def mercat_compute_alpha_beta_diversity(counts,bif):
abm = dict()
abm['shannon'] = skbio_alpha.shannon(counts)
abm['simpson'] = skbio_alpha.simpson(counts)
abm['simpson_e'] = skbio_alpha.simpson_e(counts)
abm['goods_coverage'] = skbio_alpha.goods_coverage(counts)
abm['fisher_alpha'] = skbio_alpha.fisher_alpha(counts)
abm['dominance'] = skbio_alpha.dominance(counts)
abm['chao1'] = skbio_alpha.chao1(counts)
abm['chao1_ci'] = skbio_alpha.chao1_ci(counts)
abm['ace'] = skbio_alpha.ace(counts)
with open(bif + "_diversity_metrics.txt", 'w') as dmptr:
for abmetric in abm:
dmptr.write(abmetric + " = " + str(abm[abmetric]) + "\n")
def test_goods_coverage(self):
counts = [1] * 75 + [2, 2, 2, 2, 2, 2, 3, 4, 4]
obs = goods_coverage(counts)
self.assertAlmostEqual(obs, 0.23469387755)
def test_goods_coverage(self):
counts = [1] * 75 + [2, 2, 2, 2, 2, 2, 3, 4, 4]
obs = goods_coverage(counts)
self.assertAlmostEqual(obs, 0.23469387755)