ds9norm 0.1

ds9norm
=======

This file implements a matplotlib Normalize object which mimics the
functionality of image scaling functions in
`ds9 <http://ds9.si.edu/site/Home.html>`__. It provides 5 ways of
configuring image scaling:

- Clipping the low and high intensities at specified percentiles
(``clip_lo``, ``clip_hi``)
- Specifying an intensity transfer function for ramping from black to
white (``stretch``)
- Setting the mid-point of this transfer function (``bias``, akin to
dragging the right mouse button left/right in ds9)
- Setting how sharp the transition from black-white is (``contrast``,
akin to dragging the right mouse button up/down in ds9)

Examples
--------

See the `example
notebook <http://nbviewer.ipython.org/github/glue-viz/ds9norm/blob/master/Examples.ipynb>`__

.. code:: python


data = fits.getdata('M51.fits')
norm = DS9Normalize(bias=0.2)
figure, axs = plt.subplots(ncols=3, nrows=3, squeeze=False, tight_layout=True)

for ax, bias in zip(axs[2], [.2, .5, .8]):
ax.imshow(data, norm=DS9Normalize(bias=bias))
ax.set_title('Bias = %0.1f' % bias)

for ax, contrast in zip(axs[1], [0.5, 1, 2]):
ax.imshow(data, norm=DS9Normalize(contrast=contrast))
ax.set_title('Contrast = %0.1f' % contrast)

for ax, stretch in zip(axs[0], ['linear', 'sqrt', 'arcsinh']):
ax.imshow(data, norm=DS9Normalize(stretch=stretch))
ax.set_title(stretch)

.. figure:: gallery.png
:alt: ds9norm demo

ds9norm demo
Build Status
------------

[|Build Status|\ ]
(https://travis-ci.org/glue-viz/ds9norm?branch=master) [|Coverage
Status|\ ] (https://coveralls.io/r/glue-viz/ds9norm)

.. |Build Status| image:: https://travis-ci.org/glue-viz/ds9norm.png
.. |Coverage Status| image:: https://coveralls.io/repos/glue-viz/ds9norm/badge.png