Python Axes.imshow方法代碼示例

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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() 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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=cmap, norm=norm, aspect=aspect,
                        interpolation=interpolation, alpha=alpha, vmin=vmin,
                        vmax=vmax, origin=origin, extent=extent, shape=shape,
                        filternorm=filternorm, filterrad=filterrad,
                        imlim=imlim, resample=resample, url=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 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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, e.g., with imshow')

    im.set_clim(vmin, vmax)
    draw_if_interactive() 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def gci():
    """
    Get the current colorable artist.  Specifically, returns the
    current :class:`~matplotlib.cm.ScalarMappable` instance (image or
    patch collection), or *None* if no images or patch collections
    have been defined.  The commands :func:`~matplotlib.pyplot.imshow`
    and :func:`~matplotlib.pyplot.figimage` create
    :class:`~matplotlib.image.Image` instances, and the commands
    :func:`~matplotlib.pyplot.pcolor` and
    :func:`~matplotlib.pyplot.scatter` create
    :class:`~matplotlib.collections.Collection` instances.  The
    current image is an attribute of the current axes, or the nearest
    earlier axes in the current figure that contains an image.
    """
    return gcf()._gci()


## Any Artist ##


# (getp is simply imported) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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, e.g., with imshow')

    im.set_clim(vmin, vmax) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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, *, data=None, **kwargs):
    __ret = gca().imshow(
        X, cmap=cmap, norm=norm, aspect=aspect,
        interpolation=interpolation, alpha=alpha, vmin=vmin,
        vmax=vmax, origin=origin, extent=extent, shape=shape,
        filternorm=filternorm, filterrad=filterrad, imlim=imlim,
        resample=resample, url=url, **({"data": data} if data is not
        None else {}), **kwargs)
    sci(__ret)
    return __ret


# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def clim(vmin=None, vmax=None):
    """
    Set the color limits of the current image.

    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
    `~.ScalarMappable.set_clim` on every image, for example::

      for im in gca().get_images():
          im.set_clim(0, 0.5)

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

    im.set_clim(vmin, vmax) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def imshow(
        X, cmap=None, norm=None, aspect=None, interpolation=None,
        alpha=None, vmin=None, vmax=None, origin=None, extent=None,
        shape=cbook.deprecation._deprecated_parameter, filternorm=1,
        filterrad=4.0, imlim=cbook.deprecation._deprecated_parameter,
        resample=None, url=None, *, data=None, **kwargs):
    __ret = gca().imshow(
        X, cmap=cmap, norm=norm, aspect=aspect,
        interpolation=interpolation, alpha=alpha, vmin=vmin,
        vmax=vmax, origin=origin, extent=extent, shape=shape,
        filternorm=filternorm, filterrad=filterrad, imlim=imlim,
        resample=resample, url=url, **({"data": data} if data is not
        None else {}), **kwargs)
    sci(__ret)
    return __ret


# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def gci():
    """
    Get the current colorable artist.  Specifically, returns the
    current :class:`~matplotlib.cm.ScalarMappable` instance (image or
    patch collection), or *None* if no images or patch collections
    have been defined.  The commands :func:`~matplotlib.pyplot.imshow`
    and :func:`~matplotlib.pyplot.figimage` create
    :class:`~matplotlib.image.Image` instances, and the commands
    :func:`~matplotlib.pyplot.pcolor` and
    :func:`~matplotlib.pyplot.scatter` create
    :class:`~matplotlib.collections.Collection` instances.  The
    current image is an attribute of the current axes, or the nearest
    earlier axes in the current figure that contains an image.
    """
    return gcf()._gci() 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def colorbar(mappable=None, cax=None, ax=None, **kw):
    if mappable is None:
        mappable = gci()
        if mappable is None:
            raise RuntimeError('No mappable was found to use for colorbar '
                               'creation. First define a mappable such as '
                               'an image (with imshow) or a contour set ('
                               'with contourf).')
    if ax is None:
        ax = gca()

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

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
def colorbar(mappable=None, cax=None, ax=None, **kw):
    if mappable is None:
        mappable = gci()
        if mappable is None:
            raise RuntimeError('No mappable was found to use for colorbar '
                               'creation. First define a mappable such as '
                               'an image (with imshow) or a contour set ('
                               'with contourf).')
    if ax is None:
        ax = gca()

    ret = gcf().colorbar(mappable, cax = cax, ax=ax, **kw)
    return ret 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import imshow [as 別名]
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, *, data=None, **kwargs):
    __ret = gca().imshow(
        X=X, cmap=cmap, norm=norm, aspect=aspect,
        interpolation=interpolation, alpha=alpha, vmin=vmin,
        vmax=vmax, origin=origin, extent=extent, shape=shape,
        filternorm=filternorm, filterrad=filterrad, imlim=imlim,
        resample=resample, url=url, data=data, **kwargs)
    sci(__ret)
    return __ret

# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.