multiscale.rips: Multiscale Rips Persistent Homology
In mph: Multiscale persistent homology

Description Usage Arguments Value Author(s) Examples

A multiscale approach to compute Rips persistent homology.

1	multiscale.rips.ipca( X, epsGMRA, maxD, single = FALSE )

`X`	Data set. Each row is a data point
`epsGMRA`	Accuracy of GMRA approximation
`maxD`	Highest dimensionality of simplicies to insert into the filtration
`single`	Compute single scale TRUE or FALSE

Persistent diagram, matrix with first column birth, second column death times and a third colum at which scale the death happened.

Samuel Gerber

##Noisy circle example
phi <- runif(100)*2*pi
arc <- cbind(cos(phi), sin(phi)) * (1+rnorm(length(phi)) * 0.1)

dgm <- multiscale.rips.ipca(X = arc, epsGMRA = 0, maxD = 2);

plot(x = dgm[,1], y = dgm[,2], xlim = c(0, max(dgm[,1:2]) ), ylim = c(0, max(dgm[,1:2])) ,
    asp=1, pch=19)
abline(0, 1)