computeLimits | R Documentation |
Given a list of persistence diagrams, computeLimits()
computes the extreme values of birth, death, and persistence across all diagrams for a specified homological dimension. Points with infinite death values are ignored.
computeLimits(Dlist, homDim)
Dlist |
a list of persistence diagrams, where each diagram is a matrix containing three columns representing homological dimension, birth, and death values. |
homDim |
the homological dimension (0 for |
A (named) numeric vector containing:
minB
: the minimum birth value across all diagrams.
maxB
: the maximum birth value across all diagrams.
maxD
: the maximum death value across all diagrams.
minP
: the minimum persistence value across all diagrams.
maxP
: the maximum persistence value across all diagrams.
Umar Islambekov
set.seed(123)
N <- 100 # The size of point clouds
nD <- 50 # The number of persistence diagrams
Dlist <- list()
for (i in 1:nD){
# sample N points uniformly from the unit circle and add Gaussian noise
theta <- runif(N, min = 0, max = 2 * pi)
X <- cbind(cos(theta), sin(theta)) + rnorm(2 * N, mean = 0, sd = 0.2)
# Compute the persistence diagram using the Rips filtration built on top of X
# The 'threshold' parameter specifies the maximum distance for building simplices
Dlist[[i]] <- TDAstats::calculate_homology(X, threshold = 2)
}
# Compute the extreme values of birth, death, and persistence across
# all 50 diagrams for homological dimension H_0
computeLimits(Dlist, homDim = 0)
# Compute the extreme values of birth, death, and persistence across
# all 50 diagrams for homological dimension H_1
computeLimits(Dlist, homDim = 1)
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