leastCostPathNoBlocks: Extracts the least-cost from a least cost matrix by trimming...

In distantia: Assessing Dissimilarity Between Multivariate Time Series

Description

Extracts the minimum cost of a least-cost path by trimming blocks (straight segments of the path that appear in highly dissimilar regions of the sequences). Blocks inflate psi values when two sequences are similar but have very different numbers of rows. This function is for internal use of other functions in the package.

Usage

leastCostPathNoBlocks(
  least.cost.path = NULL,
  parallel.execution = TRUE
  )

Arguments

least.cost.path	dataframe produced by leastCostPath.
parallel.execution	boolean, if TRUE (default), execution is parallelized, and serialized if FALSE.

Value

A named list with least cost values.

Examples

#'#loading data
data(sequenceA)
data(sequenceB)

#preparing datasets
AB.sequences <- prepareSequences(
 sequence.A = sequenceA,
 sequence.A.name = "A",
 sequence.B = sequenceB,
 sequence.B.name = "B",
 merge.mode = "complete",
 if.empty.cases = "zero",
 transformation = "hellinger"
 )

#computing distance matrix
AB.distance.matrix <- distanceMatrix(
 sequences = AB.sequences,
 grouping.column = "id",
 method = "manhattan",
 parallel.execution = FALSE
 )

#computing least cost matrix
AB.least.cost.matrix <- leastCostMatrix(
 distance.matrix = AB.distance.matrix,
 diagonal = FALSE,
 parallel.execution = FALSE
 )

AB.least.cost.path <- leastCostPath(
 distance.matrix = AB.distance.matrix,
 least.cost.matrix = AB.least.cost.matrix,
 parallel.execution = FALSE
 )

AB.least.cost.path.nb <- leastCostPathNoBlocks(
 least.cost.path = AB.least.cost.path,
 parallel.execution = FALSE
 )

distantia documentation built on Oct. 30, 2019, 10:05 a.m.