models.py 文件源码

def get_sudoku_matrix(n):
    X = np.array([[cp.Variable(n**2) for i in range(n**2)] for j in range(n**2)])
    cons = ([x >= 0 for row in X for x in row] +
            [cp.sum_entries(x) == 1 for row in X for x in row] +
            [sum(row) == np.ones(n**2) for row in X] +
            [sum([row[i] for row in X]) == np.ones(n**2) for i in range(n**2)] +
            [sum([sum(row[i:i+n]) for row in X[j:j+n]]) == np.ones(n**2) for i in range(0,n**2,n) for j in range(0, n**2, n)])
    f = sum([cp.sum_entries(x) for row in X for x in row])
    prob = cp.Problem(cp.Minimize(f), cons)

    A = np.asarray(prob.get_problem_data(cp.ECOS)["A"].todense())
    A0 = [A[0]]
    rank = 1
    for i in range(1,A.shape[0]):
        if np.linalg.matrix_rank(A0+[A[i]], tol=1e-12) > rank:
            A0.append(A[i])
            rank += 1

    return np.array(A0)