qc2.algorithms.base
===================

.. py:module:: qc2.algorithms.base

.. autoapi-nested-parse::

   Base Algo package.



Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/qc2/algorithms/base/base_algorithm/index
   /autoapi/qc2/algorithms/base/base_algorithm_results/index
   /autoapi/qc2/algorithms/base/vqe_base/index
   /autoapi/qc2/algorithms/base/vqe_base_results/index


Classes
-------

.. autoapisummary::

   qc2.algorithms.base.BaseAlgorithm
   qc2.algorithms.base.BaseAlgorithmResults
   qc2.algorithms.base.VQEBASE
   qc2.algorithms.base.VQEBASEResults


Package Contents
----------------

.. py:class:: BaseAlgorithm

   Bases: :py:obj:`abc.ABC`


   Base class for all qc2 algos.


   .. py:method:: set_qc2data(qc2data)

      set the data



   .. py:method:: run(*args, **kwargs)
      :abstractmethod:


      run it



.. py:class:: BaseAlgorithmResults

   Bases: :py:obj:`abc.ABC`


   Base class for all qc2 algorithms results.


.. py:class:: VQEBASE(qc2data=None, format='')

   Bases: :py:obj:`qc2.algorithms.base.base_algorithm.BaseAlgorithm`


   Base class for VQE


   .. py:attribute:: qc2data


   .. py:attribute:: format


   .. py:method:: _init_qubit_hamiltonian()


.. py:class:: VQEBASEResults

   Bases: :py:obj:`qc2.algorithms.base.base_algorithm_results.BaseAlgorithmResults`


   VQE result base class.


   .. py:attribute:: _optimizer_evals
      :type:  Optional[int]
      :value: None



   .. py:attribute:: _optimal_params
      :type:  Optional[List]
      :value: None



   .. py:attribute:: _optimal_energy
      :type:  Optional[float]
      :value: None



   .. py:attribute:: _energy
      :type:  Optional[List]
      :value: None



   .. py:attribute:: _parameters
      :type:  Optional[List]
      :value: None



   .. py:attribute:: _metadata
      :type:  Optional[Dict]
      :value: None



   .. py:property:: optimizer_evals
      :type: Optional[int]


      Returns number of optimizer evaluations.


   .. py:property:: optimal_params
      :type: Optional[List]


      Returns optimal parameters.


   .. py:property:: optimal_energy
      :type: Optional[float]


      Returns optimal energy.


   .. py:property:: energy
      :type: Optional[List]


      Returns list of energies of all iterations.


   .. py:property:: parameters
      :type: Optional[List]


      Returns list with parameters of all iteration.


   .. py:property:: metadata
      :type: Optional[Dict]


      Returns dict with metadata of all iterations.