To continue in the effort of merging Sam Shaner's transient capability,
this next PR adds the class DiffusionCoefficient to mgxs.py. It uses
the TransportXS class, but has some unique features in get_condensed_xs()
requiring its own function. There won't be any other MGXS classes added
after this.
I updated the docstrings and the appropriate regression tests.
Since my system outputs different formatting for the
mgxs_library_distribcell test, it is possible this test will continue
to fail. However, I did my best to modify it by hand so that it will pass.
Custom sources are now created only through the new class-based method,
which supports parameterization.
New method also slightly adjusted to create the source as managed by a
unique_ptr.
Examples and tests updated to align with this approach.
Documentation updated.
Accounts for serialized -> parameterized change.
Simplifies some of the examples to be more appropriate for
documentation.
Removes use of external destroy method.
In the existing custom_source implementation, the source will only be
created once. This is much more efficient than the custom serialized
source, where each sampling will create a new instance of the class.
As there could be many samples, this introduces an overhead,
particularly if the operations to instantiate the class are not trivial.
This implementation defines an abstract class, which is then used by the
custom classes to allow the custom serialized class to be created based
on the plugin, sampled from, and then destroyed.
Update documentation and test to reflect this.
Changes the implementation of the serialization to be on an attribute of
the source XML element within settings.xml. This removes the need for a
new file containing the serialization.
Parameters are provided as a key-value string, separated by a comma and
a space, although the implementation can change this is required.
Change example values to align with existing custom_source to make
comparisons easier.
Update documentation to be consistent.
This describes the general concept of serialization and gives an example
of how to write a source_sampling function that deserializes the input
and uses values set via the serialized form.
