computeNL {TDAvec} | R Documentation |
A Vector Summary of the Normalized Life Curve
Description
For a given persistence diagram D=\{(b_i,d_i)\}_{i=1}^N
, computeNL()
vectorizes the normalized life (NL) curve
sl(t)=\sum_{i=1}^N \frac{d_i-b_i}{L}\bold{1}_{[b_i,d_i)}(t),
where L=\sum_{i=1}^N (d_i-b_i)
. Points of D
with infinite death value are ignored
Usage
computeNL(D, homDim, scaleSeq)
Arguments
D |
matrix with three columns containing the dimension, birth and death values respectively |
homDim |
homological dimension (0 for |
scaleSeq |
numeric vector of increasing scale values used for vectorization |
Value
A numeric vector whose elements are the average values of the persistent entropy summary function computed between each pair of consecutive scale points of scaleSeq
=\{t_1,t_2,\ldots,t_n\}
:
\Big(\frac{1}{\Delta t_1}\int_{t_1}^{t_2}sl(t)dt,\frac{1}{\Delta t_2}\int_{t_2}^{t_3}sl(t)dt,\ldots,\frac{1}{\Delta t_{n-1}}\int_{t_{n-1}}^{t_n}sl(t)dt\Big),
where \Delta t_k=t_{k+1}-t_k
Author(s)
Umar Islambekov
References
Chung, Y. M., & Lawson, A. (2022). Persistence curves: A canonical framework for summarizing persistence diagrams. Advances in Computational Mathematics, 48(1), 1-42.
Examples
N <- 100
set.seed(123)
# sample N points uniformly from unit circle and add Gaussian noise
X <- TDA::circleUnif(N,r=1) + rnorm(2*N,mean = 0,sd = 0.2)
# compute a persistence diagram using the Rips filtration built on top of X
D <- TDA::ripsDiag(X,maxdimension = 1,maxscale = 2)$diagram
scaleSeq = seq(0,2,length.out=11) # sequence of scale values
# compute NL for homological dimension H_0
computeNL(D,homDim=0,scaleSeq)
# compute NL for homological dimension H_1
computeNL(D,homDim=1,scaleSeq)