def test_maxmin_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 = maxmin_composition(P, S)
expected = np.r_[[[0.2, 0.2, 0.2], [0.4, 0.6, 0.6], [0.4, 1., 0.8],
[0.4, 0.9, 0.8], [0.4, 0.7, 0.7]]]
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 = maxmin_composition(A, B)
assert (1, 1) == c.shape
assert_allclose(c, np.r_[[[0.6]]])
def test_maxmin_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 = maxmin_composition(P, S)
expected = np.r_[[[0.2, 0.2, 0.2],
[0.4, 0.6, 0.6],
[0.4, 1. , 0.8],
[0.4, 0.9, 0.8],
[0.4, 0.7, 0.7]]]
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 = maxmin_composition(A, B)
assert (1, 1) == c.shape
assert_allclose(c, np.r_[[[0.6]]])