`leastCostPath.Rd`

Uses the original distance matrix created by `distanceMatrix`

and the least cost path matrix created by `leastCostMatrix`

to find the least cost path between the first and the last cells of the matrix. If `diagonal`

was `TRUE`

in `leastCostMatrix`

, then it must be `TRUE`

when using this function. Otherwise, the default is `FALSE`

in both.

leastCostPath( distance.matrix = NULL, least.cost.matrix = NULL, diagonal = FALSE, parallel.execution = TRUE )

distance.matrix | numeric matrix or list of numeric matrices, a distance matrix produced by |
---|---|

least.cost.matrix | numeric matrix or list of numeric matrices produced by |

diagonal | boolean, if |

parallel.execution | boolean, if |

Alist of dataframes if `least.cost.matrix`

is a list, or a dataframe if `least.cost.matrix`

is a matrix. The dataframe/s have the following columns:

*A*row/sample of one of the sequences.*B*row/sample of one the other sequence.*distance*distance between both samples, extracted from`distance.matrix`

.*cumulative.distance*cumulative distance at the samples`A`

and`B`

.

#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 ) #plot plotMatrix(distance.matrix = AB.distance.matrix, least.cost.path = AB.least.cost.path, )