# 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 print_function

import sys, warnings

import matplotlib

from matplotlib import _pylab_helpers, interactive

from matplotlib.cbook import dedent, silent_list, is_string_like, is_numlike

from matplotlib import docstring

from matplotlib.figure import Figure, figaspect

from matplotlib.backend_bases import FigureCanvasBase

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, _string_to_bool

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, normalize # latter for backwards compat.

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

## 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 'qt' in sys.modules and not backend == 'QtAgg':

import qt

if not qt.qApp.startingUp():

# The mainloop is running.

rcParams['backend'] = 'qtAgg'

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 'gtk' in sys.modules and not backend in ('GTK', 'GTKAgg',

'GTKCairo'):

import gobject

if gobject.MainLoop().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 ##

from matplotlib.backends import pylab_setup

_backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()

@docstring.copy_dedent(Artist.findobj)

def findobj(o=None, match=None):

if o is None:

o = gcf()

return o.findobj(match)

def switch_backend(newbackend):

"""

Switch the default backend. This feature is **experimental**, and

is only expected to work switching to an image backend. Eg, 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

_show(*args, **kw)

def isinteractive():

"""

Return status of interactive mode.

"""

return matplotlib.is_interactive()

def ioff():

'Turn interactive mode off.'

matplotlib.interactive(False)

def ion():

'Turn interactive mode on.'

matplotlib.interactive(True)

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

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()

draw_if_interactive()

# 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):

ret = _setp(*args, **kwargs)

draw_if_interactive()

return ret

## 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,

**kwargs

):

"""

Create a new figure.

call signature::

figure(num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')

Create a new figure and return a :class:`matplotlib.figure.Figure`

instance. If *num* = *None*, the figure number will be incremented and

a new figure will be created. The returned figure objects have a

*number* attribute holding this number.

If *num* is an integer, and ``figure(num)`` already exists, make it

active and return a reference to it. If ``figure(num)`` does not exist

it will be created. Numbering starts at 1, MATLAB style::

figure(1)

The same applies if *num* is a string. In this case *num* will be used

as an explicit figure label::

figure("today")

and in windowed backends, the window title will be set to this figure

label.

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.

Optional keyword arguments:

========= =======================================================

Keyword Description

========= =======================================================

figsize width x height in inches; defaults to rc figure.figsize

dpi resolution; defaults to rc figure.dpi

facecolor the background color; defaults to rc figure.facecolor

edgecolor the border color; defaults to rc figure.edgecolor

========= =======================================================

rcParams defines the default values, which can be modified in the

matplotlibrc file

*FigureClass* is a :class:`~matplotlib.figure.Figure` or derived

class that will be passed on to :meth:`new_figure_manager` in the

backends which allows you to hook custom Figure classes into the

pylab interface. Additional kwargs will be passed on to your

figure init function.

"""

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 is_string_like(num):

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:

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)

figManager.canvas.figure.number = num

draw_if_interactive()

return figManager.canvas.figure

def gcf():

"Return a reference to the current figure."

figManager = _pylab_helpers.Gcf.get_active()

if figManager is not None:

return figManager.canvas.figure

else:

return figure()

fignum_exists = _pylab_helpers.Gcf.has_fignum

def get_fignums():

"Return a list of existing figure numbers."

fignums = _pylab_helpers.Gcf.figs.keys()

fignums.sort()

return fignums

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, int):

_pylab_helpers.Gcf.destroy(arg)

elif is_string_like(arg):

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()

draw_if_interactive()

def draw():

"""

Redraw the current figure.

This is used in interactive mode to update a figure that

has been altered using one or more plot object method calls;

it is not needed if figure modification is done entirely

with pyplot functions, if a sequence of modifications ends

with a pyplot function, or if matplotlib is in non-interactive

mode and the sequence of modifications ends with :func:`show` or

:func:`savefig`.

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()

"""

get_current_fig_manager().canvas.draw()

@docstring.copy_dedent(Figure.savefig)

def savefig(*args, **kwargs):

fig = gcf()

return fig.savefig(*args, **kwargs)

@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):

ret = gcf().text(*args, **kwargs)

draw_if_interactive()

return ret

@docstring.copy_dedent(Figure.suptitle)

def suptitle(*args, **kwargs):

ret = gcf().suptitle(*args, **kwargs)

draw_if_interactive()

return ret

@docstring.Appender("Addition kwargs: hold = [True|False] overrides default hold state", "\n")

@docstring.copy_dedent(Figure.figimage)

def figimage(*args, **kwargs):

# allow callers to override the hold state by passing hold=True|False

ret = gcf().figimage(*args, **kwargs)

draw_if_interactive()

#sci(ret) # JDH figimage should not set current image -- it is not mappable, etc

return ret

def figlegend(handles, labels, loc, **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.

Example::

figlegend( (line1, line2, line3),

('label1', 'label2', 'label3'),

'upper right' )

.. seealso::

:func:`~matplotlib.pyplot.legend`

"""

l = gcf().legend(handles, labels, loc, **kwargs)

draw_if_interactive()

return l

## Figure and Axes hybrid ##

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 be added 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()

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.ishold()

rc('axes', hold=b)

def ishold():

"""

Return the hold status of the current axes.

"""

return gca().ishold()

def over(func, *args, **kwargs):

"""

Call a function with hold(True).

Calls::

func(*args, **kwargs)

with ``hold(True)`` and then restores the hold state.

"""

h = ishold()

hold(True)

func(*args, **kwargs)

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, axisbg='w')`` where *rect* = [left, bottom, width,

height] in normalized (0, 1) units. *axisbg* is the background

color for the axis, default white.

- ``axes(h)`` where *h* is an axes instance makes *h* the current

axis. An :class:`~matplotlib.axes.Axes` instance is returned.

======= ============ ================================================

kwarg Accepts Description

======= ============ ================================================

axisbg 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?

======= ============ ================================================

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):

a = gcf().sca(arg)

else:

rect = arg

a = gcf().add_axes(rect, **kwargs)

draw_if_interactive()

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)

draw_if_interactive()

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):

"""

Return the current axis instance. This can be used to control

axis properties either using set or the

:class:`~matplotlib.axes.Axes` methods, for example, setting the

xaxis range::

plot(t,s)

set(gca(), 'xlim', [0,10])

or::

plot(t,s)

a = gca()

a.set_xlim([0,10])

"""

ax = gcf().gca(**kwargs)

return ax

# 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::

Creating a new subplot with a position which is entirely inside a

pre-existing axes will trigger the larger axes to be deleted::

import matplotlib.pyplot as plt

# plot a line, implicitly creating a subplot(111)

plt.plot([1,2,3])

# now create a subplot which represents the top plot of a grid

# with 2 rows and 1 column. Since this subplot will overlap the

# first, the plot (and its axes) previously created, will be removed

plt.subplot(211)

plt.plot(range(12))

plt.subplot(212, axisbg='y') # creates 2nd subplot with yellow background

If you do not want this behavior, use the

:meth:`~matplotlib.figure.Figure.add_subplot` method or the

:func:`~matplotlib.pyplot.axes` function instead.

Keyword arguments:

*axisbg*:

The background color of the subplot, which can be any valid

color specifier. See :mod:`matplotlib.colors` for more

information.

*polar*:

A boolean flag indicating whether the subplot plot should be

a polar projection. Defaults to *False*.

*projection*:

A string giving the name of a custom projection to be used

for the subplot. This projection must have been previously

registered. See :mod:`matplotlib.projections`.

.. seealso::

:func:`~matplotlib.pyplot.axes`

For additional information on :func:`axes` and

:func:`subplot` keyword arguments.

:file:`examples/pylab_examples/polar_scatter.py`

For an example

**Example:**

.. plot:: mpl_examples/pylab_examples/subplot_demo.py

"""

# if subplot called without arguments, create subplot(1,1,1)

if len(args)==0:

args=(1,1,1)

# This check was added because it is very easy to type

# subplot(1, 2, False) when subplots(1, 2, False) was intended

# (sharex=False, that is). In most cases, no error will

# ever occur, but mysterious behavior can result because what was

# intended to be the sharex argument is instead treated as a

# subplot index for subplot()

if len(args) >= 3 and isinstance(args[2], bool) :

warnings.warn("The subplot index argument to subplot() appears"

" to be a boolean. Did you intend to use subplots()?")

fig = gcf()

a = fig.add_subplot(*args, **kwargs)

bbox = a.bbox

byebye = []

for other in fig.axes:

if other==a: continue

if bbox.fully_overlaps(other.bbox):

byebye.append(other)

for ax in byebye: delaxes(ax)

draw_if_interactive()

return a

def subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True,

subplot_kw=None, **fig_kw):

"""

Create a figure with a set of subplots already made.

This utility wrapper makes it convenient to create common layouts of

subplots, including the enclosing figure object, in a single call.

Keyword arguments:

*nrows* : int

Number of rows of the subplot grid. Defaults to 1.

*ncols* : int

Number of columns of the subplot grid. Defaults to 1.

*sharex* : string or bool

If *True*, the X axis will be shared amongst all subplots. If

*True* and you have multiple rows, the x tick labels on all but

the last row of plots will have visible set to *False*

If a string must be one of "row", "col", "all", or "none".

"all" has the same effect as *True*, "none" has the same effect

as *False*.

If "row", each subplot row will share a X axis.

If "col", each subplot column will share a X axis and the x tick

labels on all but the last row will have visible set to *False*.

*sharey* : string or bool

If *True*, the Y axis will be shared amongst all subplots. If

*True* and you have multiple columns, the y tick labels on all but

the first column of plots will have visible set to *False*

If a string must be one of "row", "col", "all", or "none".

"all" has the same effect as *True*, "none" has the same effect

as *False*.

If "row", each subplot row will share a Y axis.

If "col", each subplot column will share a Y axis and the y tick

labels on all but the last row will have visible set to *False*.

*squeeze* : bool

If *True*, extra dimensions are squeezed out from the

returned axis object:

- if only one subplot is constructed (nrows=ncols=1), the

resulting single Axis object is returned as a scalar.

- for Nx1 or 1xN subplots, the returned object is a 1-d numpy

object array of Axis objects are returned as numpy 1-d

arrays.

- 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 axis

object is always a 2-d array containing Axis instances, even if it

ends up being 1x1.

*subplot_kw* : dict

Dict with keywords passed to the

:meth:`~matplotlib.figure.Figure.add_subplot` call used to

create each subplots.

*fig_kw* : dict

Dict with keywords passed to the :func:`figure` call. Note that all

keywords not recognized above will be automatically included here.

Returns:

fig, ax : tuple

- *fig* is the :class:`matplotlib.figure.Figure` object

- *ax* can be either a single axis object or an array of axis

objects if more than one subplot was created. The dimensions

of the resulting array can be controlled with the squeeze

keyword, see above.

Examples::

x = np.linspace(0, 2*np.pi, 400)

y = np.sin(x**2)

# Just a figure and one subplot

f, ax = plt.subplots()

ax.plot(x, y)

ax.set_title('Simple plot')

# Two subplots, unpack the output array immediately

f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)

ax1.plot(x, y)

ax1.set_title('Sharing Y axis')

ax2.scatter(x, y)

# Four polar axes

plt.subplots(2, 2, subplot_kw=dict(polar=True))

# Share a X axis with each column of subplots

plt.subplots(2, 2, sharex='col')

# Share a Y axis with each row of subplots

plt.subplots(2, 2, sharey='row')

# Share a X and Y axis with all subplots

plt.subplots(2, 2, sharex='all', sharey='all')

# same as

plt.subplots(2, 2, sharex=True, sharey=True)

"""

# for backwards compatibility

if isinstance(sharex, bool):

if sharex:

sharex = "all"

else:

sharex = "none"

if isinstance(sharey, bool):

if sharey:

sharey = "all"

else:

sharey = "none"

share_values = ["all", "row", "col", "none"]

if sharex not in share_values:

# This check was added because it is very easy to type subplots(1, 2, 1)

# when subplot(1, 2, 1) was intended. In most cases, no error will

# ever occur, but mysterious behavior will result because what was

# intended to be the subplot index is instead treated as a bool for

# sharex.

if isinstance(sharex, int):

warnings.warn("sharex argument to subplots() was an integer."

" Did you intend to use subplot() (without 's')?")

raise ValueError("sharex [%s] must be one of %s" % \

(sharex, share_values))

if sharey not in share_values:

raise ValueError("sharey [%s] must be one of %s" % \

(sharey, share_values))

if subplot_kw is None:

subplot_kw = {}

fig = figure(**fig_kw)

# Create empty object array to hold all axes. It's easiest to make it 1-d

# so we can just append subplots upon creation, and then

nplots = nrows*ncols

axarr = np.empty(nplots, dtype=object)

# Create first subplot separately, so we can share it if requested

ax0 = fig.add_subplot(nrows, ncols, 1, **subplot_kw)

#if sharex:

# subplot_kw['sharex'] = ax0

#if sharey:

# subplot_kw['sharey'] = ax0

axarr[0] = ax0

r, c = np.mgrid[:nrows, :ncols]

r = r.flatten() * ncols

c = c.flatten()

lookup = {

"none": np.arange(nplots),

"all": np.zeros(nplots, dtype=int),

"row": r,

"col": c,

}

sxs = lookup[sharex]

sys = lookup[sharey]

# Note off-by-one counting because add_subplot uses the MATLAB 1-based

# convention.

for i in range(1, nplots):

if sxs[i] == i:

subplot_kw['sharex'] = None

else:

subplot_kw['sharex'] = axarr[sxs[i]]

if sys[i] == i:

subplot_kw['sharey'] = None

else:

subplot_kw['sharey'] = axarr[sys[i]]

axarr[i] = fig.add_subplot(nrows, ncols, i + 1, **subplot_kw)

# returned axis array will be always 2-d, even if nrows=ncols=1

axarr = axarr.reshape(nrows, ncols)

# turn off redundant tick labeling

if sharex in ["col", "all"] and nrows > 1:

#if sharex and nrows>1: