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 up to 3 images using an asinh stretch.

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(...[, n_samples])

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.

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.

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#

Inheritance diagram of astropy.visualization.stretch.AsinhStretch, astropy.visualization.interval.AsymmetricPercentileInterval, astropy.visualization.interval.BaseInterval, astropy.visualization.stretch.BaseStretch, astropy.visualization.transform.BaseTransform, astropy.visualization.stretch.CompositeStretch, astropy.visualization.transform.CompositeTransform, astropy.visualization.stretch.ContrastBiasStretch, astropy.visualization.stretch.HistEqStretch, astropy.visualization.mpl_normalize.ImageNormalize, astropy.visualization.stretch.LinearStretch, astropy.visualization.stretch.LogStretch, astropy.visualization.interval.ManualInterval, astropy.visualization.interval.MinMaxInterval, astropy.visualization.interval.PercentileInterval, astropy.visualization.stretch.PowerDistStretch, astropy.visualization.stretch.PowerStretch, astropy.visualization.stretch.SinhStretch, astropy.visualization.stretch.SqrtStretch, astropy.visualization.stretch.SquaredStretch, astropy.visualization.interval.ZScaleInterval

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.

Class Inheritance Diagram#

Inheritance diagram of astropy.visualization.mpl_normalize.ImageNormalize