Reproducing SAOImageDS9 Colormap in Python

SAOImageDS9 is an image display and visualization tool for astronomical data, which can be used for fast image processing and inspection. In DS9, we can drag the mouse on the image viewer to manipulate the colormap and then visualize data effectively and quickly. Unlike the DS9, color normalization and stretch in Python should be set manually.

Here we take notes about how to reproduce the colormap of DS9 in Python, supposing that you have already tuned the colormap parameters in DS9.

Installation

pip install astromy_ds9

Usage

from astromy_ds9 import ds9_norm


import astropy
import matplotlib.pyplot as plt
data = astropy.io.fits.getdata('https://github.com/lmytime/Reproduce_DS9_colormap_in_Python/raw/main/doc/data/m51.fits')

norm = ds9_norm(vmin=3053.38, vmax=13513.9, bias=0.581921, contrast=0.890152, stretch='sqrt')
plt.imshow(data, norm=norm, cmap='gray', origin='lower', interpolation='None')

There are 5 input parameters for ds9_norm function.

• vmin and vmax: you can find the values in Scale -> Scale Parameters -> Below the histogram, Low is vmin and High is vmax.
• bias and contrast: you can find the values in Color -> Color Parameters
• stretch: you can find it in Scale -> see which one is marked with a check mark. Allowed values are 'linear' | 'log' | 'sqrt' | 'power' | 'squared' | 'asinh' | 'sinh'.

Check example code in test and example.

Methodology

Please check the methodology in doc. Also see ds9norm for reference.

Citation

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