"""
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, 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.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(*args, **kw):
    """
    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 *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`.

    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.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)

    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()
    figLabel = ''
    if num is None:
        if allnums:
            num = max(allnums) + 1
        else:
            num = 1
    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")
            if len(allLabels):
                num = max(allnums) + 1
            else:
                num = 1
        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):
    """
    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 :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

    """


    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
        :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 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.
    h_pad, w_pad : float
        padding (height/width) between edges of adjacent subplots.
        Defaults to `pad_inches`.
    """

    fig = gcf()
    fig.tight_layout(pad=pad, h_pad=h_pad, w_pad=w_pad)
    draw_if_interactive()



def box(on=None):
    """
    Turn the axes box on or off according to *on*.
    *on* may be a boolean or a string, 'on' or 'off'.

    If *on* is *None*, toggle state.
    """
    ax = gca()
    on = _string_to_bool(on)
    if on is None:
        on = not ax.get_frame_on()
    ax.set_frame_on(on)
    draw_if_interactive()

def title(s, *args, **kwargs):
    """
    Set the title of the current axis to *s*.

    Default font override is::

      override = {'fontsize': 'medium',
                  'verticalalignment': 'baseline',
                  'horizontalalignment': 'center'}

    .. seealso::

       :func:`~matplotlib.pyplot.text`
           for information on how override and the optional args work.
    """
    l =  gca().set_title(s, *args, **kwargs)
    draw_if_interactive()
    return l




## Axis ##

def axis(*v, **kwargs):
    """
    Set/Get the axis properties:

      >>> axis()

    returns the current axes limits ``[xmin, xmax, ymin, ymax]``.

      >>> axis(v)

    sets the min and max of the x and y axes, with
    ``v = [xmin, xmax, ymin, ymax]``.

      >>> axis('off')

    turns off the axis lines and labels.

      >>> axis('equal')

    changes limits of *x* or *y* axis so that equal increments of *x*
    and *y* have the same length; a circle is circular.

      >>> axis('scaled')

    achieves the same result by changing the dimensions of the plot box instead
    of the axis data limits.

      >>> axis('tight')

    changes *x* and *y* axis limits such that all data is shown. If
    all data is already shown, it will move it to the center of the
    figure without modifying (*xmax* - *xmin*) or (*ymax* -
    *ymin*). Note this is slightly different than in MATLAB.

      >>> axis('image')

    is 'scaled' with the axis limits equal to the data limits.

      >>> axis('auto')

    and

      >>> axis('normal')

    are deprecated. They restore default behavior; axis limits are automatically
    scaled to make the data fit comfortably within the plot box.

    if ``len(*v)==0``, you can pass in *xmin*, *xmax*, *ymin*, *ymax*
    as kwargs selectively to alter just those limits without changing
    the others.

    The xmin, xmax, ymin, ymax tuple is returned

    .. seealso::

        :func:`xlim`, :func:`ylim`
           For setting the x- and y-limits individually.
    """
    ax = gca()
    v = ax.axis(*v, **kwargs)
    draw_if_interactive()
    return v

def xlabel(s, *args, **kwargs):
    """
    Set the *x* axis label of the current axis to *s*

    Default override is::

      override = {
          'fontsize'            : 'small',
          'verticalalignment'   : 'top',
          'horizontalalignment' : 'center'
          }

    .. seealso::

        :func:`~matplotlib.pyplot.text`
            For information on how override and the optional args work
    """
    l =  gca().set_xlabel(s, *args, **kwargs)
    draw_if_interactive()
    return l

def ylabel(s, *args, **kwargs):
    """
    Set the *y* axis label of the current axis to *s*.

    Defaults override is::

        override = {
           'fontsize'            : 'small',
           'verticalalignment'   : 'center',
           'horizontalalignment' : 'right',
           'rotation'='vertical' : }

    .. seealso::

        :func:`~matplotlib.pyplot.text`
            For information on how override and the optional args
            work.
    """
    l = gca().set_ylabel(s, *args, **kwargs)
    draw_if_interactive()
    return l





def xlim(*args, **kwargs):
    """
    Set/Get the xlimits of the current axes::

      xmin, xmax = xlim()   # return the current xlim
      xlim( (xmin, xmax) )  # set the xlim to xmin, xmax
      xlim( xmin, xmax )    # set the xlim to xmin, xmax

    If you do not specify args, you can pass the xmin and xmax as
    kwargs, eg.::

      xlim(xmax=3) # adjust the max leaving min unchanged
      xlim(xmin=1) # adjust the min leaving max unchanged

    Setting limits turns autoscaling off for the x-axis.

    The new axis limits are returned as a length 2 tuple.

    """
    ax = gca()
    if not args and not kwargs:
        return ax.get_xlim()
    ret = ax.set_xlim(*args, **kwargs)
    draw_if_interactive()
    return ret


def ylim(*args, **kwargs):
    """
    Set/Get the ylimits of the current axes::

      ymin, ymax = ylim()   # return the current ylim
      ylim( (ymin, ymax) )  # set the ylim to ymin, ymax
      ylim( ymin, ymax )    # set the ylim to ymin, ymax

    If you do not specify args, you can pass the *ymin* and *ymax* as
    kwargs, eg.::

      ylim(ymax=3) # adjust the max leaving min unchanged
      ylim(ymin=1) # adjust the min leaving max unchanged

    Setting limits turns autoscaling off for the y-axis.

    The new axis limits are returned as a length 2 tuple.
    """
    ax = gca()
    if not args and not kwargs:
        return ax.get_ylim()
    ret = ax.set_ylim(*args, **kwargs)
    draw_if_interactive()
    return ret


@docstring.dedent_interpd
def xscale(*args, **kwargs):
    """
    call signature::

      xscale(scale, **kwargs)

    Set the scaling for the x-axis: %(scale)s

    Different keywords may be accepted, depending on the scale:

    %(scale_docs)s
    """
    ax = gca()
    ax.set_xscale(*args, **kwargs)
    draw_if_interactive()

@docstring.dedent_interpd
def yscale(*args, **kwargs):
    """
    call signature::

      yscale(scale, **kwargs)

    Set the scaling for the y-axis: %(scale)s

    Different keywords may be accepted, depending on the scale:

    %(scale_docs)s
    """
    ax = gca()
    ax.set_yscale(*args, **kwargs)
    draw_if_interactive()

def xticks(*args, **kwargs):
    """
    Set/Get the xlimits of the current ticklocs and labels::

      # return locs, labels where locs is an array of tick locations and
      # labels is an array of tick labels.
      locs, labels = xticks()

      # set the locations of the xticks
      xticks( arange(6) )

      # set the locations and labels of the xticks
      xticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )

    The keyword args, if any, are :class:`~matplotlib.text.Text`
    properties. For example, to rotate long labels::

      xticks( arange(12), calendar.month_name[1:13], rotation=17 )
    """
    ax = gca()

    if len(args)==0:
        locs = ax.get_xticks()
        labels = ax.get_xticklabels()
    elif len(args)==1:
        locs = ax.set_xticks(args[0])
        labels = ax.get_xticklabels()
    elif len(args)==2:
        locs = ax.set_xticks(args[0])
        labels = ax.set_xticklabels(args[1], **kwargs)
    else: raise TypeError('Illegal number of arguments to xticks')
    if len(kwargs):
        for l in labels:
            l.update(kwargs)

    draw_if_interactive()
    return locs, silent_list('Text xticklabel', labels)

def yticks(*args, **kwargs):
    """
    Set/Get the ylimits of the current ticklocs and labels::

      # return locs, labels where locs is an array of tick locations and
      # labels is an array of tick labels.
      locs, labels = yticks()

      # set the locations of the yticks
      yticks( arange(6) )

      # set the locations and labels of the yticks
      yticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )

    The keyword args, if any, are :class:`~matplotlib.text.Text`
    properties. For example, to rotate long labels::

      yticks( arange(12), calendar.month_name[1:13], rotation=45 )
    """
    ax = gca()

    if len(args)==0:
        locs = ax.get_yticks()
        labels = ax.get_yticklabels()
    elif len(args)==1:
        locs = ax.set_yticks(args[0])
        labels = ax.get_yticklabels()
    elif len(args)==2:
        locs = ax.set_yticks(args[0])
        labels = ax.set_yticklabels(args[1], **kwargs)
    else: raise TypeError('Illegal number of arguments to yticks')
    if len(kwargs):
        for l in labels:
            l.update(kwargs)

    draw_if_interactive()

    return ( locs,
             silent_list('Text yticklabel', labels)
             )

def minorticks_on():
    """
    Display minor ticks on the current plot.

    Displaying minor ticks reduces performance; turn them off using
    minorticks_off() if drawing speed is a problem.
    """
    gca().minorticks_on()
    draw_if_interactive()

def minorticks_off():
    """
    Remove minor ticks from the current plot.
    """
    gca().minorticks_off()
    draw_if_interactive()

def rgrids(*args, **kwargs):
    """
    Set/Get the radial locations of the gridlines and ticklabels on a
    polar plot.

    call signatures::

      lines, labels = rgrids()
      lines, labels = rgrids(radii, labels=None, angle=22.5, **kwargs)

    When called with no arguments, :func:`rgrid` simply returns the
    tuple (*lines*, *labels*), where *lines* is an array of radial
    gridlines (:class:`~matplotlib.lines.Line2D` instances) and
    *labels* is an array of tick labels
    (:class:`~matplotlib.text.Text` instances). When called with
    arguments, the labels will appear at the specified radial
    distances and angles.

    *labels*, if not *None*, is a len(*radii*) list of strings of the
    labels to use at each angle.

    If *labels* is None, the rformatter will be used

    Examples::

      # set the locations of the radial gridlines and labels
      lines, labels = rgrids( (0.25, 0.5, 1.0) )

      # set the locations and labels of the radial gridlines and labels
      lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )

    """
    ax = gca()
    if not isinstance(ax, PolarAxes):
        raise RuntimeError('rgrids only defined for polar axes')
    if len(args)==0:
        lines = ax.yaxis.get_gridlines()
        labels = ax.yaxis.get_ticklabels()
    else:
        lines, labels = ax.set_rgrids(*args, **kwargs)

    draw_if_interactive()
    return ( silent_list('Line2D rgridline', lines),
             silent_list('Text rgridlabel', labels) )

def thetagrids(*args, **kwargs):
    """
    Set/Get the theta locations of the gridlines and ticklabels.

    If no arguments are passed, return a tuple (*lines*, *labels*)
    where *lines* is an array of radial gridlines
    (:class:`~matplotlib.lines.Line2D` instances) and *labels* is an
    array of tick labels (:class:`~matplotlib.text.Text` instances)::

      lines, labels = thetagrids()

    Otherwise the syntax is::

      lines, labels = thetagrids(angles, labels=None, fmt='%d', frac = 1.1)

    set the angles at which to place the theta grids (these gridlines
    are equal along the theta dimension).

    *angles* is in degrees.

    *labels*, if not *None*, is a len(angles) list of strings of the
    labels to use at each angle.

    If *labels* is *None*, the labels will be ``fmt%angle``.

    *frac* is the fraction of the polar axes radius at which to place
    the label (1 is the edge). Eg. 1.05 is outside the axes and 0.95
    is inside the axes.

    Return value is a list of tuples (*lines*, *labels*):

      - *lines* are :class:`~matplotlib.lines.Line2D` instances

      - *labels* are :class:`~matplotlib.text.Text` instances.

    Note that on input, the *labels* argument is a list of strings,
    and on output it is a list of :class:`~matplotlib.text.Text`
    instances.

    Examples::

      # set the locations of the radial gridlines and labels
      lines, labels = thetagrids( range(45,360,90) )

      # set the locations and labels of the radial gridlines and labels
      lines, labels = thetagrids( range(45,360,90), ('NE', 'NW', 'SW','SE') )
    """
    ax = gca()
    if not isinstance(ax, PolarAxes):
        raise RuntimeError('rgrids only defined for polar axes')
    if len(args)==0:
        lines = ax.xaxis.get_ticklines()
        labels = ax.xaxis.get_ticklabels()
    else:
        lines, labels = ax.set_thetagrids(*args, **kwargs)

    draw_if_interactive()
    return (silent_list('Line2D thetagridline', lines),
            silent_list('Text thetagridlabel', labels)
            )


## Plotting Info ##

def plotting():
    """
    Plotting commands

    =============== =========================================================
    Command         Description
    =============== =========================================================
    axes            Create a new axes
    axis            Set or return the current axis limits
    bar             make a bar chart
    boxplot         make a box and whiskers chart
    cla             clear current axes
    clabel          label a contour plot
    clf             clear a figure window
    close           close a figure window
    colorbar        add a colorbar to the current figure
    cohere          make a plot of coherence
    contour         make a contour plot
    contourf        make a filled contour plot
    csd             make a plot of cross spectral density
    draw            force a redraw of the current figure
    errorbar        make an errorbar graph
    figlegend       add a legend to the figure
    figimage        add an image to the figure, w/o resampling
    figtext         add text in figure coords
    figure          create or change active figure
    fill            make filled polygons
    fill_between    make filled polygons between two sets of y-values
    fill_betweenx   make filled polygons between two sets of x-values
    gca             return the current axes
    gcf             return the current figure
    gci             get the current image, or None
    getp            get a graphics property
    hist            make a histogram
    hold            set the hold state on current axes
    legend          add a legend to the axes
    loglog          a log log plot
    imread          load image file into array
    imsave          save array as an image file
    imshow          plot image data
    matshow         display a matrix in a new figure preserving aspect
    pcolor          make a pseudocolor plot
    plot            make a line plot
    plotfile        plot data from a flat file
    psd             make a plot of power spectral density
    quiver          make a direction field (arrows) plot
    rc              control the default params
    savefig         save the current figure
    scatter         make a scatter plot
    setp            set a graphics property
    semilogx        log x axis
    semilogy        log y axis
    show            in non-interactive mode, display all figures and block
                    until they have been closed; in interactive mode,
                    show generally has no effect.
    specgram        a spectrogram plot
    stem            make a stem plot
    subplot         make a subplot (numrows, numcols, axesnum)
    table           add a table to the axes
    text            add some text at location x,y to the current axes
    title           add a title to the current axes
    xlabel          add an xlabel to the current axes
    ylabel          add a ylabel to the current axes
    =============== =========================================================

    The following commands will set the default colormap accordingly:

    * autumn
    * bone
    * cool
    * copper
    * flag
    * gray
    * hot
    * hsv
    * jet
    * pink
    * prism
    * spring
    * summer
    * winter
    * spectral

    """
    pass


def get_plot_commands(): return ( 'axes', 'axis', 'bar', 'boxplot', 'cla', 'clf',
    'close', 'colorbar', 'cohere', 'csd', 'draw', 'errorbar',
    'figlegend', 'figtext', 'figimage', 'figure', 'fill', 'gca',
    'gcf', 'gci', 'get', 'gray', 'barh', 'jet', 'hist', 'hold', 'imread', 'imsave',
    'imshow', 'legend', 'loglog', 'quiver', 'rc', 'pcolor', 'pcolormesh', 'plot', 'psd',
    'savefig', 'scatter', 'set', 'semilogx', 'semilogy', 'show',
    'specgram', 'stem', 'subplot', 'table', 'text', 'title', 'xlabel',
    'ylabel', 'pie', 'polar')

def colors():
    """
    This is a do-nothing function to provide you with help on how
    matplotlib handles colors.

    Commands which take color arguments can use several formats to
    specify the colors.  For the basic builtin colors, you can use a
    single letter

      =====   =======
      Alias   Color
      =====   =======
      'b'     blue
      'g'     green
      'r'     red
      'c'     cyan
      'm'     magenta
      'y'     yellow
      'k'     black
      'w'     white
      =====   =======

    For a greater range of colors, you have two options.  You can
    specify the color using an html hex string, as in::

      color = '#eeefff'

    or you can pass an R,G,B tuple, where each of R,G,B are in the
    range [0,1].

    You can also use any legal html name for a color, for example::

      color = 'red'
      color = 'burlywood'
      color = 'chartreuse'

    The example below creates a subplot with a dark
    slate gray background::

       subplot(111, axisbg=(0.1843, 0.3098, 0.3098))

    Here is an example that creates a pale turqoise title::

      title('Is this the best color?', color='#afeeee')

    """
    pass



def colormaps():
    """
    matplotlib provides the following colormaps.

    * autumn
    * bone
    * cool
    * copper
    * flag
    * gray
    * hot
    * hsv
    * jet
    * pink
    * prism
    * spring
    * summer
    * winter
    * spectral

    You can set the colormap for an image, pcolor, scatter, etc,
    either as a keyword argument::

      imshow(X, cmap=cm.hot)

    or post-hoc using the corresponding pylab interface function::

      imshow(X)
      hot()
      jet()

    In interactive mode, this will update the colormap allowing you to
    see which one works best for your data.
    """
    pass


## Plotting part 1: manually generated functions and wrappers ##

import matplotlib.colorbar
def colorbar(mappable=None, cax=None, ax=None, **kw):
    if mappable is None:
        mappable = gci()
        if mappable is None:
            raise RuntimeError('You must first define an image, eg with imshow')
    if ax is None:
        ax = gca()

    ret = gcf().colorbar(mappable, cax = cax, ax=ax, **kw)
    draw_if_interactive()
    return ret
colorbar.__doc__ = matplotlib.colorbar.colorbar_doc

def clim(vmin=None, vmax=None):
    """
    Set the color limits of the current image

    To apply clim to all axes images do::

      clim(0, 0.5)

    If either *vmin* or *vmax* is None, the image min/max respectively
    will be used for color scaling.

    If you want to set the clim of multiple images,
    use, for example::

      for im in gca().get_images():
          im.set_clim(0, 0.05)

    """
    im = gci()
    if im is None:
        raise RuntimeError('You must first define an image, eg with imshow')

    im.set_clim(vmin, vmax)
    draw_if_interactive()

def set_cmap(cmap):
    '''
    set the default colormap to *cmap* and apply to current image if any.
    See help(colormaps) for more information.

    *cmap* must be a :class:`colors.Colormap` instance, or
    the name of a registered colormap.

    See :func:`register_cmap` and :func:`get_cmap`.
    '''
    cmap = cm.get_cmap(cmap)

    rc('image', cmap=cmap.name)
    im = gci()

    if im is not None:
        im.set_cmap(cmap)
    else:
        raise RuntimeError('You must first define an image, eg with imshow')

    draw_if_interactive()


@docstring.copy_dedent(_imread)
def imread(*args, **kwargs):
    return _imread(*args, **kwargs)

@docstring.copy_dedent(_imsave)
def imsave(*args, **kwargs):
    return _imsave(*args, **kwargs)

def matshow(A, fignum=None, **kw):
    """
    Display an array as a matrix in a new figure window.

    The origin is set at the upper left hand corner and rows (first
    dimension of the array) are displayed horizontally.  The aspect
    ratio of the figure window is that of the array, unless this would
    make an excessively short or narrow figure.

    Tick labels for the xaxis are placed on top.

    With the exception of *fignum*, keyword arguments are passed to
    :func:`~matplotlib.pyplot.imshow`.  You may set the *origin*
    kwarg to "lower" if you want the first row in the array to be
    at the bottom instead of the top.


    *fignum*: [ None | integer | False ]
      By default, :func:`matshow` creates a new figure window with
      automatic numbering.  If *fignum* is given as an integer, the
      created figure will use this figure number.  Because of how
      :func:`matshow` tries to set the figure aspect ratio to be the
      one of the array, if you provide the number of an already
      existing figure, strange things may happen.

      If *fignum* is *False* or 0, a new figure window will **NOT** be created.
    """
    A = np.asanyarray(A)
    if fignum is False or fignum is 0:
        ax = gca()
    else:
        # Extract actual aspect ratio of array and make appropriately sized figure
        fig = figure(fignum, figsize=figaspect(A))
        ax  = fig.add_axes([0.15, 0.09, 0.775, 0.775])

    im = ax.matshow(A, **kw)
    sci(im)

    draw_if_interactive()
    return im

def polar(*args, **kwargs):
    """
    call signature::

      polar(theta, r, **kwargs)

    Make a polar plot.  Multiple *theta*, *r* arguments are supported,
    with format strings, as in :func:`~matplotlib.pyplot.plot`.

    An optional kwarg *resolution* sets the number of vertices to
    interpolate between each pair of points.  The default is 1,
    which disables interpolation.
    """
    resolution = kwargs.pop('resolution', None)
    ax = gca(polar=True, resolution=resolution)
    ret = ax.plot(*args, **kwargs)
    draw_if_interactive()
    return ret

def plotfile(fname, cols=(0,), plotfuncs=None,
             comments='#', skiprows=0, checkrows=5, delimiter=',', names=None,
             subplots=True, newfig=True,
             **kwargs):
    """
    Plot the data in *fname*

    *cols* is a sequence of column identifiers to plot.  An identifier
    is either an int or a string.  If it is an int, it indicates the
    column number.  If it is a string, it indicates the column header.
    matplotlib will make column headers lower case, replace spaces with
    underscores, and remove all illegal characters; so ``'Adj Close*'``
    will have name ``'adj_close'``.

    - If len(*cols*) == 1, only that column will be plotted on the *y* axis.

    - If len(*cols*) > 1, the first element will be an identifier for
      data for the *x* axis and the remaining elements will be the
      column indexes for multiple subplots if *subplots* is *True*
      (the default), or for lines in a single subplot if *subplots*
      is *False*.

    *plotfuncs*, if not *None*, is a dictionary mapping identifier to
    an :class:`~matplotlib.axes.Axes` plotting function as a string.
    Default is 'plot', other choices are 'semilogy', 'fill', 'bar',
    etc.  You must use the same type of identifier in the *cols*
    vector as you use in the *plotfuncs* dictionary, eg., integer
    column numbers in both or column names in both. If *subplots*
    is *False*, then including any function such as 'semilogy'
    that changes the axis scaling will set the scaling for all
    columns.

    *comments*, *skiprows*, *checkrows*, *delimiter*, and *names*
    are all passed on to :func:`matplotlib.pylab.csv2rec` to
    load the data into a record array.

    If *newfig* is *True*, the plot always will be made in a new figure;
    if *False*, it will be made in the current figure if one exists,
    else in a new figure.

    kwargs are passed on to plotting functions.

    Example usage::

      # plot the 2nd and 4th column against the 1st in two subplots
      plotfile(fname, (0,1,3))

      # plot using column names; specify an alternate plot type for volume
      plotfile(fname, ('date', 'volume', 'adj_close'),
                                    plotfuncs={'volume': 'semilogy'})

    Note: plotfile is intended as a convenience for quickly plotting
    data from flat files; it is not intended as an alternative
    interface to general plotting with pyplot or matplotlib.
    """

    if newfig:
        fig = figure()
    else:
        fig = gcf()

    if len(cols)<1:
        raise ValueError('must have at least one column of data')

    if plotfuncs is None:
        plotfuncs = dict()
    r = mlab.csv2rec(fname, comments=comments, skiprows=skiprows,
                     checkrows=checkrows, delimiter=delimiter, names=names)

    def getname_val(identifier):
        'return the name and column data for identifier'
        if is_string_like(identifier):
            return identifier, r[identifier]
        elif is_numlike(identifier):
            name = r.dtype.names[int(identifier)]
            return name, r[name]
        else:
            raise TypeError('identifier must be a string or integer')

    xname, x = getname_val(cols[0])
    ynamelist = []

    if len(cols)==1:
        ax1 = fig.add_subplot(1,1,1)
        funcname = plotfuncs.get(cols[0], 'plot')
        func = getattr(ax1, funcname)
        func(x, **kwargs)
        ax1.set_ylabel(xname)
    else:
        N = len(cols)
        for i in range(1,N):
            if subplots:
                if i==1:
                    ax = ax1 = fig.add_subplot(N-1,1,i)
                else:
                    ax = fig.add_subplot(N-1,1,i, sharex=ax1)
            elif i==1:
                ax = fig.add_subplot(1,1,1)

            ax.grid(True)


            yname, y = getname_val(cols[i])
            ynamelist.append(yname)

            funcname = plotfuncs.get(cols[i], 'plot')
            func = getattr(ax, funcname)

            func(x, y, **kwargs)
            if subplots:
                ax.set_ylabel(yname)
            if ax.is_last_row():
                ax.set_xlabel(xname)
            else:
                ax.set_xlabel('')

    if not subplots:
        ax.legend(ynamelist, loc='best')

    if xname=='date':
        fig.autofmt_xdate()

    draw_if_interactive()


def autogen_docstring(base):
    """Autogenerated wrappers will get their docstring from a base function
    with an addendum."""
    msg = "\n\nAdditional kwargs: hold = [True|False] overrides default hold state"
    addendum = docstring.Appender(msg, '\n\n')
    return lambda func: addendum(docstring.copy_dedent(base)(func))


# This function cannot be generated by boilerplate.py because it may
# return an image or a line.
@autogen_docstring(Axes.spy)
def spy(Z, precision=0, marker=None, markersize=None, aspect='equal', hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.spy(Z, precision, marker, markersize, aspect, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    if isinstance(ret, cm.ScalarMappable):
        sci(ret)
    return ret


## Plotting part 2: autogenerated wrappers for axes methods ##

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.acorr)
def acorr(x, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.acorr(x, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.arrow)
def arrow(x, y, dx, dy, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.arrow(x, y, dx, dy, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.axhline)
def axhline(y=0, xmin=0, xmax=1, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.axhline(y, xmin, xmax, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.axhspan)
def axhspan(ymin, ymax, xmin=0, xmax=1, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.axhspan(ymin, ymax, xmin, xmax, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.axvline)
def axvline(x=0, ymin=0, ymax=1, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.axvline(x, ymin, ymax, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.axvspan)
def axvspan(xmin, xmax, ymin=0, ymax=1, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.axvspan(xmin, xmax, ymin, ymax, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.bar)
def bar(left, height, width=0.80000000000000004, bottom=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.bar(left, height, width, bottom, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.barh)
def barh(bottom, width, height=0.80000000000000004, left=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.barh(bottom, width, height, left, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.broken_barh)
def broken_barh(xranges, yrange, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.broken_barh(xranges, yrange, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.boxplot)
def boxplot(x, notch=0, sym='b+', vert=1, whis=1.5, positions=None, widths=None, patch_artist=False, bootstrap=None, hold=None):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.boxplot(x, notch, sym, vert, whis, positions, widths, patch_artist, bootstrap)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.cohere)
def cohere(x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none, window=mlab.window_hanning, noverlap=0, pad_to=None, sides='default', scale_by_freq=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.cohere(x, y, NFFT, Fs, Fc, detrend, window, noverlap, pad_to, sides, scale_by_freq, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.clabel)
def clabel(CS, *args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.clabel(CS, *args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.contour)
def contour(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.contour(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    if ret._A is not None: sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.contourf)
def contourf(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.contourf(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    if ret._A is not None: sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.csd)
def csd(x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none, window=mlab.window_hanning, noverlap=0, pad_to=None, sides='default', scale_by_freq=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.csd(x, y, NFFT, Fs, Fc, detrend, window, noverlap, pad_to, sides, scale_by_freq, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.errorbar)
def errorbar(x, y, yerr=None, xerr=None, fmt='-', ecolor=None, elinewidth=None, capsize=3, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.errorbar(x, y, yerr, xerr, fmt, ecolor, elinewidth, capsize, barsabove, lolims, uplims, xlolims, xuplims, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.fill)
def fill(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.fill(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.fill_between)
def fill_between(x, y1, y2=0, where=None, interpolate=False, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.fill_between(x, y1, y2, where, interpolate, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.fill_betweenx)
def fill_betweenx(y, x1, x2=0, where=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.fill_betweenx(y, x1, x2, where, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.hexbin)
def hexbin(x, y, C=None, gridsize=100, bins=None, xscale='linear', yscale='linear', extent=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, edgecolors='none', reduce_C_function=np.mean, mincnt=None, marginals=False, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.hexbin(x, y, C, gridsize, bins, xscale, yscale, extent, cmap, norm, vmin, vmax, alpha, linewidths, edgecolors, reduce_C_function, mincnt, marginals, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.hist)
def hist(x, bins=10, range=None, normed=False, weights=None, cumulative=False, bottom=None, histtype='bar', align='mid', orientation='vertical', rwidth=None, log=False, color=None, label=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.hist(x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.hlines)
def hlines(y, xmin, xmax, colors='k', linestyles='solid', label='', hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.hlines(y, xmin, xmax, colors, linestyles, label, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.imshow)
def imshow(X, cmap=None, norm=None, aspect=None, interpolation=None, alpha=None, vmin=None, vmax=None, origin=None, extent=None, shape=None, filternorm=1, filterrad=4.0, imlim=None, resample=None, url=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.imshow(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.loglog)
def loglog(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.loglog(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.pcolor)
def pcolor(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.pcolor(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.pcolormesh)
def pcolormesh(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.pcolormesh(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.pie)
def pie(x, explode=None, labels=None, colors=None, autopct=None, pctdistance=0.59999999999999998, shadow=False, labeldistance=1.1000000000000001, hold=None):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.pie(x, explode, labels, colors, autopct, pctdistance, shadow, labeldistance)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.plot)
def plot(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.plot(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.plot_date)
def plot_date(x, y, fmt='bo', tz=None, xdate=True, ydate=False, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.plot_date(x, y, fmt, tz, xdate, ydate, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.psd)
def psd(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none, window=mlab.window_hanning, noverlap=0, pad_to=None, sides='default', scale_by_freq=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.psd(x, NFFT, Fs, Fc, detrend, window, noverlap, pad_to, sides, scale_by_freq, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.quiver)
def quiver(*args, **kw):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kw.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.quiver(*args, **kw)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.quiverkey)
def quiverkey(*args, **kw):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kw.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.quiverkey(*args, **kw)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.scatter)
def scatter(x, y, s=20, c='b', marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, faceted=True, verts=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.scatter(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, faceted, verts, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.semilogx)
def semilogx(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.semilogx(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.semilogy)
def semilogy(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.semilogy(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.specgram)
def specgram(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none, window=mlab.window_hanning, noverlap=128, cmap=None, xextent=None, pad_to=None, sides='default', scale_by_freq=None, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.specgram(x, NFFT, Fs, Fc, detrend, window, noverlap, cmap, xextent, pad_to, sides, scale_by_freq, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret[-1])
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.stem)
def stem(x, y, linefmt='b-', markerfmt='bo', basefmt='r-', hold=None):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.stem(x, y, linefmt, markerfmt, basefmt)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.step)
def step(x, y, *args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.step(x, y, *args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.tricontour)
def tricontour(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.tricontour(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    if ret._A is not None: sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.tricontourf)
def tricontourf(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.tricontourf(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    if ret._A is not None: sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.tripcolor)
def tripcolor(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.tripcolor(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.triplot)
def triplot(*args, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kwargs.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.triplot(*args, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.vlines)
def vlines(x, ymin, ymax, colors='k', linestyles='solid', label='', hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.vlines(x, ymin, ymax, colors, linestyles, label, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.xcorr)
def xcorr(x, y, normed=True, detrend=mlab.detrend_none, usevlines=True, maxlags=10, hold=None, **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.xcorr(x, y, normed, detrend, usevlines, maxlags, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@autogen_docstring(Axes.barbs)
def barbs(*args, **kw):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()
    hold = kw.pop('hold', None)
    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.barbs(*args, **kw)
        draw_if_interactive()
    finally:
        ax.hold(washold)

    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.cla)
def cla():
    ret =  gca().cla()
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.grid)
def grid(b=None, which='major', axis='both', **kwargs):
    ret =  gca().grid(b, which, axis, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.legend)
def legend(*args, **kwargs):
    ret =  gca().legend(*args, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.table)
def table(**kwargs):
    ret =  gca().table(**kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.text)
def text(x, y, s, fontdict=None, withdash=False, **kwargs):
    ret =  gca().text(x, y, s, fontdict, withdash, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.annotate)
def annotate(*args, **kwargs):
    ret =  gca().annotate(*args, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.ticklabel_format)
def ticklabel_format(**kwargs):
    ret =  gca().ticklabel_format(**kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.locator_params)
def locator_params(axis='both', tight=None, **kwargs):
    ret =  gca().locator_params(axis, tight, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.tick_params)
def tick_params(axis='both', **kwargs):
    ret =  gca().tick_params(axis, **kwargs)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.margins)
def margins(*args, **kw):
    ret =  gca().margins(*args, **kw)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
@docstring.copy_dedent(Axes.autoscale)
def autoscale(enable=True, axis='both', tight=None):
    ret =  gca().autoscale(enable, axis, tight)
    draw_if_interactive()
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def autumn():
    '''
    set the default colormap to autumn and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='autumn')
    im = gci()

    if im is not None:
        im.set_cmap(cm.autumn)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def bone():
    '''
    set the default colormap to bone and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='bone')
    im = gci()

    if im is not None:
        im.set_cmap(cm.bone)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def cool():
    '''
    set the default colormap to cool and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='cool')
    im = gci()

    if im is not None:
        im.set_cmap(cm.cool)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def copper():
    '''
    set the default colormap to copper and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='copper')
    im = gci()

    if im is not None:
        im.set_cmap(cm.copper)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def flag():
    '''
    set the default colormap to flag and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='flag')
    im = gci()

    if im is not None:
        im.set_cmap(cm.flag)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def gray():
    '''
    set the default colormap to gray and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='gray')
    im = gci()

    if im is not None:
        im.set_cmap(cm.gray)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def hot():
    '''
    set the default colormap to hot and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='hot')
    im = gci()

    if im is not None:
        im.set_cmap(cm.hot)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def hsv():
    '''
    set the default colormap to hsv and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='hsv')
    im = gci()

    if im is not None:
        im.set_cmap(cm.hsv)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def jet():
    '''
    set the default colormap to jet and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='jet')
    im = gci()

    if im is not None:
        im.set_cmap(cm.jet)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def pink():
    '''
    set the default colormap to pink and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='pink')
    im = gci()

    if im is not None:
        im.set_cmap(cm.pink)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def prism():
    '''
    set the default colormap to prism and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='prism')
    im = gci()

    if im is not None:
        im.set_cmap(cm.prism)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def spring():
    '''
    set the default colormap to spring and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='spring')
    im = gci()

    if im is not None:
        im.set_cmap(cm.spring)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def summer():
    '''
    set the default colormap to summer and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='summer')
    im = gci()

    if im is not None:
        im.set_cmap(cm.summer)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def winter():
    '''
    set the default colormap to winter and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='winter')
    im = gci()

    if im is not None:
        im.set_cmap(cm.winter)
    draw_if_interactive()


# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost
def spectral():
    '''
    set the default colormap to spectral and apply to current image if any.
    See help(colormaps) for more information
    '''
    rc('image', cmap='spectral')
    im = gci()

    if im is not None:
        im.set_cmap(cm.spectral)
    draw_if_interactive()


