<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def asarray(self, out=None):
 """Extract the data of this vector as a numpy array. Only available if `is_power_space` is True. The ordering is such that it commutes with indexing:: self[ind].asarray() == self.asarray()[ind] Parameters out : `numpy.ndarray`, optional Array in which the result should be written in-place. Has to be contiguous and of the correct dtype and shape. Raises ------ ValueError If `is_power_space` is false. Examples -------- array([[ 1., 2., 3.], [ 4., 5., 6.]]) """

        if not self.space.is_power_space:
            raise ValueError('cannot use `asarray` if `space.is_power_space` '
                             'is `False`')
        else:
            if out is None:
                out = np.empty(self.shape, self.dtype)

            for i in range(len(self)):
                out[i] = np.asarray(self[i])
            return out