Enumerate all the possible regime allocations, given a clustering of the tips.

enumerate_parsimony enumerate all the equivalent allocation of the regimes in the tree, a clustering of the tips being given. The number of such equivalent regimes is given by parsimonyNumber (which is faster).

enumerate_parsimony(phylo, clusters = rep(1, length(phylo$tip.label)))

Arguments

phylo

a phylogenetic tree, class phylo.

clusters

a vector representing the group of each tip. (Default to only one group with all the tips.)

Value

an S3 object of class "enumerate_parsimony", with:

nbrReconstructions

an object of class "parsimonyCost", result of function parsimonyCost.

allocations

a list of size Nnode + ntaxa. Each entry i of the list represents the solutions for the subtree starting at node i. It is a list with nclus entries, each entry being a matrix. A line of the kth matrix for the ith node is one possible allocation of the shifts, starting with regime k for node i.

phylo

the entry phylogenetic tree

Details

Function extract.enumerate_parsimony furnishes the result in a human readable form (for any subtree). Function plot.enumerate_parsimony plots all the solutions found on the tree.

See also

extract.enumerate_parsimony, plot.enumerate_parsimony, parsimonyCost, parsimonyNumber, partitionsNumber, equivalent_shifts

Examples

tree <- read.tree(text="(((A,B),C),D);")
plot(tree)

clusters <- c(0, 1, 2, 2)
sols <- enumerate_parsimony(tree, clusters)
plot(sols)


## Extract the parsimonious solutions from the root
extract(sols) # each line is a solution, with states of each node
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,]    0    1    2    2    2    2    0
#> [2,]    0    1    2    2    2    2    1
#> [3,]    0    1    2    2    2    2    2

## Extract the number of solutions from the root
extract(sols, what = "number")
#> [1] 3
extract(parsimonyNumber(tree, clusters)) # same result, more efficient
#> [1] 3

## Extract the cost of the solutions from the root
extract(sols, what = "cost")
#> [1] 2
extract(parsimonyCost(tree, clusters)) # same result, more efficient:
#> [1] 2

## Extract for the sub-tree below node 7
extract(sols, 7) # NAs: non-existing nodes in the sub-tree
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#> [1,]    0    1   NA   NA   NA   NA    0
#> [2,]    0    1   NA   NA   NA   NA    1