def quasi_clique_expansions2(quasi_cliques, cliques, incomp):
array_cliques = [np.array(c) for c in cliques.keys()]
c_comps = np.array([[valid_combo(array_cliques[i], array_cliques[j], incomp)
if j > i else 0
for j in range(len(array_cliques))] for i in range(len(array_cliques))])
#print('ccomps', c_comps.shape)
c_comp_graph = graph_from_matrix(c_comps)[0]
#print('cgraph', c_comp_graph)
max_expansions = dict()
for q,r in quasi_cliques.items():
q = np.array(q)
qcomps = np.array([valid_combo(q, array_cliques[i], incomp)
for i in range(len(array_cliques))])
#print('qcomps', len(qcomps))
if np.any(qcomps):
view = GraphView(c_comp_graph, vfilt=qcomps > 0)
#get max cliques of compatible patterns
combos = list(max_cliques(view))
#add compatible isolated vertices missing in cliques
vs = view.get_vertices()
isolated = vs[view.get_total_degrees(vs) == 0]
combos += [[i] for i in isolated]
#build combos and merge into quasi-cliques
combos = [[array_cliques[i] for i in c] for c in combos]
qcliques = [tuple(list(snp.kway_merge(*([q]+co), duplicates=snp.DROP)))
for co in combos]
qratings = [r+sum([cliques[tuple(c)] for c in co]) for co in combos]
max_expansions.update(zip(qcliques, qratings))
#print('upd')
return max_expansions#[np.array(m) for m in max_expansions] if len(max_expansions) > 1 else []
def test_simple_1_not_sorted(self):
"""
Check that the same array is returned, if only one sorted array is
passed to the merger and assume_sorted is False.
"""
a = np.array([3, 1, 7], dtype=self.get_dtype())
m = snp.kway_merge(a, assume_sorted=False)
self.assertEqual(list(m), [1, 3, 7])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_2_not_sorted(self):
"""
Check that the correctly merged array is returned when called with
two sorted arrays and assume_sorted is False.
"""
a = np.array([1, 7, 3], dtype=self.get_dtype())
b = np.array([9, 2, 5], dtype=self.get_dtype())
m = snp.kway_merge(a, b, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 5, 7, 9])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_2_sorted(self):
"""
Check that the correctly merged array is returned when called with
two sorted arrays.
"""
a = np.array([1, 3, 7], dtype=self.get_dtype())
b = np.array([2, 5, 9], dtype=self.get_dtype())
m = snp.kway_merge(a, b)
self.assertEqual(list(m), [1, 2, 3, 5, 7, 9])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_3_callable_1_not_sorted(self):
"""
Check that the correctly merged array is returned when called with
one callable and two arrays and assume_sorted is False.
"""
a = lambda: np.array([3, 1, 7], dtype=self.get_dtype())
b = np.array([2, 5, 9], dtype=self.get_dtype())
c = np.array([8, 4], dtype=self.get_dtype())
m = snp.kway_merge(a, b, c, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
m = snp.kway_merge(b, a, c, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
m = snp.kway_merge(c, b, a, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_1_callable_1_not_sorted(self):
"""
Check that the generated array is returned if a single generated is
given and assume_sorted is False.
"""
a = lambda: np.array([3, 7, 5], dtype=self.get_dtype())
m = snp.kway_merge(a, assume_sorted=False)
self.assertEqual(list(m), [3, 5, 7])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_3_callable_1(self):
"""
Check that the correctly merged array is returned when called with
one callable and two arrays.
"""
a = lambda: np.array([1, 3, 7], dtype=self.get_dtype())
b = np.array([2, 5, 9], dtype=self.get_dtype())
c = np.array([4, 8], dtype=self.get_dtype())
m = snp.kway_merge(a, b, c)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
m = snp.kway_merge(b, a, c)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
m = snp.kway_merge(c, b, a)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_1_callable_1(self):
"""
Check that the generated array is returned if a single generated is
given.
"""
a = lambda: np.array([3, 5, 7], dtype=self.get_dtype())
m = snp.kway_merge(a)
self.assertEqual(list(m), [3, 5, 7])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_3_callable_3_not_sorted(self):
"""
Check that the correctly merged array is returned when called with
three callable objects and assume_sorted is False.
"""
a = lambda: np.array([7, 1, 3], dtype=self.get_dtype())
b = lambda: np.array([2, 9, 5], dtype=self.get_dtype())
c = lambda: np.array([8, 4], dtype=self.get_dtype())
m = snp.kway_merge(a, b, c, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 4, 5, 7, 8, 9])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_4_not_sorted(self):
"""
Check that the correctly merged array is returned when called with
four sorted arrays and assume_sorted is False.
"""
a = np.array([3, 1, 7], dtype=self.get_dtype())
b = np.array([9, 2, 5], dtype=self.get_dtype())
c = np.array([4, 8], dtype=self.get_dtype())
d = np.array([10, 6, 3], dtype=self.get_dtype())
m = snp.kway_merge(a, b, c, d, assume_sorted=False)
self.assertEqual(list(m), [1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10])
self.assertEqual(m.dtype, self.get_dtype())
def test_simple_4_sorted(self):
"""
Check that the correctly merged array is returned when called with
four sorted arrays.
"""
a = np.array([1, 3, 7], dtype=self.get_dtype())
b = np.array([2, 5, 9], dtype=self.get_dtype())
c = np.array([4, 8], dtype=self.get_dtype())
d = np.array([3, 6, 10], dtype=self.get_dtype())
m = snp.kway_merge(a, b, c, d)
self.assertEqual(list(m), [1, 2, 3, 3, 4, 5, 6, 7, 8, 9, 10])
self.assertEqual(m.dtype, self.get_dtype())