def test_make_unifrac_metric2(self):
""" samples with no seqs, and identical samples, should behave correctly
"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
otu_data = numpy.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0], #sam1 zeros
[4, 2, 0, 0, 0, 1, 0, 0, 0],
[2, 4, 0, 0, 0, 1, 0, 0, 0],
[1, 7, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 7, 1, 0, 0, 0, 0, 0, 0],
[0, 4, 2, 0, 0, 0, 2, 0, 0],
[0, 2, 4, 0, 0, 0, 1, 0, 0],
[0, 1, 7, 0, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 1, 0, 0, 0, 0, 0],
[0, 0, 4, 2, 0, 0, 0, 3, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0], #sam14 zeros
[0, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0], #sam 16 now like sam 13
[0, 0, 0, 4, 2, 0, 0, 0, 4],
[0, 0, 0, 2, 4, 0, 0, 0, 1],
[0, 0, 0, 1, 7, 0, 0, 0, 0]
])
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree, self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 13], 0.0)
self.assertEqual(res[12, 15], 0.0)
self.assertEqual(res[0, 1], 1.0)
warnings.resetwarnings()
def test_make_unifrac_metric(self):
""" exercise of the unweighted unifrac metric should not throw errors"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
res = unif(self.l19_data, self.l19_taxon_names, tree, self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names, self.l19_taxon_names)
unifrac_mat, unifrac_names = fast_unifrac(tree, envs, modes=["distance_matrix"])["distance_matrix"]
self.assertFloatEqual(res, _reorder_unifrac_res([unifrac_mat, unifrac_names], self.l19_sample_names))
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 3], 0.0)
self.assertNotEqual(res[0, 1], 1.0)
def test_make_unifrac_row_metric3(self):
treestr = '((((tax7:0.1):.98,tax8:.3, tax4:.3):.4, ' +\
'((tax6:.09):0.43):0.5):.2,' +\
'(tax9:0.3, endbigtaxon:.08));' # taxa 1,2,3 removed
tree = parse_newick(treestr, PhyloNode)
otu_data = numpy.array([
[7, 1, 0, 0, 0, 0, 0, 0, 0], # 1 now zeros
[4, 2, 0, 0, 0, 1, 0, 0, 0],
[2, 4, 0, 0, 0, 1, 0, 0, 0],
[1, 7, 0, 0, 0, 0, 0, 0, 0], # 4 now zeros
[0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 7, 1, 0, 0, 0, 0, 0, 0],
[0, 4, 2, 0, 0, 0, 2, 0, 0],
[0, 2, 4, 0, 0, 0, 1, 0, 0],
[0, 1, 7, 0, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 1, 0, 0, 0, 0, 0],
[0, 0, 4, 2, 0, 0, 0, 3, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0],
[0, 0, 1, 7, 0, 0, 0, 0, 0],
[0, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 0, 7, 1, 0, 0, 0, 0],
[0, 0, 0, 4, 2, 0, 0, 0, 4],
[0, 0, 0, 2, 4, 0, 0, 0, 1],
[0, 0, 0, 1, 7, 0, 0, 0, 0]
])
unif = make_unifrac_metric(False, unifrac, True)
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names)
warnings.resetwarnings()
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 3], 0.0)
self.assertEqual(res[0, 1], 1.0)
warnings.filterwarnings('ignore')
unif_row = make_unifrac_row_metric(False, unifrac, True)
for i, sam_name in enumerate(self.l19_sample_names):
if i in [0, 3, 4, 5, 8, 9]:
continue
# these have no data and are warned "meaningless".
# I Would prefer if they matched res anyway though
res_row = unif_row(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names, sam_name)
for j in range(len(self.l19_sample_names)):
if j in [0, 3, 4, 5, 8, 9]:
continue # ok if meaningless number in zero sample
self.assertEqual(res_row[j], res[i, j])
warnings.resetwarnings()
def test_make_unifrac_row_metric3(self):
treestr = '((((tax7:0.1):.98,tax8:.3, tax4:.3):.4, ' +\
'((tax6:.09):0.43):0.5):.2,' +\
'(tax9:0.3, endbigtaxon:.08));' # taxa 1,2,3 removed
tree = parse_newick(treestr, PhyloNode)
otu_data = numpy.array([
[7, 1, 0, 0, 0, 0, 0, 0, 0], # 1 now zeros
[4, 2, 0, 0, 0, 1, 0, 0, 0],
[2, 4, 0, 0, 0, 1, 0, 0, 0],
[1, 7, 0, 0, 0, 0, 0, 0, 0], # 4 now zeros
[0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 7, 1, 0, 0, 0, 0, 0, 0],
[0, 4, 2, 0, 0, 0, 2, 0, 0],
[0, 2, 4, 0, 0, 0, 1, 0, 0],
[0, 1, 7, 0, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 1, 0, 0, 0, 0, 0],
[0, 0, 4, 2, 0, 0, 0, 3, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0],
[0, 0, 1, 7, 0, 0, 0, 0, 0],
[0, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 0, 7, 1, 0, 0, 0, 0],
[0, 0, 0, 4, 2, 0, 0, 0, 4],
[0, 0, 0, 2, 4, 0, 0, 0, 1],
[0, 0, 0, 1, 7, 0, 0, 0, 0]
])
unif = make_unifrac_metric(False, unifrac, True)
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree, self.l19_sample_names)
warnings.resetwarnings()
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 3], 0.0)
self.assertEqual(res[0, 1], 1.0)
warnings.filterwarnings('ignore')
unif_row = make_unifrac_row_metric(False, unifrac, True)
for i, sam_name in enumerate(self.l19_sample_names):
if i in [0, 3, 4, 5, 8, 9]:
continue
# these have no data and are warned "meaningless".
# I Would prefer if they matched res anyway though
res_row = unif_row(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names, sam_name)
for j in range(len(self.l19_sample_names)):
if j in [0, 3, 4, 5, 8, 9]:
continue # ok if meaningless number in zero sample
self.assertAlmostEqual(res_row[j], res[i, j])
warnings.resetwarnings()
def test_make_unifrac_row_metric2(self):
""" samples with no seqs, and identical samples, should behave correctly
"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
otu_data = numpy.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0], # sam1 zeros
[4, 2, 0, 0, 0, 1, 0, 0, 0],
[2, 4, 0, 0, 0, 1, 0, 0, 0],
[1, 7, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 7, 1, 0, 0, 0, 0, 0, 0],
[0, 4, 2, 0, 0, 0, 2, 0, 0],
[0, 2, 4, 0, 0, 0, 1, 0, 0],
[0, 1, 7, 0, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 1, 0, 0, 0, 0, 0],
[0, 0, 4, 2, 0, 0, 0, 3, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0], # sam14 zeros
[0, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0], # sam 16 now like sam 13
[0, 0, 0, 4, 2, 0, 0, 0, 4],
[0, 0, 0, 2, 4, 0, 0, 0, 1],
[0, 0, 0, 1, 7, 0, 0, 0, 0]
])
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 13], 0.0)
self.assertEqual(res[12, 15], 0.0)
self.assertEqual(res[0, 1], 1.0)
warnings.resetwarnings()
warnings.filterwarnings('ignore')
unif_row = make_unifrac_row_metric(False, unifrac, True)
for i, sam_name in enumerate(self.l19_sample_names):
if i in [0]:
continue
# these have no data and are warned "meaningless".
# I Would prefer if they matched res anyway though
res_row = unif_row(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names, sam_name)
for j in range(len((self.l19_sample_names))):
if j in [0]:
continue # ok if meaningless number in zero sample
self.assertEqual(res_row[j], res[i, j])
warnings.resetwarnings()
def test_make_unifrac_row_metric2(self):
""" samples with no seqs, and identical samples, should behave correctly
"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
otu_data = numpy.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0], # sam1 zeros
[4, 2, 0, 0, 0, 1, 0, 0, 0],
[2, 4, 0, 0, 0, 1, 0, 0, 0],
[1, 7, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 0, 0, 0, 0, 0, 0, 0],
[0, 7, 1, 0, 0, 0, 0, 0, 0],
[0, 4, 2, 0, 0, 0, 2, 0, 0],
[0, 2, 4, 0, 0, 0, 1, 0, 0],
[0, 1, 7, 0, 0, 0, 0, 0, 0],
[0, 0, 8, 0, 0, 0, 0, 0, 0],
[0, 0, 7, 1, 0, 0, 0, 0, 0],
[0, 0, 4, 2, 0, 0, 0, 3, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0], # sam14 zeros
[0, 0, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 2, 4, 0, 0, 0, 1, 0], # sam 16 now like sam 13
[0, 0, 0, 4, 2, 0, 0, 0, 4],
[0, 0, 0, 2, 4, 0, 0, 0, 1],
[0, 0, 0, 1, 7, 0, 0, 0, 0]
])
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree, self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0, 0], 0)
self.assertEqual(res[0, 13], 0.0)
self.assertEqual(res[12, 15], 0.0)
self.assertEqual(res[0, 1], 1.0)
warnings.resetwarnings()
warnings.filterwarnings('ignore')
unif_row = make_unifrac_row_metric(False, unifrac, True)
for i, sam_name in enumerate(self.l19_sample_names):
if i in [0]:
continue
# these have no data and are warned "meaningless".
# I Would prefer if they matched res anyway though
res_row = unif_row(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names, sam_name)
for j in range(len((self.l19_sample_names))):
if j in [0]:
continue # ok if meaningless number in zero sample
self.assertEqual(res_row[j], res[i, j])
warnings.resetwarnings()
def test_make_unifrac_metric(self):
""" exercise of the unweighted unifrac metric should not throw errors"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
res = unif(self.l19_data, self.l19_taxon_names, tree,
self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
unifrac_mat, unifrac_names = fast_unifrac(tree, envs,
modes=['distance_matrix'])['distance_matrix']
self.assertFloatEqual(res, _reorder_unifrac_res([unifrac_mat,
unifrac_names], self.l19_sample_names))
self.assertEqual(res[0,0], 0)
self.assertEqual(res[0,3], 0.0)
self.assertNotEqual(res[0,1], 1.0)
def test_make_unifrac_metric3(self):
treestr = '((((tax7:0.1):.98,tax8:.3, tax4:.3):.4, '+\
'((tax6:.09):0.43):0.5):.2,'+\
'(tax9:0.3, endbigtaxon:.08));' # taxa 1,2,3 removed
tree = parse_newick(treestr, PhyloNode)
otu_data = numpy.array([
[7,1,0,0,0,0,0,0,0], # 1 now zeros
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0], # 4 now zeros
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,1,7,0,0,0,0,0],
[0,0,0,8,0,0,0,0,0],
[0,0,0,7,1,0,0,0,0],
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]
])
unif = make_unifrac_metric(False, unifrac, True)
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names)
warnings.resetwarnings()
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0,0], 0)
self.assertEqual(res[0,3], 0.0)
self.assertEqual(res[0,1], 1.0)
def test_make_unifrac_metric3(self):
treestr = '((((tax7:0.1):.98,tax8:.3, tax4:.3):.4, '+\
'((tax6:.09):0.43):0.5):.2,'+\
'(tax9:0.3, endbigtaxon:.08));' # taxa 1,2,3 removed
tree = parse_newick(treestr, PhyloNode)
otu_data = numpy.array([
[7,1,0,0,0,0,0,0,0], # 1 now zeros
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0], # 4 now zeros
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,1,7,0,0,0,0,0],
[0,0,0,8,0,0,0,0,0],
[0,0,0,7,1,0,0,0,0],
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]
])
unif = make_unifrac_metric(False, unifrac, True)
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names)
warnings.resetwarnings()
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0,0], 0)
self.assertEqual(res[0,3], 0.0)
self.assertEqual(res[0,1], 1.0)
def test_make_unifrac_metric2(self):
""" samples with no seqs, and identical samples, should behave correctly
"""
tree = parse_newick(self.l19_treestr, PhyloNode)
unif = make_unifrac_metric(False, unifrac, True)
otu_data = numpy.array([
[0,0,0,0,0,0,0,0,0],#sam1 zeros
[4,2,0,0,0,1,0,0,0],
[2,4,0,0,0,1,0,0,0],
[1,7,0,0,0,0,0,0,0],
[0,8,0,0,0,0,0,0,0],
[0,7,1,0,0,0,0,0,0],
[0,4,2,0,0,0,2,0,0],
[0,2,4,0,0,0,1,0,0],
[0,1,7,0,0,0,0,0,0],
[0,0,8,0,0,0,0,0,0],
[0,0,7,1,0,0,0,0,0],
[0,0,4,2,0,0,0,3,0],
[0,0,2,4,0,0,0,1,0],
[0,0,0,0,0,0,0,0,0],#sam14 zeros
[0,0,0,8,0,0,0,0,0],
[0,0,2,4,0,0,0,1,0], #sam 16 now like sam 13
[0,0,0,4,2,0,0,0,4],
[0,0,0,2,4,0,0,0,1],
[0,0,0,1,7,0,0,0,0]
])
warnings.filterwarnings('ignore')
res = unif(otu_data, self.l19_taxon_names, tree,
self.l19_sample_names)
envs = make_envs_dict(self.l19_data, self.l19_sample_names,
self.l19_taxon_names)
self.assertEqual(res[0,0], 0)
self.assertEqual(res[0,13], 0.0)
self.assertEqual(res[12,15], 0.0)
self.assertEqual(res[0,1], 1.0)
warnings.resetwarnings()
