Data Visualization (astropy.visualization)

Introduction

astropy.visualization provides functionality that can be helpful when visualizing data. At the moment, functionalities include enhanced histograms, image normalizing (including both scaling and stretching), and custom plotting styles for matplotlib.

Using astropy.visualization

• Image stretching and normalization
  • Intervals and Normalization
  • Stretching
  • Combining transformations
  • Matplotlib normalization
• Choosing Histogram Bins
  • Normal Reference Rules
  • Bayesian Models

Scripts

This module includes a command-line script, fits2bitmap to convert FITS images to bitmaps, including scaling and stretching of the image. To find out more about the available options and how to use it, type:

$ fits2bitmap --help

Reference/API

astropy.visualization.mpl_style Module

astropy.visualization Package

Functions

hist(x[, bins, ax])	Enhanced histogram function
quantity_support([format])	Enable support for plotting astropy.units.Quantity instances in matplotlib.
scale_image(image[, scale, power, asinh_a, ...])	Perform scaling/stretching of an image between minimum and maximum cut levels.

Classes

AsinhStretch	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], return an transformed array of values, also in the range [0:1].
BaseTransform	A transformation object.
CompositeTransform(transform_1, transform_2)	A combination of two transforms.
ContrastBiasStretch	A stretch that takes into account contrast and bias.
HistEqStretch	A histogram equalization stretch.
LinearStretch	A linear stretch.
LogStretch	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	An alternative power stretch.
PowerStretch	A power stretch.
SinhStretch	A sinh stretch.
SqrtStretch	A square root stretch.
SquaredStretch	A convenience class for a power stretch of 2.

Class Inheritance Diagram

astropy.visualization.mpl_normalize Module

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

Classes

ImageNormalize([vmin, vmax, stretch, clip])

Normalization class to be used with Matplotlib.

Class Inheritance Diagram