#! /usr/bin/env python
# -*- coding: utf-8 -*-
import dendropy
from dendropy.calculate import treemeasure
trees = dendropy.TreeList.get(
path="pythonidae.beast-mcmc.trees",
schema="nexus",
tree_offset=200)
pbhg = []
for idx, tree in enumerate(trees):
pbhg.append(treemeasure.pybus_harvey_gamma(tree))
print("Mean Pybus-Harvey-Gamma: %s" \
% (float(sum(pbhg))/len(pbhg)))
import dendropy
from dendropy.calculate import treemeasure
from dendropy.calculate import statistics
# Since we do not want to waste memory by keeping the actual trees around
# after we are done calculating the statistics, we use the tree yielder
# instead of:
# dendropy.TreeList.get(
# path="pythonidae.beast-mcmc.trees",
# schema="nexus",
# tree_offset=200)
tree_stats = collections.defaultdict(list)
for tree_idx, tree in enumerate(
dendropy.Tree.yield_from_files(files=["pythonidae.beast-mcmc.trees"],
schema="nexus")):
if tree_idx < 200:
continue # burnin
tree_stats["B1"].append(treemeasure.B1(tree))
tree_stats["colless"].append(treemeasure.colless_tree_imbalance(tree))
tree_stats["PBH"].append(treemeasure.pybus_harvey_gamma(tree))
tree_stats["sackin"].append(treemeasure.sackin_index(tree))
tree_stats["treeness"].append(treemeasure.treeness(tree))
for key in tree_stats:
values = tree_stats[key]
mean, var = statistics.mean_and_sample_variance(values)
hpd = statistics.empirical_hpd(values)
print("{:15}: mean = {}, variance = {}, hpd = ({}, {})".format(
key, mean, var, hpd[0], hpd[1]))
import collections
import dendropy
from dendropy.calculate import treemeasure
from dendropy.calculate import statistics
# Since we do not want to waste memory by keeping the actual trees around
# after we are done calculating the statistics, we use the tree yielder
# instead of:
# dendropy.TreeList.get(
# path="pythonidae.beast-mcmc.trees",
# schema="nexus",
# tree_offset=200)
tree_stats = collections.defaultdict(list)
for tree_idx, tree in enumerate(dendropy.Tree.yield_from_files(
files=["pythonidae.beast-mcmc.trees"],
schema="nexus")):
if tree_idx < 200:
continue # burnin
tree_stats["B1"].append(treemeasure.B1(tree))
tree_stats["colless"].append(treemeasure.colless_tree_imbalance(tree))
tree_stats["PBH"].append(treemeasure.pybus_harvey_gamma(tree))
tree_stats["sackin"].append(treemeasure.sackin_index(tree))
tree_stats["treeness"].append(treemeasure.treeness(tree))
for key in tree_stats:
values = tree_stats[key]
mean, var = statistics.mean_and_sample_variance(values)
hpd = statistics.empirical_hpd(values)
print("{:15}: mean = {}, variance = {}, hpd = ({}, {})".format(key, mean, var, hpd[0], hpd[1]))
#! /usr/bin/env python
import dendropy
from dendropy.calculate import treemeasure
trees = dendropy.TreeList.get(path="pythonidae.beast-mcmc.trees",
schema="nexus",
tree_offset=200)
pbhg = []
for idx, tree in enumerate(trees):
pbhg.append(treemeasure.pybus_harvey_gamma(tree))
print("Mean Pybus-Harvey-Gamma: %s" \
% (float(sum(pbhg))/len(pbhg)))
