psis.py 文件源码

def gpinv(p, k, sigma):
    """Inverse Generalised Pareto distribution function."""
    x = np.empty(p.shape)
    x.fill(np.nan)
    if sigma <= 0:
        return x
    ok = (p > 0) & (p < 1)
    if np.all(ok):
        if np.abs(k) < np.finfo(float).eps:
            np.negative(p, out=x)
            np.log1p(x, out=x)
            np.negative(x, out=x)
        else:
            np.negative(p, out=x)
            np.log1p(x, out=x)
            x *= -k
            np.expm1(x, out=x)
            x /= k
        x *= sigma
    else:
        if np.abs(k) < np.finfo(float).eps:
            # x[ok] = - np.log1p(-p[ok])
            temp = p[ok]
            np.negative(temp, out=temp)
            np.log1p(temp, out=temp)
            np.negative(temp, out=temp)
            x[ok] = temp
        else:
            # x[ok] = np.expm1(-k * np.log1p(-p[ok])) / k
            temp = p[ok]
            np.negative(temp, out=temp)
            np.log1p(temp, out=temp)
            temp *= -k
            np.expm1(temp, out=temp)
            temp /= k
            x[ok] = temp
        x *= sigma
        x[p == 0] = 0
        if k >= 0:
            x[p == 1] = np.inf
        else:
            x[p == 1] = -sigma / k
    return x