def test_frontend():
'''
Test maxmin product frontend.
'''
A = sp.rand(5, 5, .2, 'csr')
AP = _maxmin_naive(A)
AP2 = maxmin(A)
assert np.array_equal(AP, AP2.todense())
def test_naive_sparse():
'''
Test parameter checking cythonized maxmin product.
'''
A = sp.rand(5, 5, .2, 'csr')
AP = _maxmin_naive(A)
AP2 = c_maxmin_naive(A) # expects ndarray type
assert np.array_equal(AP, AP2)
def test_naive():
'''
Test naive implementation Python vs Cython.
'''
A = np.random.rand(5, 5)
AP = _maxmin_naive(A)
AP2 = c_maxmin_naive(A)
assert np.array_equal(AP, AP2)
def test_naive_subset():
'''
Test naive implementation Python vs Cython with source/target parameters.
'''
a = 1
b = 3
A = np.random.rand(5, 5)
AP = _maxmin_naive(A, a, b)
AP2 = c_maxmin_naive(A, a, b)
assert np.array_equal(AP, AP2)
def test_sparse():
'''
Test maxmin product sparse implementation.
'''
A = sp.rand(5, 5, .2, 'csr')
AP = _maxmin_naive(A)
AP2 = _maxmin_sparse(A)
assert np.array_equal(AP, AP2.todense())
AP3 = c_maxmin_sparse(A)
assert np.array_equal(AP, AP3.todense())
def test_sparse_subset():
'''
Test maxmin product with source/target parameters.
'''
a = 1
b = 3
A = sp.rand(5, 5, .2, 'csr')
AP = _maxmin_naive(A, a, b)
AP2 = _maxmin_sparse(A, a, b)
assert np.array_equal(AP, AP2.todense())
AP3 = c_maxmin_sparse(A, a, b)
assert np.array_equal(AP, AP3.todense())