def main(
original_in_degree, original_out_degree, parent_dir
# original_average_neighbor_degree, \
# original_pageRank, \
# original_triangle, \
# original_local_clustering_coefficient,\
# original_core_number
):
#############################Random Node###############################################################################
#GraphGT = nx.read_graphml("Simulation.graphml")
EdgeList_Simulation = []
simulated_file = parent_dir + "/SimulatedGraph/localgen_0.csv"
#with open('/work/fz56/LANS-6.0/SimulatedGraph/localgen_0.csv') as csvfile:
with open(simulated_file) as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
EdgeList_Simulation.append((row["source"], row["destination"]))
GraphGT = nx.MultiDiGraph()
GraphGT.add_edges_from(EdgeList_Simulation)
PropertyGT = Property(GraphGT)
propertyDistance = [0.0] * 7
in_degree = PropertyGT.getInDegree()
New_Node_In_Degree = open('New_Node_In_Degree.txt', "w")
for e in in_degree:
New_Node_In_Degree.write(str(e) + "\n")
New_Node_In_Degree.close()
out_degree = PropertyGT.getOutDegree()
New_Node_Out_Degree = open('New_Node_Out_Degree.txt', "w")
for e in out_degree:
New_Node_Out_Degree.write(str(e) + "\n")
New_Node_Out_Degree.close()
# average_neighbor_degree = PropertyGT.getAverageNeighborDegree()
# New_Average_Neighbor_Degree = open('New_Average_Neighbor_Degree.txt', "w")
# for e in average_neighbor_degree:
# New_Average_Neighbor_Degree.write(str(e) + "\n")
# New_Average_Neighbor_Degree.close()
#
# pageRank = PropertyGT.getPageRank()
# New_pageRank = open('New_pageRank.txt', "w")
# for e in pageRank:
# New_pageRank.write(str(e) + "\n")
# New_pageRank.close()
#
# triangle = PropertyGT.getTriangles()
# New_triangle = open('New_triangle.txt', "w")
# for e in triangle:
# New_triangle.write(str(e) + "\n")
# New_triangle.close()
#
# local_clustering_coefficient = PropertyGT.getLocalClusteringCoefficient()
# New_local_clustering_coefficient = open('New_local_clustering_coefficient.txt', "w")
# for e in local_clustering_coefficient:
# New_local_clustering_coefficient.write(str(e) + "\n")
# New_local_clustering_coefficient.close()
#
# core_number = PropertyGT.getCoreNumber()
# New_core_number = open('New_core_number.txt', "w")
# for e in core_number:
# New_core_number.write(str(e) + "\n")
# New_core_number.close()
propertyDistance[0] = originalPropertyGT.averageKL(original_in_degree,
in_degree)
propertyDistance[1] = originalPropertyGT.averageKL(original_out_degree,
out_degree)
# propertyDistance[2] = originalPropertyGT.averageKL(original_average_neighbor_degree, average_neighbor_degree)
# propertyDistance[3] = originalPropertyGT.averageKL(original_pageRank, pageRank)
# propertyDistance[4] = originalPropertyGT.averageKL(original_triangle, triangle)
# propertyDistance[5] = originalPropertyGT.averageKL(original_local_clustering_coefficient, local_clustering_coefficient)
# propertyDistance[6] = originalPropertyGT.averageKL(original_core_number, core_number)
print('\n')
for i in range(len(propertyDistance)):
print(propertyDistance[i], end="\t")
print('\n')
#with open('/work/fz56/LANS-6.0/input_files/8.binetflow') as csvfile:
with open(data_file) as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
EdgeList_Original.append((row["SrcAddr"], row["DstAddr"]))
GT = nx.MultiDiGraph()
GT.add_edges_from(EdgeList_Original)
#GT = nx.read_graphml("CTU13_4_Original.graphml")
originalPropertyGT = Property(GT)
original_in_degree = originalPropertyGT.getInDegree()
Original_Node_In_Degree = open('Original_Node_In_Degree.txt', "w")
for e in original_in_degree:
Original_Node_In_Degree.write(str(e) + "\n")
Original_Node_In_Degree.close()
original_out_degree = originalPropertyGT.getOutDegree()
Original_Node_Out_Degree = open('Original_Node_Out_Degree.txt', "w")
for e in original_out_degree:
Original_Node_Out_Degree.write(str(e) + "\n")
Original_Node_Out_Degree.close()
# original_average_neighbor_degree = originalPropertyGT.getAverageNeighborDegree()
# Original_average_neighbor = open('Original_average_neighbor_Degree.txt', "w")
# for e in original_average_neighbor_degree:
# Original_average_neighbor.write(str(e) + "\n")
# Original_average_neighbor.close()
#
# original_pageRank = originalPropertyGT.getPageRank()
# Original_PageRank = open('Original_PageRank.txt', "w")
# for e in original_pageRank:
# Original_PageRank.write(str(e) + "\n")
