n = 300; noise = 0.05; seed = 1782;
theta <- seq(0, pi, length.out = n / 2)
x1 <- cos(theta) + rnorm(n / 2, sd = noise)
y1 <- sin(theta) + rnorm(n / 2, sd = noise)
x2 <- cos(theta + pi) + rnorm(n / 2, sd = noise)
y2 <- sin(theta + pi) + rnorm(n / 2, sd = noise)
X <- rbind(cbind(x1, y1), cbind(x2, y2))
y <- c(rep(0, n / 2), rep(1, n / 2))
nfeatures <- ncol(X)
i <- 1
clusters <- unique(y)
objcl <- which(y == clusters[i])
nuobjcl <- length(objcl)
noiseLabel <- -1
distX <- as.matrix(dist(X))^2
distXy <- distX[y != noiseLabel, y != noiseLabel]
mr <- matrix_mutual_reachability_distance(nuobjcl, distXy[objcl, objcl], nfeatures)
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