Solver

CassiopeiaSolvers

We have several algorithms available for solving phylogenies:

solver.HybridSolver(top_solver, bottom_solver)	The Hybrid Cassiopeia solver.
solver.ILPSolver([convergence_time_limit, ...])	The Cassiopeia ILP-based maximum parsimony solver.
solver.MaxCutSolver([sdimension, ...])	A MaxCut graph-based CassiopeiaSolver.
solver.MaxCutGreedySolver([...])	A CassiopeiaGreedy solver with the max cut criterion.
solver.NeighborJoiningSolver([...])	Neighbor-Joining class for Cassiopeia.
solver.PercolationSolver(joining_solver[, ...])	A top-down percolatin-based CassiopeiaSolver.
solver.SharedMutationJoiningSolver([...])	Shared-Mutation-Joining class for Cassiopeia.
solver.SpectralSolver([similarity_function, ...])	A spectral-based CassiopeiaSolver.
solver.SpectralGreedySolver([...])	A CassiopeiaGreedy solver with a spectral heuristic.
solver.UPGMASolver([dissimilarity_function, ...])	UPGMA CassiopeiaSolver.
solver.VanillaGreedySolver([...])	A class for the basic Cassiopeia-Greedy solver.

Dissimilarity Maps

For use in our distance-based solver and for comparing character states, we also have available several dissimilarity functions:

solver.dissimilarity_functions.cluster_dissimilarity(...)	Compute the dissimilarity between (possibly) ambiguous character strings.
solver.dissimilarity_functions.hamming_distance(s1, s2)	Computes the vanilla hamming distance between two samples.
solver.dissimilarity_functions.hamming_similarity_normalized_over_missing(s1, ...)	A function to return the number of (non-missing) character/state mutations shared by two samples, normalized over the amount of missing data.
solver.dissimilarity_functions.hamming_similarity_without_missing(s1, ...)	A function to return the number of (non-missing) character/state mutations shared by two samples.
solver.dissimilarity_functions.weighted_hamming_distance(s1, s2)	Computes the weighted hamming distance between samples.
solver.dissimilarity_functions.weighted_hamming_similarity(s1, ...)	A function to return the weighted number of (non-missing) character/state mutations shared by two samples.