pyepo.model.mpax.mpaxmodel
==========================

.. py:module:: pyepo.model.mpax.mpaxmodel

.. autoapi-nested-parse::

   Abstract optimization model based on MPAX



Attributes
----------

.. autoapisummary::

   pyepo.model.mpax.mpaxmodel._HAS_MPAX
   pyepo.model.mpax.mpaxmodel.num_vars


Classes
-------

.. autoapisummary::

   pyepo.model.mpax.mpaxmodel.optMpaxModel


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

.. py:data:: _HAS_MPAX
   :value: True


.. py:class:: optMpaxModel(A=None, b=None, G=None, h=None, l=None, u=None, use_sparse_matrix=True, minimize=True)

   Bases: :py:obj:`pyepo.model.opt.optModel`


   This is an abstract class for MPAX-based optimization model

   .. attribute:: A

      The matrix of equality constraints.

      :type: jnp.ndarray, BCOO or BCSR

   .. attribute:: b

      The right hand side of equality constraints.

      :type: jnp.ndarray

   .. attribute:: G

      The matrix for inequality constraints.

      :type: jnp.ndarray, BCOO or BCSR

   .. attribute:: h

      The right hand side of inequality constraints.

      :type: jnp.ndarray

   .. attribute:: l

      The lower bound of the variables.

      :type: jnp.ndarray

   .. attribute:: u

      The upper bound of the variables.

      :type: jnp.ndarray

   .. attribute:: use_sparse_matrix

      Whether to use sparse matrix format, by default True.

      :type: bool

   .. attribute:: minimize

      Whether to minimize objective, by default True.

      :type: bool


   .. py:attribute:: l


   .. py:attribute:: u


   .. py:attribute:: use_sparse_matrix
      :value: True



   .. py:attribute:: modelSense
      :value: 1



   .. py:attribute:: device
      :value: None



   .. py:attribute:: jitted_solve
      :value: None



   .. py:attribute:: batch_optimize


   .. py:method:: __repr__()


   .. py:property:: num_cost

      number of cost to be predicted


   .. py:method:: setObj(c)

      A method to set objective function

      :param c: cost of objective function
      :type c: np.ndarray / list



   .. py:method:: solve()

      A method to solve model

      :returns: optimal solution (list) and objective value (jnp.float32)
      :rtype: tuple



   .. py:method:: _jitted_solve(c, A, b, G, h, l, u, use_sparse_matrix)
      :staticmethod:


      A static method for JIT complile



   .. py:method:: copy()

      A method to copy model

      :returns: new copied model
      :rtype: optModel



   .. py:method:: addConstr(coefs, rhs)

      A method to add new constraint

      :param coefs: coeffcients of new constraint
      :type coefs: np.ndarray / list
      :param rhs: right-hand side of new constraint
      :type rhs: jnp.float32

      :returns: new model with the added constraint
      :rtype: optModel



   .. py:method:: _getModel()

      Placeholder method for MPAX. MPAX does not require an explicit model creation.



.. py:data:: num_vars
   :value: 10