:py:mod:`bhepop2.enrichment.uniform`
====================================

.. py:module:: bhepop2.enrichment.uniform

.. autoapi-nested-parse::

   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
~~~~~~~

.. autoapisummary::

   bhepop2.enrichment.uniform.SimpleUniformEnrichment




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


   Bases: :py:obj:`bhepop2.enrichment.base.SyntheticPopulationEnrichment`

   This class implements a simple enrichment using a global distribution.

   **Expected source types**:

   .. autosummary::
       :nosignatures:

       ~bhepop2.sources.global_distribution.QuantitativeGlobalDistribution

   ------

   The global distribution describes the feature values of the whole population,
   using deciles (see :mod:`~bhepop2.sources.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.

   .. py:method:: _evaluate_feature_on_population()

      Evaluate a list of feature values for each individual.

      :return: iterable with same size and order than the population


   .. py:method:: _draw_feature_value()