likelihoods.py 文件源码

def __split_apply(self, func_y_lt_f, func_y_gt_f, func_f_lt_0, y, f):

        # Make sure all arrays are of a compatible type
        y, f = np.broadcast_arrays(y, f)
        y = y.astype(float, copy=False)
        f = f.astype(float, copy=False)

        if any(y < 0):
            raise ValueError("y has to be > 0!")

        # get indicators of which likelihoods to apply where
        y_lt_f = np.logical_and(y <= f, f > 0)
        y_gt_f = np.logical_and(y > f, f > 0)
        f_lt_0 = f <= 0

        result = np.zeros_like(y)

        result[y_lt_f] = func_y_lt_f(y[y_lt_f], f[y_lt_f])
        result[y_gt_f] = func_y_gt_f(y[y_gt_f], f[y_gt_f])
        result[f_lt_0] = func_f_lt_0(y[f_lt_0], f[f_lt_0])

        return result