JS9 brings image display right into your browser:
- display URL-based FITS images and binary tables - drag and drop FITS images and binary tables - change the colormap and scale - manipulate the contrast/bias with the mouse - display pixel values and WCS position information - create and manipulate geometric regions of interest - add your own extensions using plugins and the Public API - perform data analysis (local and server-side) - display RGB composite images - control JS9 from the command line - print images - more to come!
See: http://js9.si.edu for more information about JS9.
pyjs9.py connects python and JS9 via the js9Helper.js back-end server:
- The JS9 class constructor connects to a single JS9 instance in a Web page. - The JS9 object supports the JS9 Public API and a shorter command-line syntax. - See: http://js9.si.edu/js9/help/publicapi.html for info about the public api - Send/retrieve numpy arrays and astropy (or pyfits) hdulists to/from js9.
Requirements: pyjs9 utilizes the urllib module to communicate with a JS9 back-end Node server (which communicates with the browser itself). The JS9 back-end server must be version 1.2 or higher.
Install using setup.py, as usual:
> python setup.py install
To run:
> python
... (startup messages) ...
>>> from pyjs9 import *
>>> dir()
['JS9', ..., 'js9Globals']
>>>
>>> j = JS9()
>>>
>>> j.SetColormap('red')
>>> j.GetColormap('red')
{'bias': 0.5, 'colormap': 'red', 'contrast': 1}
>>> j.cmap()
'cool 1 0.5'
>>>
>>> hdul = j.GetFITS()
>>> hdul.info()
Filename: (No file associated with this HDUList)
No. Name Type Cards Dimensions Format
0 PRIMARY PrimaryHDU 6 (1025, 1025) int32
>>>
>>> narr = j.GetNumpy()
>>> narr.shape
(1025, 1025)
Or, if you have relatively fast internet connectivity, try the JS9 Web page:
> python
... (startup messages) ...
>>> from pyjs9 import *
>>> dir()
['JS9', ..., 'js9Globals']
>>>
>>> j = JS9('js9.si.edu')
>>> etc ...