% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Filtration.R
\name{build_filtration}
\alias{build_filtration}
\title{Build a filtration from a point cloud, for any of five complex types}
\usage{
build_filtration(
  points,
  method = c("VR", "Delaunay", "Alpha", "Cech", "Witness"),
  eps_max = NULL,
  landmarks = NULL,
  nu = 1,
  max_dimension = NULL
)
}
\arguments{
\item{points}{A numeric matrix or data.frame, one point per row.}

\item{method}{One of \code{"VR"}, \code{"Delaunay"}, \code{"Alpha"},
\code{"Cech"}, \code{"Witness"}.}

\item{eps_max}{Maximum scale. Required for \code{"VR"}, \code{"Cech"} and
\code{"Witness"}; for \code{"Alpha"} it caps the alpha value (defaults
to \code{Inf}, i.e. no cap); ignored for \code{"Delaunay"} (which has no
scale parameter - see \code{\link{DelaunayComplex}}).}

\item{landmarks}{For \code{method = "Witness"} only: either an integer
(number of landmarks to select via \code{\link{generate_landmarks}}) or
an integer vector of landmark row indices into \code{points}. Required
for \code{"Witness"}.}

\item{nu}{For \code{method = "Witness"} only: the landmark-distance
parameter passed to \code{\link{WitnessComplex}}. Defaults to \code{1}.}

\item{max_dimension}{Optional maximum homology dimension you intend to
compute persistence for.}
}
\value{
A filtration list, as described above. When \code{max_dimension}
  is set, the list carries it as a \code{"max_dimension"} attribute (see
  above); otherwise the attribute is absent, exactly as before this
  parameter existed.
}
\description{
Build a filtration from a point cloud, for any of five complex types
}
\examples{
points <- matrix(c(0, 1, 1, 0, 0, 0, 1, 1), ncol = 2)
vr_filtration <- build_filtration(points, method = "VR", eps_max = 1.2)
alpha_filtration <- build_filtration(points, method = "Alpha")
delaunay_filtration <- build_filtration(points, method = "Delaunay")
cech_filtration <- build_filtration(points, method = "Cech", eps_max = 0.8)
# cap at H1: persistence_pairs()/etc. need no max_dimension of their own
vr_capped <- build_filtration(points, method = "VR", eps_max = 1.2,
                               max_dimension = 1)
pairs <- persistence_pairs(vr_capped)
}
