default: 'right'
The horizontal alignment of the xticklabels.
which : {'major', 'minor', 'both'}, default: 'major'
Selects which ticklabels to rotate.
"""
_api.check_in_list(['major', 'minor', 'both'], which=which)
allsubplots = all(ax.get_subplotspec() for ax in self.axes)
if len(self.axes) == 1:
for label in self.axes[0].get_xticklabels(which=which):
label.set_ha(ha)
label.set_rotation(rotation)
else:
if allsubplots:
for ax in self.get_axes():
if ax.get_subplotspec().is_last_row():
for label in ax.get_xticklabels(which=which):
label.set_ha(ha)
label.set_rotation(rotation)
else:
for label in ax.get_xticklabels(which=which):
label.set_visible(False)
ax.set_xlabel('')
if allsubplots:
self.subplots_adjust(bottom=bottom)
self.stale = True
def get_children(self):
"""Get a list of artists contained in the figure."""
return [self.patch,
*self.artists,
*self._localaxes,
*self.lines,
*self.patches,
*self.texts,
*self.images,
*self.legends,
*self.subfigs]
def contains(self, mouseevent):
"""
Test whether the mouse event occurred on the figure.
Returns
-------
bool, {}
"""
if self._different_canvas(mouseevent):
return False, {}
inside = self.bbox.contains(mouseevent.x, mouseevent.y)
return inside, {}
def get_window_extent(self, renderer=None):
# docstring inherited
return self.bbox
def _suplabels(self, t, info, **kwargs):
"""
Add a centered %(name)s to the figure.
Parameters
----------
t : str
The %(name)s text.
x : float, default: %(x0)s
The x location of the text in figure coordinates.
y : float, default: %(y0)s
The y location of the text in figure coordinates.
horizontalalignment, ha : {'center', 'left', 'right'}, default: %(ha)s
The horizontal alignment of the text relative to (*x*, *y*).
verticalalignment, va : {'top', 'center', 'bottom', 'baseline'}, \
default: %(va)s
The vertical alignment of the text relative to (*x*, *y*).
fontsize, size : default: :rc:`figure.%(rc)ssize`
The font size of the text. See `.Text.set_size` for possible
values.
fontweight, weight : default: :rc:`figure.%(rc)sweight`
The font weight of the text. See `.Text.set_weight` for possible
values.
Returns
-------
text
The `.Text` instance of the %(name)s.
Other Parameters
----------------
fontproperties : None or dict, optional
A dict of font properties. If *fontproperties* is given the
default values for font size and weight are taken from the
`.FontProperties` defaults. :rc:`figure.%(rc)ssize` and
:rc:`figure.%(rc)sweight` are ignored in this case.
**kwargs
Additional kwargs are `matplotlib.text.Text` properties.
"""
suplab = getattr(self, info['name'])
x = kwargs.pop('x', None)
y = kwargs.pop('y', None)
if info['name'] in ['_supxlabel', '_suptitle']:
autopos = y is None
elif info['name'] == '_supylabel':
autopos = x is None
if x is None:
x = info['x0']
if y is None:
y = info['y0']
if 'horizontalalignment' not in kwargs and 'ha' not in kwargs:
kwargs['horizontalalignment'] = info['ha']
if 'verticalalignment' not in kwargs and 'va' not in kwargs:
kwargs['verticalalignment'] = info['va']
if 'rotation' not in kwargs:
kwargs['rotation'] = info['rotation']
if 'fontproperties' not in kwargs:
if 'fontsize' not in kwargs and 'size' not in kwargs:
kwargs['size'] = mpl.rcParams[info['size']]
if 'fontweight' not in kwargs and 'weight' not in kwargs:
kwargs['weight'] = mpl.rcParams[info['weight']]
sup = self.text(x, y, t, **kwargs)
if suplab is not None:
suplab.set_text(t)
suplab.set_position((x, y))
suplab.update_from(sup)
sup.remove()
else:
suplab = sup
suplab._autopos = autopos
setattr(self, info['name'], suplab)
self.stale = True
return suplab
@_docstring.Substitution(x0=0.5, y0=0.98, name='suptitle', ha='center',
va='top', rc='title')
@_docstring.copy(_suplabels)
def suptitle(self, t, **kwargs):
# docstring from _suplabels...
info = {'name': '_suptitle', 'x0': 0.5, 'y0': 0.98,
'ha': 'center', 'va': 'top', 'rotation': 0,
'size': 'figure.titlesize', 'weight': 'figure.titleweight'}
return self._suplabels(t, info, **kwargs)
def get_suptitle(self):
"""Return the suptitle as string or an empty string if not set."""
text_obj = self._suptitle
return "" if text_obj is None else text_obj.get_text()
@_docstring.Substitution(x0=0.5, y0=0.01, name='supxlabel', ha='center',
va='bottom', rc='label')
@_docstring.copy(_suplabels)
def supxlabel(self, t, **kwargs):
# docstring from _suplabels...
info = {'name': '_supxlabel', 'x0': 0.5, 'y0': 0.01,
'ha': 'center', 'va': 'bottom', 'rotation': 0,
'size': 'figure.labelsize', 'weight': 'figure.labelweight'}
return self._suplabels(t, info, **kwargs)
def get_supxlabel(self):
"""Return the supxlabel as string or an empty string if not set."""
text_obj = self._supxlabel
return "" if text_obj is None else text_obj.get_text()
@_docstring.Substitution(x0=0.02, y0=0.5, name='supylabel', ha='left',
va='center', rc='label')
@_docstring.copy(_suplabels)
def supylabel(self, t, **kwargs):
# docstring from _suplabels...
info = {'name': '_supylabel', 'x0': 0.02, 'y0': 0.5,
'ha': 'left', 'va': 'center', 'rotation': 'vertical',
'rotation_mode': 'anchor', 'size': 'figure.labelsize',
'weight': 'figure.labelweight'}
return self._suplabels(t, info, **kwargs)
def get_supylabel(self):
"""Return the supylabel as string or an empty string if not set."""
text_obj = self._supylabel
return "" if text_obj is None else text_obj.get_text()
def get_edgecolor(self):
"""Get the edge color of the Figure rectangle."""
return self.patch.get_edgecolor()
def get_facecolor(self):
"""Get the face color of the Figure rectangle."""
return self.patch.get_facecolor()
def get_frameon(self):
"""
Return the figure's background patch visibility, i.e.
whether the figure background will be drawn. Equivalent to
``Figure.patch.get_visible()``.
"""
return self.patch.get_visible()
def set_linewidth(self, linewidth):
"""
Set the line width of the Figure rectangle.
Parameters
----------
linewidth : number
"""
self.patch.set_linewidth(linewidth)
def get_linewidth(self):
"""
Get the line width of the Figure rectangle.
"""
return self.patch.get_linewidth()
def set_edgecolor(self, color):
"""
Set the edge color of the Figure rectangle.
Parameters
----------
color : color
"""
self.patch.set_edgecolor(color)
def set_facecolor(self, color):
"""
Set the face color of the Figure rectangle.
Parameters
----------
color : color
"""
self.patch.set_facecolor(color)
def set_frameon(self, b):
"""
Set the figure's background patch visibility, i.e.
whether the figure background will be drawn. Equivalent to
``Figure.patch.set_visible()``.
Parameters
----------
b : bool
"""
self.patch.set_visible(b)
self.stale = True
frameon = property(get_frameon, set_frameon)
def add_artist(self, artist, clip=False):
"""
Add an `.Artist` to the figure.
Usually artists are added to `~.axes.Axes` objects using
`.Axes.add_artist`; this method can be used in the rare cases where
one needs to add artists directly to the figure instead.
Parameters
----------
artist : `~matplotlib.artist.Artist`
The artist to add to the figure. If the added artist has no
transform previously set, its transform will be set to
``figure.transSubfigure``.
clip : bool, default: False
Whether the added artist should be clipped by the figure patch.
Returns
-------
`~matplotlib.artist.Artist`
The added artist.
"""
artist.set_figure(self)
self.artists.append(artist)
artist._remove_method = self.artists.remove
if not artist.is_transform_set():
artist.set_transform(self.transSubfigure)
if clip and artist.get_clip_path() is None:
artist.set_clip_path(self.patch)
self.stale = True
return artist
@_docstring.dedent_interpd
def add_axes(self, *args, **kwargs):
"""
Add an `~.axes.Axes` to the figure.
Call signatures::
add_axes(rect, projection=None, polar=False, **kwargs)
add_axes(ax)
Parameters
----------
rect : tuple (left, bottom, width, height)
The dimensions (left, bottom, width, height) of the new
`~.axes.Axes`. All quantities are in fractions of figure width and
height.
projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \
'polar', 'rectilinear', str}, optional
The projection type of the `~.axes.Axes`. *str* is the name of
a custom projection, see `~matplotlib.projections`. The default
None results in a 'rectilinear' projection.
polar : bool, default: False
If True, equivalent to projection='polar'.
axes_class : subclass type of `~.axes.Axes`, optional
The `.axes.Axes` subclass that is instantiated. This parameter
is incompatible with *projection* and *polar*. See
:ref:`axisartist_users-guide-index` for examples.
sharex, sharey : `~matplotlib.axes.Axes`, optional
Share the x or y `~matplotlib.axis` with sharex and/or sharey.
The axis will have the same limits, ticks, and scale as the axis
of the shared axes.
label : str
A label for the returned Axes.
Returns
-------
`~.axes.Axes`, or a subclass of `~.axes.Axes`
The returned axes class depends on the projection used. It is
`~.axes.Axes` if rectilinear projection is used and
`.projections.polar.PolarAxes` if polar projection is used.
Other Parameters
----------------
**kwargs
This method also takes the keyword arguments for
the returned Axes class. The keyword arguments for the
rectilinear Axes class `~.axes.Axes` can be found in
the following table but there might also be other keyword
arguments if another projection is used, see the actual Axes
class.
%(Axes:kwdoc)s
Notes
-----
In rare circumstances, `.add_axes` may be called with a single
argument, an Axes instance already created in the present figure but
not in the figure's list of Axes.
See Also
--------
.Figure.add_subplot
.pyplot.subplot
.pyplot.axes
.Figure.subplots
.pyplot.subplots
Examples
--------
Some simple examples::
rect = l, b, w, h
fig = plt.figure()
fig.add_axes(rect)
fig.add_axes(rect, frameon=False, facecolor='g')
fig.add_axes(rect, polar=True)
ax = fig.add_axes(rect, projection='polar')
fig.delaxes(ax)
fig.add_axes(ax)
"""
if not len(args) and 'rect' not in kwargs:
raise TypeError(
"add_axes() missing 1 required positional argument: 'rect'")
elif 'rect' in kwargs:
if len(args):
raise TypeError(
"add_axes() got multiple values for argument 'rect'")
args = (kwargs.pop('rect'), )
if isinstance(args[0], Axes):
a, *extra_args = args
key = a._projection_init
if a.get_figure() is not self:
raise ValueError(
"The Axes must have been created in the present figure")
else:
rect, *extra_args = args
if not np.isfinite(rect).all():
raise ValueError(f'all entries in rect must be finite not {rect}')
projection_class, pkw = self._process_projection_requirements(**kwargs)
# create the new axes using the axes class given
a = projection_class(self, rect, **pkw)
key = (projection_class, pkw)
if extra_args:
_api.warn_deprecated(
"3.8",
name="Passing more than one positional argument to Figure.add_axes",
addendum="Any additional positional arguments are currently ignored.")
return self._add_axes_internal(a, key)
@_docstring.dedent_interpd
def add_subplot(self, *args, **kwargs):
"""
Add an `~.axes.Axes` to the figure as part of a subplot arrangement.
Call signatures::
add_subplot(nrows, ncols, index, **kwargs)
add_subplot(pos, **kwargs)
add_subplot(ax)
add_subplot()
Parameters
----------
*args : int, (int, int, *index*), or `.SubplotSpec`, default: (1, 1, 1)
The position of the subplot described by one of
- Three integers (*nrows*, *ncols*, *index*). The subplot will
take the *index* position on a grid with *nrows* rows and
*ncols* columns. *index* starts at 1 in the upper left corner
and increases to the right. *index* can also be a two-tuple
specifying the (*first*, *last*) indices (1-based, and including
*last*) of the subplot, e.g., ``fig.add_subplot(3, 1, (1, 2))``
makes a subplot that spans the upper 2/3 of the figure.
- A 3-digit integer. The digits are interpreted as if given
separately as three single-digit integers, i.e.
``fig.add_subplot(235)`` is the same as
``fig.add_subplot(2, 3, 5)``. Note that this can only be used
if there are no more than 9 subplots.
- A `.SubplotSpec`.
In rare circumstances, `.add_subplot` may be called with a single
argument, a subplot Axes instance already created in the
present figure but not in the figure's list of Axes.
projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \
'polar', 'rectilinear', str}, optional
The projection type of the subplot (`~.axes.Axes`). *str* is the
name of a custom projection, see `~matplotlib.projections`. The
default None results in a 'rectilinear' projection.
polar : bool, default: False
If True, equivalent to projection='polar'.
axes_class : subclass type of `~.axes.Axes`, optional
The `.axes.Axes` subclass that is instantiated. This parameter
is incompatible with *projection* and *polar*. See
:ref:`axisartist_users-guide-index` for examples.
sharex, sharey : `~matplotlib.axes.Axes`, optional
Share the x or y `~matplotlib.axis` with sharex and/or sharey.
The axis will have the same limits, ticks, and scale as the axis
of the shared axes.
label : str
A label for the returned Axes.
Returns
-------
`~.axes.Axes`
The Axes of the subplot. The returned Axes can actually be an
instance of a subclass, such as `.projections.polar.PolarAxes` for
polar projections.
Other Parameters
----------------
**kwargs
This method also takes the keyword arguments for the returned Axes
base class; except for the *figure* argument. The keyword arguments
for the rectilinear base class `~.axes.Axes` can be found in
the following table but there might also be other keyword
arguments if another projection is used.
%(Axes:kwdoc)s
See Also
--------
.Figure.add_axes
.pyplot.subplot
.pyplot.axes
.Figure.subplots
.pyplot.subplots
Examples
--------
::
fig = plt.figure()
fig.add_subplot(231)
ax1 = fig.add_subplot(2, 3, 1) # equivalent but more general
fig.add_subplot(232, frameon=False) # subplot with no frame
fig.add_subplot(233, projection='polar') # polar subplot
fig.add_subplot(234, sharex=ax1) # subplot sharing x-axis with ax1
fig.add_subplot(235, facecolor="red") # red subplot
ax1.remove() # delete ax1 from the figure
fig.add_subplot(ax1) # add ax1 back to the figure
"""
if 'figure' in kwargs:
# Axes itself allows for a 'figure' kwarg, but since we want to
# bind the created Axes to self, it is not allowed here.
raise _api.kwarg_error("add_subplot", "figure")
if (len(args) == 1
and isinstance(args[0], mpl.axes._base._AxesBase)
and args[0].get_subplotspec()):
ax = args[0]
key = ax._projection_init
if ax.get_figure() is not self:
raise ValueError("The Axes must have been created in "
"the present figure")
else:
if not args:
args = (1, 1, 1)
# Normalize correct ijk values to (i, j, k) here so that
# add_subplot(211) == add_subplot(2, 1, 1). Invalid values will
# trigger errors later (via SubplotSpec._from_subplot_args).
if (len(args) == 1 and isinstance(args[0], Integral)
and 100 <= args[0] <= 999):
args = tuple(map(int, str(args[0])))
projection_class, pkw = self._process_projection_requirements(**kwargs)
ax = projection_class(self, *args, **pkw)
key = (projection_class, pkw)
return self._add_axes_internal(ax, key)
def _add_axes_internal(self, ax, key):
"""Private helper for `add_axes` and `add_subplot`."""
self._axstack.add(ax)
if ax not in self._localaxes:
self._localaxes.append(ax)
self.sca(ax)
ax._remove_method = self.delaxes
# this is to support plt.subplot's re-selection logic
ax._projection_init = key
self.stale = True
ax.stale_callback = _stale_figure_callback
return ax
def subplots(self, nrows=1, ncols=1, *, sharex=False, sharey=False,
squeeze=True, width_ratios=None, height_ratios=None,
subplot_kw=None, gridspec_kw=None):
"""
Add a set of subplots to this figure.
This utility wrapper makes it convenient to create common layouts of
subplots in a single call.
Parameters
----------
nrows, ncols : int, default: 1
Number of rows/columns of the subplot grid.
sharex, sharey : bool or {'none', 'all', 'row', 'col'}, default: False
Controls sharing of x-axis (*sharex*) or y-axis (*sharey*):
- True or 'all': x- or y-axis will be shared among all subplots.
- False or 'none': each subplot x- or y-axis will be independent.
- 'row': each subplot row will share an x- or y-axis.
- 'col': each subplot column will share an x- or y-axis.
When subplots have a shared x-axis along a column, only the x tick
labels of the bottom subplot are created. Similarly, when subplots
have a shared y-axis along a row, only the y tick labels of the
first column subplot are created. To later turn other subplots'
ticklabels on, use `~matplotlib.axes.Axes.tick_params`.
When subplots have a shared axis that has units, calling
`.Axis.set_units` will update each axis with the new units.
squeeze : bool, default: True
- If True, extra dimensions are squeezed out from the returned
array of Axes:
- if only one subplot is constructed (nrows=ncols=1), the
resulting single Axes object is returned as a scalar.
- for Nx1 or 1xM subplots, the returned object is a 1D numpy
object array of Axes objects.
- for NxM, subplots with N>1 and M>1 are returned as a 2D array.
- If False, no squeezing at all is done: the returned Axes object
is always a 2D array containing Axes instances, even if it ends
up being 1x1.
width_ratios : array-like of length *ncols*, optional
Defines the relative widths of the columns. Each column gets a
relative width of ``width_ratios[i] / sum(width_ratios)``.
If not given, all columns will have the same width. Equivalent
to ``gridspec_kw={'width_ratios': [...]}``.
height_ratios : array-like of length *nrows*, optional
Defines the relative heights of the rows. Each row gets a
relative height of ``height_ratios[i] / sum(height_ratios)``.
If not given, all rows will have the same height. Equivalent
to ``gridspec_kw={'height_ratios': [...]}``.
subplot_kw : dict, optional
Dict with keywords passed to the `.Figure.add_subplot` call used to
create each subplot.
gridspec_kw : dict, optional
Dict with keywords passed to the
`~matplotlib.gridspec.GridSpec` constructor used to create
the grid the subplots are placed on.
Returns
-------
`~.axes.Axes` or array of Axes
Either a single `~matplotlib.axes.Axes` object or an array of Axes
objects if more than one subplot was created. The dimensions of the
resulting array can be controlled with the *squeeze* keyword, see
above.
See Also
--------
.pyplot.subplots
.Figure.add_subplot
.pyplot.subplot
Examples
--------
::
# First create some toy data:
x = np.linspace(0, 2*np.pi, 400)
y = np.sin(x**2)
# Create a figure
fig = plt.figure()
# Create a subplot
ax = fig.subplots()
ax.plot(x, y)
ax.set_title('Simple plot')
# Create two subplots and unpack the output array immediately
ax1, ax2 = fig.subplots(1, 2, sharey=True)
ax1.plot(x, y)
ax1.set_title('Sharing Y axis')
ax2.scatter(x, y)
# Create four polar Axes and access them through the returned array
axes = fig.subplots(2, 2, subplot_kw=dict(projection='polar'))
axes[0, 0].plot(x, y)
axes[1, 1].scatter(x, y)
# Share an X-axis with each column of subplots
fig.subplots(2, 2, sharex='col')
# Share a Y-axis with each row of subplots
fig.subplots(2, 2, sharey='row')
# Share both X- and Y-axes with all subplots
fig.subplots(2, 2, sharex='all', sharey='all')
# Note that this is the same as
fig.subplots(2, 2, sharex=True, sharey=True)
"""
gridspec_kw = dict(gridspec_kw or {})
if height_ratios is not None:
if 'height_ratios' in gridspec_kw:
raise ValueError("'height_ratios' must not be defined both as "
"parameter and as key in 'gridspec_kw'")
gridspec_kw['height_ratios'] = height_ratios
if width_ratios is not None:
if 'width_ratios' in gridspec_kw:
raise ValueError("'width_ratios' must not be defined both as "
"parameter and as key in 'gridspec_kw'")
gridspec_kw['width_ratios'] = width_ratios
gs = self.add_gridspec(nrows, ncols, figure=self, **gridspec_kw)
axs = gs.subplots(sharex=sharex, sharey=sharey, squeeze=squeeze,
subplot_kw=subplot_kw)
return axs
def delaxes(self, ax):
"""
Remove the `~.axes.Axes` *ax* from the figure; update the current Axes.
"""
self._remove_axes(ax, owners=[self._axstack, self._localaxes])
def _remove_axes(self, ax, owners):
"""
Common helper for removal of standard axes (via delaxes) and of child axes.
Parameters
----------
ax : `~.AxesBase`
The Axes to remove.
owners
List of objects (list or _AxesStack) "owning" the axes, from which the Axes
will be remove()d.
"""
for owner in owners:
owner.remove(ax)
self._axobservers.process("_axes_change_event", self)
self.stale = True
self.canvas.release_mouse(ax)
for name in ax._axis_names: # Break link between any shared axes
grouper = ax._shared_axes[name]
siblings = [other for other in grouper.get_siblings(ax) if other is not ax]
if not siblings: # Axes was not shared along this axis; we're done.
continue
grouper.remove(ax)
# Formatters and locators may previously have been associated with the now
# removed axis. Update them to point to an axis still there (we can pick
# any of them, and use the first sibling).
remaining_axis = siblings[0]._axis_map[name]
remaining_axis.get_major_formatter().set_axis(remaining_axis)
remaining_axis.get_major_locator().set_axis(remaining_axis)
remaining_axis.get_minor_formatter().set_axis(remaining_axis)
remaining_axis.get_minor_locator().set_axis(remaining_axis)
ax._twinned_axes.remove(ax) # Break link between any twinned axes.
def clear(self, keep_observers=False):
"""
Clear the figure.
Parameters
----------
keep_observers : bool, default: False
Set *keep_observers* to True if, for example,
a gui widget is tracking the Axes in the figure.
"""
self.suppressComposite = None
# first clear the axes in any subfigures
for subfig in self.subfigs:
subfig.clear(keep_observers=keep_observers)
self.subfigs = []
for ax in tuple(self.axes): # Iterate over the copy.
ax.clear()
self.delaxes(ax) # Remove ax from self._axstack.
self.artists = []
self.lines = []
self.patches = []
self.texts = []
self.images = []
self.legends = []
if not keep_observers:
self._axobservers = cbook.CallbackRegistry()
self._suptitle = None
self._supxlabel = None
self._supylabel = None
self.stale = True
# synonym for `clear`.
def clf(self, keep_observers=False):
"""
[*Discouraged*] Alias for the `clear()` method.
.. admonition:: Discouraged
The use of ``clf()`` is discouraged. Use ``clear()`` instead.
Parameters
----------
keep_observers : bool, default: False
Set *keep_observers* to True if, for example,
a gui widget is tracking the Axes in the figure.
"""
return self.clear(keep_observers=keep_observers)
# Note: the docstring below is modified with replace for the pyplot
# version of this function because the method name differs (plt.figlegend)
# the replacements are:
# " legend(" -> " figlegend(" for the signatures
# "fig.legend(" -> "plt.figlegend" for the code examples
# "ax.plot" -> "plt.plot" for consistency in using pyplot when able
@_docstring.dedent_interpd
def legend(self, *args, **kwargs):
"""
Place a legend on the figure.
Call signatures::
legend()
legend(handles, labels)
legend(handles=handles)
legend(labels)
The call signatures correspond to the following different ways to use
this method:
**1. Automatic detection of elements to be shown in the legend**
The elements to be added to the legend are automatically determined,
when you do not pass in any extra arguments.
In this case, the labels are taken from the artist. You can specify
them either at artist creation or by calling the
:meth:`~.Artist.set_label` method on the artist::
ax.plot([1, 2, 3], label='Inline label')
fig.legend()
or::
line, = ax.plot([1, 2, 3])
line.set_label('Label via method')
fig.legend()
Specific lines can be excluded from the automatic legend element
selection by defining a label starting with an underscore.
This is default for all artists, so calling `.Figure.legend` without
any arguments and without setting the labels manually will result in
no legend being drawn.
**2. Explicitly listing the artists and labels in the legend**
For full control of which artists have a legend entry, it is possible
to pass an iterable of legend artists followed by an iterable of
legend labels respectively::
fig.legend([line1, line2, line3], ['label1', 'label2', 'label3'])
**3. Explicitly listing the artists in the legend**
This is similar to 2, but the labels are taken from the artists'
label properties. Example::
line1, = ax1.plot([1, 2, 3], label='label1')
line2, = ax2.plot([1, 2, 3], label='label2')
fig.legend(handles=[line1, line2])
**4. Labeling existing plot elements**
.. admonition:: Discouraged
This call signature is discouraged, because the relation between
plot elements and labels is only implicit by their order and can
easily be mixed up.
To make a legend for all artists on all Axes, call this function with
an iterable of strings, one for each legend item. For example::
fig, (ax1, ax2) = plt.subplots(1, 2)
ax1.plot([1, 3, 5], color='blue')
ax2.plot([2, 4, 6], color='red')
fig.legend(['the blues', 'the reds'])
Parameters
----------
handles : list of `.Artist`, optional
A list of Artists (lines, patches) to be added to the legend.
Use this together with *labels*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
The length of handles and labels should be the same in this
case. If they are not, they are truncated to the smaller length.
labels : list of str, optional
A list of labels to show next to the artists.
Use this together with *handles*, if you need full control on what
is shown in the legend and the automatic mechanism described above
is not sufficient.
Returns
-------
`~matplotlib.legend.Legend`
Other Parameters
----------------
%(_legend_kw_figure)s
See Also
--------
.Axes.legend
Notes
-----
Some artists are not supported by this function. See
:ref:`legend_guide` for details.
"""
handles, labels, kwargs = mlegend._parse_legend_args(self.axes, *args, **kwargs)
# explicitly set the bbox transform if the user hasn't.
kwargs.setdefault("bbox_transform", self.transSubfigure)
l = mlegend.Legend(self, handles, labels, **kwargs)
self.legends.append(l)
l._remove_method = self.legends.remove
self.stale = True
return l
@_docstring.dedent_interpd
def text(self, x, y, s, fontdict=None, **kwargs):
"""
Add text to figure.
Parameters
----------
x, y : float
The position to place the text. By default, this is in figure
coordinates, floats in [0, 1]. The coordinate system can be changed
using the *transform* keyword.
s : str
The text string.
fontdict : dict, optional
A dictionary to override the default text properties. If not given,
the defaults are determined by :rc:`font.*`. Properties passed as
*kwargs* override the corresponding ones given in *fontdict*.
Returns
-------
`~.text.Text`
Other Parameters
----------------
**kwargs : `~matplotlib.text.Text` properties
Other miscellaneous text parameters.
%(Text:kwdoc)s
See Also
--------
.Axes.text
.pyplot.text
"""
effective_kwargs = {
'transform': self.transSubfigure,
**(fontdict if fontdict is not None else {}),
**kwargs,
}
text = Text(x=x, y=y, text=s, **effective_kwargs)
text.set_figure(self)
text.stale_callback = _stale_figure_callback
self.texts.append(text)
text._remove_method = self.texts.remove
self.stale = True
return text
@_docstring.dedent_interpd
def colorbar(
self, mappable, cax=None, ax=None, use_gridspec=True, **kwargs):
"""
Add a colorbar to a plot.
Parameters
----------
mappable
The `matplotlib.cm.ScalarMappable` (i.e., `.AxesImage`,
`.ContourSet`, etc.) described by this colorbar. This argument is
mandatory for the `.Figure.colorbar` method but optional for the
`.pyplot.colorbar` function, which sets the default to the current
image.
Note that one can create a `.ScalarMappable` "on-the-fly" to
generate colorbars not attached to a previously drawn artist, e.g.
::
fig.colorbar(cm.ScalarMappable(norm=norm, cmap=cmap), ax=ax)
cax : `~matplotlib.axes.Axes`, optional
Axes into which the colorbar will be drawn. If `None`, then a new
Axes is created and the space for it will be stolen from the Axes(s)
specified in *ax*.
ax : `~matplotlib.axes.Axes` or iterable or `numpy.ndarray` of Axes, optional
The one or more parent Axes from which space for a new colorbar Axes
will be stolen. This parameter is only used if *cax* is not set.
Defaults to the Axes that contains the mappable used to create the
colorbar.
use_gridspec : bool, optional
If *cax* is ``None``, a new *cax* is created as an instance of
Axes. If *ax* is positioned with a subplotspec and *use_gridspec*
is ``True``, then *cax* is also positioned with a subplotspec.
Returns
-------
colorbar : `~matplotlib.colorbar.Colorbar`
Other Parameters
----------------
%(_make_axes_kw_doc)s
%(_colormap_kw_doc)s
Notes
-----
If *mappable* is a `~.contour.ContourSet`, its *extend* kwarg is
included automatically.
The *shrink* kwarg provides a simple way to scale the colorbar with
respect to the axes. Note that if *cax* is specified, it determines the
size of the colorbar, and *shrink* and *aspect* are ignored.
For more precise control, you can manually specify the positions of the
axes objects in which the mappable and the colorbar are drawn. In this
case, do not use any of the axes properties kwargs.
It is known that some vector graphics viewers (svg and pdf) render
white gaps between segments of the colorbar. This is due to bugs in
the viewers, not Matplotlib. As a workaround, the colorbar can be
rendered with overlapping segments::
cbar = colorbar()
cbar.solids.set_edgecolor("face")
draw()
However, this has negative consequences in other circumstances, e.g.
with semi-transparent images (alpha < 1) and colorbar extensions;
therefore, this workaround is not used by default (see issue #1188).
"""
if ax is None:
ax = getattr(mappable, "axes", None)
if cax is None:
if ax is None:
raise ValueError(
'Unable to determine Axes to steal space for Colorbar. '
'Either provide the *cax* argument to use as the Axes for '
'the Colorbar, provide the *ax* argument to steal space '
'from it, or add *mappable* to an Axes.')
fig = ( # Figure of first axes; logic copied from make_axes.
[*ax.flat] if isinstance(ax, np.ndarray)
else [*ax] if np.iterable(ax)
else [ax])[0].figure
current_ax = fig.gca()
if (fig.get_layout_engine() is not None and
not fig.get_layout_engine().colorbar_gridspec):
use_gridspec = False
if (use_gridspec
and isinstance(ax, mpl.axes._base._AxesBase)
and ax.get_subplotspec()):
cax, kwargs = cbar.make_axes_gridspec(ax, **kwargs)
else:
cax, kwargs = cbar.make_axes(ax, **kwargs)
# make_axes calls add_{axes,subplot} which changes gca; undo that.
fig.sca(current_ax)
cax.grid(visible=False, which='both', axis='both')
NON_COLORBAR_KEYS = [ # remove kws that cannot be passed to Colorbar
'fraction', 'pad', 'shrink', 'aspect', 'anchor', 'panchor']
cb = cbar.Colorbar(cax, mappable, **{
k: v for k, v in kwargs.items() if k not in NON_COLORBAR_KEYS})
cax.figure.stale = True
return cb
def subplots_adjust(self, left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None):
"""
Adjust the subplot layout parameters.
Unset parameters are left unmodified; initial values are given by
:rc:`figure.subplot.[name]`.
Parameters
----------
left : float, optional
The position of the left edge of the subplots,
as a fraction of the figure width.
right : float, optional
The position of the right edge of the subplots,
as a fraction of the figure width.
bottom : float, optional
The position of the bottom edge of the subplots,
as a fraction of the figure height.
top : float, optional
The position of the top edge of the subplots,
as a fraction of the figure height.
wspace : float, optional
The width of the padding between subplots,
as a fraction of the average Axes width.
hspace : float, optional
The height of the padding between subplots,
as a fraction of the average Axes height.
"""
if (self.get_layout_engine() is not None and
not self.get_layout_engine().adjust_compatible):
_api.warn_external(
"This figure was using a layout engine that is "
"incompatible with subplots_adjust and/or tight_layout; "
"not calling subplots_adjust.")
return
self.subplotpars.update(left, bottom, right, top, wspace, hspace)
for ax in self.axes:
if ax.get_subplotspec() is not None:
ax._set_position(ax.get_subplotspec().get_position(self))
self.stale = True
def align_xlabels(self, axs=None):
"""
Align the xlabels of subplots in the same subplot column if label
alignment is being done automatically (i.e. the label position is
not manually set).
Alignment persists for draw events after this is called.
If a label is on the bottom, it is aligned with labels on Axes that
also have their label on the bottom and that have the same
bottom-most subplot row. If the label is on the top,
it is aligned with labels on Axes with the same top-most row.
Parameters
----------
axs : list of `~matplotlib.axes.Axes`
Optional list of (or `~numpy.ndarray`) `~matplotlib.axes.Axes`
to align the xlabels.
Default is to align all Axes on the figure.
See Also
--------
matplotlib.figure.Figure.align_ylabels
matplotlib.figure.Figure.align_labels
Notes
-----
This assumes that ``axs`` are from the same `.GridSpec`, so that
their `.SubplotSpec` positions correspond to figure positions.
Examples
--------
Example with rotated xtick labels::
fig, axs = plt.subplots(1, 2)
for tick in axs[0].get_xticklabels():
tick.set_rotation(55)
axs[0].set_xlabel('XLabel 0')
axs[1].set_xlabel('XLabel 1')
fig.align_xlabels()
"""
if axs is None:
axs = self.axes
axs = [ax for ax in np.ravel(axs) if ax.get_subplotspec() is not None]
for ax in axs:
_log.debug(' Working on: %s', ax.get_xlabel())
rowspan = ax.get_subplotspec().rowspan
pos = ax.xaxis.get_label_position() # top or bottom
# Search through other axes for label positions that are same as
# this one and that share the appropriate row number.
# Add to a grouper associated with each axes of siblings.
# This list is inspected in `axis.draw` by
# `axis._update_label_position`.
for axc in axs:
if axc.xaxis.get_label_position() == pos:
rowspanc = axc.get_subplotspec().rowspan
if (pos == 'top' and rowspan.start == rowspanc.start or
pos == 'bottom' and rowspan.stop == rowspanc.stop):
# grouper for groups of xlabels to align
self._align_label_groups['x'].join(ax, axc)
def align_ylabels(self, axs=None):
"""
Align the ylabels of subplots in the same subplot column if label
alignment is being done automatically (i.e. the label position is
not manually set).
Alignment persists for draw events after this is called.
If a label is on the left, it is aligned with labels on Axes that
also have their label on the left and that have the same
left-most subplot column. If the label is on the right,
it is aligned with labels on Axes with the same right-most column.
Parameters
----------
axs : list of `~matplotlib.axes.Axes`
Optional list (or `~numpy.ndarray`) of `~matplotlib.axes.Axes`
to align the ylabels.
Default is to align all Axes on the figure.
See Also
--------
matplotlib.figure.Figure.align_xlabels
matplotlib.figure.Figure.align_labels
Notes
-----
This assumes that ``axs`` are from the same `.GridSpec`, so that
their `.SubplotSpec` positions correspond to figure positions.
Examples
--------
Example with large yticks labels::
fig, axs = plt.subplots(2, 1)
axs[0].plot(np.arange(0, 1000, 50))
axs[0].set_ylabel('YLabel 0')
axs[1].set_ylabel('YLabel 1')
fig.align_ylabels()
"""
if axs is None:
axs = self.axes
axs = [ax for ax in np.ravel(axs) if ax.get_subplotspec() is not None]
for ax in axs:
_log.debug(' Working on: %s', ax.get_ylabel())
colspan = ax.get_subplotspec().colspan
pos = ax.yaxis.get_label_position() # left or right
# Search through other axes for label positions that are same as
# this one and that share the appropriate column number.
# Add to a list associated with each axes of siblings.
# This list is inspected in `axis.draw` by
# `axis._update_label_position`.
for axc in axs:
if axc.yaxis.get_label_position() == pos:
colspanc = axc.get_subplotspec().colspan
if (pos == 'left' and colspan.start == colspanc.start or
pos == 'right' and colspan.stop == colspanc.stop):
# grouper for groups of ylabels to align
self._align_label_groups['y'].join(ax, axc)
def align_labels(self, axs=None):
"""
Align the xlabels and ylabels of subplots with the same subplots
row or column (respectively) if label alignment is being
done automatically (i.e. the label position is not manually set).
Alignment persists for draw events after this is called.
Parameters
----------
axs : list of `~matplotlib.axes.Axes`
Optional list (or `~numpy.ndarray`) of `~matplotlib.axes.Axes`
to align the labels.
Default is to align all Axes on the figure.
See Also
--------
matplotlib.figure.Figure.align_xlabels
matplotlib.figure.Figure.align_ylabels
"""
self.align_xlabels(axs=axs)
self.align_ylabels(axs=axs)
def add_gridspec(self, nrows=1, ncols=1, **kwargs):
"""
Return a `.GridSpec` that has this figure as a parent. This allows
complex layout of Axes in the figure.
Parameters
----------
nrows : int, default: 1
Number of rows in grid.
ncols : int, default: 1
Number of columns in grid.
Returns
-------
`.GridSpec`
Other Parameters
----------------
**kwargs
Keyword arguments are passed to `.GridSpec`.
See Also
--------
matplotlib.pyplot.subplots
Examples
--------
Adding a subplot that spans two rows::
fig = plt.figure()
gs = fig.add_gridspec(2, 2)
ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[1, 0])
# spans two rows:
ax3 = fig.add_subplot(gs[:, 1])
"""
_ = kwargs.pop('figure', None) # pop in case user has added this...
gs = GridSpec(nrows=nrows, ncols=ncols, figure=self, **kwargs)
return gs
def subfigures(self, nrows=1, ncols=1, squeeze=True,
wspace=None, hspace=None,
width_ratios=None, height_ratios=None,
**kwargs):
"""
Add a set of subfigures to this figure or subfigure.
A subfigure has the same artist methods as a figure, and is logically
the same as a figure, but cannot print itself.
See :doc:`/gallery/subplots_axes_and_figures/subfigures`.
.. note::
The *subfigure* concept is new in v3.4, and the API is still provisional.
Parameters
----------
nrows, ncols : int, default: 1
Number of rows/columns of the subfigure grid.
squeeze : bool, default: True
If True, extra dimensions are squeezed out from the returned
array of subfigures.
wspace, hspace : float, default: None
The amount of width/height reserved for space between subfigures,
expressed as a fraction of the average subfigure width/height.
If not given, the values will be inferred from rcParams if using
constrained layout (see `~.ConstrainedLayoutEngine`), or zero if
not using a layout engine.
width_ratios : array-like of length *ncols*, optional
Defines the relative widths of the columns. Each column gets a
relative width of ``width_ratios[i] / sum(width_ratios)``.
If not given, all columns will have the same width.
height_ratios : array-like of length *nrows*, optional
Defines the relative heights of the rows. Each row gets a
relative height of ``height_ratios[i] / sum(height_ratios)``.
If not given, all rows will have the same height.
"""
gs = GridSpec(nrows=nrows, ncols=ncols, figure=self,
wspace=wspace, hspace=hspace,
width_ratios=width_ratios,
height_ratios=height_ratios,
left=0, right=1, bottom=0, top=1)
sfarr = np.empty((nrows, ncols), dtype=object)
for i in range(ncols):
for j in range(nrows):
sfarr[j, i] = self.add_subfigure(gs[j, i], **kwargs)
if self.get_layout_engine() is None and (wspace is not None or
hspace is not None):
# Gridspec wspace and hspace is ignored on subfigure instantiation,
# and no space is left. So need to account for it here if required.
bottoms, tops, lefts, rights = gs.get_grid_positions(self)
for sfrow, bottom, top in zip(sfarr, bottoms, tops):
for sf, left, right in zip(sfrow, lefts, rights):
bbox = Bbox.from_extents(left, bottom, right, top)
sf._redo_transform_rel_fig(bbox=bbox)
if squeeze:
# Discarding unneeded dimensions that equal 1. If we only have one
# subfigure, just return it instead of a 1-element array.
return sfarr.item() if sfarr.size == 1 else sfarr.squeeze()
else:
# Returned axis array will be always 2-d, even if nrows=ncols=1.
return sfarr
def add_subfigure(self, subplotspec, **kwargs):
"""
Add a `.SubFigure` to the figure as part of a subplot arrangement.
Parameters
----------
subplotspec : `.gridspec.SubplotSpec`
Defines the region in a parent gridspec where the subfigure will
be placed.
Returns
-------
`.SubFigure`
Other Parameters
----------------
**kwargs
Are passed to the `.SubFigure` object.
See Also
--------
.Figure.subfigures
"""
sf = SubFigure(self, subplotspec, **kwargs)
self.subfigs += [sf]
return sf
def sca(self, a):
"""Set the current Axes to be *a* and return *a*."""
self._axstack.bubble(a)
self._axobservers.process("_axes_change_event", self)
return a
def gca(self):
"""
Get the current Axes.
If there is currently no Axes on this Figure, a new one is created
using `.Figure.add_subplot`. (To test whether there is currently an
Axes on a Figure, check whether ``figure.axes`` is empty. To test
whether there is currently a Figure on the pyplot figure stack, check
whether `.pyplot.get_fignums()` is empty.)
"""
ax = self._axstack.current()
return ax if ax is not None else self.add_subplot()
def _gci(self):
# Helper for `~matplotlib.pyplot.gci`. Do not use elsewhere.
"""
Get the current colorable artist.
Specifically, returns the current `.ScalarMappable` instance (`.Image`
created by `imshow` or `figimage`, `.Collection` created by `pcolor` or
`scatter`, etc.), or *None* if no such instance has been defined.
The current image is an attribute of the current Axes, or the nearest
earlier Axes in the current figure that contains an image.
Notes
-----
Historically, the only colorable artists were images; hence the name
``gci`` (get current image).
"""
# Look first for an image in the current Axes.
ax = self._axstack.current()
if ax is None:
return None
im = ax._gci()
if im is not None:
return im
# If there is no image in the current Axes, search for
# one in a previously created Axes. Whether this makes
# sense is debatable, but it is the documented behavior.
for ax in reversed(self.axes):
im = ax._gci()
if im is not None:
return im
return None
def _process_projection_requirements(self, *, axes_class=None, polar=False,
projection=None, **kwargs):
"""
Handle the args/kwargs to add_axes/add_subplot/gca, returning::
(axes_proj_class, proj_class_kwargs)
which can be used for new Axes initialization/identification.
"""
if axes_class is not None:
if polar or projection is not None:
raise ValueError(
"Cannot combine 'axes_class' and 'projection' or 'polar'")
projection_class = axes_class
else:
if polar:
if projection is not None and projection != 'polar':
raise ValueError(
f"polar={polar}, yet projection={projection!r}. "
"Only one of these arguments should be supplied."
)
projection = 'polar'
if isinstance(projection, str) or projection is None:
projection_class = projections.get_projection_class(projection)
elif hasattr(projection, '_as_mpl_axes'):
projection_class, extra_kwargs = projection._as_mpl_axes()
kwargs.update(**extra_kwargs)
else:
raise TypeError(
f"projection must be a string, None or implement a "
f"_as_mpl_axes method, not {projection!r}")
return projection_class, kwargs
def get_default_bbox_extra_artists(self):
bbox_artists = [artist for artist in self.get_children()
if (artist.get_visible() and artist.get_in_layout())]
for ax in self.axes:
if ax.get_visible():
bbox_artists.extend(ax.get_default_bbox_extra_artists())
return bbox_artists
@_api.make_keyword_only("3.8", "bbox_extra_artists")
def get_tightbbox(self, renderer=None, bbox_extra_artists=None):
"""
Return a (tight) bounding box of the figure *in inches*.
Note that `.FigureBase` differs from all other artists, which return
their `.Bbox` in pixels.
Artists that have ``artist.set_in_layout(False)`` are not included
in the bbox.
Parameters
----------
renderer : `.RendererBase` subclass
Renderer that will be used to draw the figures (i.e.
``fig.canvas.get_renderer()``)
bbox_extra_artists : list of `.Artist` or ``None``
List of artists to include in the tight bounding box. If
``None`` (default), then all artist children of each Axes are
included in the tight bounding box.
Returns
-------
`.BboxBase`
containing the bounding box (in figure inches).
"""
if renderer is None:
renderer = self.figure._get_renderer()
bb = []
if bbox_extra_artists is None:
artists = self.get_default_bbox_extra_artists()
else:
artists = bbox_extra_artists
for a in artists:
bbox = a.get_tightbbox(renderer)
if bbox is not None:
bb.append(bbox)
for ax in self.axes:
if ax.get_visible():
# some axes don't take the bbox_extra_artists kwarg so we
# need this conditional....
try:
bbox = ax.get_tightbbox(
renderer, bbox_extra_artists=bbox_extra_artists)
except TypeError:
bbox = ax.get_tightbbox(renderer)
bb.append(bbox)
bb = [b for b in bb
if (np.isfinite(b.width) and np.isfinite(b.height)
and (b.width != 0 or b.height != 0))]
isfigure = hasattr(self, 'bbox_inches')
if len(bb) == 0:
if isfigure:
return self.bbox_inches
else:
# subfigures do not have bbox_inches, but do have a bbox
bb = [self.bbox]
_bbox = Bbox.union(bb)
if isfigure:
# transform from pixels to inches...
_bbox = TransformedBbox(_bbox, self.dpi_scale_trans.inverted())
return _bbox
@staticmethod
def _norm_per_subplot_kw(per_subplot_kw):
expanded = {}
for k, v in per_subplot_kw.items():
if isinstance(k, tuple):
for sub_key in k:
if sub_key in expanded:
raise ValueError(f'The key {sub_key!r} appears multiple times.')
expanded[sub_key] = v
else:
if k in expanded:
raise ValueError(f'The key {k!r} appears multiple times.')
expanded[k] = v
return expanded
@staticmethod
def _normalize_grid_string(layout):
if '\n' not in layout:
# single-line string
return [list(ln) for ln in layout.split(';')]
else:
# multi-line string
layout = inspect.cleandoc(layout)
return [list(ln) for ln in layout.strip('\n').split('\n')]
def subplot_mosaic(self, mosaic, *, sharex=False, sharey=False,
width_ratios=None, height_ratios=None,
empty_sentinel='.',
subplot_kw=None, per_subplot_kw=None, gridspec_kw=None):
"""
Build a layout of Axes based on ASCII art or nested lists.
This is a helper function to build complex GridSpec layouts visually.
See :ref:`mosaic`
for an example and full API documentation
Parameters
----------
mosaic : list of list of {hashable or nested} or str
A visual layout of how you want your Axes to be arranged
labeled as strings. For example ::
x = [['A panel', 'A panel', 'edge'],
['C panel', '.', 'edge']]
produces 4 Axes:
- 'A panel' which is 1 row high and spans the first two columns
- 'edge' which is 2 rows high and is on the right edge
- 'C panel' which in 1 row and 1 column wide in the bottom left
- a blank space 1 row and 1 column wide in the bottom center
Any of the entries in the layout can be a list of lists
of the same form to create nested layouts.
If input is a str, then it can either be a multi-line string of
the form ::
'''
AAE
C.E
'''
where each character is a column and each line is a row. Or it
can be a single-line string where rows are separated by ``;``::
'AB;CC'
The string notation allows only single character Axes labels and
does not support nesting but is very terse.
The Axes identifiers may be `str` or a non-iterable hashable
object (e.g. `tuple` s may not be used).
sharex, sharey : bool, default: False
If True, the x-axis (*sharex*) or y-axis (*sharey*) will be shared
among all subplots. In that case, tick label visibility and axis
units behave as for `subplots`. If False, each subplot's x- or
y-axis will be independent.
width_ratios : array-like of length *ncols*, optional
Defines the relative widths of the columns. Each column gets a
relative width of ``width_ratios[i] / sum(width_ratios)``.
If not given, all columns will have the same width. Equivalent
to ``gridspec_kw={'width_ratios': [...]}``. In the case of nested
layouts, this argument applies only to the outer layout.
height_ratios : array-like of length *nrows*, optional
Defines the relative heights of the rows. Each row gets a
relative height of ``height_ratios[i] / sum(height_ratios)``.
If not given, all rows will have the same height. Equivalent
to ``gridspec_kw={'height_ratios': [...]}``. In the case of nested
layouts, this argument applies only to the outer layout.
subplot_kw : dict, optional
Dictionary with keywords passed to the `.Figure.add_subplot` call
used to create each subplot. These values may be overridden by
values in *per_subplot_kw*.
per_subplot_kw : dict, optional
A dictionary mapping the Axes identifiers or tuples of identifiers
to a dictionary of keyword arguments to be passed to the
`.Figure.add_subplot` call used to create each subplot. The values
in these dictionaries have precedence over the values in
*subplot_kw*.
If *mosaic* is a string, and thus all keys are single characters,
it is possible to use a single string instead of a tuple as keys;
i.e. ``"AB"`` is equivalent to ``("A", "B")``.
.. versionadded:: 3.7
gridspec_kw : dict, optional
Dictionary with keywords passed to the `.GridSpec` constructor used
to create the grid the subplots are placed on. In the case of
nested layouts, this argument applies only to the outer layout.
For more complex layouts, users should use `.Figure.subfigures`
to create the nesting.
empty_sentinel : object, optional
Entry in the layout to mean "leave this space empty". Defaults
to ``'.'``. Note, if *layout* is a string, it is processed via
`inspect.cleandoc` to remove leading white space, which may
interfere with using white-space as the empty sentinel.
Returns
-------
dict[label, Axes]
A dictionary mapping the labels to the Axes objects. The order of
the axes is left-to-right and top-to-bottom of their position in the
total layout.
"""
subplot_kw = subplot_kw or {}
gridspec_kw = dict(gridspec_kw or {})
per_subplot_kw = per_subplot_kw or {}
if height_ratios is not None:
if 'height_ratios' in gridspec_kw:
raise ValueError("'height_ratios' must not be defined both as "
"parameter and as key in 'gridspec_kw'")
gridspec_kw['height_ratios'] = height_ratios
if width_ratios is not None:
if 'width_ratios' in gridspec_kw:
raise ValueError("'width_ratios' must not be defined both as "
"parameter and as key in 'gridspec_kw'")
gridspec_kw['width_ratios'] = width_ratios
# special-case string input
if isinstance(mosaic, str):
mosaic = self._normalize_grid_string(mosaic)
per_subplot_kw = {
tuple(k): v for k, v in per_subplot_kw.items()
}
per_subplot_kw = self._norm_per_subplot_kw(per_subplot_kw)
# Only accept strict bools to allow a possible future API expansion.
_api.check_isinstance(bool, sharex=sharex, sharey=sharey)
def _make_array(inp):
"""
Convert input into 2D array
We need to have this internal function rather than
``np.asarray(..., dtype=object)`` so that a list of lists
of lists does not get converted to an array of dimension > 2.
Returns
-------
2D object array
"""
r0, *rest = inp
if isinstance(r0, str):
raise ValueError('List mosaic specification must be 2D')
for j, r in enumerate(rest, start=1):
if isinstance(r, str):
raise ValueError('List mosaic specification must be 2D')
if len(r0) != len(r):
raise ValueError(
"All of the rows must be the same length, however "
f"the first row ({r0!r}) has length {len(r0)} "
f"and row {j} ({r!r}) has length {len(r)}."
)
out = np.zeros((len(inp), len(r0)), dtype=object)
for j, r in enumerate(inp):
for k, v in enumerate(r):
out[j, k] = v
return out
def _identify_keys_and_nested(mosaic):
"""
Given a 2D object array, identify unique IDs and nested mosaics
Parameters
----------
mosaic : 2D object array
Returns
-------
unique_ids : tuple
The unique non-sub mosaic entries in this mosaic
nested : dict[tuple[int, int], 2D object array]
"""
# make sure we preserve the user supplied order
unique_ids = cbook._OrderedSet()
nested = {}
for j, row in enumerate(mosaic):
for k, v in enumerate(row):
if v == empty_sentinel:
continue
elif not cbook.is_scalar_or_string(v):
nested[(j, k)] = _make_array(v)
else:
unique_ids.add(v)
return tuple(unique_ids), nested
def _do_layout(gs, mosaic, unique_ids, nested):
"""
Recursively do the mosaic.
Parameters
----------
gs : GridSpec
mosaic : 2D object array
The input converted to a 2D array for this level.
unique_ids : tuple
The identified scalar labels at this level of nesting.
nested : dict[tuple[int, int]], 2D object array
The identified nested mosaics, if any.
Returns
-------
dict[label, Axes]
A flat dict of all of the Axes created.
"""
output = dict()
# we need to merge together the Axes at this level and the axes
# in the (recursively) nested sub-mosaics so that we can add
# them to the figure in the "natural" order if you were to
# ravel in c-order all of the Axes that will be created
#
# This will stash the upper left index of each object (axes or
# nested mosaic) at this level
this_level = dict()
# go through the unique keys,
for name in unique_ids:
# sort out where each axes starts/ends
indx = np.argwhere(mosaic == name)
start_row, start_col = np.min(indx, axis=0)
end_row, end_col = np.max(indx, axis=0) + 1
# and construct the slice object
slc = (slice(start_row, end_row), slice(start_col, end_col))
# some light error checking
if (mosaic[slc] != name).any():
raise ValueError(
f"While trying to layout\n{mosaic!r}\n"
f"we found that the label {name!r} specifies a "
"non-rectangular or non-contiguous area.")
# and stash this slice for later
this_level[(start_row, start_col)] = (name, slc, 'axes')
# do the same thing for the nested mosaics (simpler because these
# cannot be spans yet!)
for (j, k), nested_mosaic in nested.items():
this_level[(j, k)] = (None, nested_mosaic, 'nested')
# now go through the things in this level and add them
# in order left-to-right top-to-bottom
for key in sorted(this_level):
name, arg, method = this_level[key]
# we are doing some hokey function dispatch here based
# on the 'method' string stashed above to sort out if this
# element is an Axes or a nested mosaic.
if method == 'axes':
slc = arg
# add a single axes
if name in output:
raise ValueError(f"There are duplicate keys {name} "
f"in the layout\n{mosaic!r}")
ax = self.add_subplot(
gs[slc], **{
'label': str(name),
**subplot_kw,
**per_subplot_kw.get(name, {})
}
)
output[name] = ax
elif method == 'nested':
nested_mosaic = arg
j, k = key
# recursively add the nested mosaic
rows, cols = nested_mosaic.shape
nested_output = _do_layout(
gs[j, k].subgridspec(rows, cols),
nested_mosaic,
*_identify_keys_and_nested(nested_mosaic)
)
overlap = set(output) & set(nested_output)
if overlap:
raise ValueError(
f"There are duplicate keys {overlap} "
f"between the outer layout\n{mosaic!r}\n"
f"and the nested layout\n{nested_mosaic}"
)
output.update(nested_output)
else:
raise RuntimeError("This should never happen")
return output
mosaic = _make_array(mosaic)
rows, cols = mosaic.shape
gs = self.add_gridspec(rows, cols, **gridspec_kw)
ret = _do_layout(gs, mosaic, *_identify_keys_and_nested(mosaic))
ax0 = next(iter(ret.values()))
for ax in ret.values():
if sharex:
ax.sharex(ax0)
ax._label_outer_xaxis(skip_non_rectangular_axes=True)
if sharey:
ax.sharey(ax0)
ax._label_outer_yaxis(skip_non_rectangular_axes=True)
if extra := set(per_subplot_kw) - set(ret):
raise ValueError(
f"The keys {extra} are in *per_subplot_kw* "
"but not in the mosaic."
)
return ret
def _set_artist_props(self, a):
if a != self:
a.set_figure(self)
a.stale_callback = _stale_figure_callback
a.set_transform(self.transSubfigure)
@_docstring.interpd
class SubFigure(FigureBase):
"""
Logical figure that can be placed inside a figure.
Typically instantiated using `.Figure.add_subfigure` or
`.SubFigure.add_subfigure`, or `.SubFigure.subfigures`. A subfigure has
the same methods as a figure except for those particularly tied to the size
or dpi of the figure, and is confined to a prescribed region of the figure.
For example the following puts two subfigures side-by-side::
fig = plt.figure()
sfigs = fig.subfigures(1, 2)
axsL = sfigs[0].subplots(1, 2)
axsR = sfigs[1].subplots(2, 1)
See :doc:`/gallery/subplots_axes_and_figures/subfigures`
.. note::
The *subfigure* concept is new in v3.4, and the API is still provisional.
"""
def __init__(self, parent, subplotspec, *,
facecolor=None,
edgecolor=None,
linewidth=0.0,
frameon=None,
**kwargs):
"""
Parameters
----------
parent : `.Figure` or `.SubFigure`
Figure or subfigure that contains the SubFigure. SubFigures
can be nested.
subplotspec : `.gridspec.SubplotSpec`
Defines the region in a parent gridspec where the subfigure will
be placed.
facecolor : default: ``"none"``
The figure patch face color; transparent by default.
edgecolor : default: :rc:`figure.edgecolor`
The figure patch edge color.
linewidth : float
The linewidth of the frame (i.e. the edge linewidth of the figure
patch).
frameon : bool, default: :rc:`figure.frameon`
If ``False``, suppress drawing the figure background patch.
Other Parameters
----------------
**kwargs : `.SubFigure` properties, optional
%(SubFigure:kwdoc)s
"""
super().__init__(**kwargs)
if facecolor is None:
facecolor = "none"
if edgecolor is None:
edgecolor = mpl.rcParams['figure.edgecolor']
if frameon is None:
frameon = mpl.rcParams['figure.frameon']
self._subplotspec = subplotspec
self._parent = parent
self.figure = parent.figure
# subfigures use the parent axstack
self._axstack = parent._axstack
self.subplotpars = parent.subplotpars
self.dpi_scale_trans = parent.dpi_scale_trans
self._axobservers = parent._axobservers
self.canvas = parent.canvas
self.transFigure = parent.transFigure
self.bbox_relative = Bbox.null()
self._redo_transform_rel_fig()
self.figbbox = self._parent.figbbox
self.bbox = TransformedBbox(self.bbox_relative,
self._parent.transSubfigure)
self.transSubfigure = BboxTransformTo(self.bbox)
self.patch = Rectangle(
xy=(0, 0), width=1, height=1, visible=frameon,
facecolor=facecolor, edgecolor=edgecolor, linewidth=linewidth,
# Don't let the figure patch influence bbox calculation.
in_layout=False, transform=self.transSubfigure)
self._set_artist_props(self.patch)
self.patch.set_antialiased(False)
@property
def dpi(self):
return self._parent.dpi
@dpi.setter
def dpi(self, value):
self._parent.dpi = value
def get_dpi(self):
"""
Return the resolution of the parent figure in dots-per-inch as a float.
"""
return self._parent.dpi
def set_dpi(self, val):
"""
Set the resolution of parent figure in dots-per-inch.
Parameters
----------
val : float
"""
self._parent.dpi = val
self.stale = True
def _get_renderer(self):
return self._parent._get_renderer()
def _redo_transform_rel_fig(self, bbox=None):
"""
Make the transSubfigure bbox relative to Figure transform.
Parameters
----------
bbox : bbox or None
If not None, then the bbox is used for relative bounding box.
Otherwise, it is calculated from the subplotspec.
"""
if bbox is not None:
self.bbox_relative.p0 = bbox.p0
self.bbox_relative.p1 = bbox.p1
return
# need to figure out *where* this subplotspec is.
gs = self._subplotspec.get_gridspec()
wr = np.asarray(gs.get_width_ratios())
hr = np.asarray(gs.get_height_ratios())
dx = wr[self._subplotspec.colspan].sum() / wr.sum()
dy = hr[self._subplotspec.rowspan].sum() / hr.sum()
x0 = wr[:self._subplotspec.colspan.start].sum() / wr.sum()
y0 = 1 - hr[:self._subplotspec.rowspan.stop].sum() / hr.sum()
self.bbox_relative.p0 = (x0, y0)
self.bbox_relative.p1 = (x0 + dx, y0 + dy)
def get_constrained_layout(self):
"""
Return whether constrained layout is being used.
See :ref:`constrainedlayout_guide`.
"""
return self._parent.get_constrained_layout()
def get_constrained_layout_pads(self, relative=False):
"""
Get padding for ``constrained_layout``.
Returns a list of ``w_pad, h_pad`` in inches and
``wspace`` and ``hspace`` as fractions of the subplot.
See :ref:`constrainedlayout_guide`.
Parameters
----------
relative : bool
If `True`, then convert from inches to figure relative.
"""
return self._parent.get_constrained_layout_pads(relative=relative)
def get_layout_engine(self):
return self._parent.get_layout_engine()
@property
def axes(self):
"""
List of Axes in the SubFigure. You can access and modify the Axes
in the SubFigure through this list.
Modifying this list has no effect. Instead, use `~.SubFigure.add_axes`,
`~.SubFigure.add_subplot` or `~.SubFigure.delaxes` to add or remove an
Axes.
Note: The `.SubFigure.axes` property and `~.SubFigure.get_axes` method
are equivalent.
"""
return self._localaxes[:]
get_axes = axes.fget
def draw(self, renderer):
# docstring inherited
# draw the figure bounding box, perhaps none for white figure
if not self.get_visible():
return
artists = self._get_draw_artists(renderer)
try:
renderer.open_group('subfigure', gid=self.get_gid())
self.patch.draw(renderer)
mimage._draw_list_compositing_images(
renderer, self, artists, self.figure.suppressComposite)
for sfig in self.subfigs:
sfig.draw(renderer)
renderer.close_group('subfigure')
finally:
self.stale = False
@_docstring.interpd
class Figure(FigureBase):
"""
The top level container for all the plot elements.
Attributes
----------
patch
The `.Rectangle` instance representing the figure background patch.
suppressComposite
For multiple images, the figure will make composite images
depending on the renderer option_image_nocomposite function. If
*suppressComposite* is a boolean, this will override the renderer.
"""
# we want to cache the fonts and mathtext at a global level so that when
# multiple figures are created we can reuse them. This helps with a bug on
# windows where the creation of too many figures leads to too many open
# file handles and improves the performance of parsing mathtext. However,
# these global caches are not thread safe. The solution here is to let the
# Figure acquire a shared lock at the start of the draw, and release it when it
# is done. This allows multiple renderers to share the cached fonts and
# parsed text, but only one figure can draw at a time and so the font cache
# and mathtext cache are used by only one renderer at a time.
_render_lock = threading.RLock()
def __str__(self):
return "Figure(%gx%g)" % tuple(self.bbox.size)
def __repr__(self):
return "<{clsname} size {h:g}x{w:g} with {naxes} Axes>".format(
clsname=self.__class__.__name__,
h=self.bbox.size[0], w=self.bbox.size[1],
naxes=len(self.axes),
)
def pick(self, mouseevent):
if not self.canvas.widgetlock.locked():
super().pick(mouseevent)
def _check_layout_engines_compat(self, old, new):
"""
Helper for set_layout engine
If the figure has used the old engine and added a colorbar then the
value of colorbar_gridspec must be the same on the new engine.
"""
if old is None or new is None:
return True
if old.colorbar_gridspec == new.colorbar_gridspec:
return True
# colorbar layout different, so check if any colorbars are on the
# figure...
for ax in self.axes:
if hasattr(ax, '_colorbar'):
# colorbars list themselves as a colorbar.
return False
return True
def set_layout_engine(self, layout=None, **kwargs):
"""
Set the layout engine for this figure.
Parameters
----------
layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}
- 'constrained' will use `~.ConstrainedLayoutEngine`
- 'compressed' will also use `~.ConstrainedLayoutEngine`, but with
a correction that attempts to make a good layout for fixed-aspect
ratio Axes.
- 'tight' uses `~.TightLayoutEngine`
- 'none' removes layout engine.
If a `.LayoutEngine` instance, that instance will be used.
If `None`, the behavior is controlled by :rc:`figure.autolayout`
(which if `True` behaves as if 'tight' was passed) and
:rc:`figure.constrained_layout.use` (which if `True` behaves as if
'constrained' was passed). If both are `True`,
:rc:`figure.autolayout` takes priority.
Users and libraries can define their own layout engines and pass
the instance directly as well.
**kwargs
The keyword arguments are passed to the layout engine to set things
like padding and margin sizes. Only used if *layout* is a string.
"""
if layout is None:
if mpl.rcParams['figure.autolayout']:
layout = 'tight'
elif mpl.rcParams['figure.constrained_layout.use']:
layout = 'constrained'
else:
self._layout_engine = None
return
if layout == 'tight':
new_layout_engine = TightLayoutEngine(**kwargs)
elif layout == 'constrained':
new_layout_engine = ConstrainedLayoutEngine(**kwargs)
elif layout == 'compressed':
new_layout_engine = ConstrainedLayoutEngine(compress=True,
**kwargs)
elif layout == 'none':
if self._layout_engine is not None:
new_layout_engine = PlaceHolderLayoutEngine(
self._layout_engine.adjust_compatible,
self._layout_engine.colorbar_gridspec
)
else:
new_layout_engine = None
elif isinstance(layout, LayoutEngine):
new_layout_engine = layout
else:
raise ValueError(f"Invalid value for 'layout': {layout!r}")
if self._check_layout_engines_compat(self._layout_engine,
new_layout_engine):
self._layout_engine = new_layout_engine
else:
raise RuntimeError('Colorbar layout of new layout engine not '
'compatible with old engine, and a colorbar '
'has been created. Engine not changed.')
def get_layout_engine(self):
return self._layout_engine
# TODO: I'd like to dynamically add the _repr_html_ method
# to the figure in the right context, but then IPython doesn't
# use it, for some reason.
def _repr_html_(self):
# We can't use "isinstance" here, because then we'd end up importing
# webagg unconditionally.
if 'WebAgg' in type(self.canvas).__name__:
from matplotlib.backends import backend_webagg
return backend_webagg.ipython_inline_display(self)
def show(self, warn=True):
"""
If using a GUI backend with pyplot, display the figure window.
If the figure was not created using `~.pyplot.figure`, it will lack
a `~.backend_bases.FigureManagerBase`, and this method will raise an
AttributeError.
.. warning::
This does not manage an GUI event loop. Consequently, the figure
may only be shown briefly or not shown at all if you or your
environment are not managing an event loop.
Use cases for `.Figure.show` include running this from a GUI
application (where there is persistently an event loop running) or
from a shell, like IPython, that install an input hook to allow the
interactive shell to accept input while the figure is also being
shown and interactive. Some, but not all, GUI toolkits will
register an input hook on import. See :ref:`cp_integration` for
more details.
If you're in a shell without input hook integration or executing a
python script, you should use `matplotlib.pyplot.show` with
``block=True`` instead, which takes care of starting and running
the event loop for you.
Parameters
----------
warn : bool, default: True
If ``True`` and we are not running headless (i.e. on Linux with an
unset DISPLAY), issue warning when called on a non-GUI backend.
"""
if self.canvas.manager is None:
raise AttributeError(
"Figure.show works only for figures managed by pyplot, "
"normally created by pyplot.figure()")
try:
self.canvas.manager.show()
except NonGuiException as exc:
if warn:
_api.warn_external(str(exc))
@property
def axes(self):
"""
List of Axes in the Figure. You can access and modify the Axes in the
Figure through this list.
Do not modify the list itself. Instead, use `~Figure.add_axes`,
`~.Figure.add_subplot` or `~.Figure.delaxes` to add or remove an Axes.
Note: The `.Figure.axes` property and `~.Figure.get_axes` method are
equivalent.
"""
return self._axstack.as_list()
get_axes = axes.fget
def _get_renderer(self):
if hasattr(self.canvas, 'get_renderer'):
return self.canvas.get_renderer()
else:
return _get_renderer(self)
def _get_dpi(self):
return self._dpi
def _set_dpi(self, dpi, forward=True):
"""
Parameters
----------
dpi : float
forward : bool
Passed on to `~.Figure.set_size_inches`
"""
if dpi == self._dpi:
# We don't want to cause undue events in backends.
return
self._dpi = dpi
self.dpi_scale_trans.clear().scale(dpi)
w, h = self.get_size_inches()
self.set_size_inches(w, h, forward=forward)
dpi = property(_get_dpi, _set_dpi, doc="The resolution in dots per inch.")
def get_tight_layout(self):
"""Return whether `.tight_layout` is called when drawing."""
return isinstance(self.get_layout_engine(), TightLayoutEngine)
@_api.deprecated("3.6", alternative="set_layout_engine",
pending=True)
def set_tight_layout(self, tight):
"""
Set whether and how `.tight_layout` is called when drawing.
Parameters
----------
tight : bool or dict with keys "pad", "w_pad", "h_pad", "rect" or None
If a bool, sets whether to call `.tight_layout` upon drawing.
If ``None``, use :rc:`figure.autolayout` instead.
If a dict, pass it as kwargs to `.tight_layout`, overriding the
default paddings.
"""
if tight is None:
tight = mpl.rcParams['figure.autolayout']
_tight = 'tight' if bool(tight) else 'none'
_tight_parameters = tight if isinstance(tight, dict) else {}
self.set_layout_engine(_tight, **_tight_parameters)
self.stale = True
def get_constrained_layout(self):
"""
Return whether constrained layout is being used.
See :ref:`constrainedlayout_guide`.
"""
return isinstance(self.get_layout_engine(), ConstrainedLayoutEngine)
@_api.deprecated("3.6", alternative="set_layout_engine('constrained')",
pending=True)
def set_constrained_layout(self, constrained):
"""
Set whether ``constrained_layout`` is used upon drawing.
If None, :rc:`figure.constrained_layout.use` value will be used.
When providing a dict containing the keys ``w_pad``, ``h_pad``
the default ``constrained_layout`` paddings will be
overridden. These pads are in inches and default to 3.0/72.0.
``w_pad`` is the width padding and ``h_pad`` is the height padding.
Parameters
----------
constrained : bool or dict or None
"""
if constrained is None:
constrained = mpl.rcParams['figure.constrained_layout.use']
_constrained = 'constrained' if bool(constrained) else 'none'
_parameters = constrained if isinstance(constrained, dict) else {}
self.set_layout_engine(_constrained, **_parameters)
self.stale = True
@_api.deprecated(
"3.6", alternative="figure.get_layout_engine().set()",
pending=True)
def set_constrained_layout_pads(self, **kwargs):
"""
Set padding for ``constrained_layout``.
Tip: The parameters can be passed from a dictionary by using
``fig.set_constrained_layout(**pad_dict)``.
See :ref:`constrainedlayout_guide`.
Parameters
----------
w_pad : float, default: :rc:`figure.constrained_layout.w_pad`
Width padding in inches. This is the pad around Axes
and is meant to make sure there is enough room for fonts to
look good. Defaults to 3 pts = 0.04167 inches
h_pad : float, default: :rc:`figure.constrained_layout.h_pad`
Height padding in inches. Defaults to 3 pts.
wspace : float, default: :rc:`figure.constrained_layout.wspace`
Width padding between subplots, expressed as a fraction of the
subplot width. The total padding ends up being w_pad + wspace.
hspace : float, default: :rc:`figure.constrained_layout.hspace`
Height padding between subplots, expressed as a fraction of the
subplot width. The total padding ends up being h_pad + hspace.
"""
if isinstance(self.get_layout_engine(), ConstrainedLayoutEngine):
self.get_layout_engine().set(**kwargs)
@_api.deprecated("3.6", alternative="fig.get_layout_engine().get()",
pending=True)
def get_constrained_layout_pads(self, relative=False):
"""
Get padding for ``constrained_layout``.
Returns a list of ``w_pad, h_pad`` in inches and
``wspace`` and ``hspace`` as fractions of the subplot.
All values are None if ``constrained_layout`` is not used.
See :ref:`constrainedlayout_guide`.
Parameters
----------
relative : bool
If `True`, then convert from inches to figure relative.
"""
if not isinstance(self.get_layout_engine(), ConstrainedLayoutEngine):
return None, None, None, None
info = self.get_layout_engine().get()
w_pad = info['w_pad']
h_pad = info['h_pad']
wspace = info['wspace']
hspace = info['hspace']
if relative and (w_pad is not None or h_pad is not None):
renderer = self._get_renderer()
dpi = renderer.dpi
w_pad = w_pad * dpi / renderer.width
h_pad = h_pad * dpi / renderer.height
return w_pad, h_pad, wspace, hspace
def set_canvas(self, canvas):
"""
Set the canvas that contains the figure
Parameters
----------
canvas : FigureCanvas
"""
self.canvas = canvas
@_docstring.interpd
def figimage(self, X, xo=0, yo=0, alpha=None, norm=None, cmap=None,
vmin=None, vmax=None, origin=None, resize=False, **kwargs):
"""
Add a non-resampled image to the figure.
The image is attached to the lower or upper left corner depending on
*origin*.
Parameters
----------
X
The image data. This is an array of one of the following shapes:
- (M, N): an image with scalar data. Color-mapping is controlled
by *cmap*, *norm*, *vmin*, and *vmax*.
- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),
i.e. including transparency.
xo, yo : int
The *x*/*y* image offset in pixels.
alpha : None or float
The alpha blending value.
%(cmap_doc)s
This parameter is ignored if *X* is RGB(A).
%(norm_doc)s
This parameter is ignored if *X* is RGB(A).
%(vmin_vmax_doc)s
This parameter is ignored if *X* is RGB(A).
origin : {'upper', 'lower'}, default: :rc:`image.origin`
Indicates where the [0, 0] index of the array is in the upper left
or lower left corner of the axes.
resize : bool
If *True*, resize the figure to match the given image size.
Returns
-------
`matplotlib.image.FigureImage`
Other Parameters
----------------
**kwargs
Additional kwargs are `.Artist` kwargs passed on to `.FigureImage`.
Notes
-----
figimage complements the Axes image (`~matplotlib.axes.Axes.imshow`)
which will be resampled to fit the current Axes. If you want
a resampled image to fill the entire figure, you can define an
`~matplotlib.axes.Axes` with extent [0, 0, 1, 1].
Examples
--------
::
f = plt.figure()
nx = int(f.get_figwidth() * f.dpi)
ny = int(f.get_figheight() * f.dpi)
data = np.random.random((ny, nx))
f.figimage(data)
plt.show()
"""
if resize:
dpi = self.get_dpi()
figsize = [x / dpi for x in (X.shape[1], X.shape[0])]
self.set_size_inches(figsize, forward=True)
im = mimage.FigureImage(self, cmap=cmap, norm=norm,
offsetx=xo, offsety=yo,
origin=origin, **kwargs)
im.stale_callback = _stale_figure_callback
im.set_array(X)
im.set_alpha(alpha)
if norm is None:
im.set_clim(vmin, vmax)
self.images.append(im)
im._remove_method = self.images.remove
self.stale = True
return im
def set_size_inches(self, w, h=None, forward=True):
"""
Set the figure size in inches.
Call signatures::
fig.set_size_inches(w, h) # OR
fig.set_size_inches((w, h))
Parameters
----------
w : (float, float) or float
Width and height in inches (if height not specified as a separate
argument) or width.
h : float
Height in inches.
forward : bool, default: True
If ``True``, the canvas size is automatically updated, e.g.,
you can resize the figure window from the shell.
See Also
--------
matplotlib.figure.Figure.get_size_inches
matplotlib.figure.Figure.set_figwidth
matplotlib.figure.Figure.set_figheight
Notes
-----
To transform from pixels to inches divide by `Figure.dpi`.
"""
if h is None: # Got called with a single pair as argument.
w, h = w
size = np.array([w, h])
if not np.isfinite(size).all() or (size < 0).any():
raise ValueError(f'figure size must be positive finite not {size}')
self.bbox_inches.p1 = size
if forward:
manager = self.canvas.manager
if manager is not None:
manager.resize(*(size * self.dpi).astype(int))
self.stale = True
def get_size_inches(self):
"""
Return the current size of the figure in inches.
Returns
-------
ndarray
The size (width, height) of the figure in inches.
See Also
--------
matplotlib.figure.Figure.set_size_inches
matplotlib.figure.Figure.get_figwidth
matplotlib.figure.Figure.get_figheight
Notes
-----
The size in pixels can be obtained by multiplying with `Figure.dpi`.
"""
return np.array(self.bbox_inches.p1)
def get_figwidth(self):
"""Return the figure width in inches."""
return self.bbox_inches.width
def get_figheight(self):
"""Return the figure height in inches."""
return self.bbox_inches.height
def get_dpi(self):
"""Return the resolution in dots per inch as a float."""
return self.dpi
def set_dpi(self, val):
"""
Set the resolution of the figure in dots-per-inch.
Parameters
----------
val : float
"""
self.dpi = val
self.stale = True
def set_figwidth(self, val, forward=True):
"""
Set the width of the figure in inches.
Parameters
----------
val : float
forward : bool
See `set_size_inches`.
See Also
--------
matplotlib.figure.Figure.set_figheight
matplotlib.figure.Figure.set_size_inches
"""
self.set_size_inches(val, self.get_figheight(), forward=forward)
def set_figheight(self, val, forward=True):
"""
Set the height of the figure in inches.
Parameters
----------
val : float
forward : bool
See `set_size_inches`.
See Also
--------
matplotlib.figure.Figure.set_figwidth
matplotlib.figure.Figure.set_size_inches
"""
self.set_size_inches(self.get_figwidth(), val, forward=forward)
def clear(self, keep_observers=False):
# docstring inherited
super().clear(keep_observers=keep_observers)
# FigureBase.clear does not clear toolbars, as
# only Figure can have toolbars
toolbar = self.canvas.toolbar
if toolbar is not None:
toolbar.update()
@_finalize_rasterization
@allow_rasterization
def draw(self, renderer):
# docstring inherited
if not self.get_visible():
return
with self._render_lock:
artists = self._get_draw_artists(renderer)
try:
renderer.open_group('figure', gid=self.get_gid())
if self.axes and self.get_layout_engine() is not None:
try:
self.get_layout_engine().execute(self)
except ValueError:
pass
# ValueError can occur when resizing a window.
self.patch.draw(renderer)
mimage._draw_list_compositing_images(
renderer, self, artists, self.suppressComposite)
for sfig in self.subfigs:
sfig.draw(renderer)
renderer.close_group('figure')
finally:
self.stale = False
DrawEvent("draw_event", self.canvas, renderer)._process()
def draw_without_rendering(self):
"""
Draw the figure with no output. Useful to get the final size of
artists that require a draw before their size is known (e.g. text).
"""
renderer = _get_renderer(self)
with renderer._draw_disabled():
self.draw(renderer)
def draw_artist(self, a):
"""
Draw `.Artist` *a* only.
"""
a.draw(self.canvas.get_renderer())
def __getstate__(self):
state = super().__getstate__()
# The canvas cannot currently be pickled, but this has the benefit
# of meaning that a figure can be detached from one canvas, and
# re-attached to another.
state.pop("canvas")
# discard any changes to the dpi due to pixel ratio changes
state["_dpi"] = state.get('_original_dpi', state['_dpi'])
# add version information to the state
state['__mpl_version__'] = mpl.__version__
# check whether the figure manager (if any) is registered with pyplot
from matplotlib import _pylab_helpers
if self.canvas.manager in _pylab_helpers.Gcf.figs.values():
state['_restore_to_pylab'] = True
return state
def __setstate__(self, state):
version = state.pop('__mpl_version__')
restore_to_pylab = state.pop('_restore_to_pylab', False)
if version != mpl.__version__:
_api.warn_external(
f"This figure was saved with matplotlib version {version} and "
f"is unlikely to function correctly.")
self.__dict__ = state
# re-initialise some of the unstored state information
FigureCanvasBase(self) # Set self.canvas.
if restore_to_pylab:
# lazy import to avoid circularity
import matplotlib.pyplot as plt
import matplotlib._pylab_helpers as pylab_helpers
allnums = plt.get_fignums()
num = max(allnums) + 1 if allnums else 1
backend = plt._get_backend_mod()
mgr = backend.new_figure_manager_given_figure(num, self)
pylab_helpers.Gcf._set_new_active_manager(mgr)
plt.draw_if_interactive()
self.stale = True
def add_axobserver(self, func):
"""Whenever the Axes state change, ``func(self)`` will be called."""
# Connect a wrapper lambda and not func itself, to avoid it being
# weakref-collected.
self._axobservers.connect("_axes_change_event", lambda arg: func(arg))
def savefig(self, fname, *, transparent=None, **kwargs):
"""
Save the current figure.
Call signature::
savefig(fname, *, transparent=None, dpi='figure', format=None,
metadata=None, bbox_inches=None, pad_inches=0.1,
facecolor='auto', edgecolor='auto', backend=None,
**kwargs
)
The available output formats depend on the backend being used.
Parameters
----------
fname : str or path-like or binary file-like
A path, or a Python file-like object, or
possibly some backend-dependent object such as
`matplotlib.backends.backend_pdf.PdfPages`.
If *format* is set, it determines the output format, and the file
is saved as *fname*. Note that *fname* is used verbatim, and there
is no attempt to make the extension, if any, of *fname* match
*format*, and no extension is appended.
If *format* is not set, then the format is inferred from the
extension of *fname*, if there is one. If *format* is not
set and *fname* has no extension, then the file is saved with
:rc:`savefig.format` and the appropriate extension is appended to
*fname*.
Other Parameters
----------------
transparent : bool, default: :rc:`savefig.transparent`
If *True*, the Axes patches will all be transparent; the
Figure patch will also be transparent unless *facecolor*
and/or *edgecolor* are specified via kwargs.
If *False* has no effect and the color of the Axes and
Figure patches are unchanged (unless the Figure patch
is specified via the *facecolor* and/or *edgecolor* keyword
arguments in which case those colors are used).
The transparency of these patches will be restored to their
original values upon exit of this function.
This is useful, for example, for displaying
a plot on top of a colored background on a web page.
dpi : float or 'figure', default: :rc:`savefig.dpi`
The resolution in dots per inch. If 'figure', use the figure's
dpi value.
format : str
The file format, e.g. 'png', 'pdf', 'svg', ... The behavior when
this is unset is documented under *fname*.
metadata : dict, optional
Key/value pairs to store in the image metadata. The supported keys
and defaults depend on the image format and backend:
- 'png' with Agg backend: See the parameter ``metadata`` of
`~.FigureCanvasAgg.print_png`.
- 'pdf' with pdf backend: See the parameter ``metadata`` of
`~.backend_pdf.PdfPages`.
- 'svg' with svg backend: See the parameter ``metadata`` of
`~.FigureCanvasSVG.print_svg`.
- 'eps' and 'ps' with PS backend: Only 'Creator' is supported.
Not supported for 'pgf', 'raw', and 'rgba' as those formats do not support
embedding metadata.
Does not currently support 'jpg', 'tiff', or 'webp', but may include
embedding EXIF metadata in the future.
bbox_inches : str or `.Bbox`, default: :rc:`savefig.bbox`
Bounding box in inches: only the given portion of the figure is
saved. If 'tight', try to figure out the tight bbox of the figure.
pad_inches : float or 'layout', default: :rc:`savefig.pad_inches`
Amount of padding in inches around the figure when bbox_inches is
'tight'. If 'layout' use the padding from the constrained or
compressed layout engine; ignored if one of those engines is not in
use.
facecolor : color or 'auto', default: :rc:`savefig.facecolor`
The facecolor of the figure. If 'auto', use the current figure
facecolor.
edgecolor : color or 'auto', default: :rc:`savefig.edgecolor`
The edgecolor of the figure. If 'auto', use the current figure
edgecolor.
backend : str, optional
Use a non-default backend to render the file, e.g. to render a
png file with the "cairo" backend rather than the default "agg",
or a pdf file with the "pgf" backend rather than the default
"pdf". Note that the default backend is normally sufficient. See
:ref:`the-builtin-backends` for a list of valid backends for each
file format. Custom backends can be referenced as "module://...".
orientation : {'landscape', 'portrait'}
Currently only supported by the postscript backend.
papertype : str
One of 'letter', 'legal', 'executive', 'ledger', 'a0' through
'a10', 'b0' through 'b10'. Only supported for postscript
output.
bbox_extra_artists : list of `~matplotlib.artist.Artist`, optional
A list of extra artists that will be considered when the
tight bbox is calculated.
pil_kwargs : dict, optional
Additional keyword arguments that are passed to
`PIL.Image.Image.save` when saving the figure.
"""
kwargs.setdefault('dpi', mpl.rcParams['savefig.dpi'])
if transparent is None:
transparent = mpl.rcParams['savefig.transparent']
with ExitStack() as stack:
if transparent:
def _recursively_make_subfig_transparent(exit_stack, subfig):
exit_stack.enter_context(
subfig.patch._cm_set(
facecolor="none", edgecolor="none"))
for ax in subfig.axes:
exit_stack.enter_context(
ax.patch._cm_set(
facecolor="none", edgecolor="none"))
for sub_subfig in subfig.subfigs:
_recursively_make_subfig_transparent(
exit_stack, sub_subfig)
def _recursively_make_axes_transparent(exit_stack, ax):
exit_stack.enter_context(
ax.patch._cm_set(facecolor="none", edgecolor="none"))
for child_ax in ax.child_axes:
exit_stack.enter_context(
child_ax.patch._cm_set(
facecolor="none", edgecolor="none"))
for child_childax in ax.child_axes:
_recursively_make_axes_transparent(
exit_stack, child_childax)
kwargs.setdefault('facecolor', 'none')
kwargs.setdefault('edgecolor', 'none')
# set subfigure to appear transparent in printed image
for subfig in self.subfigs:
_recursively_make_subfig_transparent(stack, subfig)
# set axes to be transparent
for ax in self.axes:
_recursively_make_axes_transparent(stack, ax)
self.canvas.print_figure(fname, **kwargs)
def ginput(self, n=1, timeout=30, show_clicks=True,
mouse_add=MouseButton.LEFT,
mouse_pop=MouseButton.RIGHT,
mouse_stop=MouseButton.MIDDLE):
"""
Blocking call to interact with a figure.
Wait until the user clicks *n* times on the figure, and return the
coordinates of each click in a list.
There are three possible interactions:
- Add a point.
- Remove the most recently added point.
- Stop the interaction and return the points added so far.
The actions are assigned to mouse buttons via the arguments
*mouse_add*, *mouse_pop* and *mouse_stop*.
Parameters
----------
n : int, default: 1
Number of mouse clicks to accumulate. If negative, accumulate
clicks until the input is terminated manually.
timeout : float, default: 30 seconds
Number of seconds to wait before timing out. If zero or negative
will never time out.
show_clicks : bool, default: True
If True, show a red cross at the location of each click.
mouse_add : `.MouseButton` or None, default: `.MouseButton.LEFT`
Mouse button used to add points.
mouse_pop : `.MouseButton` or None, default: `.MouseButton.RIGHT`
Mouse button used to remove the most recently added point.
mouse_stop : `.MouseButton` or None, default: `.MouseButton.MIDDLE`
Mouse button used to stop input.
Returns
-------
list of tuples
A list of the clicked (x, y) coordinates.
Notes
-----
The keyboard can also be used to select points in case your mouse
does not have one or more of the buttons. The delete and backspace
keys act like right-clicking (i.e., remove last point), the enter key
terminates input and any other key (not already used by the window
manager) selects a point.
"""
clicks = []
marks = []
def handler(event):
is_button = event.name == "button_press_event"
is_key = event.name == "key_press_event"
# Quit (even if not in infinite mode; this is consistent with
# MATLAB and sometimes quite useful, but will require the user to
# test how many points were actually returned before using data).
if (is_button and event.button == mouse_stop
or is_key and event.key in ["escape", "enter"]):
self.canvas.stop_event_loop()
# Pop last click.
elif (is_button and event.button == mouse_pop
or is_key and event.key in ["backspace", "delete"]):
if clicks:
clicks.pop()
if show_clicks:
marks.pop().remove()
self.canvas.draw()
# Add new click.
elif (is_button and event.button == mouse_add
# On macOS/gtk, some keys return None.
or is_key and event.key is not None):
if event.inaxes:
clicks.append((event.xdata, event.ydata))
_log.info("input %i: %f, %f",
len(clicks), event.xdata, event.ydata)
if show_clicks:
line = mpl.lines.Line2D([event.xdata], [event.ydata],
marker="+", color="r")
event.inaxes.add_line(line)
marks.append(line)
self.canvas.draw()
if len(clicks) == n and n > 0:
self.canvas.stop_event_loop()
_blocking_input.blocking_input_loop(
self, ["button_press_event", "key_press_event"], timeout, handler)
# Cleanup.
for mark in marks:
mark.remove()
self.canvas.draw()
return clicks
def waitforbuttonpress(self, timeout=-1):
"""
Blocking call to interact with the figure.
Wait for user input and return True if a key was pressed, False if a
mouse button was pressed and None if no input was given within
*timeout* seconds. Negative values deactivate *timeout*.
"""
event = None
def handler(ev):
nonlocal event
event = ev
self.canvas.stop_event_loop()
_blocking_input.blocking_input_loop(
self, ["button_press_event", "key_press_event"], timeout, handler)
return None if event is None else event.name == "key_press_event"
def tight_layout(self, *, pad=1.08, h_pad=None, w_pad=None, rect=None):
"""
Adjust the padding between and around subplots.
To exclude an artist on the Axes from the bounding box calculation
that determines the subplot parameters (i.e. legend, or annotation),
set ``a.set_in_layout(False)`` for that artist.
Parameters
----------
pad : float, default: 1.08
Padding between the figure edge and the edges of subplots,
as a fraction of the font size.
h_pad, w_pad : float, default: *pad*
Padding (height/width) between edges of adjacent subplots,
as a fraction of the font size.
rect : tuple (left, bottom, right, top), default: (0, 0, 1, 1)
A rectangle in normalized figure coordinates into which the whole
subplots area (including labels) will fit.
See Also
--------
.Figure.set_layout_engine
.pyplot.tight_layout
"""
# note that here we do not permanently set the figures engine to
# tight_layout but rather just perform the layout in place and remove
# any previous engines.
engine = TightLayoutEngine(pad=pad, h_pad=h_pad, w_pad=w_pad, rect=rect)
try:
previous_engine = self.get_layout_engine()
self.set_layout_engine(engine)
engine.execute(self)
if previous_engine is not None and not isinstance(
previous_engine, (TightLayoutEngine, PlaceHolderLayoutEngine)
):
_api.warn_external('The figure layout has changed to tight')
finally:
self.set_layout_engine('none')
def figaspect(arg):
"""
Calculate the width and height for a figure with a specified aspect ratio.
While the height is taken from :rc:`figure.figsize`, the width is
adjusted to match the desired aspect ratio. Additionally, it is ensured
that the width is in the range [4., 16.] and the height is in the range
[2., 16.]. If necessary, the default height is adjusted to ensure this.
Parameters
----------
arg : float or 2D array
If a float, this defines the aspect ratio (i.e. the ratio height /
width).
In case of an array the aspect ratio is number of rows / number of
columns, so that the array could be fitted in the figure undistorted.
Returns
-------
width, height : float
The figure size in inches.
Notes
-----
If you want to create an Axes within the figure, that still preserves the
aspect ratio, be sure to create it with equal width and height. See
examples below.
Thanks to Fernando Perez for this function.
Examples
--------
Make a figure twice as tall as it is wide::
w, h = figaspect(2.)
fig = Figure(figsize=(w, h))
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax.imshow(A, **kwargs)
Make a figure with the proper aspect for an array::
A = rand(5, 3)
w, h = figaspect(A)
fig = Figure(figsize=(w, h))
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax.imshow(A, **kwargs)
"""
isarray = hasattr(arg, 'shape') and not np.isscalar(arg)
# min/max sizes to respect when autoscaling. If John likes the idea, they
# could become rc parameters, for now they're hardwired.
figsize_min = np.array((4.0, 2.0)) # min length for width/height
figsize_max = np.array((16.0, 16.0)) # max length for width/height
# Extract the aspect ratio of the array
if isarray:
nr, nc = arg.shape[:2]
arr_ratio = nr / nc
else:
arr_ratio = arg
# Height of user figure defaults
fig_height = mpl.rcParams['figure.figsize'][1]
# New size for the figure, keeping the aspect ratio of the caller
newsize = np.array((fig_height / arr_ratio, fig_height))
# Sanity checks, don't drop either dimension below figsize_min
newsize /= min(1.0, *(newsize / figsize_min))
# Avoid humongous windows as well
newsize /= max(1.0, *(newsize / figsize_max))
# Finally, if we have a really funky aspect ratio, break it but respect
# the min/max dimensions (we don't want figures 10 feet tall!)
newsize = np.clip(newsize, figsize_min, figsize_max)
return newsize