def testRandStochasticRightSeed(self):
"Random: Stochastic - right with seed"
seed = 12345
U0 = rand_stochastic(10, kind='right', seed=seed)
U1 = rand_stochastic(10, kind='right', seed=None)
U2 = rand_stochastic(10, kind='right', seed=seed)
assert_(U0 != U1)
assert_(U0 == U2)
def testRandStochasticLeftSeed(self):
"Random: Stochastic - left with seed"
seed = 12345
U0 = rand_stochastic(10, seed=seed)
U1 = rand_stochastic(10, seed=None)
U2 = rand_stochastic(10, seed=seed)
assert_(U0 != U1)
assert_(U0 == U2)
def testRandStochasticRightSeed(self):
"Random: Stochastic - right with seed"
seed = 12345
U0 = rand_stochastic(10, kind='right', seed=seed)
U1 = rand_stochastic(10, kind='right', seed=None)
U2 = rand_stochastic(10, kind='right', seed=seed)
assert_(U0 != U1)
assert_(U0 == U2)
def testRandStochasticLeftSeed(self):
"Random: Stochastic - left with seed"
seed = 12345
U0 = rand_stochastic(10, seed=seed)
U1 = rand_stochastic(10, seed=None)
U2 = rand_stochastic(10, seed=seed)
assert_(U0 != U1)
assert_(U0 == U2)
def testRandStochasticRight(self):
'Random: Stochastic - right'
Q = [rand_stochastic(10, kind='right') for k in range(5)]
for i in range(5):
A = Q[i].data
for j in range(10):
assert_(np.abs(np.sum(A.getrow(j).todense().real)-1.0) < 1e-15)
def testRandStochasticLeft(self):
'Random: Stochastic - left'
Q = [rand_stochastic(10) for k in range(5)]
for i in range(5):
A = Q[i].data.tocsc()
for j in range(10):
assert_(np.abs(np.sum(A.getcol(j).todense().real)-1.0) < 1e-15)
def test_rand_stochastic(kind):
"""
Random Qobjs: Test random stochastic
"""
random_qobj = rand_stochastic(5, kind=kind)
axis = {"left":0, "right":1}[kind]
np.testing.assert_allclose(np.sum(random_qobj.full(), axis=axis), 1,
atol=1e-14)
def testRandStochasticRight(self):
'Random: Stochastic - right'
Q = [rand_stochastic(10, kind='right') for k in range(5)]
for i in range(5):
A = Q[i].data
for j in range(10):
assert_(
np.abs(np.sum(A.getrow(j).todense().real) - 1.0) < 1e-15)
def testRandStochasticLeft(self):
'Random: Stochastic - left'
Q = [rand_stochastic(10) for k in range(5)]
for i in range(5):
A = Q[i].data.tocsc()
for j in range(10):
assert_(
np.abs(np.sum(A.getcol(j).todense().real) - 1.0) < 1e-15)
