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
- much more ...

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 communicates with a JS9 back-end Node server (which communicates with the browser itself). By default, pyjs9 utilizes the requests <http://www.python-requests.org/en/latest/> module to communicate with the JS9 back-end server. However, if you install socketIO_client <https://pypi.python.org/pypi/socketIO-client>, pyjs9 will use the faster, persistent socket.io http://socket.io/ protocol.

Install from the repository using pip, as usual:

> pip install git+https://github.com/ericmandel/pyjs9.git#egg=pyjs9

or from a local copy:

> pip install /path/to/local/copy

Mandatory dependencies:

six
requests

Optional dependencies:

numpy               # support for GetNumpy and SetNumpy methods
astropy             # support for GetFITS and SetFITS methods
socketIO-client     # fast, persistent socket.io protocol, instead of html

To run:

> # ensure JS9 node-server is running ...
> # visit your local JS9 Web page in your browser ...
> python
... (startup messages) ...
>>> import pyjs9
>>>
>>> j = pyjs9.JS9()        # default: connect to 'http://localhost'
>>>
>>> j.GetColormap()
{'bias': 0.5, 'colormap': 'grey', 'contrast': 1}
>>> j.SetColormap('red')
>>> j.cmap()
'red 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   (1024, 1024)   int32
>>>
>>> narr = j.GetNumpy()
>>> narr.shape
(1024, 1024)

If you have internet connectivity, visit the JS9 Web page at http://js9.si.edu with your browser and:

> python
... (startup messages) ...
>>> import pyjs9
>>>
>>> j = pyjs9.JS9('js9.si.edu')        # connect to JS9 Web site
>>>
>>> j.GetColormap()
{'bias': 0.5, 'colormap': 'grey', 'contrast': 1}
>>>
>>> # etc ...