pyepo.model.grb.grbmodel
========================

.. py:module:: pyepo.model.grb.grbmodel

.. autoapi-nested-parse::

   Abstract optimization model based on GurobiPy



Classes
-------

.. autoapisummary::

   pyepo.model.grb.grbmodel.optGrbModel


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

.. py:class:: optGrbModel

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


   Abstract base class for GurobiPy-backed optimization models.

   Subclasses implement ``_getModel`` to build a ``gurobipy.Model`` and
   return ``(model, variables)``. The objective sense is auto-detected
   from the underlying Gurobi model -- ``modelSense`` does not need to be
   set manually. Solver output is silenced by default; cost-vector updates
   use the C-level ``setAttr("Obj", ...)`` batch path for efficiency.

   :ivar _model: underlying Gurobi model

   :vartype _model: gurobipy.Model


   .. py:property:: num_cost
      :type: int


      number of costs to be predicted


   .. py:method:: setObj(c: numpy.ndarray | torch.Tensor | list) -> None

      A method to set the objective function

      :param c: cost of objective function



   .. py:method:: solve() -> tuple[numpy.ndarray, float]

      A method to solve the model

      :returns: optimal solution (list) and objective value (float)
      :rtype: tuple



   .. py:method:: copy() -> Self

      A method to copy the model

      :returns: new copied model
      :rtype: optModel



   .. py:method:: addConstr(coefs: numpy.ndarray | torch.Tensor | list, rhs: float) -> Self

      A method to add a new constraint

      :param coefs: coefficients of new constraint
      :param rhs: right-hand side of new constraint

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