.. _Evaluate NeurEco Parametric Frequency Sweep model with the Python API:

Evaluate NeurEco Parametric Frequency Sweep model with the Python API
=======================================================================

To evaluate a NeurEco **Parametric Frequency Sweep** model in Python API, **NeurEcoFrequential** library:

.. code-block:: python

  from NeurEco import NeurEcoFrequential as Frequential 
	
Initialize a NeurEco object to handle the **Parametric Frequency Sweep** problem:

.. code-block:: python

  model = Frequential.PFS()
	
:std:ref:`Build NeurEco Parametric Frequency Sweep model with the Python API` or load previously build and saved to *"the/path/to/the/saved/parametric/frequency/sweep/model.efnn"* model:

.. code-block:: python

  model.load("the/path/to/the/saved/parametric/frequency/sweep/model.efnn")

Once **model** contains a **Parametric Frequency Sweep** model, call method **evaluate** with the parameters set accordingly to the data to evaluate:	

.. code-block:: python

  model.evaluate(inputs,
                 vec=None)

Evaluates a Parametric Frequency Sweep model.

:inputs: required, NumPy array, dtype=float64 : input data array: shape :math:`(n,\ m)` where :math:`n` is the number of samples and :math:`m` is the number of input variables.
:vec: optional, NumPy array: perform evaluation with the model’s weights set to values in **vec**
:return: NumPy array of outputs: shape :math:`(n, p)`, where :math:`n` is the number of samples and :math:`p` is the number of output variables

For more information on the data format, see :std:ref:`Data preparation for NeurEco Parametric Frequency Sweep python`.