HoloNet.tools.compute_ce_network_eigenvector_centrality#
- HoloNet.tools.compute_ce_network_eigenvector_centrality(ce_tensor, max_iter=500, tol=0.1, diff_thres=0.1)#
Calculate the eigenvector centrality of each cell in the CE network.
- Parameters
- ce_tensor
Tensor A CE tensor (LR_pair_num * cell_num * cell_num)
- max_iter
int(default:500) Maximum iteration number for get stable eigenvector centrality.
- tol
float(default:0.1) Defining stablity, we need the eigenvector centralities similar to the last iteration in how many cells.
- diff_thres
float(default:0.1) Defining stablity, the centrality of cells differs less than how much we consider similar.
- ce_tensor
- Return type
Tensor- Returns
: A tensor (LR_num * cell_num) for the eigenvector centrality of each cell according to each LR pair.