API Reference

Set Cover (cover)

Functions to find minimum weight set covers.

cover.coverage	Returns each elements coverage by the sets given by ind.
cover.valid_cover	Determines whether given sets form a feasible cover over the universe.
cover.set_cover	Computes an approximate solution to the weighted set cover problem.
cover.set_cover_greedy	Approximates the weighted set cover problem via greedy steps.
cover.set_cover_rr	Approximates the weighted set cover problem via randomized rounding.
cover.set_cover_ilp	Approximates the weighted set cover problem via integer linear programming.
cover.set_cover_sat	Computes an approximate solution to the weighted set cover problem via weighted MaxSAT.

Linear Algebra (linalg)

Standard linear algebra algorithms.

linalg.pca	Projects X onto a d-dimensional linear subspace via Principal Component Analysis.
linalg.cmds	Constructs coordinates from squared distances using Classical Multi-Dimensional Scaling.

Geometry (geometry)

Algorithms for computing information on manifolds.

geometry.tangent_bundle	Estimates the tangent bundle of a range space (X,M) via local PCA.
geometry.bundle_weights	Computes geometrically informative statistics about a given tangent bundle.

Cluster (cluster)

Algorithms related to clustering points in metric spaces.

cluster.mean_shift

Mean shift algorithm for clustering or smoothing points via kernel density estimation.

I/O (io)

Algorithms for loading, parsing, and cleaning set cover data sets.

io.load_set_cover	Loads an instance of for testing weighted set cover algorithms.
io.to_canonical	Converts a sparse array into a supplied form, gauranteeing canonical format.
io.sets_to_sparse	Converts a collection of sets into a sparse array.
io.sparse_to_sets	Converts a collection of sets into a sparse CSC array.
io.reindex_sparse	Reindexes the indices of a given sparse array to the base index set.