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- import numpy as np
- import networkx as nx
- import matplotlib.pyplot as plt
- import scipy.io as sp
- import os
-
- path = 'output\mine'
- missing_node_count = 2
- mae_list = list()
- for filename in os.listdir(path):
- adj_matrix_orig = sp.loadmat(path + '\\' + filename)['remapped_data'].A
- adj_matrix_p = sp.loadmat(path + '\\' + filename)['out_data'].A
- mae = np.sum(abs(adj_matrix_orig - adj_matrix_p))
- mae = mae / (adj_matrix_p.shape[0] * 2 * missing_node_count)
- mae_list.append(mae)
-
- print(np.mean(mae_list))
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