simple_norm

astropy.visualization.simple_norm(data, stretch='linear', power=1.0, asinh_a=0.1, min_cut=None, max_cut=None, min_percent=None, max_percent=None, percent=None, clip=True)[source] [edit on github]

Return a Normalization class that can be used for displaying images with Matplotlib.

This function enables only a subset of image stretching functions available in ImageNormalize.

This function is used by the astropy.visualization.scripts.fits2bitmap script.

Parameters:
data : ndarray

The image array.

stretch : {‘linear’, ‘sqrt’, ‘power’, log’, ‘asinh’}, optional

The stretch function to apply to the image. The default is ‘linear’.

power : float, optional

The power index for stretch='power'. The default is 1.0.

asinh_a : float, optional

For stretch='asinh', the value where the asinh curve transitions from linear to logarithmic behavior, expressed as a fraction of the normalized image. Must be in the range between 0 and 1. The default is 0.1.

min_cut : float, optional

The pixel value of the minimum cut level. Data values less than min_cut will set to min_cut before stretching the image. The default is the image minimum. min_cut overrides min_percent.

max_cut : float, optional

The pixel value of the maximum cut level. Data values greater than min_cut will set to min_cut before stretching the image. The default is the image maximum. max_cut overrides max_percent.

min_percent : float, optional

The percentile value used to determine the pixel value of minimum cut level. The default is 0.0. min_percent overrides percent.

max_percent : float, optional

The percentile value used to determine the pixel value of maximum cut level. The default is 100.0. max_percent overrides percent.

percent : float, optional

The percentage of the image values used to determine the pixel values of the minimum and maximum cut levels. The lower cut level will set at the (100 - percent) / 2 percentile, while the upper cut level will be set at the (100 + percent) / 2 percentile. The default is 100.0. percent is ignored if either min_percent or max_percent is input.

clip : bool, optional

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

An ImageNormalize instance that can be used for displaying images with Matplotlib.