qemcmc.coarse_grain
===================

.. py:module:: qemcmc.coarse_grain


Classes
-------

.. autoapisummary::

   qemcmc.coarse_grain.CoarseGraining


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

.. py:class:: CoarseGraining(n, subgroups=None, subgroup_probs=None, repeated=True)

   CoarseGraining class to generate partitions of spins for quantum proposals.

   :param n: Number of spins in the system.
   :type n: int
   :param subgroups: A list of subgroups, where each subgroup is a list of spin indices. If None, the entire set of spins is treated as one subgroup.
   :type subgroups: list[list[int]], optional
   :param subgroup_probs: A list of probabilities corresponding to each subgroup, used for weighted random selection. Must sum to 1. If None, subgroups are selected uniformly at random.
   :type subgroup_probs: list[float], optional
   :param repeated: If True, then multiple subgroups are run on the quantum computer in serial, if not then only one subgroup is selected at random and run on the quantum computer. Default is ``True``.
   :type repeated: bool, optional


   .. py:attribute:: _user_specified


   .. py:attribute:: n


   .. py:attribute:: subgroups
      :value: None



   .. py:attribute:: subgroup_probs
      :value: None



   .. py:attribute:: repeated
      :value: True



   .. py:method:: sample() -> list[int]

      Randomly samples a subgroup according to the specified probability distribution.



   .. py:method:: get_partitions(m: int) -> list[list[int]]

      Returns partitions of spins for sequential quantum updates.

      If the user provided explicit subgroups at initialisation, those are
      returned directly (all if ``repeated=True``, otherwise just the first).
      If no subgroups were specified, random disjoint partitions of
      approximate size n/m are generated.

      :param m: The number of partitions to generate. Ignored if user-specified subgroups are provided.
      :type m: int