synthpop.modules.evolution._evolution
=====================================

.. py:module:: synthpop.modules.evolution._evolution

.. autoapi-nested-parse::

   This is a module containing the base classes for the evolution process.

   The Evolution class is split into a EvolutionIsochrones and EvolutionInterpolator.
   This allows to vary both independently.
   Those are combined into a common Evolution Class using the CombineEvolution function

   A EvolutionIsochrones subclass should also have an EvolutionInterpolator as second Parent
   to specify a default interpolator. This interpolator is used whenever no Interpolator is defined.



Attributes
----------

.. autoapisummary::

   synthpop.modules.evolution._evolution.ISOCHRONES_DIR
   synthpop.modules.evolution._evolution.EVOLUTION_DIR
   synthpop.modules.evolution._evolution.MUST_HAVE_COLUMNS


Classes
-------

.. autoapisummary::

   synthpop.modules.evolution._evolution.EvolutionIsochrones
   synthpop.modules.evolution._evolution.EvolutionInterpolator


Functions
---------

.. autoapisummary::

   synthpop.modules.evolution._evolution.CombineEvolution


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

.. py:data:: ISOCHRONES_DIR
   :value: "b'.'/data/isochrones"


.. py:data:: EVOLUTION_DIR

.. py:data:: MUST_HAVE_COLUMNS
   :value: ['log10_isochrone_age_yr', 'initial_mass', '[Fe/H]_init', 'phase']


.. py:class:: EvolutionIsochrones(columns=None, logger: types.ModuleType = None, **kwargs)

   Bases: :py:obj:`abc.ABC`


   The EvolutionIsochrones base class. The appropriate subclass is
   assigned based on Population[evolution_class][name] through the "get_subclass" factory.
   must specify at least this "log10_isochrone_age_yr", "initial_mass", "[Fe/H]_init", "star_mass"

   Current included subclasses:
   ----------------------------
   -MIST': Using the MIST isochrones systems,


   Attributes
   ----------
   isochrones :  Pandas DataFrame
       DataFrame of the loaded isochrones
   isochrones_grouped : Pandas DataFrameGroupBy
       Isochrones groupend in metallicity and age

   more Attributes can be specified in the subclasses

   Methods
   -------
   __init__(self,**kwargs) : None
       initialize the EvolutionIsochrones class from a Population dictionary
   get_isochrones(self) : None
       return the Isochrones Data Frame


   .. py:attribute:: isochrones_name
      :value: None



   .. py:attribute:: isochrones_grouped
      :value: None



   .. py:attribute:: columns
      :value: None



   .. py:attribute:: logger
      :value: None



   .. py:method:: get_isochrones()

      Returns
      -------
      isochrones : Pandas.DataFrame
          Isochrone Grid



   .. py:method:: get_mass_min(band: str, magnitude_limit: float, distances: np.ndarray or float, max_age: float = None, extinction_at_slice_front: np.ndarray or float = None) -> numpy.ndarray

      gets the minimum mass of stars still passing the magnitude_limit

      Parameters
      ----------
      magnitude_limit : float
          maximum observed magnitude, (set distance to 0.01 if absolute magnitudes),
      distances : np.ndarray or float
          distances in kpc
      max_age: float [Gyr]
      Returns
      -------
      min_mass :  np.ndarray or float
      Returns minimum mass for stars brighter than magnitude_limit



.. py:class:: EvolutionInterpolator(logger: types.ModuleType = None, **kwargs)

   Bases: :py:obj:`abc.ABC`


   The EvolutionInterpolator base class. The appropriate subclass is
   assigned based on Population[evolution_class][Interpolator] through the "get_subclass" factory.
   Each EvolutionIsochrone Class should have a specified default Interpolator

   Current included subclasses:
   ----------------------------
   -LagrangeInterpolator: Using Lagrange Polynomials to interpolate
           between Consecutive stars in the Isochrone grid


   Attributes
   ----------
   accept_np_arrays :  Bool
       should be set to True if the interpolator can work with multiple stars given as array.

   more Attributes can be specified in the subclasses

   Methods
   -------
   __init__(self,**kwargs) : None
       initialize the EvolutionIsochrones class from a Population dictionary
   get_evolved_props(self) : pandas.DataFrame
       return the Isochrones



   .. py:attribute:: interpolator_name
      :value: None



   .. py:attribute:: accept_np_arrays
      :value: False



   .. py:attribute:: isochrones
      :value: None



   .. py:attribute:: met_to_file_iso
      :value: None



   .. py:attribute:: file_met
      :value: None



   .. py:attribute:: iso_ages
      :value: None



   .. py:attribute:: logger
      :value: None



   .. py:method:: get_evolved_props(m_init, met, age, props, **kwargs)
      :abstractmethod:


      Get the interpolated properties from the isochrones.

      Parameters
      ----------
      m_init : float, ndarray [Msun]
          initial mass for the stars
      met : float, ndarray [dex]
          initial metallicity for the stars
      age : float, ndarray [Gyr]
          initial age for the stars
      props : set
          a set of properties
      kwargs : dict, optional
          further ignored keywords


      Returns
      -------
      s_track : dict
          interpolator properties for all keywords specified in props
      in_grid : bool , ndarray
          indicator if the star is within the Isochrone Grid
      final_phase : bool, ndarray
          indicator if the star is in its final phase and might need special treatment.
          (can be the same as in_grid)

      Note: if accept_np_arrays is set to True.
          each entry in s_track has to be a ndarray of the same shape as the input parameters




.. py:function:: CombineEvolution(Isochrones=None, Interpolator=None)

   This function combines the isochrones and Interpolator into a common Evolution Class
   Parameters
   ----------
   Isochrones : class
       Class of the Isochrone system
   Interpolator : class or None
       Class of the Interpolator
   Returns
   -------
   Evolution: class