update

app_utils.py

@@ -10,7 +10,7 @@ from scipy.interpolate import Rbf
 from scipy.optimize import linear_sum_assignment
 from sklearn.neighbors import NearestNeighbors
 
-def reorder_data(idx_order, fill_flags, inputname, m_filename):
+def reorder_data(idx_order, fill_flags, inputname, filename):
 	# read the input data
 	raw_data = utils.read_train_data(inputname)
 	#print(raw_data.shape)
@@ -26,12 +26,12 @@ def reorder_data(idx_order, fill_flags, inputname, m_filename):
 			tmp_data = [raw_data[j, :] for j in idx_set]
 			new_data[i, :] = np.mean(tmp_data, axis=0)
 	
-	utils.save_data(new_data, m_filename)
+	utils.save_data(new_data, filename)
 	return raw_data.shape
 
-def restore_order(batch_cnt, raw_data_shape, idx_order, fill_flags, d_filename, outputname):
+def restore_order(batch_cnt, raw_data_shape, idx_order, fill_flags, filename, outputname):
 	# read the denoised data
-	d_data = utils.read_train_data(d_filename)
+	d_data = utils.read_train_data(filename)
 	if batch_cnt == 0:
 		new_data = np.zeros((raw_data_shape[0], d_data.shape[1]))
 		#print(new_data.shape)