bhepop2.enrichment.uniform

Simple uniform enrichment using a global distribution.

This enrichment method is not very interesting, but it provides a simple implementation of the enrichment logic. It also provides a good comparison point with other enrichment methods.

Module Contents

Classes

SimpleUniformEnrichment

This class implements a simple enrichment using a global distribution.

class bhepop2.enrichment.uniform.SimpleUniformEnrichment(population: pandas.DataFrame, source, feature_name: str = None, seed=None)

Bases: bhepop2.enrichment.base.SyntheticPopulationEnrichment

This class implements a simple enrichment using a global distribution.

Expected source types:

---

The global distribution describes the feature values of the whole population, using deciles (see global_distribution).

To evaluate a feature value for an individual, we randomly choose one of the deciles, and then draw a random value between its two boundaries.

This method ensures a good distribution of the feature values over the total population, but no more.

_evaluate_feature_on_population()

Evaluate a list of feature values for each individual.

Returns:

iterable with same size and order than the population

_draw_feature_value()