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kernelTDA (version 1.0.0)

sw.kernel: Persistence Sliced Wasserstein Kernel (SWK)

Description

Computes the Persistence Sliced Wasserstein Kernel (SWK) between persistence diagrams.

Usage

sw.kernel(d1, d2 = NULL, h, dimension, M = 10)

Arguments

d1

A persistence diagram (matrix with 3 col where the first one is the dimension, the second is the birth-time and the third is the death-time) or a list of diagrams

d2

A persistence diagram (matrix with 3 col where the first one is the dimension, the second is the birth-time and the third is the death-time).

h

bandwidth of the kernel

dimension

The dimension of the topological feature (0 for connected components, 1 for cycles etc)

M

number of directions on which to approximate the Sliced Wasserstein Distance

Value

If d1 is a list of Persistence Diagrams, this function returns a matrix whose (i,j) entry is the SWK computed in (d1[[i]], d2[[j]]), otherwise it returns the value for the SWK computed in (d1, d2)

References

carriere2017slicedkernelTDA

Examples

Run this code
# NOT RUN {
diag1 <- matrix(c(1,1,1,0,2,3,2,2.5,4), ncol = 3, byrow = FALSE)
diag2 <- matrix(c(1,1,0,1,1,2), ncol = 3, byrow = FALSE)
sw.kernel(d1 = diag1, d2 = diag2, h = 1, dimension = 1)
# }

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