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 ...