:py:mod:`starling_sim.utils.demand`
===================================

.. py:module:: starling_sim.utils.demand

.. autoapi-nested-parse::

   This module contains utils for generating and managing Starling demand.



Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   starling_sim.utils.demand.demand_from_eqasim
   starling_sim.utils.demand.default_agent_ids
   starling_sim.utils.demand.add_starling_demand_attributes



Attributes
~~~~~~~~~~

.. autoapisummary::

   starling_sim.utils.demand.STARLING_MINIMUM_COLUMNS


.. py:data:: STARLING_MINIMUM_COLUMNS
   :value: ['agent_type', 'icon', 'agent_id', 'mode', 'origin_time', 'geometry']

   

.. py:function:: demand_from_eqasim(eqasim_population: geopandas.GeoDataFrame, sample_rate: float = None, sample_seed=None, spatial_filter: geopandas.GeoDataFrame = None) -> geopandas.GeoDataFrame

   Generate a Starling population from an Eqasim population.

   :param eqasim_population: GeoDataFrame describing an Eqasim population
   :param sample_rate: fraction of the original population that is kept in the final population
   :param sample_seed: seed used for sampling
   :param spatial_filter: GeoDataFrame used as spatial filter

   :return: GeoDataFrame of a Starling population generated from the Eqasim population


.. py:function:: default_agent_ids(population: pandas.DataFrame) -> list

   Default function for generating agent ids on a population.

   :param population: population DataFrame on which agent ids are generated
   :return: list of agent ids


.. py:function:: add_starling_demand_attributes(population: pandas.DataFrame, agent_id_generator: callable = default_agent_ids) -> pandas.DataFrame

   Add default Starling users attributes: agent type, icon, agent id and mode.

   Caution: this function modifies the original DataFrame.

   :param population: population DataFrame to enrich
   :param agent_id_generator: function that takes the population as parameter and returns an "agent_id" column

   :return: enriched population DataFrame