bbobbenchmarks.py 文件源码

def fCauchy(ftrue, alpha, p):
    """Returns Cauchy model noisy value

    Cauchy with median 1e3*alpha and with p=0.2, zero otherwise

    P(Cauchy > 1,10,100,1000) = 0.25, 0.032, 0.0032, 0.00032

    """
    # expects ftrue to be a np.array
    popsi = np.shape(ftrue)
    fval = ftrue + alpha * np.maximum(0., 1e3 + (_rand(popsi) < p) *
                                          _randn(popsi) / (np.abs(_randn(popsi)) + 1e-199))
    tol = 1e-8
    fval = fval + 1.01 * tol
    idx = ftrue < tol
    try:
        fval[idx] = ftrue[idx]
    except IndexError: # fval is a scalar
        if idx:
            fval = ftrue
    return fval

### CLASS DEFINITION ###