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# 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

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

### 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