The OptArgs
object
run_treeknit!
and several other functions take an OptArgs
object that controls several parameters of the inference process.
TreeKnit.OptArgs
— Typestruct OptArgs
Storing parameters for SplitGraph.runopt
function.
General
γ::Float64 = 2
itmax::Int64 = 15
: maximal number of iterations of naive MCCs / SA cycles.likelihood_sort::Bool = true
: sort equivalent configurations using likelihood test based on branch length.resolve::Bool = true
: try to resolve trees while finding MCCs.strict::Bool = true
: only resolve unambiguous splitsseq_lengths
: lengths of sequences that trees were built from. Used in likelihood calculations. This is initialized from other input arguments, and defaults to sequences of length one.
Pipeline options - necessary for K>2 trees
pre_resolve::Bool = true
: pre-resolve all trees using each other prior to MCC inferencerounds::Int=1
: #rounds of MCC inference and tree resolution on all tree pairsfinal_no_resolve::Bool = false
: do not resolve in the final round of pair-wise MCC inferenceparallel::Bool = false
: parallelize MCC inference as much as possible.
Simulated annealing
nMCMC::Int = 25
: The total number of MCMC steps (swaps) for a tree ofn
leaves isnMCMC*n
. The number of MCMC steps at one temperature isnMCMC * n / nT
.cooling_schedule = :geometric
: type of cooling schedule(:geometric, :linear, :acos)
Tmin::Float64 = 0.05
: minimal temperature of SA.Tmax::Float64 = 0.8
: maximal temperature of SA.nT::Int = 3000
: number of steps in the cooling schedule
The MCC_set
object
We define an MCC_set
object to store the inferred MCCs of multiple trees.
TreeKnit.MCC_set
— Typestruct MCC_set
structure to store and access computed MCCs for tree pairs
no_trees
: number of treesorder_trees
: vector of tree labels.mccs
: Dictionary of calculated mccs, key is set of labels of trees in each tree pair
Add and retrieve mccs with get!
and add!
and Tuple or Vararg of tree labels or position of tree labels in order_trees