stateinterpreter.metastable.identify_metastable_states#

class stateinterpreter.metastable.identify_metastable_states(colvar, selected_cvs, kBT, bandwidth, logweights=None, fes_cutoff=None, gradient_descent_iterates=0, sort_minima_by='cvs_grid', optimizer_kwargs={})[source]#

Bases:

Label configurations based on free energy

Parameters

  • colvar (Pandas dataframe) – ###

  • selected_cvs (list of strings) – Names of the collective variables used for clustering

  • kBT (scalar) – Temperature

  • bandwidth (scalar) – Bandwidth method for FES calculations

  • logweights (pandas.DataFrame, np.array or string , optional) – Logweights used for FES calculation, by default None

  • fes_cutoff (float, optional) – Cutoff used to select only low free-energy configurations, if None fes_cutoff is 2k_BT

  • sort_minima_by (string, optional) – Sort labels based on energy, cvs, or cvs_grid values, by default cvs_grid.

  • optimizer_kwargs (optional) –

    Arguments for optimizer, by default dict(). Possible kwargs are:

    (int) num_init: number of initialization point, (int) decimals_tolerance: number of decimals to retain to identify unique minima, (str) sampling: sampling scheme. Accepted strings are ‘data_driven’ or ‘uniform’.

__init__(**kwargs)#