Sherpa 4.9.1 Release

Sherpa 4.9.1 - an incremental improvement over the Sherpa 4.9 release - has now been released and is available via our Conda channel (https://conda.anaconda.org/sherpa), pip (https://pypi.python.org/pypi/sherpa/4.9.1), Zenodo (http://doi.org/10.5281/zenodo.838686), and GitHub (https://github.com/sherpa/sherpa/tree/4.9.1). This release supports Python 2.7, 3.5, and 3.6.

We thank everyone who contributed to this release with feature requests, bug reports, testing, code contributions, or questions.  Please join in the fun on GitHub: https://github.com/sherpa/sherpa/

Overview

This version introduces full support for Python 3.6. It also fixes issues with non-Chandra response files, correctly handles the AREASCAL column in PHA files, and fixes a significant regression that was preventing user statistics from working in v4.8.2. It also introduces a number of smaller improvements and fixes. In particular, quite a few improvements have been made to the documentation and to the testing framework, including several new tests to improve stability.

Details

Infrastructure and minor non-functional changes have been omitted.

#335 Fix `setup.py` install command

The `setup.py install` command was not enforcing the installation of the dependencies listed in `setup.py`. This has been fixed.

#368 Remove ds9 warnings when run under Python 3.6

Update the DS9 code so that external processes are cleaned up properly, so to remove the potential ResourceWarning warnings when running DS9 on Python 3.6.

#351 fix handling of AREASCAL column in PHA files (fix #350)

Add support for handling the AREASCAL value (either scalar of vector) for PHA data sets. This array is used in XMM RGS data to handle missing chips.

#358 Properly handle Swift RMF when using Astropy backend (fix #357)

A Swift RMF could not be read in when the AstroPy back end was in use. The problem was that the code did not support RMF matrices that were not stored as variable-length arrays. This has now been fixed, and new tests have been added for this kind of file.

#343 Fix user statistics regression (fix #341)

A number of regressions were introduced in version 4.8.1 up to version 4.9.0, so user statistics that were properly working in version 4.7 have not been working any more. This has been fixed, and a number of regression tests have been added.

#381 Fix `bdist_wheel` command

We reviewed our customization of the setuptools commands as we realized that a recent bug fix (#335) introduced a regression in the bdist_wheel command used by pip to build Sherpa from source distributions. Both commands should now properly work.

SABA  Sherpa Bridge to Astropy

Sherpa can be used as part of astropy.modeling thanks to SABA - Sherpa Bridge to Astropy

https://saba.readthedocs.io/en/latest/

The development of this package was made possible by the generous support of the Google Summer of Code program in 2016 under the OpenAstronomy by Michele Costa with the support and advice of mentors Tom Aldcroft, Omar Laurino, Moritz Guenther, and Doug Burke.

Sherpa 4.9 Release 

Sherpa 4.9 was just released this week. It now runs in Python 2.7 and Python 3.5. There has been minimal testing with Python 3.6. Support for versions 3.3 and 3.4 would require community support.

Check our GitHub page:
https://github.com/sherpa/sherpa/

Jupyter Notebooks are available on the wiki:

https://github.com/sherpa/sherpa/wiki

Sherpa 4.8.2 Release with Python 3.5 Beta

Sherpa 4.8.2 was released on September 22, 2016. This is the first release for both Python 2.7 and Python 3.5 (Beta release). The 4.8.2 release is available for Python 2.7 and for the first time (as a beta release) for Python 3.5 The Python 3.5 release is considered a Beta designed to maintain backwards compatibility with Python 2.7.

Check our GitHub page:
https://github.com/sherpa/sherpa/

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 https://github.com/DougBurke/sherpa-standalone-notebooks/ and the current collection contains:

•  A simple fit
•  Writing your own user model
•  An integrated user model
•  How can I plot data and models using the lower-level interface

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!

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:
http://xmm-catalog.irap.omp.eu/source/201068601010004

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 https://github.com/sherpa/sherpa.git

Next go and install sherpa:

$ cd sherpa
$ sherpa setup.py install

The build failed as I did not have gfortran. 
Installing gfortran was easy - just got the package from https://gcc.gnu.org/wiki/GFortranBinaries
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.

Used 

$ 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.