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This package aims to provide a user-friendly TDA application. Although many TDA libraries, such as Dionysus, PHAT, and GUDHI, have been developed in Python and C++, I believe it would be valuable to implement simplicial complex functionality in R, making it compatible with the wide range of statistical methods available in R.
Example code
# Get its' simplices by specific epsilon
<- matrix(c(0, 1, 1, 0, 0, 0, 1, 1), ncol = 2)
points <- 1.5
epsilon <- VietorisRipsComplex(points, epsilon)
vr_complex
# You can find its' topology feature by using these functions
faces(vr_complex$simplices, target_dim=1)
boundary(vr_complex$simplices, 1)
betti_number(vr_complex$simplices, 1, tol=0.1)
euler_characteristic(simplices, tol=0.1)
abstract_simplicial_complex(simplices, 2)
# Plot the Vietoris-rips complex
plot(
$network,
vr_complexlayout = points,
vertex.label = 1:nrow(points),
vertex.size = 12,
edge.arrow.mode = 0,
asp = 1
)
# Filtration, Boundary reduction, and Persistence informations
<- build_vr_filtration(points, eps_max=1.2)
F <- boundary_info(F)
res <- extract_persistence_pairs(F, res$last_1, res$pivot_owner)
pairs plot_persistence(pairs)
Playground
Try this playground
to get familier with all of the concept that will be used in TDA.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.