:py:mod:`IMLCV.scheme`
======================

.. py:module:: IMLCV.scheme


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

Classes
~~~~~~~

.. autoapisummary::

   IMLCV.scheme.Scheme




.. py:class:: Scheme(Engine: IMLCV.base.MdEngine.MDEngine, folder='output')

   base class that implements iterative scheme.

   :param format: intermediate file type between rounds
   :type format: String
   :param CVs: list of CV instances.

   .. py:method:: from_rounds(rounds: IMLCV.base.rounds.Rounds) -> Scheme
      :staticmethod:


   .. py:method:: MTDBias(steps, K=None, sigmas=None, start=500, step=250)
      :abstractmethod:

      generate a metadynamics bias.


   .. py:method:: FESBias(**kwargs)

      replace the current md bias with the computed FES from current
      round.


   .. py:method:: grid_umbrella(steps=10000.0, k=None, n=8, max_grad=None)


   .. py:method:: new_metric(plot=False, r=None)


   .. py:method:: inner_loop(rnds=10, init=500, steps=50000.0, K=None, update_metric=False, n=4, samples_per_bin=500, init_max_grad=None, max_grad=None, plot=True)


   .. py:method:: update_CV(cvd: IMLCV.base.CVDiscovery.CVDiscovery, chunk_size=None, samples=2000.0, plot=True, **kwargs)


   .. py:method:: save(filename)
      :abstractmethod:


   .. py:method:: load(filename)
      :classmethod:
      :abstractmethod: