ImageNormalize

class astropy.visualization.ImageNormalize(data=None, interval=None, vmin=None, vmax=None, stretch=<astropy.visualization.stretch.LinearStretch object>, clip=True)

Bases: matplotlib.colors.Normalize

Normalization class to be used with Matplotlib.

Parameters:

data : ndarray, optional

The image array. This input is used only if interval is also input. data and interval are used to compute the vmin and/or vmax values only if vmin or vmax are not input.

interval : BaseInterval subclass instance, optional

The interval object to apply to the input data to determine the vmin and vmax values. This input is used only if data is also input. data and interval are used to compute the vmin and/or vmax values only if vmin or vmax are not input.

vmin, vmax : float

The minimum and maximum levels to show for the data. The vmin and vmax inputs override any calculated values from the interval and data inputs.

stretch : BaseStretch subclass instance, optional

The stretch object to apply to the data. The default is LinearStretch.

clip : bool, optional

If True (default), data values outside the [0:1] range are clipped to the [0:1] range.

Methods Summary

__call__(values[, clip])	Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it.
inverse(values)

Methods Documentation

__call__(values, clip=None)

Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. clip defaults to self.clip (which defaults to False). If not already initialized, vmin and vmax are initialized using autoscale_None(value).

inverse(values)