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# Note: The first part of this file can be modified in place, but the latter
# part is autogenerated by the boilerplate.py script.
"""
Provides a MATLAB-like plotting framework.
:mod:`~matplotlib.pylab` combines pyplot with numpy into a single namespace.
This is convenient for interactive work, but for programming it
is recommended that the namespaces be kept separate, e.g.::
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import sys
import warnings
import types
from cycler import cycler
import matplotlib
import matplotlib.colorbar
from matplotlib import style
from matplotlib import _pylab_helpers, interactive
from matplotlib.cbook import dedent, silent_list, is_numlike
from matplotlib.cbook import _string_to_bool
from matplotlib.cbook import deprecated
from matplotlib import docstring
from matplotlib.backend_bases import FigureCanvasBase
from matplotlib.figure import Figure, figaspect
from matplotlib.gridspec import GridSpec
from matplotlib.image import imread as _imread
from matplotlib.image import imsave as _imsave
from matplotlib import rcParams, rcParamsDefault, get_backend
from matplotlib import rc_context
from matplotlib.rcsetup import interactive_bk as _interactive_bk
from matplotlib.artist import getp, get, Artist
from matplotlib.artist import setp as _setp
from matplotlib.axes import Axes, Subplot
from matplotlib.projections import PolarAxes
from matplotlib import mlab # for csv2rec, detrend_none, window_hanning
from matplotlib.scale import get_scale_docs, get_scale_names
from matplotlib import cm
from matplotlib.cm import get_cmap, register_cmap
import numpy as np
# We may not need the following imports here:
from matplotlib.colors import Normalize
from matplotlib.lines import Line2D
from matplotlib.text import Text, Annotation
from matplotlib.patches import Polygon, Rectangle, Circle, Arrow
from matplotlib.widgets import SubplotTool, Button, Slider, Widget
from .ticker import TickHelper, Formatter, FixedFormatter, NullFormatter,\
FuncFormatter, FormatStrFormatter, ScalarFormatter,\
LogFormatter, LogFormatterExponent, LogFormatterMathtext,\
Locator, IndexLocator, FixedLocator, NullLocator,\
LinearLocator, LogLocator, AutoLocator, MultipleLocator,\
MaxNLocator
from matplotlib.backends import pylab_setup
## Backend detection ##
def _backend_selection():
""" If rcParams['backend_fallback'] is true, check to see if the
current backend is compatible with the current running event
loop, and if not switches to a compatible one.
"""
backend = rcParams['backend']
if not rcParams['backend_fallback'] or \
backend not in _interactive_bk:
return
is_agg_backend = rcParams['backend'].endswith('Agg')
if 'wx' in sys.modules and not backend in ('WX', 'WXAgg'):
import wx
if wx.App.IsMainLoopRunning():
rcParams['backend'] = 'wx' + 'Agg' * is_agg_backend
elif 'PyQt4.QtCore' in sys.modules and not backend == 'Qt4Agg':
import PyQt4.QtGui
if not PyQt4.QtGui.qApp.startingUp():
# The mainloop is running.
rcParams['backend'] = 'qt4Agg'
elif 'PyQt5.QtCore' in sys.modules and not backend == 'Qt5Agg':
import PyQt5.QtWidgets
if not PyQt5.QtWidgets.qApp.startingUp():
# The mainloop is running.
rcParams['backend'] = 'qt5Agg'
elif ('gtk' in sys.modules and
backend not in ('GTK', 'GTKAgg', 'GTKCairo')):
if 'gi' in sys.modules:
from gi.repository import GObject
ml = GObject.MainLoop
else:
import gobject
ml = gobject.MainLoop
if ml().is_running():
rcParams['backend'] = 'gtk' + 'Agg' * is_agg_backend
elif 'Tkinter' in sys.modules and not backend == 'TkAgg':
# import Tkinter
pass # what if anything do we need to do for tkinter?
_backend_selection()
## Global ##
_backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
_IP_REGISTERED = None
_INSTALL_FIG_OBSERVER = False
def install_repl_displayhook():
"""
Install a repl display hook so that any stale figure are automatically
redrawn when control is returned to the repl.
This works with IPython terminals and kernels,
as well as vanilla python shells.
"""
global _IP_REGISTERED
global _INSTALL_FIG_OBSERVER
class _NotIPython(Exception):
pass
# see if we have IPython hooks around, if use them
try:
if 'IPython' in sys.modules:
from IPython import get_ipython
ip = get_ipython()
if ip is None:
raise _NotIPython()
if _IP_REGISTERED:
return
def post_execute():
if matplotlib.is_interactive():
draw_all()
# IPython >= 2
try:
ip.events.register('post_execute', post_execute)
except AttributeError:
# IPython 1.x
ip.register_post_execute(post_execute)
_IP_REGISTERED = post_execute
_INSTALL_FIG_OBSERVER = False
# trigger IPython's eventloop integration, if available
from IPython.core.pylabtools import backend2gui
ipython_gui_name = backend2gui.get(get_backend())
if ipython_gui_name:
ip.enable_gui(ipython_gui_name)
else:
_INSTALL_FIG_OBSERVER = True
# import failed or ipython is not running
except (ImportError, _NotIPython):
_INSTALL_FIG_OBSERVER = True
def uninstall_repl_displayhook():
"""
Uninstalls the matplotlib display hook.
.. warning
Need IPython >= 2 for this to work. For IPython < 2 will raise a
``NotImplementedError``
.. warning
If you are using vanilla python and have installed another
display hook this will reset ``sys.displayhook`` to what ever
function was there when matplotlib installed it's displayhook,
possibly discarding your changes.
"""
global _IP_REGISTERED
global _INSTALL_FIG_OBSERVER
if _IP_REGISTERED:
from IPython import get_ipython
ip = get_ipython()
try:
ip.events.unregister('post_execute', _IP_REGISTERED)
except AttributeError:
raise NotImplementedError("Can not unregister events "
"in IPython < 2.0")
_IP_REGISTERED = None
if _INSTALL_FIG_OBSERVER:
_INSTALL_FIG_OBSERVER = False
draw_all = _pylab_helpers.Gcf.draw_all
@docstring.copy_dedent(Artist.findobj)
def findobj(o=None, match=None, include_self=True):
if o is None:
o = gcf()
return o.findobj(match, include_self=include_self)
def switch_backend(newbackend):
"""
Switch the default backend. This feature is **experimental**, and
is only expected to work switching to an image backend. e.g., if
you have a bunch of PostScript scripts that you want to run from
an interactive ipython session, you may want to switch to the PS
backend before running them to avoid having a bunch of GUI windows
popup. If you try to interactively switch from one GUI backend to
another, you will explode.
Calling this command will close all open windows.
"""
close('all')
global _backend_mod, new_figure_manager, draw_if_interactive, _show
matplotlib.use(newbackend, warn=False, force=True)
from matplotlib.backends import pylab_setup
_backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
def show(*args, **kw):
"""
Display a figure.
When running in ipython with its pylab mode, display all
figures and return to the ipython prompt.
In non-interactive mode, display all figures and block until
the figures have been closed; in interactive mode it has no
effect unless figures were created prior to a change from
non-interactive to interactive mode (not recommended). In
that case it displays the figures but does not block.
A single experimental keyword argument, *block*, may be
set to True or False to override the blocking behavior
described above.
"""
global _show
return _show(*args, **kw)
def isinteractive():
"""
Return status of interactive mode.
"""
return matplotlib.is_interactive()
def ioff():
'Turn interactive mode off.'
matplotlib.interactive(False)
uninstall_repl_displayhook()
def ion():
'Turn interactive mode on.'
matplotlib.interactive(True)
install_repl_displayhook()
def pause(interval):
"""
Pause for *interval* seconds.
If there is an active figure it will be updated and displayed,
and the GUI event loop will run during the pause.
If there is no active figure, or if a non-interactive backend
is in use, this executes time.sleep(interval).
This can be used for crude animation. For more complex
animation, see :mod:`matplotlib.animation`.
This function is experimental; its behavior may be changed
or extended in a future release.
"""
backend = rcParams['backend']
if backend in _interactive_bk:
figManager = _pylab_helpers.Gcf.get_active()
if figManager is not None:
canvas = figManager.canvas
if canvas.figure.stale:
canvas.draw()
show(block=False)
canvas.start_event_loop(interval)
return
# No on-screen figure is active, so sleep() is all we need.
import time
time.sleep(interval)
@docstring.copy_dedent(matplotlib.rc)
def rc(*args, **kwargs):
matplotlib.rc(*args, **kwargs)
@docstring.copy_dedent(matplotlib.rc_context)
def rc_context(rc=None, fname=None):
return matplotlib.rc_context(rc, fname)
@docstring.copy_dedent(matplotlib.rcdefaults)
def rcdefaults():
matplotlib.rcdefaults()
if matplotlib.is_interactive():
draw_all()
# The current "image" (ScalarMappable) is retrieved or set
# only via the pyplot interface using the following two
# functions:
def gci():
"""
Get the current colorable artist. Specifically, returns the
current :class:`~matplotlib.cm.ScalarMappable` instance (image or
patch collection), or *None* if no images or patch collections
have been defined. The commands :func:`~matplotlib.pyplot.imshow`
and :func:`~matplotlib.pyplot.figimage` create
:class:`~matplotlib.image.Image` instances, and the commands
:func:`~matplotlib.pyplot.pcolor` and
:func:`~matplotlib.pyplot.scatter` create
:class:`~matplotlib.collections.Collection` instances. The
current image is an attribute of the current axes, or the nearest
earlier axes in the current figure that contains an image.
"""
return gcf()._gci()
def sci(im):
"""
Set the current image. This image will be the target of colormap
commands like :func:`~matplotlib.pyplot.jet`,
:func:`~matplotlib.pyplot.hot` or
:func:`~matplotlib.pyplot.clim`). The current image is an
attribute of the current axes.
"""
gca()._sci(im)
## Any Artist ##
# (getp is simply imported)
@docstring.copy(_setp)
def setp(*args, **kwargs):
return _setp(*args, **kwargs)
def xkcd(scale=1, length=100, randomness=2):
"""
Turns on `xkcd <http://xkcd.com/>`_ sketch-style drawing mode.
This will only have effect on things drawn after this function is
called.
For best results, the "Humor Sans" font should be installed: it is
not included with matplotlib.
Parameters
----------
scale : float, optional
The amplitude of the wiggle perpendicular to the source line.
length : float, optional
The length of the wiggle along the line.
randomness : float, optional
The scale factor by which the length is shrunken or expanded.
Notes
-----
This function works by a number of rcParams, so it will probably
override others you have set before.
If you want the effects of this function to be temporary, it can
be used as a context manager, for example::
with plt.xkcd():
# This figure will be in XKCD-style
fig1 = plt.figure()
# ...
# This figure will be in regular style
fig2 = plt.figure()
"""
if rcParams['text.usetex']:
raise RuntimeError(
"xkcd mode is not compatible with text.usetex = True")
from matplotlib import patheffects
context = rc_context()
try:
rcParams['font.family'] = ['xkcd', 'Humor Sans', 'Comic Sans MS']
rcParams['font.size'] = 14.0
rcParams['path.sketch'] = (scale, length, randomness)
rcParams['path.effects'] = [
patheffects.withStroke(linewidth=4, foreground="w")]
rcParams['axes.linewidth'] = 1.5
rcParams['lines.linewidth'] = 2.0
rcParams['figure.facecolor'] = 'white'
rcParams['grid.linewidth'] = 0.0
rcParams['axes.grid'] = False
rcParams['axes.unicode_minus'] = False
rcParams['axes.edgecolor'] = 'black'
rcParams['xtick.major.size'] = 8
rcParams['xtick.major.width'] = 3
rcParams['ytick.major.size'] = 8
rcParams['ytick.major.width'] = 3
except:
context.__exit__(*sys.exc_info())
raise
return context
## Figures ##
def figure(num=None, # autoincrement if None, else integer from 1-N
figsize=None, # defaults to rc figure.figsize
dpi=None, # defaults to rc figure.dpi
facecolor=None, # defaults to rc figure.facecolor
edgecolor=None, # defaults to rc figure.edgecolor
frameon=True,
FigureClass=Figure,
clear=False,
**kwargs
):
"""
Creates a new figure.
Parameters
----------
num : integer or string, optional, default: none
If not provided, a new figure will be created, and the figure number
will be incremented. The figure objects holds this number in a `number`
attribute.
If num is provided, and a figure with this id already exists, make
it active, and returns a reference to it. If this figure does not
exists, create it and returns it.
If num is a string, the window title will be set to this figure's
`num`.
figsize : tuple of integers, optional, default: None
width, height in inches. If not provided, defaults to rc
figure.figsize.
dpi : integer, optional, default: None
resolution of the figure. If not provided, defaults to rc figure.dpi.
facecolor :
the background color. If not provided, defaults to rc figure.facecolor.
edgecolor :
the border color. If not provided, defaults to rc figure.edgecolor.
frameon : bool, optional, default: True
If False, suppress drawing the figure frame.
FigureClass : class derived from matplotlib.figure.Figure
Optionally use a custom Figure instance.
clear : bool, optional, default: False
If True and the figure already exists, then it is cleared.
Returns
-------
figure : Figure
The Figure instance returned will also be passed to new_figure_manager
in the backends, which allows to hook custom Figure classes into the
pylab interface. Additional kwargs will be passed to the figure init
function.
Notes
-----
If you are creating many figures, make sure you explicitly call "close"
on the figures you are not using, because this will enable pylab
to properly clean up the memory.
rcParams defines the default values, which can be modified in the
matplotlibrc file
"""
if figsize is None:
figsize = rcParams['figure.figsize']
if dpi is None:
dpi = rcParams['figure.dpi']
if facecolor is None:
facecolor = rcParams['figure.facecolor']
if edgecolor is None:
edgecolor = rcParams['figure.edgecolor']
allnums = get_fignums()
next_num = max(allnums) + 1 if allnums else 1
figLabel = ''
if num is None:
num = next_num
elif isinstance(num, six.string_types):
figLabel = num
allLabels = get_figlabels()
if figLabel not in allLabels:
if figLabel == 'all':
warnings.warn("close('all') closes all existing figures")
num = next_num
else:
inum = allLabels.index(figLabel)
num = allnums[inum]
else:
num = int(num) # crude validation of num argument
figManager = _pylab_helpers.Gcf.get_fig_manager(num)
if figManager is None:
max_open_warning = rcParams['figure.max_open_warning']
if (max_open_warning >= 1 and len(allnums) >= max_open_warning):
warnings.warn(
"More than %d figures have been opened. Figures "
"created through the pyplot interface "
"(`matplotlib.pyplot.figure`) are retained until "
"explicitly closed and may consume too much memory. "
"(To control this warning, see the rcParam "
"`figure.max_open_warning`)." %
max_open_warning, RuntimeWarning)
if get_backend().lower() == 'ps':
dpi = 72
figManager = new_figure_manager(num, figsize=figsize,
dpi=dpi,
facecolor=facecolor,
edgecolor=edgecolor,
frameon=frameon,
FigureClass=FigureClass,
**kwargs)
if figLabel:
figManager.set_window_title(figLabel)
figManager.canvas.figure.set_label(figLabel)
# make this figure current on button press event
def make_active(event):
_pylab_helpers.Gcf.set_active(figManager)
cid = figManager.canvas.mpl_connect('button_press_event', make_active)
figManager._cidgcf = cid
_pylab_helpers.Gcf.set_active(figManager)
fig = figManager.canvas.figure
fig.number = num
# make sure backends (inline) that we don't ship that expect this
# to be called in plotting commands to make the figure call show
# still work. There is probably a better way to do this in the
# FigureManager base class.
if matplotlib.is_interactive():
draw_if_interactive()
if _INSTALL_FIG_OBSERVER:
fig.stale_callback = _auto_draw_if_interactive
if clear:
figManager.canvas.figure.clear()
return figManager.canvas.figure
def _auto_draw_if_interactive(fig, val):
"""
This is an internal helper function for making sure that auto-redrawing
works as intended in the plain python repl.
Parameters
----------
fig : Figure
A figure object which is assumed to be associated with a canvas
"""
if val and matplotlib.is_interactive() and not fig.canvas.is_saving():
fig.canvas.draw_idle()
def gcf():
"Get a reference to the current figure."
figManager = _pylab_helpers.Gcf.get_active()
if figManager is not None:
return figManager.canvas.figure
else:
return figure()
def fignum_exists(num):
return _pylab_helpers.Gcf.has_fignum(num) or num in get_figlabels()
def get_fignums():
"""Return a list of existing figure numbers."""
return sorted(_pylab_helpers.Gcf.figs)
def get_figlabels():
"Return a list of existing figure labels."
figManagers = _pylab_helpers.Gcf.get_all_fig_managers()
figManagers.sort(key=lambda m: m.num)
return [m.canvas.figure.get_label() for m in figManagers]
def get_current_fig_manager():
figManager = _pylab_helpers.Gcf.get_active()
if figManager is None:
gcf() # creates an active figure as a side effect
figManager = _pylab_helpers.Gcf.get_active()
return figManager
@docstring.copy_dedent(FigureCanvasBase.mpl_connect)
def connect(s, func):
return get_current_fig_manager().canvas.mpl_connect(s, func)
@docstring.copy_dedent(FigureCanvasBase.mpl_disconnect)
def disconnect(cid):
return get_current_fig_manager().canvas.mpl_disconnect(cid)
def close(*args):
"""
Close a figure window.
``close()`` by itself closes the current figure
``close(h)`` where *h* is a :class:`Figure` instance, closes that figure
``close(num)`` closes figure number *num*
``close(name)`` where *name* is a string, closes figure with that label
``close('all')`` closes all the figure windows
"""
if len(args) == 0:
figManager = _pylab_helpers.Gcf.get_active()
if figManager is None:
return
else:
_pylab_helpers.Gcf.destroy(figManager.num)
elif len(args) == 1:
arg = args[0]
if arg == 'all':
_pylab_helpers.Gcf.destroy_all()
elif isinstance(arg, six.integer_types):
_pylab_helpers.Gcf.destroy(arg)
elif hasattr(arg, 'int'):
# if we are dealing with a type UUID, we
# can use its integer representation
_pylab_helpers.Gcf.destroy(arg.int)
elif isinstance(arg, six.string_types):
allLabels = get_figlabels()
if arg in allLabels:
num = get_fignums()[allLabels.index(arg)]
_pylab_helpers.Gcf.destroy(num)
elif isinstance(arg, Figure):
_pylab_helpers.Gcf.destroy_fig(arg)
else:
raise TypeError('Unrecognized argument type %s to close' % type(arg))
else:
raise TypeError('close takes 0 or 1 arguments')
def clf():
"""
Clear the current figure.
"""
gcf().clf()
def draw():
"""Redraw the current figure.
This is used to update a figure that has been altered, but not
automatically re-drawn. If interactive mode is on (:func:`.ion()`), this
should be only rarely needed, but there may be ways to modify the state of
a figure without marking it as `stale`. Please report these cases as
bugs.
A more object-oriented alternative, given any
:class:`~matplotlib.figure.Figure` instance, :attr:`fig`, that
was created using a :mod:`~matplotlib.pyplot` function, is::
fig.canvas.draw_idle()
"""
get_current_fig_manager().canvas.draw_idle()
@docstring.copy_dedent(Figure.savefig)
def savefig(*args, **kwargs):
fig = gcf()
res = fig.savefig(*args, **kwargs)
fig.canvas.draw_idle() # need this if 'transparent=True' to reset colors
return res
@docstring.copy_dedent(Figure.ginput)
def ginput(*args, **kwargs):
"""
Blocking call to interact with the figure.
This will wait for *n* clicks from the user and return a list of the
coordinates of each click.
If *timeout* is negative, does not timeout.
"""
return gcf().ginput(*args, **kwargs)
@docstring.copy_dedent(Figure.waitforbuttonpress)
def waitforbuttonpress(*args, **kwargs):
"""
Blocking call to interact with the figure.
This will wait for *n* key or mouse clicks from the user and
return a list containing True's for keyboard clicks and False's
for mouse clicks.
If *timeout* is negative, does not timeout.
"""
return gcf().waitforbuttonpress(*args, **kwargs)
# Putting things in figures
@docstring.copy_dedent(Figure.text)
def figtext(*args, **kwargs):
return gcf().text(*args, **kwargs)
@docstring.copy_dedent(Figure.suptitle)
def suptitle(*args, **kwargs):
return gcf().suptitle(*args, **kwargs)
@docstring.copy_dedent(Figure.figimage)
def figimage(*args, **kwargs):
return gcf().figimage(*args, **kwargs)
def figlegend(*args, **kwargs):
"""
Place a legend in the figure.
*labels*
a sequence of strings
*handles*
a sequence of :class:`~matplotlib.lines.Line2D` or
:class:`~matplotlib.patches.Patch` instances
*loc*
can be a string or an integer specifying the legend
location
A :class:`matplotlib.legend.Legend` instance is returned.
Examples
--------
To make a legend from existing artists on every axes::
figlegend()
To make a legend for a list of lines and labels::
figlegend( (line1, line2, line3),
('label1', 'label2', 'label3'),
'upper right' )
.. seealso::
:func:`~matplotlib.pyplot.legend`
"""
return gcf().legend(*args, **kwargs)
## Figure and Axes hybrid ##
_hold_msg = """pyplot.hold is deprecated.
Future behavior will be consistent with the long-time default:
plot commands add elements without first clearing the
Axes and/or Figure."""
@deprecated("2.0", message=_hold_msg)
def hold(b=None):
"""
Set the hold state. If *b* is None (default), toggle the
hold state, else set the hold state to boolean value *b*::
hold() # toggle hold
hold(True) # hold is on
hold(False) # hold is off
When *hold* is *True*, subsequent plot commands will add elements to
the current axes. When *hold* is *False*, the current axes and
figure will be cleared on the next plot command.
"""
fig = gcf()
ax = fig.gca()
if b is not None:
b = bool(b)
fig._hold = b
ax._hold = b
# b=None toggles the hold state, so let's get get the current hold
# state; but should pyplot hold toggle the rc setting - me thinks
# not
b = ax._hold
# The comment above looks ancient; and probably the line below,
# contrary to the comment, is equally ancient. It will trigger
# a second warning, but "Oh, well...".
rc('axes', hold=b)
@deprecated("2.0", message=_hold_msg)
def ishold():
"""
Return the hold status of the current axes.
"""
return gca()._hold
@deprecated("2.0", message=_hold_msg)
def over(func, *args, **kwargs):
"""
Call a function with hold(True).
Calls::
func(*args, **kwargs)
with ``hold(True)`` and then restores the hold state.
"""
ax = gca()
h = ax._hold
ax._hold = True
func(*args, **kwargs)
ax._hold = h
## Axes ##
def axes(*args, **kwargs):
"""
Add an axes to the figure.
The axes is added at position *rect* specified by:
- ``axes()`` by itself creates a default full ``subplot(111)`` window axis.
- ``axes(rect, facecolor='w')`` where *rect* = [left, bottom, width,
height] in normalized (0, 1) units. *facecolor* is the background
color for the axis, default white.
- ``axes(h)`` where *h* is an axes instance makes *h* the current
axis and the parent of *h* the current figure.
An :class:`~matplotlib.axes.Axes` instance is returned.
========= ============== ==============================================
kwarg Accepts Description
========= ============== ==============================================
facecolor color the axes background color
frameon [True|False] display the frame?
sharex otherax current axes shares xaxis attribute
with otherax
sharey otherax current axes shares yaxis attribute
with otherax
polar [True|False] use a polar axes?
aspect [str | num] ['equal', 'auto'] or a number. If a number
the ratio of x-unit/y-unit in screen-space.
Also see
:meth:`~matplotlib.axes.Axes.set_aspect`.
========= ============== ==============================================
Examples:
* :file:`examples/pylab_examples/axes_demo.py` places custom axes.
* :file:`examples/pylab_examples/shared_axis_demo.py` uses
*sharex* and *sharey*.
"""
nargs = len(args)
if len(args) == 0:
return subplot(111, **kwargs)
if nargs > 1:
raise TypeError('Only one non keyword arg to axes allowed')
arg = args[0]
if isinstance(arg, Axes):
sca(arg)
a = arg
else:
rect = arg
a = gcf().add_axes(rect, **kwargs)
return a
def delaxes(*args):
"""
Remove an axes from the current figure. If *ax*
doesn't exist, an error will be raised.
``delaxes()``: delete the current axes
"""
if not len(args):
ax = gca()
else:
ax = args[0]
ret = gcf().delaxes(ax)
return ret
def sca(ax):
"""
Set the current Axes instance to *ax*.
The current Figure is updated to the parent of *ax*.
"""
managers = _pylab_helpers.Gcf.get_all_fig_managers()
for m in managers:
if ax in m.canvas.figure.axes:
_pylab_helpers.Gcf.set_active(m)
m.canvas.figure.sca(ax)
return
raise ValueError("Axes instance argument was not found in a figure.")
def gca(**kwargs):
"""
Get the current :class:`~matplotlib.axes.Axes` instance on the
current figure matching the given keyword args, or create one.
Examples
--------
To get the current polar axes on the current figure::
plt.gca(projection='polar')
If the current axes doesn't exist, or isn't a polar one, the appropriate
axes will be created and then returned.
See Also
--------
matplotlib.figure.Figure.gca : The figure's gca method.
"""
return gcf().gca(**kwargs)
# More ways of creating axes:
def subplot(*args, **kwargs):
"""
Return a subplot axes positioned by the given grid definition.
Typical call signature::
subplot(nrows, ncols, plot_number)
Where *nrows* and *ncols* are used to notionally split the figure
into ``nrows * ncols`` sub-axes, and *plot_number* is used to identify
the particular subplot that this function is to create within the notional
grid. *plot_number* starts at 1, increments across rows first and has a
maximum of ``nrows * ncols``.
In the case when *nrows*, *ncols* and *plot_number* are all less than 10,
a convenience exists, such that the a 3 digit number can be given instead,
where the hundreds represent *nrows*, the tens represent *ncols* and the
units represent *plot_number*. For instance::
subplot(211)
produces a subaxes in a figure which represents the top plot (i.e. the
first) in a 2 row by 1 column notional grid (no grid actually exists,
but conceptually this is how the returned subplot has been positioned).
.. note::