Skip to the navigation links
Last modified: 8 December 2023


Visualizing data in CIAO

CIAO provides several means of visualizing your data, including

SAOImage DS9

CIAO 4.16 comes with version 8.5 of SAOImage DS9, which can be used to visualize images, event files, and even tabular data.

Recent changes have greatly improved the capabilities of the dax analysis menu, which lets you run a number of CIAO tasks from the DS9 analysis menu. These include tasks such as spectral extraction and then analysis (fitting a simple spectral model), or point-source photometry. For more information, see the dax presentation at the X-Ray Astronomy 19 CIAO workshop and our YouTube channel.

Sherpa uses DS9 for image analysis (the image_data set of commands). For an example see the Sherpa thread Fitting FITS Image Data.


CIAO includes the Python Matplotlib plotting package for plotting and imaging.

Sherpa uses Matplotlib for line plots - that is, those created with the plot and contour commands, like plot_fit and contour_model. Examples can be found in the Sherpa threads and FAQ.


[New] CIAO 4.16 adds experimental support for using bokeh as the visualization tool in Sherpa. Since it behaves rather differently to Matplotlib it is not quite a simple replacement, but it does provide interactive access to plot data from a Jupter notebook.


Prior to CIAO 4.12, CIAO included the ChIPS (Chandra Imaging and Plotting System) for data visualization. Please see the ChIPS to Matplotlib conversion guide for information on how to convert any code, notes, or muscle memory you have. The CXC Helpdesk can also be consulted for guidance.


Prior to CIAO 4.14, CIAO include the prism file viewer. Prism users can now find most of the functionality available in SAOImage ds9 under the File: Prism menu, or via the -prism option when starting ds9:

unix% ds9 -prism table.fits