Documentation How To#

Documentation building#

Generating the HTML docs for Gammapy is straight-forward:

make docs-sphinx
make docs-show

Or one can equivalently use tox:

tox -e build_docs

Generating the PDF docs is more complex. This should work:

# build the latex file
cd docs
python -m sphinx . _build/latex -b latex -j auto
# first generation of pdf file
cd _build/latex
pdflatex -interaction=nonstopmode gammapy.tex
# final generation of pdf file
pdflatex -interaction=nonstopmode gammapy.tex
# clean the git repo
git reset --hard
# open the pdf file
open gammapy.pdf

You need a bunch or LaTeX stuff, specifically texlive-fonts-extra is needed.

Check Python code#

Code in RST files#

Most of the documentation of Gammapy is present in RST files that are converted into HTML pages using Sphinx during the build documentation process. You may include snippets of Python code in these RST files within blocks labelled with .. code-block:: python Sphinx directive. However, this code could not be tested, and it will not be possible to know if it fails in following versions of Gammapy. That’s why we recommend using the .. testcode:: directive to enclose code that will be tested against the results present in a block labelled with .. testoutput:: directive. If not .. testoutput:: directive is provided, only execution tests will be performed.

For example, we could check that the code below does not fail, since it does not provide any output.

.. testcode::

    from gammapy.astro import source
    from gammapy.astro import population
    from gammapy.astro import darkmatter

On the contrary, we could check the execution of the following code as well as the output values produced.

.. testcode::

    from astropy.time import Time
    time = Time(['1999-01-01T00:00:00.123456789', '2010-01-01T00:00:00'])

.. testoutput::

    [51179.00000143 55197.        ]

In order to perform tests of these snippets of code present in RST files, you may run the following command.

pytest --doctest-glob="*.rst" docs/

Code in docstrings in Python files#

It is also advisable to add code snippets within the docstrings of the classes and functions present in Python files. These snippets show how to use the function or class that is documented, and are written in the docstrings using the following syntax.

>>> from astropy.units import Quantity
>>> from import EventList
>>> event_list ='events.fits') # doctest: +SKIP

In the case above, we could check the execution of the first two lines importing the Quantity and EventList modules, whilst the third line will be skipped. On the contrary, in the example below we could check the execution of the code as well as the output value produced.

>>> from regions import Regions
>>> regions = Regions.parse("galactic;circle(10,20,3)", format="ds9")
>>> print(regions[0])
Region: CircleSkyRegion
center: <SkyCoord (Galactic): (l, b) in deg
    (10., 20.)>
radius: 3.0 deg

In order to perform tests of these snippets of code present in the docstrings of the Python files, you may run the following command.

pytest --doctest-modules --ignore-glob=*/tests gammapy

If you get a zsh error try using putting to ignore block inside quotes

pytest --doctest-modules "--ignore-glob=*/tests" gammapy

Include png files as images#

In the RST files#

Gammapy has a gp-image directive to include an image from $GAMMAPY_DATA/figures/, use the gp-image directive instead of the usual Sphinx image directive like this:

.. gp-image:: detect/fermi_ts_image.png
    :scale: 100%

More info on the image directive.

Documentation guidelines#

Like almost all Python projects, the Gammapy documentation is written in a format called restructured text (RST) and built using Sphinx. We mostly follow the Astropy documentation guidelines, which are based on the Numpy docstring standard, which is what most scientific Python packages use.

There’s a few details that are not easy to figure out by browsing the Numpy or Astropy documentation guidelines, or that we actually do differently in Gammapy. These are listed here so that Gammapy developers have a reference.

Usually the quickest way to figure out how something should be done is to browse the Astropy or Gammapy code a bit (either locally with your editor or online on GitHub or via the HTML docs), or search the Numpy or Astropy documentation guidelines mentioned above. If that doesn’t quickly turn up something useful, please ask by putting a comment on the issue or pull request you’re working on GitHub, or email the Gammapy mailing list.

Functions or class methods that return a single object#

For functions or class methods that return a single object, following the Numpy docstring standard and adding a Returns section usually means that you duplicate the one-line description and repeat the function name as return variable name. See w or sidereal_time as examples in the Astropy codebase. Here’s a simple example:

def circle_area(radius):
    """Circle area.

    radius : `~astropy.units.Quantity`
        Circle radius

    area : `~astropy.units.Quantity`
        Circle area
    return 3.14 * (radius ** 2)

In these cases, the following shorter format omitting the Returns section is recommended:

def circle_area(radius):
    """Circle area (`~astropy.units.Quantity`).

    radius : `~astropy.units.Quantity`
        Circle radius
    return 3.14 * (radius ** 2)

Usually the parameter description doesn’t fit on the one line, so it’s recommended to always keep this in the Parameters section.

A common case where the short format is appropriate are class properties, because they always return a single object. As an example see radec, which is reproduced here:

def radec(self):
    """Event RA / DEC sky coordinates (`~astropy.coordinates.SkyCoord`)."""
    lon, lat = self['RA'], self['DEC']
    return SkyCoord(lon, lat, unit='deg', frame='icrs')

Class attributes#

Class attributes (data members) and properties are currently a bit of a mess. Attributes are listed in an Attributes section because I’ve listed them in a class-level docstring attributes section as recommended here. Properties are listed in separate Attributes summary and Attributes Documentation sections, which is confusing to users (“what’s the difference between attributes and properties?”).

One solution is to always use properties, but that can get very verbose if we have to write so many getters and setters. We could start using descriptors.

TODO: make a decision on this and describe the issue / solution here.