Python package which implements split- and rank-based tools for inferring phylogenies, such as flattenings and subflattenings.
Installation
The latest version of SplitP can be installed via the command
pip install splitp
Examples
Import splitp and the associated helper functions
import splitp as sp
from splitp import tree_helper_functions as hfDefine trees and work with splits
splits = list(hf.all_splits(4)) # [01|23, 02|13, 03|12]
tree = sp.NXTree('((0,1),(2,3));')
true_splits = tree.true_splits() # 01|23Let site patterns evolve under any submodel of the general markov model.
JC_subs_matrix = tree.build_JC_matrix(branch_length:=0.05)
tree.reassign_all_transition_matrices(JC_subs_matrix)
pattern_probs = tree.get_pattern_probabilities()> 0 1
0 AAAA 0.185844
1 AAAC 0.003262
.. ... ...
254 TTTG 0.003262
255 TTTT 0.185844Simulate sequence alignments from pattern distributions
pattern_frequencies = tree.draw_from_multinomial(pattern_probs, 100)> 0 1
0 AAAA 0.22
1 AAAC 0.01
.. ... ...
2 CCGC 0.03
3 TTTT 0.14Reconstruct trees using split based methods including flattenings:
F1 = tree.flattening('01|23', pattern_frequencies)
F2 = tree.flattening('02|13', pattern_frequencies)
print(tree.split_score(F1) < tree.split_score(F2)) # TrueOr subflattenings:
SF = tree.signed_sum_subflattening('01|23', pattern_probs)
print(tree.split_score(SF)) # 0.0For more functionality please see the documentation at splitp.joshuastevenson.me.
Please see CONTRIBUTING.md for information on contributing to this project.
