Installation

Quick overview

For those users who have already read this page, and need a quick refresher (or prefer to act first, and read documentation later), the following commands can be used to install Sherpa, depending on your environment and set up.

  1. Using conda

    conda install -c https://cxc.cfa.harvard.edu/conda/sherpa -c conda-forge sherpa

  2. Install Sherpa using pip

    pip install sherpa

  3. Building from source

    pip install .

Requirements

Sherpa has the following requirements:

  • Python 3.10 to 3.12

  • NumPy (version 2.0 should work but there has been limited testing)

  • Linux or OS-X (patches to add Windows support are welcome)

Sherpa can take advantage of the following Python packages if installed:

  • Astropy: for reading and writing files in FITS format.

  • matplotlib: for visualisation of one-dimensional data or models, one- or two- dimensional error analysis, and the results of Monte-Carlo Markov Chain runs. There are no known incompatibilities with matplotlib, but there has only been limited testing. Please report any problems you find.

The Sherpa build can be configured to create the sherpa.astro.xspec module, which provides the models and utility functions from XSPEC.

Interactive display and manipulation of two-dimensional images is available if the DS9 image viewer and the XPA commands are installed. It is expected that any recent version of DS9 can be used.

Releases and version numbers

The Sherpa release policy has a major release at the start of the year, corresponding to the code that is released in the previous December as part of the CIAO release, followed by several smaller releases throughout the year.

Information on the Sherpa releases is available from the Zenodo page for Sherpa, using the Digital Object Identifier (DOI) 10.5281/zenodo.593753.

What version of Sherpa is installed?

The version number and git commit id of Sherpa can be retrieved from the sherpa._version module using the following command:

% python -c 'import sherpa._version; print(sherpa._version.get_versions())'
{'version': '4.10.0', 'full': 'c7732043124b08d5e949b9a95c2eb6833e009421'}

Citing Sherpa

Information on citing Sherpa can be found from the CITATION document in the Sherpa repository, or from the Sherpa Zenodo page.

Installing a pre-compiled version of Sherpa

Additional useful Python packages include astropy, matplotlib, and ipython-notebook.

Using the Conda python distribution

The Chandra X-ray Center provides releases of Sherpa that can be installed using Miniforge. First check to see what the latest available version is by using:

conda install -c https://cxc.cfa.harvard.edu/conda/sherpa -c conda-forge sherpa --dry-run

and then, if there is a version available and there are no significant upgrades to the dependencies, Sherpa can be installed using:

conda install -c https://cxc.cfa.harvard.edu/conda/sherpa -c conda-forge sherpa

It is strongly suggested that Sherpa is installed into a named conda environment (i.e. not the default environment).

Using pip

Sherpa is also available from PyPI at https://pypi.python.org/pypi/sherpa and can be installed with the command:

pip install sherpa

Building from source

Prerequisites

The prerequisites for building from source are:

  • Python versions: 3.9 to 3.12

  • Python packages: setuptools, numpy (these should be automatically installed by pip)

  • System: gcc and g++ or clang and clang++, make, flex, bison, ar (which may be provided by the binutils package)

The aim is to support recent versions of these tools and libraries; please report problems to the Sherpa issue tracker.

It is highly recommended that matplotlib and astropy be installed before building Sherpa, to avoid skipping a number of tests in the test suite.

The full Sherpa test suite requires pytest, which is included when using the .[test] option with pip. The pytest-xvfb package can be useful if DS9 is installed, as it hides the DS9 windows created during the tests.

Note

As of the Sherpa 4.10.1 release, a Fortran compiler is no-longer required to build Sherpa.

Obtaining the source package

The source code can be obtained as a release package from Zenodo - e.g. the Sherpa 4.16.0 release - or from the Sherpa repository on GitHub, either a release version, such as the 4.16.0 tag, or the main branch (which is not guaranteed to be stable).

For example:

git clone https://github.com/sherpa/sherpa.git
cd sherpa
git checkout 4.16.0

will use the 4.16.0 tag (although we strongly suggest using a newer release now!).

Configuring the build

The Sherpa build is controlled by the setup.cfg file in the root of the Sherpa source tree. These configuration options include:

FFTW

Sherpa ships with the fftw library source code and builds it by default. To use a different version, change the fftw options in the sherpa_config section of the setup.cfg file. The options to change are:

fftw=local
fftw-include_dirs=/usr/local/include
fftw-lib-dirs=/use/local/lib
fftw-libraries=fftw3

The fftw option must be set to local and then the remaining options changed to match the location of the local installation.

XSPEC

Sherpa can be built to use the Astronomy models provided by XSPEC. To enable XSPEC support, several changes must be made to the xspec_config section of the setup.cfg file. The available options (with default values) are:

with-xspec = False
xspec_version = 12.12.0
xspec_lib_dirs = None
xspec_include_dirs = None
xspec_libraries = XSFunctions XSUtil XS
cfitsio_lib_dirs = None
cfitsio_libraries =
ccfits_lib_dirs = None
ccfits_libraries =
wcslib_lib_dirs = None
wcslib_libraries =
gfortran_lib_dirs = None
gfortran_libraries =

To build the sherpa.astro.xspec module, the with-xspec option must be set to True and the xspec_version option set to the correct version string (the XSPEC patch level must not be included), and then the remaining options depend on the version of XSPEC and whether the XSPEC model library or the full XSPEC system has been installed.

In the examples below, the $HEADAS value must be replaced by the actual path to the HEADAS installation, and the versions of the libraries - such as CCfits_2.6 - may need to be changed to match the contents of the XSPEC installation.

  1. If the full XSPEC 12.14.0 system has been built then use:

    with-xspec = True
xspec_version = 12.14.0
xspec_lib_dirs = $HEADAS/lib
xspec_include_dirs = $HEADAS/include
xspec_libraries = XSFunctions XSUtil XS hdsp_6.33
ccfits_libraries = CCfits_2.6
wcslib_libraries = wcs-8.2.1

    where the version numbers were taken from version 6.33.1 of HEASOFT and may need updating with a newer release.

  2. If the full XSPEC 12.13.1 system has been built then use:

    with-xspec = True
xspec_version = 12.13.1
xspec_lib_dirs = $HEADAS/lib
xspec_include_dirs = $HEADAS/include
xspec_libraries = XSFunctions XSUtil XS hdsp_6.32
ccfits_libraries = CCfits_2.6
wcslib_libraries = wcs-7.7

    where the version numbers were taken from version 6.32 of HEASOFT and may need updating with a newer release.

  3. If the full XSPEC 12.13.0 system has been built then use:

    with-xspec = True
xspec_version = 12.13.0
xspec_lib_dirs = $HEADAS/lib
xspec_include_dirs = $HEADAS/include
xspec_libraries = XSFunctions XSUtil XS hdsp_6.31
ccfits_libraries = CCfits_2.6
wcslib_libraries = wcs-7.7

  4. If the full XSPEC 12.12.1 system has been built then use:

    with-xspec = True
xspec_version = 12.12.1
xspec_lib_dirs = $HEADAS/lib
xspec_include_dirs = $HEADAS/include
xspec_libraries = XSFunctions XSUtil XS hdsp_6.30
ccfits_libraries = CCfits_2.6
wcslib_libraries = wcs-7.7

  5. If the full XSPEC 12.12.0 system has been built then use:

    with-xspec = True
xspec_version = 12.12.0
xspec_lib_dirs = $HEADAS/lib
xspec_include_dirs = $HEADAS/include
xspec_libraries = XSFunctions XSUtil XS hdsp_6.29
ccfits_libraries = CCfits_2.6
wcslib_libraries = wcs-7.3.1

  6. If the model-only build of XSPEC - created with the --enable-xs-models-only flag when building HEASOFT - has been installed, then the configuration is similar, but the library names may not need version numbers and locations, depending on how the cfitsio, CCfits, and wcs libraries were installed.

A common problem is to set one or both of the xspec_lib_dirs and xspec_lib_include options to the value of $HEADAS instead of $HEADAS/lib and $HEADAS/include (after expanding out the environment variable). Doing so will cause the build to fail with errors about being unable to find various XSPEC libraries such as XSFunctions and XSModel.

The gfortran options should be adjusted if there are problems using the XSPEC module.

In order for the XSPEC module to be used from Python, the HEADAS environment variable must be set before the sherpa.astro.xspec module is imported.

The Sherpa test suite includes an extensive set of tests of this module, but a quick check of an installed version can be made with the following command:

% python -c 'from sherpa.astro import xspec; print(xspec.get_xsversion())'
12.14.0i

Other options

The remaining options in the setup.cfg file allow Sherpa to be built in specific environments, such as when it is built as part of the CIAO analysis system. Please see the comments in the setup.cfg file for more information on these options.

Installing all dependencies with conda

See Install from source in conda for details on how to set up all dependencies for the Sherpa build with conda.

Building and Installing

It is highly recommended that some form of virtual environment, such as a conda environment or that provided by Virtualenv, be used when building and installing Sherpa.

The CC and CXX environment variables can be set to the C and C++ compilers to use if not found by setup.py.

Warning

When building Sherpa on macOS within a conda environment, the following environment variable must be set otherwise importing Sherpa will crash Python:

export PYTHON_LDFLAGS=' '

That is, the variable is set to a space, not the empty string.

A standard installation

From the root of the Sherpa source tree, Sherpa can be built with

pip install .

Please report any problems to the Sherpa issues page.

A development build

The code can be built locally, which is useful when adding new functionality or fixing a bug (the [test] term just ensures that pytest is also installed):

pip install -e .[test]

This will need to be re-run when any of the extension models - that is, any compiled code - is changed.

The --verbose flag is useful when diagnosing problems when building Sherpa:

pip install -e .[test] --verbose

Testing Sherpa

Tests can be run directly for the development build with:

pytest

You can pass additional arguments to pytest. As examples, the following two commands run all the tests in test_data.py and then a single named test in the file:

pytest sherpa/tests/test_data.py
pytest sherpa/tests/test_data.py::test_data_eval_model

The full set of options, including those added by the Sherpa test suite - which are listed at the end of the custom options section - can be found with:

pytest --pyargs sherpa --help

and to pass an argument to the Sherpa test suite (there are currently three options, namely --test-data, --runslow, and --runzenodo):

pytest --pyargs sherpa --runslow

The Sherpa test data suite can be installed to reduce the number of tests that are skipped with the following (this is only for those builds which used git to access the source code):

git submodule init
git submodule update

When both the DS9 image viewer and XPA toolset are installed, the test suite will include tests that check that DS9 can be used from Sherpa. This causes several copies of the DS9 viewer to be created, which can be distracting, as it can cause loss of mouse focus (depending on how X-windows is set up). This can be avoided by installing the X virtual-frame buffer (Xvfb) and ensuring that the pytest-xvfb Python package is installed.

Tests can be run in parallel with the pytest-xdist package installed. The safest way is to include the --dist=loadgroup option (although this is only needed if the DS9 tests are run):

pip install pytest-xdist
pytest --dist=loadgroup -n auto

Building the documentation

Building the documentation requires a Sherpa installation and several additional packages:

  • Sphinx, version 1.8 or later

  • The sphinx_rtd_theme

  • NumPy and sphinx-astropy (the latter can be installed with pip)

  • nbsphinx, ipykernel, and pandoc for including Jupyter notebooks

  • Graphviz (for the inheritance diagrams)

With these installed, the documentation can be built by saying:

cd docs
make html

Note that this uses the installed version of sherpa, so if you want to make sure the current repository version is used, you will need to install it with e.g.:

pip install -e .

before changing to the docs directory. Only very specific modules are mocked out because they are hard to build and are not needed for the documentation build (currently ds9 and XSPEC).

The documentation should be placed in docs/_build/html/index.html.

Note

Prior to Sherpa 4.16.0 the documentation was built directly from the source - using mock objects to handle compiled code - rather than using a Sherpa installation. As of 4.16.0, mock objects are only handled for the XSPEC and DS9 modules.

Testing the Sherpa installation

A very-brief “smoke” test can be run from the command-line with the sherpa_smoke executable:

sherpa_smoke
WARNING: failed to import sherpa.astro.xspec; XSPEC models will not be available
----------------------------------------------------------------------
Ran 7 tests in 0.456s

OK (skipped=5)

or from the Python prompt:

>>> import sherpa
>>> sherpa.smoke()
WARNING: failed to import sherpa.astro.xspec; XSPEC models will not be available
----------------------------------------------------------------------
Ran 7 tests in 0.447s

OK (skipped=5)

This provides basic validation that Sherpa has been installed correctly, but does not run many functional tests. The screen output will include additional warning messages if the astropy or matplotlib packages are not installed, or Sherpa was built without support for the XSPEC model library.

The Sherpa installation also includes the sherpa_test command-line tool which will run through the Sherpa test suite (the number of tests depends on what optional packages are available and how Sherpa was configured when built):

sherpa_test

The sherpa_test command supports the same optional arguments as pytest does (the --pyargs sherpa option is, however, not needed).

The Sherpa test data suite contains the sherpatest package, which provides a number of data files in ASCII and FITS formats. This is only useful when developing Sherpa, since the package is large. A version of the test data is released for each version of Sherpa.

As an example, the 4.15.1 version of the test data can be installed with pip:

pip install https://github.com/sherpa/sherpa-test-data/archive/4.15.1.zip

The test data will automatically be picked up by the sherpa_test script once it is installed.