functions.py 文件源码

def _mat_inv_mul(A, B):
    """
    Computes A^-1 * B symbolically w/ substitution, where B is not
    necessarily a vector, but can be a matrix.

    """

    r1, c1 = A.shape
    r2, c2 = B.shape
    temp1 = Matrix(r1, c1, lambda i, j: Symbol('x' + str(j) + str(r1 * i)))
    temp2 = Matrix(r2, c2, lambda i, j: Symbol('y' + str(j) + str(r2 * i)))
    for i in range(len(temp1)):
        if A[i] == 0:
            temp1[i] = 0
    for i in range(len(temp2)):
        if B[i] == 0:
            temp2[i] = 0
    temp3 = []
    for i in range(c2):
        temp3.append(temp1.LDLsolve(temp2[:, i]))
    temp3 = Matrix([i.T for i in temp3]).T
    return temp3.subs(dict(list(zip(temp1, A)))).subs(dict(list(zip(temp2, B))))