import numpy as np
from scipy.linalg import fractional_matrix_power

T = int(input())

def cb(a):
    if a >= 0:
        return pow(a, 1 / 3)
    else:
        return -pow(-a, 1 / 3)

for _ in range(T):
    a, b = map(float, input().split())
    c, d = map(float, input().split())
    A = np.array([[a, b], [c, d]])
    B = fractional_matrix_power(A, 1 / 3)

    eig = np.linalg.eig(A)
    M = np.array([[eig.eigenvectors[0][0], eig.eigenvectors[1][0]], [eig.eigenvectors[0][1], eig.eigenvectors[1][1]]])

    e0 = cb(eig.eigenvalues[0])
    e1 = cb(eig.eigenvalues[1])

    B = M.T * np.diag([e0, e1]) * M
    print("{:1.5f}".format(B[0][0]), "{:1.5f}".format(B[0][1]))
    print("{:1.5f}".format(B[1][0]), "{:1.5f}".format(B[1][1]))