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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _generate_G_points(self, kpoint):
 """ Helper function to generate G-points based on nbmax. This function iterates over possible G-point values and determines if the energy is less than G_{cut}. Valid values are appended to the output array. This function should not be called outside of initialization. Args: kpoint (np.array):
 the array containing the current k-point value Returns: a list containing valid G-points """

        gpoints = []
        for i in range(2 * self._nbmax[2] + 1):
            i3 = i - 2 * self._nbmax[2] - 1 if i > self._nbmax[2] else i
            for j in range(2 * self._nbmax[1] + 1):
                j2 = j - 2 * self._nbmax[1] - 1 if j > self._nbmax[1] else j
                for k in range(2 * self._nbmax[0] + 1):
                    k1 = k - 2 * self._nbmax[0] - 1 if k > self._nbmax[0] else k
                    G = np.array([k1, j2, i3])
                    v = kpoint + G
                    g = np.linalg.norm(np.dot(v, self.b))
                    E = g ** 2 / self._C
                    if E < self.encut:
                        gpoints.append(G)
        return np.array(gpoints, dtype=np.float64)