One of the difficulties in the expansion of light field data is to expand the viewpoint and image point plane support simultaneously and maintain a good space-angle consistency. In this paper, we propose to use the neural light field network to represent the rays parameterized by a biplane, generate the rays that do not exist in the atomic light field data, and extend the viewpoint and image plane branches. To gather statistics of extension part of the error of generated rays, we refer to the error between the generated rays and original data in the overlapping area of the sub-light field. It allows determining the proportion of data with good generation effect in the extended part. We analyze the influence of the size of the overlapping area of the sub-light field on the effect of the extended light field. Experimental results on Blender simulation data show that the proposed method can realize the simultaneous expansion of the sub-light field viewpoint and image plane branch, and the epipolar plane images (EPI) display extension part can maintain a good space-angle consistency. When the proportion of overlapping regions of sub-light field data increases from 42.9% to 77.8%, the proportion of data with good generation effect in extended regions increases from 82.91% to 84.68%. This analysis has certain guiding significance for the design of sub-light field data when expanding light field data.