Toy implementation of Bayesian phylogenetic analysis algorithms for learning purposes and experimentation with the method.

• Loading a phylogenetic tree in Newick format
• The Mk constant-rates model
• Felsenstein’s pruning algorithm for efficiently computing likelihoods
• Estimation of Mk model Q parameter using Metropolis algorithm:

INFO    P = 0.9255830319969596, L = 0.0015366202831402559
┌────────────────────────────────────────────────────────────────────────────────┐
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│▐█▟▝████▐▌▌██████▛██▟████ ▌ ███▌████████▐█▐██▌██████████▐██▜▌██▄███▌█▜▌█▌▌██████│ 
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│▝▌  ▌ ▐▌    ▐   ▝   ▐     █  ▌▐ ▐ ▐  ▐▘▌ ▌ ▌█   ▌             ▐          ▐▌    ▐│ 0.8
││▌  ▌  ▌    ▝       ▐     █  ▌▐ ▐ ▐  ▐   ▌  ▐   ▌             ▐          ▐▌    ▐│ 
││   ▘  ▌                  █  ▌  ▐    ▐   ▌  ▐   ▌             ▐          ▐▌    ▝│ 
││      ▌                  ▘     ▐    ▐   ▌      ▌             ▐          ▐      │ 
││      ▌                        ▐    ▐          ▌             ▐          ▐      │ 0.7
││                                    ▐          ▌                        ▐      │ 
││                                    ▐                                   ▐      │ 
││                                                                        ▐      │ 
└────────────────────────────────────────────────────────────────────────────────┘
 0                 1,000               2,000              3,000               4,000

• More models, such as Yule and Birth/Death
• Simultaneous estimation of topology, branch lengths and multiple model parameters
• Generation of animated visualisations for educational purposes
• Features specific to phylolinguistics?
• More speed, most probably via a rewrite in Nim or good old CL. Matrix exponentiation with Scipy is really slow for some reason

Contains test data from [Phylogenetic Comparative Methods](https://lukejharmon.github.io/pcm/chapters/) by Luke J. Harmon. This is a great book and is helping me a lot