floyd: Shortest Path Distances

In spa: Implements The Sequential Predictions Algorithm

Description

‘uDist’ Computing shortest path distance (hop count) for an unweighted similarity graph where 1=edge and 0=no edge (i.e. invoke knnGraph with weight=FALSE)

‘floyd’ Floyd's algorithm (SLOW) for computing shortest path distances (weighted hop count) for distance weighted graphs (i.e. invoke knnGraph with weight=TRUE).

Usage

floyd(x,verbose=FALSE)

uDist(g, k)

Arguments

x	the adjacency n by n matrix (distance weighted)
verbose	print the progress for Floyd's algorithm
g	the adjacency n by n matrix (unweighted)
k	input parameter for determining the maximum distance to compute (a distance of greater than k is taken as infinity)

Details

These implementations are not yet optimized for large data sets (>5000 observations)

Value

D	Distance Matrix n by n

Author(s)

Mark Culp

See Also

spa knnGraph epsGraph

spa documentation built on May 30, 2017, 1:27 a.m.