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# Data Visualization (`astropy.visualization`)

## Introduction

`astropy.visualization` provides functionality that can be helpful when visualizing data. This includes a framework for plotting Astronomical images with coordinates with Matplotlib (previously the standalone wcsaxes package), functionality related to image normalization (including both scaling and stretching), smart histogram plotting, RGB color image creation from separate images, and custom plotting styles for Matplotlib.

## Using `astropy.visualization`

- Plotting Astropy objects in Matplotlib
  - Plotting quantities
  - Plotting times
- Making plots with world coordinates (WCSAxes)
  - Getting started
  - Using WCSAxes
  - Reference/API
- Image stretching and normalization
  - Intervals and Normalization
  - Stretching
  - Combining transformations
  - Matplotlib normalization
  - Combining stretches and Matplotlib normalization
- Choosing Histogram Bins
  - Normal Reference Rules
  - Bayesian Models
- Creating color RGB images
  - RGB images using the Lupton et al (2004) scheme
  - RGB images using arbitrary stretching

## 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

- Reference/API
  - astropy.visualization Package
  - astropy.visualization.mpl_normalize Module