dislib.cluster.Daura¶
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class
dislib.cluster.daura.base.
Daura
(cutoff)[source]¶ Bases:
sklearn.base.BaseEstimator
Daura clustering.
Distributed implementation of the distances-based Daura clustering, introduced on Daura et al. [1]. A description of the algorithm can be found on:Parameters: cutoff (float) – Distance to determine the neighbors of a sample. References
[1] Daura, X., Gademann, K., Jaun, B., Seebach, D., van Gunsteren, W.F. and Mark, A.E. (1999). Peptide Folding: When Simulation Meets Experiment. In Angewandte Chemie International Edition, 38 (pp. 236-240). -
fit_predict
(distances)[source]¶ Compute Daura clustering.
Parameters: distances (ds-array (n_samples, n_samples)) – Pairwise distances between the samples. Returns: clusters – A list of clusters. Each cluster is a list of sample indices, starting with the cluster center. Return type: List[ List[ int ] ]
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