Static and dynamical isomerization of Cu38 cluster ... - Nature
May 20, 2019 · In this study, we first adopt a genetic algorithm combined with the Gupta interatomic many-body potential to get a number of initial structures of Cu 38 cluster, and followed by DFT...
2.3. Clustering — scikit-learn 1.8.0 documentation
Non-flat geometry clustering is useful when the clusters have a specific shape, i.e. a non-flat manifold, and the standard euclidean distance is not the right metric. This case arises in the two top rows of …
Clustering package (scipy.cluster) — SciPy v1.17.0 Manual
Its features include generating hierarchical clusters from distance matrices, calculating statistics on clusters, cutting linkages to generate flat clusters, and visualizing clusters with dendrograms.
SpectralClustering — scikit-learn 1.8.0 documentation
In contrast to k-means and discretization, cluster_qr has no tuning parameters and runs no iterations, yet may outperform k-means and discretization in terms of both quality and speed.
Cluster analysis — OVITO User Manual 3.14.1 documentation
A cluster is defined as a set of connected particles, where each particle is within the (indirect) reach of the others in the same cluster. In other words, any two particles within a cluster are connected by a …
fcluster — SciPy v1.17.0 Manual
Forms a flat cluster from a cluster node c with index i when monocrit[j] <= t. Forms a flat cluster from a non-singleton cluster node c when monocrit[i] <= r for all cluster indices i below and including c. r is …
AgglomerativeClustering — scikit-learn 1.8.0 documentation
Computes distances between clusters even if distance_threshold is not used. This can be used to make dendrogram visualization, but introduces a computational and memory overhead.