rms_model.py 文件源码

def fit_power_law(x, y):
    """
    """
    ln_x = NP.log(x)
    ln_y = NP.log(y)
    # least squares solution
    A = NP.empty((len(x), 2))
    A[:, 0] = 1
    A[:, 1] = ln_x
    #b_ls = NP.linalg.lstsq(A, ln_y)[0]
    # total least-squares solution
    X = NP.empty((len(x), 3))
    X[:, :2] = A
    X[:, 2] = ln_y
    U, S, V = NP.linalg.svd(X, 1)
    b_tls = (V[-1, :] / -V[-1, -1])[:2]
    alpha = math.exp(b_tls[0])
    beta = b_tls[1]
    return alpha, beta