Reference/API

astropy.visualization Package

Functions

hist(x[, bins, ax, max_bins])	Enhanced histogram function.
imshow_norm(data[, ax])	A convenience function to call matplotlib's matplotlib.pyplot.imshow function, using an ImageNormalize object as the normalization.
make_lupton_rgb(image_r, image_g, image_b[, ...])	Return a Red/Green/Blue color image from 3 images using interconnected band scaling, and an arbitrary stretch function (by default, an asinh stretch).
make_rgb(image_r, image_g, image_b[, ...])	Base class to return a Red/Green/Blue color image from 3 images using a specified stretch and interval, for each band independently.
quantity_support([format])	Enable support for plotting astropy.units.Quantity instances in matplotlib.
simple_norm(data[, stretch, power, asinh_a, ...])	Return a Normalization class that can be used for displaying images with Matplotlib.
time_support(*[, scale, format, simplify])	Enable support for plotting astropy.time.Time instances in matplotlib.

Classes

AsinhStretch([a])	An asinh stretch.
AsymmetricPercentileInterval([...])	Interval based on a keeping a specified fraction of pixels (can be asymmetric).
BaseInterval()	Base class for the interval classes, which, when called with an array of values, return an interval computed following different algorithms.
BaseStretch()	Base class for the stretch classes, which when called with an array of values in the range [0:1], returns an transformed array of values also in the range [0:1].
BaseTransform()	A transformation object.
CompositeStretch(transform_1, transform_2)	A combination of two stretches.
CompositeTransform(transform_1, transform_2)	A combination of two transforms.
ContrastBiasStretch(contrast, bias)	A stretch that takes into account contrast and bias.
HistEqStretch(data[, values])	A histogram equalization stretch.
ImageNormalize([data, interval, vmin, vmax, ...])	Normalization class to be used with Matplotlib.
LinearStretch([slope, intercept])	A linear stretch with a slope and offset.
LogStretch([a])	A log stretch.
LuptonAsinhStretch([stretch, Q])	A modified asinh stretch, with some changes to the constants relative to AsinhStretch.
LuptonAsinhZscaleStretch(image[, Q, pedestal])	A modified asinh stretch, where the linear stretch is calculated using zscale.
ManualInterval([vmin, vmax])	Interval based on user-specified values.
MinMaxInterval()	Interval based on the minimum and maximum values in the data.
PercentileInterval(percentile[, n_samples])	Interval based on a keeping a specified fraction of pixels.
PowerDistStretch([a])	An alternative power stretch.
PowerStretch(a)	A power stretch.
SimpleNorm([stretch, percent, min_percent, ...])	Class to create a normalization object that can be used for displaying images with Matplotlib.
SinhStretch([a])	A sinh stretch.
SqrtStretch()	A square root stretch.
SquaredStretch()	A convenience class for a power stretch of 2.
ZScaleInterval([n_samples, contrast, ...])	Interval based on IRAF's zscale.

Class Inheritance Diagram

astropy.visualization.mpl_normalize Module

Normalization class for Matplotlib that can be used to produce colorbars.

Functions

simple_norm(data[, stretch, power, asinh_a, ...])	Return a Normalization class that can be used for displaying images with Matplotlib.
imshow_norm(data[, ax])	A convenience function to call matplotlib's matplotlib.pyplot.imshow function, using an ImageNormalize object as the normalization.

Classes

ImageNormalize([data, interval, vmin, vmax, ...])	Normalization class to be used with Matplotlib.
SimpleNorm([stretch, percent, min_percent, ...])	Class to create a normalization object that can be used for displaying images with Matplotlib.

Class Inheritance Diagram