I released a new version of my
epyc experimental management
Nothing too dramatic, but I did start the process of refactoring the way in which experiments are assigned parameters, which is something I've been meaning to do for a while.
In previous versions an experiment was performed at every point in the cross-product of all parameters. This can be quite wasteful, and one of my MSc students used a different approach where they created experiments pointwise from the corresponding values of each parameter, which leads to better control.
This is actually a specific example of a more general concept of an
experimental design, which imports into computational science the
ways in which traditional experiments are set up. I refactored how
epyc labs create experiments to use an externally-specified design
class, and implemented the old and alternative versions as standard
designs (called "factorial" and "pointwise" respectively).
There's actually another model that we need, the so-called "block"
designs, which would be great for creating fewer networks under
`epydemic -- but that needs some more thought as to exactly how to
manage the data flow.