Identify consistent / conflicting splits

SplitConsistent() and SplitConflict() determine whether a series of splits haystack are consistent with or contradict the focal split needle.

Usage

SplitConsistent(needle, haystack)

SplitConflicts(needle, haystack)

Arguments

needle

Splits object containing the single split to evaluate

haystack

Splits object, or list thereof, containing the splits to compare against needle.

Value

SplitConsistent() returns a list of logical vectors. Each list item corresponds to an entry in haystack, reporting whether each split is consistent with (TRUE) or in conflict with (FALSE) needle. SplitConflicts() returns the inverse.

See also

Other split manipulation functions: DropTip(), Subsplit(), TrivialSplits()

Author

Martin R. Smith (martin.smith@durham.ac.uk)

Examples

splits1 <- as.Splits(BalancedTree(8))
splits2 <- as.Splits(PectinateTree(8))
summary(splits1[[4]])
#> 1 bipartition split dividing 8 tips, t1 .. t8
#>      12345678
#>  14  ....**..
#> 
#>  Tip 1: t1	 Tip 2: t2	 Tip 3: t3	 Tip 4: t4	 Tip 5: t5	
#>  Tip 6: t6	 Tip 7: t7	 Tip 8: t8	
SplitConsistent(splits1[[4]], splits2)
#> [[1]]
#> [1]  TRUE  TRUE  TRUE FALSE  TRUE
#> 
SplitConflicts(splits1[[4]], list(splits1, splits2))
#> [[1]]
#> [1] FALSE FALSE FALSE FALSE FALSE
#> 
#> [[2]]
#> [1] FALSE FALSE FALSE  TRUE FALSE
#>