trop.tri.plot.w.pts: Plotting PCA-derived tropical triangles

In TML: Tropical Geometry Tools for Machine Learning

Plotting PCA-derived tropical triangles

Description

This function conducts tropical PCA to find the best fit tropical triangle given data defined in the tropical projective torus. It employs the vertex HAR with extrapolation sampler to sample points to determine the vertices of the tropical triangle.

Usage

trop.tri.plot.w.pts(S, D)

Arguments

S	inital set of vertices for the tropical triangle
D	matrix of data where each row is an observation in the tropical projective torus

Value

rendering of tropical triangle saved to current directory

Author(s)

Ruriko Yoshida [e-mail]

Examples

s <- 3 #number of vertices.  Here it is a tropical triangle
d <- 3 ## dimension
N <- 100 ## sample size
V <- matrix(c(100, 0, 0, 0, 100, 0, 0, 0, 100, -100, 0, 0, 0, -100, 0, 0, 0, -100), 6, 3, TRUE)
D <- matrix(rep(0, N*d), N, d)
D[, 1] <- rnorm(N, mean = 5, sd = 5)
D[, 2] <- rnorm(N, mean = -5, sd = 5)
D[, 3] <- rnorm(N, mean = 0, sd = 5)
index <- sample(1:N, s)
S <- D[index,]
res <- tropical.PCA.Polytope(S, D, V, I = 1000,50)
DD <- pre.pplot.pro(res[[2]], res[[3]])
trop.tri.plot.w.pts(normaliz.ultrametrics(res[[2]]), DD)

TML documentation built on Sept. 11, 2024, 6:19 p.m.