def setUp(self):
self.pair_matrix_fn = tmpname()
self.pair_matrix = SimilarityMatrix(self.pair_matrix_fn, "a", driver="H5FD_CORE", driver_core_backing_store=0)
labels = {"a": 0, "b": 1, "c": 2, "d": 3}
similarities = [("a", "b", 0.9), ("a", "c", 0.5), ("b", "c", 0.6), ("d", "c", 0.7)]
self.pair_matrix.update(similarities, labels)
self.matrix_fn = tmpname()
self.matrix = FrozenSimilarityMatrix(self.matrix_fn, "a", driver="H5FD_CORE", driver_core_backing_store=0)
def test_simmatrix_import_run_ignore_upper_triangle():
output_fn = tmpname()
tsv = '''frag_id1 frag_id2 score
2mlm_2W7_frag1 2mlm_2W7_frag1 1.0000000000000000
2mlm_2W7_frag2 2mlm_2W7_frag2 1.0000000000000000
2mlm_2W7_frag1 2mlm_2W7_frag2 0.5877164873731594
2mlm_2W7_frag2 3wvm_STE_frag1 0.4633096818493935
2mlm_2W7_frag2 2mlm_2W7_frag1 0.5877164873731594
3wvm_STE_frag1 2mlm_2W7_frag2 0.4633096818493935
'''
inputfile = StringIO(tsv)
try:
script.simmatrix_import_run(inputfile=inputfile,
format='tsv',
simmatrixfn=output_fn,
fragmentsdb='data/fragments.sqlite',
nrrows=2,
ignore_upper_triangle=True)
simmatrix = SimilarityMatrix(output_fn)
result = [r for r in simmatrix]
simmatrix.close()
print(result)
expected = [('2mlm_2W7_frag1', '2mlm_2W7_frag2xx', 0.5877), ('2mlm_2W7_frag2', '3wvm_STE_frag1', 0.4633)]
assert_array_almost_equal([r[2] for r in result], [r[2] for r in expected], 3)
eq_([(r[0], r[1],) for r in result], [(r[0], r[1],) for r in result])
finally:
if os.path.exists(output_fn):
os.remove(output_fn)
def test_simmatrix_importfpneigh_run_ignore_upper_triangle():
output_fn = tmpname()
tsv = '''Compounds similar to 2mlm_2W7_frag1:
2mlm_2W7_frag1 1.0000
2mlm_2W7_frag2 0.5877
Compounds similar to 2mlm_2W7_frag2:
2mlm_2W7_frag2 1.0000
2mlm_2W7_frag1 0.5877
3wvm_STE_frag1 0.4633
'''
inputfile = StringIO(tsv)
try:
script.simmatrix_importfpneigh_run(inputfile=inputfile,
simmatrixfn=output_fn,
fragmentsdb='data/fragments.sqlite',
nrrows=3,
ignore_upper_triangle=True)
simmatrix = SimilarityMatrix(output_fn)
rows = [r for r in simmatrix]
simmatrix.close()
expected = [(u'2mlm_2W7_frag1', u'2mlm_2W7_frag2', 0.5877), (u'2mlm_2W7_frag2', u'3wvm_STE_frag1', 0.4633)]
eq_(rows, expected)
finally:
os.remove(output_fn)
