Friday, June 5, 2015

A few IPython notebooks

I have started to collect together a few IPython notebooks highlighting a few features of Sherpa - in particular the standalone version. They can be found on GitHub at and the current collection contains:

The first one is the same as referenced in my
How do I use the standalone build of Sherpa to fit my data?
post from last year, but the last three are *new*.

We will soon have a better location for this style of information, as we continue work on our "Open Sherpa" project. Please come along and help out!

Tuesday, May 5, 2015

Ivan Zolotukhin posted on Facebook the link to his web application that wraps Sherpa to fit the spectra in the new XMM catalog 3XMM-DR5:

Tuesday, April 28, 2015

Installing Sherpa

My new iMac with Yosemite arrived this week and I have to install all the software packages I  use including Sherpa.  I had to install Python Anaconda then setup my local git directory
and clone sherpa:

$ git clone

Next go and install sherpa:

$ cd sherpa
$ sherpa install

The build failed as I did not have gfortran. 
Installing gfortran was easy - just got the package from
and follow the instructions.

With this update the basic Sherpa installation completed. I run the sherpa_test which failed as I did not have pyfits.


$ pip install pyfits

Then I run sherpa_test  and this time the tests passed. I still need to install ds9, but now I have Sherpa and can run some of the analysis that I have to do today.

Tuesday, April 21, 2015

Sherpa Becomes an Open Project!

On April 20, 2015 Sherpa became an Open Source project!  The source code repository is now on GitHub.   The project repository can be 'cloned'  allowing for development of  the new code, new extensions  or bug fixes.  The Sherpa Project welcomes contributions via GitHub.  

Now, you can build Sherpa from source on your own platform within your Python environment with additional customization. See more details on Sherpa documentation page.

Monday, October 20, 2014

How do I use the standalone build of Sherpa to fit my data?

I've put together a simple IPython notebook showing off the new standalone Sherpa build. The notebook runs through a simple polynomial fit and is based on the "Introduction to NumPy/SciPy" course from the Practical Python for Astronomers site. 

It highlights

  • using the Sherpa standalone package along with other Python packages (astropy, matplotlib, numpy)
  • how to use the "high-level" API (as described in the CIAO documentation), which provides  data management in a manner similar to the Xspec spectral fitting package
  • how to use the "low-level" API, which is unfortunately poorly documented as this time 
One thing it doesn't really cover is how easy it is to switch from a polynomial model to a more-complex one. Oh well, perhaps next time.

Mentioning a next time, hopefully I'll have time to add more notebooks soon; check at the notebook viewer page to see if any have been added, or go to the GitHub page for this project. If you'd like to see any topic covered, please mention it in the comments.

Saturday, October 4, 2014

Sherpa 4.7b binary release

Sherpa standalone binary package was released on 26 September, 2014.  It was built and tested on Linux 32, Linux 64 and Mac OSX and can be installed into Anaconda Python. The plan is to migrate the code to github for  December source release.

Thursday, January 30, 2014

Sherpa Fitting in ds9

You can now use Sherpa fitting directly from ds9. Several basic spectral and image models are loaded via CIAO analysis tools for a quick look at the model parameters. Here is the video from Kenny showing you how to do it: Fitting in ds9