Index

_

__init__() (pgcuts.losses.HyCutLoss method) (pgcuts.losses.pncut.NCutLoss method) (pgcuts.losses.pncut.RatioCutLoss method) (pgcuts.losses.PRCutBatchLoss method) (pgcuts.optim.GradientMixer method) (pgcuts.utils.data.ShuffledRangeDataset method)

A

ari_score() (in module pgcuts.metrics) assign_clusters() (in module pgcuts.metrics)

assign_unique_clusters() (in module pgcuts.metrics) attach() (pgcuts.optim.GradientMixer method)

B

backward() (pgcuts.hyp2f1.Hyp2F1 static method)

build_rbf_knn_graph() (in module pgcuts.graph)

C

cluster_acc_score() (in module pgcuts.metrics) cluster_likelihood (pgcuts.losses.PRCutBatchLoss property) compute_ncut_bin_phi() (in module pgcuts.losses.pncut)

compute_phi() (pgcuts.losses.pncut.NCutLoss method) compute_rcut_ncut() (in module pgcuts.metrics) compute_sp_similarities() (in module pgcuts.graph)

D

detach() (pgcuts.optim.GradientMixer method)

E

equal_size_bins() (in module pgcuts.losses.pncut)

evaluate_clustering() (in module pgcuts.metrics)

F

forward() (pgcuts.hyp2f1.Hyp2F1 static method) (pgcuts.losses.HyCutLoss method) (pgcuts.losses.pncut.NCutLoss method) (pgcuts.losses.pncut.RatioCutLoss method) (pgcuts.losses.PRCutBatchLoss method) (pgcuts.losses.PRCutGradLoss method) (pgcuts.losses.SimplexL2Loss method)

G

gaussian_rbf_kernel() (in module pgcuts.graph) get_knn_distances() (in module pgcuts.graph)

get_pairs_unique_map() (in module pgcuts.utils.pairs) GradientMixer (class in pgcuts.optim)

H

HyCutLoss (class in pgcuts.losses)

Hyp2F1 (class in pgcuts.hyp2f1)

K

knn_graph() (in module pgcuts.graph)

L

log_kmeans_bins() (in module pgcuts.losses.pncut)

M

make_grad_scaler_hook() (pgcuts.optim.GradientMixer static method)

N

NCutLoss (class in pgcuts.losses.pncut)

nmi_score() (in module pgcuts.metrics)

P

PRCutBatchLoss (class in pgcuts.losses)

PRCutGradLoss (class in pgcuts.losses)

R

ratio_cut_score() (in module pgcuts.metrics)

RatioCutLoss (class in pgcuts.losses.pncut)

S

shuffle() (pgcuts.utils.data.ShuffledRangeDataset method) ShuffledRangeDataset (class in pgcuts.utils.data) SimplexL2Loss (class in pgcuts.losses) soft_ncut() (in module pgcuts.metrics)

soft_rcut() (in module pgcuts.metrics) sp_knn_similarity() (in module pgcuts.graph) sparse_laplacian() (in module pgcuts.graph) symmetrize() (in module pgcuts.graph)

T

torch_knn_similarity() (in module pgcuts.graph)

torch_pairwise_similarities() (in module pgcuts.graph)

U

update_cluster_p() (pgcuts.losses.PRCutBatchLoss method)