View source: R/vietoris_rips.R
| vietoris_rips | R Documentation | 
This function is an R wrapper for the Ripser C++ library to
calculate persistent homology. For more information on the C++ library, see
https://github.com/Ripser/ripser. For more information on how objects of
different classes are evaluated by vietoris_rips, read the Details
section below.
vietoris_rips(dataset, ...)
## S3 method for class 'data.frame'
vietoris_rips(dataset, ...)
## S3 method for class 'matrix'
vietoris_rips(dataset, max_dim = 1L, threshold = -1, p = 2L, dim = NULL, ...)
## S3 method for class 'dist'
vietoris_rips(dataset, max_dim = 1L, threshold = -1, p = 2L, dim = NULL, ...)
## S3 method for class 'numeric'
vietoris_rips(
  dataset,
  data_dim = 2L,
  dim_lag = 1L,
  sample_lag = 1L,
  method = "qa",
  ...
)
## S3 method for class 'ts'
vietoris_rips(dataset, ...)
## Default S3 method:
vietoris_rips(dataset, ...)
dataset | 
 object on which to calculate persistent homology  | 
... | 
 other relevant parameters  | 
max_dim | 
 maximum dimension of persistent homology features to be calculated  | 
threshold | 
 maximum simplicial complex diameter to explore  | 
p | 
 prime field in which to calculate persistent homology  | 
dim | 
 deprecated; passed to   | 
data_dim | 
 desired end data dimension  | 
dim_lag | 
 time series lag factor between dimensions  | 
sample_lag | 
 time series lag factor between samples (rows)  | 
method | 
 currently only allows   | 
vietoris_rips.data.frame assumes dataset is a point cloud, with each row
representing a point and each column representing a dimension.
vietoris_rips.matrix currently assumes dataset is a point cloud (similar
to vietoris_rips.data.frame). Currently in the process of adding network
representation to this method.
vietoris_rips.dist takes a dist object and calculates persistent homology
based on pairwise distances. The dist object could have been calculated
from a point cloud, network, or any object containing elements from a finite
metric space.
vietoris_rips.numeric and vietoris_rips.ts both calculate persistent
homology of a time series object. The time series object is converted to a
matrix using the quasi-attractor method detailed in Umeda (2017)
doi:10.1527/tjsai.D-G72. Persistent homology of the resulting matrix is
then calculated.
PHom object
# create a 2-d point cloud of a circle (100 points)
num.pts <- 100
rand.angle <- runif(num.pts, 0, 2*pi)
pt.cloud <- cbind(cos(rand.angle), sin(rand.angle))
# calculate persistent homology (num.pts by 3 numeric matrix)
pers.hom <- vietoris_rips(pt.cloud)
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