def test_CbGiGiGaD_traversal():
"""
Test path counts and degree-weighted path counts for the CbGiGiGaD
metapath between bupropion and nicotine dependence. These values are not
intended to correspond to the values from the entire Hetionet v1.0. Hence,
the expected values are generated using hetio.pathtools.
"""
graph = get_graph('bupropion-subgraph')
compound = 'DB01156' # Bupropion
disease = 'DOID:0050742' # nicotine dependence
metapath = graph.metagraph.metapath_from_abbrev('CbGiGiGaD')
paths = hetio.pathtools.paths_between(
graph,
source=('Compound', compound),
target=('Disease', disease),
metapath=metapath,
duplicates=False,
)
hetio_dwpc = hetio.pathtools.DWPC(paths, damping_exponent=0.4)
rows, cols, pc_matrix = dwpc(graph, metapath, damping=0)
rows, cols, dwpc_matrix = dwpc(graph, metapath, damping=0.4)
i = rows.index(compound)
j = cols.index(disease)
assert pc_matrix[i, j] == len(paths)
assert dwpc_matrix[i, j] == pytest.approx(hetio_dwpc)
def test_path_traversal(metapath, hetmat, tmpdir):
"""
Test PC (path count) and DWPC (degree-weighted path count) computation
on the random subgraph of Hetionet v1.0. Evaluates max path count
compound-disease pair where errors are most likely to appear.
"""
# Read graph
graph = get_graph('random-subgraph')
graph_or_hetmat = graph
if hetmat:
graph_or_hetmat = get_graph('random-subgraph', hetmat=hetmat, directory=tmpdir)
metapath = graph.metagraph.metapath_from_abbrev(metapath)
# Matrix computations
rows, cols, pc_matrix = dwpc(graph_or_hetmat, metapath, damping=0)
rows, cols, dwpc_matrix = dwpc(graph_or_hetmat, metapath, damping=0.4)
# Find compound-disease pair with the max path count
i, j = numpy.unravel_index(pc_matrix.argmax(), pc_matrix.shape)
compound = rows[i]
disease = cols[j]
# hetnetpy.pathtools computations
paths = hetnetpy.pathtools.paths_between(
graph,
source=('Compound', compound),
target=('Disease', disease),
metapath=metapath,
duplicates=False,
)
hetnetpy_dwpc = hetnetpy.pathtools.DWPC(paths, damping_exponent=0.4)
# Check matrix values match hetnetpy.pathtools
assert pc_matrix[i, j] == len(paths)
assert dwpc_matrix[i, j] == pytest.approx(hetnetpy_dwpc)
def test_CbGpPWpGaD_traversal():
"""
Test path counts and degree-weighted path counts for the CbGpPWpGaD
metapath between bupropion and nicotine dependence. Expected values from
the network traversal methods at https://git.io/vHBh2.
"""
graph = get_graph('bupropion-subgraph')
compound = 'DB01156' # Bupropion
disease = 'DOID:0050742' # nicotine dependence
metapath = graph.metagraph.metapath_from_abbrev('CbGpPWpGaD')
rows, cols, pc_matrix = dwpc(graph, metapath, damping=0)
rows, cols, dwpc_matrix = dwpc(graph, metapath, damping=0.4)
i = rows.index(compound)
j = cols.index(disease)
assert pc_matrix[i, j] == 142
assert dwpc_matrix[i, j] == pytest.approx(0.03287590886921623)
def test_dtype(metapath, dtype, dwwc_method):
graph = get_graph('disease-gene-example')
metapath = graph.metagraph.metapath_from_abbrev(metapath)
rows, cols, dwpc_matrix = dwpc(graph,
metapath,
dtype=dtype,
dwwc_method=dwwc_method)
assert dwpc_matrix.dtype == dtype
def test_disjoint_dwpc(metapath, exp_row, exp_col, exp_data, shape):
graph = get_graph('random-subgraph')
metapath = graph.metagraph.metapath_from_abbrev(metapath)
row, col, dwpc_matrix = dwpc(graph, metapath)
# expected = numpy.array(expected, dtype=numpy.float64)
expected = sparse.coo_matrix((exp_data, (exp_row, exp_col)), shape=shape)
assert abs(dwpc_matrix - expected).max() == pytest.approx(0, abs=1e-7)
def test_dwpc(metapath, expected, dense_threshold):
if expected is not None:
expected = numpy.array(expected, dtype=numpy.float64)
graph = get_graph('disease-gene-example')
metapath = graph.metagraph.metapath_from_abbrev(metapath)
if expected is None:
with pytest.raises(Exception):
dwpc(graph, metapath, damping=0.5, dense_threshold=dense_threshold)
else:
row, col, dwpc_matrix = dwpc(graph,
metapath,
damping=0.5,
dense_threshold=dense_threshold)
assert abs(expected - dwpc_matrix).max() == pytest.approx(0, abs=1e-7)
if dense_threshold == 1:
assert sparse.issparse(dwpc_matrix)
else:
assert not sparse.issparse(dwpc_matrix)
def test_dwpc_approx(metapath, relative):
graph = get_graph('random-subgraph')
metapath = graph.metagraph.metapath_from_abbrev(metapath)
rows, cols, dwpc_matrix = dwpc(graph, metapath)
rows, cols, dwpc_approx = _dwpc_approx(graph, metapath)
rows, cols, dwwc_matrix = dwwc(graph, metapath)
if relative == 'equal':
assert abs(
(dwpc_approx - dwpc_matrix)).max() == pytest.approx(0, abs=1e-7)
else:
assert numpy.sum((dwpc_approx - dwpc_matrix)) >= 0
assert abs((dwwc_matrix - dwpc_approx)).max() >= 0