DiscreteHistogram

class madspace.DiscreteHistogram(self: madspace._madspace_py.DiscreteHistogram, option_counts: collections.abc.Sequence[SupportsInt])

Bases: FunctionGenerator

Per-category weight accumulator that adapts a DiscreteSampler.

During the warm-up run it sums the sample weights for each category of each discrete dimension. The accumulated values_d and counts_d are then used to refine the learned categorical distributions (Sec. 3.2.2 of [1]).

batch is the leading batch dimension. d indexes the discrete dimensions.

Arguments

• index_d – int, shape (batch,) – the chosen category per dimension.

• weight – float, shape (batch,) – the per-sample weights.

Returns

• values_d – float, shape (option_counts[d],) – summed weight per category.

• counts_d – int, shape (option_counts[d],) – sample count per category.

References

• [1] T. Heimel, O. Mattelaer, R. Winterhalder, “MadSpace”, https://arxiv.org/abs/2602.06895 (Sec. 3.2.2)

Parameters:

option_counts – Number of categories for each discrete dimension.