`IMLCV.base.CVDiscovery`#

Module Contents#

`Transformer`
`CVDiscovery`	convert set of coordinates to good collective variables.

class IMLCV.base.CVDiscovery.Transformer(outdim, periodicity=None, bounding_box=None, descriptor='sb', descriptor_kwargs={})[source]#

pre_fit(z: list[IMLCV.base.CV.SystemParams], nl: list[NeighbourList] | None, chunk_size=None, scale=True) → tuple[list[IMLCV.base.CV.CV], IMLCV.base.CV.CvFlow][source]#

fit(sp_list: list[IMLCV.base.CV.SystemParams], nl_list: list[NeighbourList] | None, chunk_size=None, prescale=True, postscale=True, jac=jacrev, *fit_args, **fit_kwargs) → tuple[IMLCV.base.CV.CV, IMLCV.base.CV.CollectiveVariable][source]#

post_fit(y: list[IMLCV.base.CV.CV], scale) → tuple[IMLCV.base.CV.CV, IMLCV.base.CV.CvTrans][source]#

class IMLCV.base.CVDiscovery.CVDiscovery(transformer: Transformer)[source]#

convert set of coordinates to good collective variables.

data_loader(rounds: IMLCV.base.rounds.Rounds, num=4, out=-1, split_data=False, new_r_cut=None) → tuple[list[IMLCV.base.CV.SystemParams], list[NeighbourList] | None, IMLCV.base.CV.CollectiveVariable, IMLCV.base.MdEngine.StaticTrajectoryInfo][source]#

compute(rounds: IMLCV.base.rounds.Rounds, num_rounds=4, samples=3000.0, plot=True, new_r_cut=None, chunk_size=None, split_data=False, name=None, **kwargs) → IMLCV.base.CV.CollectiveVariable[source]#

static plot_app(sps: IMLCV.base.CV.SystemParams, nl: IMLCV.base.CV.NeighbourList, old_cv: IMLCV.base.CV.CollectiveVariable, new_cv: IMLCV.base.CV.CollectiveVariable, name, labels=None, chunk_size: int | None = None)[source]#