Description Usage Arguments Examples
Function for computing Gromov-Wasserstein distance between metric measure spaces.
1 | gwDist(initial_values,d_X,d_Y,mu_X,mu_Y,tol = 0.001, p = 1)
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initial_values |
initial values for solving initial LOP's |
d_X |
metric of first metric measure space |
d_Y |
metric of second metric measure space |
mu_X |
probability measure of first metric measure space |
mu_Y |
probability measure of second metric measure space |
tol |
tolerance |
p |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | library(gwDist)
# load metric measure spaces of 3D animal data into worksapce
data(mmspaces_3D)
# subset of metric measure spaces
mm_sub <- mmspaces_3D[c(12:16,61:65)]
# compute GW distance between 10 objects selected
gw_mat <- matrix(nrow = length(mm_sub), ncol = length(mm_sub))
for(i in 1:length(mm_sub))
{
X <- mm_sub[[i]]$points
d_X <- mm_sub[[i]]$dist
mu_X <- mm_sub[[i]]$prob
for(j in i:length(mm_sub))
{
Y <- mm_sub[[j]]$points
d_Y <- mm_sub[[j]]$dist
mu_Y <- mm_sub[[j]]$prob
# compute initial values using solve_FLB_Rglpk
sol <- solve_FLB_Rglpk(X,Y,d_X,d_Y,mu_X,mu_Y)$solution
# compute Gromov-Wasserstein distance
gw_mat[i,j] <- gwDist(sol, d_X, d_Y, mu_X, mu_Y)$optimum
gw_mat[j,i] <- gw_mat[i,j]
}
}
rownames(gw_mat) <- colnames(gw_mat) <- names(mm_sub)
heatmap(gw_mat)
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