:py:mod:`parameter_sweep.reader`
================================

.. py:module:: parameter_sweep.reader


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

Classes
~~~~~~~

.. autoapisummary::

   parameter_sweep.reader.ParameterSweepReader



Functions
~~~~~~~~~

.. autoapisummary::

   parameter_sweep.reader.get_sweep_params_from_yaml
   parameter_sweep.reader.set_defaults_from_yaml



.. py:class:: ParameterSweepReader


   .. py:method:: get_sweep_params_from_yaml(m, yaml_filename)

      Creates a dictionary of swept model parameters specified via yaml file

      This function creates a dictionary of the items to vary during a parameter
      sweep where the variable name, model attribute, and sweeping domain are
      specified in a YAML file.  The YAML file should have the following format::

          A_comp:
              type: NormalSample
              param: fs.RO.A_comp
              mean: 4.0e-12
              std: 0.5e-12

      where the top-level keyword can be any short, easily understood identifier
      for the parameter.  ``type`` must be one of ``LinearSample``, ``UniformSample``,
      ``NormalSample``, or ``LatinHypercubeSample``.  ``param`` must be a valid
      dot-sperated string path to the object attribute (in this case, an RO attribute
      on the flowsheet ``m``) that you wish to vary.  The remaining arguments are
      dependent on the sample type selected.  For ``NormalSample`` information about
      the mean and standard deviation is required.  Consult the ``parameter_sweep``
      help for more information on the different sample classes.

      :param m: The flowsheet containing the model to deploy with the parameter sweep
                tool.
      :type m: pyomo model
      :param yaml_filename: The path to the yaml file.
      :type yaml_filename: str

      :returns:     A dictionary containing different instances of parameter sweep samples
      :rtype: sweep_params (dict)


   .. py:method:: set_defaults_from_yaml(m, yaml_filename, verbose=False)

      Sets default model values using values stored in a yaml file

      This function reads a yaml file with the structure::

          fs.path.to.attribute_1: 0.123
          fs.path.to.attribute_2: 1.234
          ...

      and uses the (key, default_value) pairs to set default values
      for the attributes in model ``m``.

      :param m: The flowsheet containing the model to set default values for
      :type m: pyomo model
      :param yaml_filename: The path to the yaml file.
      :type yaml_filename: str

      :returns: N/A



.. py:function:: get_sweep_params_from_yaml(m, yaml_filename)

   Creates a dictionary of swept model parameters specified via yaml file

   This function creates a dictionary of the items to vary during a parameter
   sweep where the variable name, model attribute, and sweeping domain are
   specified in a YAML file.  The YAML file should have the following format::

       A_comp:
           type: NormalSample
           param: fs.RO.A_comp
           mean: 4.0e-12
           std: 0.5e-12

   where the top-level keyword can be any short, easily understood identifier
   for the parameter.  ``type`` must be one of ``LinearSample``, ``UniformSample``,
   ``NormalSample``, or ``LatinHypercubeSample``.  ``param`` must be a valid
   dot-sperated string path to the object attribute (in this case, an RO attribute
   on the flowsheet ``m``) that you wish to vary.  The remaining arguments are
   dependent on the sample type selected.  For ``NormalSample`` information about
   the mean and standard deviation is required.  Consult the ``parameter_sweep``
   help for more information on the different sample classes.

   :param m: The flowsheet containing the model to deploy with the parameter sweep
             tool.
   :type m: pyomo model
   :param yaml_filename: The path to the yaml file.
   :type yaml_filename: str

   :returns:     A dictionary containing different instances of parameter sweep samples
   :rtype: sweep_params (dict)


.. py:function:: set_defaults_from_yaml(m, yaml_filename, verbose=False)

   Sets default model values using values stored in a yaml file

   This function reads a yaml file with the structure::

       fs.path.to.attribute_1: 0.123
       fs.path.to.attribute_2: 1.234
       ...

   and uses the (key, default_value) pairs to set default values
   for the attributes in model ``m``.

   :param m: The flowsheet containing the model to set default values for
   :type m: pyomo model
   :param yaml_filename: The path to the yaml file.
   :type yaml_filename: str

   :returns: N/A