def test_maxprod_composition():
mfI = np.r_[0.4, 0.7, 1.0, 0.8, 0.6]
mfV = np.r_[0.2, 0.6, 1.0, 0.9, 0.7]
mfC = np.r_[0.4, 1.0, 0.8]
P = cartprod(mfV, mfI)
S = cartprod(mfI, mfC)
test = maxprod_composition(P, S)
expected = np.r_[[[0.08, 0.2, 0.16], [0.24, 0.6, 0.48], [0.4, 1., 0.8],
[0.36, 0.9, 0.72], [0.28, 0.7, 0.56]]]
assert_allclose(test, expected)
A = np.r_[0.3, 0.2, 0.1, 0, 0.7, 0.9, 1]
B = np.r_[0.5, 0.5, 0.6, 0.4, 0.6, 0.3, 0.2]
c = maxprod_composition(A, B)
assert (1, 1) == c.shape
assert_allclose(c, np.r_[[[0.42]]])
def test_maxprod_composition():
mfI = np.r_[0.4, 0.7, 1.0, 0.8, 0.6]
mfV = np.r_[0.2, 0.6, 1.0, 0.9, 0.7]
mfC = np.r_[0.4, 1.0, 0.8]
P = cartprod(mfV, mfI)
S = cartprod(mfI, mfC)
test = maxprod_composition(P, S)
expected = np.r_[[[0.08, 0.2 , 0.16],
[0.24, 0.6 , 0.48],
[0.4 , 1. , 0.8 ],
[0.36, 0.9 , 0.72],
[0.28, 0.7 , 0.56]]]
assert_allclose(test, expected)
A = np.r_[0.3, 0.2, 0.1, 0, 0.7, 0.9, 1]
B = np.r_[0.5, 0.5, 0.6, 0.4, 0.6, 0.3, 0.2]
c = maxprod_composition(A, B)
assert (1, 1) == c.shape
assert_allclose(c, np.r_[[[0.42]]])
def test_cartprod():
a = np.r_[0, 0, 0, 0.3, 0.7, 1, 0.9, 0]
b = np.r_[0, 0, 1, 0.2, 0.1, 0, 0]
z = cartprod(a, b)
expected = np.r_[[[0., 0., 0. , 0. , 0. , 0., 0.],
[0., 0., 0. , 0. , 0. , 0., 0.],
[0., 0., 0. , 0. , 0. , 0., 0.],
[0., 0., 0.3, 0.2, 0.1, 0., 0.],
[0., 0., 0.7, 0.2, 0.1, 0., 0.],
[0., 0., 1. , 0.2, 0.1, 0., 0.],
[0., 0., 0.9, 0.2, 0.1, 0., 0.],
[0., 0., 0. , 0. , 0. , 0., 0.]]]
assert_allclose(z, expected)
def test_cartprod():
a = np.r_[0, 0, 0, 0.3, 0.7, 1, 0.9, 0]
b = np.r_[0, 0, 1, 0.2, 0.1, 0, 0]
z = cartprod(a, b)
expected = np.r_[[[0., 0., 0., 0., 0., 0.,
0.], [0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0.3, 0.2, 0.1, 0., 0.],
[0., 0., 0.7, 0.2, 0.1, 0., 0.],
[0., 0., 1., 0.2, 0.1, 0., 0.],
[0., 0., 0.9, 0.2, 0.1, 0., 0.],
[0., 0., 0., 0., 0., 0., 0.]]]
assert_allclose(z, expected)
