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"""

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)

"""

import sys

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.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

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 to newbackend. 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 new_figure_manager, draw_if_interactive, _show

matplotlib.use(newbackend, warn=False)

reload(matplotlib.backends)

from matplotlib.backends import pylab_setup

new_figure_manager, draw_if_interactive, _show = pylab_setup()

def show():

"""

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.

"""

global _show

_show()

def isinteractive():

"""

Return *True* if matplotlib is in interactive mode, *False* otherwise.

"""

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`.

"""

backend = rcParams['backend']

if backend in _interactive_bk:

figManager = _pylab_helpers.Gcf.get_active()

if figManager is not None:

canvas = figManager.canvas

canvas.draw()

was_interactive = isinteractive()

if not was_interactive:

ion()

show()

canvas.start_event_loop(interval)

if not was_interactive:

ioff()

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.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 :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 (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

"""

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)

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']

if num is None:

allnums = [f.num for f in _pylab_helpers.Gcf.get_all_fig_managers()]

if allnums:

num = max(allnums) + 1

else:

num = 1

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)

# 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_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(num)`` closes figure number *num*

``close(h)`` where *h* is a :class:`Figure` instance, closes that figure

``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 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 :module:`~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):

"""

over 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 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 Desctiption

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

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):

"""

``delaxes(ax)``: remove *ax* 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):

"""

Create a subplot command, creating axes with::

subplot(numRows, numCols, plotNum)

where *plotNum* = 1 is the first plot number and increasing *plotNums*

fill rows first. max(*plotNum*) == *numRows* * *numCols*

You can leave out the commas if *numRows* <= *numCols* <=

*plotNum* < 10, as in::

subplot(211) # 2 rows, 1 column, first (upper) plot

``subplot(111)`` is the default axis.

New subplots that overlap old will delete the old axes. If you do

not want this behavior, use

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

:func:`~matplotlib.pyplot.axes` command. Eg.::

from pylab import *

plot([1,2,3]) # implicitly creates subplot(111)

subplot(211) # overlaps, subplot(111) is killed

plot(rand(12), rand(12))

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

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 :func:`matplotlib.projections.register_projection`

.. 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

"""

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 : 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

sharey : 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

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 contaning Axis instances, even if it ends up being 1x1.

subplot_kw : dict

Dict with keywords passed to the add_subplot() call used to create each

subplots.

fig_kw : dict

Dict with keywords passed to the figure() call. Note that all keywords

not recognized above will be automatically included here.

Returns:

fig, ax : tuple

- fig is the Matplotlib Figure object

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

objects if more than one supblot 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))

"""

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

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

# convention.

for i in range(1, nplots):

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 and nrows>1:

# turn off all but the bottom row

for ax in axarr[:-1,:].flat:

for label in ax.get_xticklabels():

label.set_visible(False)

if sharey and ncols>1:

# turn off all but the first column

for ax in axarr[:,1:].flat:

for label in ax.get_yticklabels():

label.set_visible(False)

if squeeze:

# Reshape the array to have the final desired dimension (nrow,ncol),

# though discarding unneeded dimensions that equal 1. If we only have

# one subplot, just return it instead of a 1-element array.

if nplots==1:

ret = fig, axarr[0,0]

else:

ret = fig, axarr.squeeze()

else:

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

ret = fig, axarr.reshape(nrows, ncols)

return ret

from gridspec import GridSpec

def subplot2grid(shape, loc, rowspan=1, colspan=1, **kwargs):

"""

It creates a subplot in a grid of *shape*, at location of *loc*,

spanning *rowspan*, *colspan* cells in each direction.

The index for loc is 0-based. ::

subplot2grid(shape, loc, rowspan=1, colspan=1)

is identical to ::

gridspec=GridSpec(shape[0], shape[2])

subplotspec=gridspec.new_subplotspec(loc, rowspan, colspan)

subplot(subplotspec)

"""

fig = gcf()

s1, s2 = shape

subplotspec = GridSpec(s1, s2).new_subplotspec(loc,

rowspan=rowspan,

colspan=colspan)

a = fig.add_subplot(subplotspec, **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 twinx(ax=None):

"""

Make a second axes overlay *ax* (or the current axes if *ax* is

*None*) sharing the xaxis. The ticks for *ax2* will be placed on

the right, and the *ax2* instance is returned.

.. seealso::

:file:`examples/api_examples/two_scales.py`

For an example

"""

if ax is None:

ax=gca()

ax1 = ax.twinx()

draw_if_interactive()

return ax1

def twiny(ax=None):

"""

Make a second axes overlay *ax* (or the current axes if *ax* is

*None*) sharing the yaxis. The ticks for *ax2* will be placed on

the top, and the *ax2* instance is returned.

"""

if ax is None:

ax=gca()

ax1 = ax.twiny()

draw_if_interactive()

return ax1

def subplots_adjust(*args, **kwargs):

"""

call signature::

subplots_adjust(left=None, bottom=None, right=None, top=None,

wspace=None, hspace=None)

Tune the subplot layout via the

:class:`matplotlib.figure.SubplotParams` mechanism. The parameter

meanings (and suggested defaults) are::

left = 0.125 # the left side of the subplots of the figure

right = 0.9 # the right side of the subplots of the figure

bottom = 0.1 # the bottom of the subplots of the figure

top = 0.9 # the top of the subplots of the figure

wspace = 0.2 # the amount of width reserved for blank space between subplots

hspace = 0.2 # the amount of height reserved for white space between subplots

The actual defaults are controlled by the rc file

"""

fig = gcf()

fig.subplots_adjust(*args, **kwargs)

draw_if_interactive()

def subplot_tool(targetfig=None):

"""

Launch a subplot tool window for *targetfig* (default gcf).

A :class:`matplotlib.widgets.SubplotTool` instance is returned.

"""

tbar = rcParams['toolbar'] # turn off the navigation toolbar for the toolfig

rcParams['toolbar'] = 'None'

if targetfig is None:

manager = get_current_fig_manager()

targetfig = manager.canvas.figure

else:

# find the manager for this figure

for manager in _pylab_helpers.Gcf._activeQue:

if manager.canvas.figure==targetfig: break

else: raise RuntimeError('Could not find manager for targetfig')

toolfig = figure(figsize=(6,3))

toolfig.subplots_adjust(top=0.9)

ret = SubplotTool(targetfig, toolfig)

rcParams['toolbar'] = tbar

_pylab_helpers.Gcf.set_active(manager) # restore the current figure

return ret

def tight_layout(pad=1.2, h_pad=None, w_pad=None):

"""Adjust subplot parameters to give specified padding.

Parameters

----------

pad : float

padding between the figure edge and the edges of subplots, as a fraction of the font-size.

View remainder of file in raw view

matplotlib/lib/matplotlib/pyplot.py at mplot3d/asanyarray · WeatherGod/matplotlib · GitHub

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