:mod:`memote.experimental.config`
=================================

.. py:module:: memote.experimental.config

.. autoapi-nested-parse::

   Provide a YAML parser for experiment configuration files.

   ..
       !! processed by numpydoc !!



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

Classes
~~~~~~~

.. autoapisummary::

   memote.experimental.config.ExperimentConfiguration



.. py:class:: ExperimentConfiguration(filename, **kwargs)

   Bases: :class:`object`

   Represent an experimental configuration.
















   ..
       !! processed by numpydoc !!

   .. method:: load(self, model)

      Load all information from an experimental configuration file.


      :Parameters:

          **model** : cobra.Model
              The metabolic model under investigation.














      ..
          !! processed by numpydoc !!


   .. method:: validate(self)

      Validate the configuration file.
















      ..
          !! processed by numpydoc !!


   .. method:: load_medium(self, model)

      Load and validate all media.
















      ..
          !! processed by numpydoc !!


   .. method:: load_essentiality(self, model)

      Load and validate all data files.
















      ..
          !! processed by numpydoc !!


   .. method:: load_growth(self, model)

      Load and validate all data files.
















      ..
          !! processed by numpydoc !!


   .. method:: get_path(self, obj, default)

      Return a relative or absolute path to experimental data.
















      ..
          !! processed by numpydoc !!


   .. method:: get_minimal_growth_rate(self, model, threshold=0.1)

      Calculate min growth default value or return input value.

      This value is used to determine if a model is capable of growth under
      certain experimental conditions.

      :Parameters:

          **model** : cobra.Model
              ..

          **threshold** : float, optional
              If no input is provided by the user the default value is set to a
              coefficient `threshold` times the growth under default constraints
              (default: 0.1).














      ..
          !! processed by numpydoc !!