def test_mult_Lbeta(n):
p = 20
for i in range(n):
A, Afull = gen_adj(p)
regreg._check_adj(A)
nadj = regreg._create_nadj(A)
beta = np.random.normal(0, 1, p)
s1 = regreg._mult_Lbeta(A, nadj, beta)
s2 = 2 * np.dot(beta, np.dot(Afull, beta))
assert np.allclose(s1, s2)
def test_mult_Lbeta(n):
p = 20
for i in range(n):
A, Afull = gen_adj(p)
regreg._check_adj(A)
nadj = regreg._create_nadj(A)
beta = np.random.normal(0, 1, p)
s1 = regreg._mult_Lbeta(A, nadj, beta)
s2 = 2 * np.dot(beta, np.dot(Afull, beta))
assert (np.allclose(s1, s2))
def test_gen_adj(n):
for i in range(n):
p = np.random.randint(100) + 2
A, Afull = gen_adj(p)
regreg._check_adj(A)
v1 = np.diag(Afull)
v2 = np.array([np.sum(r >= 0) for r in A], dtype=int)
assert np.sum((v1 - v2) ** 2) == 0
v = np.unique(np.triu(Afull, 1) + np.tril(Afull, -1))
if len(v) == 1:
assert np.product(np.unique(np.triu(Afull, 1)) in [-1, 0])
else:
assert np.product(np.unique(np.triu(Afull, 1)) == [-1, 0])
assert np.unique([np.sum(r) for r in Afull]) == [0]
assert np.sum(np.fabs(Afull - Afull.T)) == 0.0
for j in range(A.shape[0]):
for k in range(A.shape[1]):
if A[j, k] > -1:
assert Afull[j, A[j, k]] == -1
def test_gen_adj(n):
for i in range(n):
p = np.random.randint(100) + 2
A, Afull = gen_adj(p)
regreg._check_adj(A)
v1 = np.diag(Afull)
v2 = np.array([np.sum(r >= 0) for r in A], dtype=int)
assert (np.sum((v1 - v2)**2) == 0)
v = np.unique(np.triu(Afull, 1) + np.tril(Afull, -1))
if len(v) == 1:
assert (np.product(np.unique(np.triu(Afull, 1)) in [-1, 0]))
else:
assert (np.product(np.unique(np.triu(Afull, 1)) == [-1, 0]))
assert (np.unique([np.sum(r) for r in Afull]) == [0])
assert (np.sum(np.fabs(Afull - Afull.T)) == 0.)
for j in range(A.shape[0]):
for k in range(A.shape[1]):
if A[j, k] > -1:
assert (Afull[j, A[j, k]] == -1)