class FrozenSimilarityMatrixInMemory(object):
def __init__(self):
self.matrix_fn = tmpname()
self.matrix = FrozenSimilarityMatrix(self.matrix_fn, 'a', driver='H5FD_CORE', driver_core_backing_store=0)
def __enter__(self):
return self.matrix
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
def close(self):
self.matrix.close()
if os.path.isfile(self.matrix_fn):
os.remove(self.matrix_fn)
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)
class FrozenSimilarityMatrixInMemory(object):
def __init__(self):
self.matrix_fn = tmpname()
self.matrix = FrozenSimilarityMatrix(self.matrix_fn,
'a',
driver='H5FD_CORE',
driver_core_backing_store=0)
def __enter__(self):
return self.matrix
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
def close(self):
self.matrix.close()
if os.path.isfile(self.matrix_fn):
os.remove(self.matrix_fn)
def open_similarity_matrix(fn):
"""Open read-only similarity matrix file.
Args:
fn (str): Filename of similarity matrix
Returns:
SimilarityMatrix | FrozenSimilarityMatrix: A read-only similarity matrix object
"""
# peek in file to detect format
f = tables.open_file(fn, 'r')
is_frozen = 'scores' in f.root
f.close()
if is_frozen:
matrix = FrozenSimilarityMatrix(fn)
else:
matrix = SimilarityMatrix(fn, cache_labels=True)
return matrix
def __init__(self):
self.matrix_fn = tmpname()
self.matrix = FrozenSimilarityMatrix(self.matrix_fn,
'a',
driver='H5FD_CORE',
driver_core_backing_store=0)
def __init__(self):
self.matrix_fn = tmpname()
self.matrix = FrozenSimilarityMatrix(self.matrix_fn, 'a', driver='H5FD_CORE', driver_core_backing_store=0)
class TestFrozenSimilarityMatrix(object):
pair_matrix_fn = None
pair_matrix = None
matrix_fn = None
matrix = None
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 tearDown(self):
self.pair_matrix.close()
if os.path.isfile(self.pair_matrix_fn):
os.remove(self.pair_matrix_fn)
self.matrix.close()
if os.path.isfile(self.matrix_fn):
os.remove(self.matrix_fn)
def test_from_pairs_defaults(self):
self.matrix.from_pairs(self.pair_matrix, 10)
result = self.matrix.to_pandas()
labels = ["a", "b", "c", "d"]
expected = pd.DataFrame(
[[0.0, 0.9, 0.5, 0.0], [0.9, 0.0, 0.6, 0.0], [0.5, 0.6, 0.0, 0.7], [0.0, 0.0, 0.7, 0.0]],
index=labels,
columns=labels,
)
pdt.assert_almost_equal(result, expected)
def test_from_pairs_multiframe(self):
self.matrix.from_pairs(self.pair_matrix, 1, None, False)
result = self.matrix.to_pandas()
labels = ["a", "b", "c", "d"]
expected = pd.DataFrame(
[[0.0, 0.9, 0.5, 0.0], [0.9, 0.0, 0.6, 0.0], [0.5, 0.6, 0.0, 0.7], [0.0, 0.0, 0.7, 0.0]],
index=labels,
columns=labels,
)
pdt.assert_almost_equal(result, expected)
def test_from_pairs_limited(self):
self.matrix.from_pairs(self.pair_matrix, 1, 1, False)
result = self.matrix.to_pandas()
labels = ["a", "b", "c", "d"]
expected = pd.DataFrame(
[[0.0, 0.9, 0.0, 0.0], [0.9, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.0, 0.0]],
index=labels,
columns=labels,
)
pdt.assert_almost_equal(result, expected)
def test_from_pairs_singlesided(self):
self.matrix.from_pairs(self.pair_matrix, 10, None, True)
result = self.matrix.to_pandas()
print(result)
labels = ["a", "b", "c", "d"]
expected = pd.DataFrame(
[[0.0, 0.9, 0.5, 0.0], [0.0, 0.0, 0.6, 0.0], [0.0, 0.0, 0.0, 0.0], [0.0, 0.0, 0.7, 0.0]],
index=labels,
columns=labels,
)
pdt.assert_almost_equal(result, expected)
def test_find_defaults(self):
self.matrix.from_pairs(self.pair_matrix, 10)
hits = self.matrix.find("c", 0.55)
expected = [("d", 0.7), ("b", 0.6)]
eq_(hits, expected)
def test_find_limit(self):
self.matrix.from_pairs(self.pair_matrix, 10)
hits = self.matrix.find("c", 0.55, 1)
expected = [("d", 0.7)]
eq_(hits, expected)
def test_find_cutoffhigh_nohits(self):
self.matrix.from_pairs(self.pair_matrix, 10)
hits = self.matrix.find("c", 0.9)
expected = []
eq_(hits, expected)
def test_find_badkey_keyerror(self):
self.matrix.from_pairs(self.pair_matrix, 10)
with assert_raises(KeyError):
self.matrix.find("f", 0.45)
def test_find_singlesided(self):
self.matrix.from_pairs(self.pair_matrix, 10, None, True)
print(self.matrix.scores.read())
hits = self.matrix.find("c", 0.0)
expected = []
eq_(hits, expected)
