for batch_size in input_cons.batch_size:
for chain_num in input_cons.chains_num:
#chain.generate(chain_num, funs, randomChain=True)
#chain.user_generatore(0, forEachChain=True)
#chain.read(input_cons.chains_random_path + input_cons.chains_random_name)
#user_num = chain.num()
# chain = Chains(graph, funs)
#print('##############')
#print('number of chains: {}/ number of users: {} / KSP: {} / alpha: {} / bathc size: {}'.format(chain_num, chain_num, k, alpha, batch_size))
for i in range(input_cons.run_num):
print('*********')
print('epoch: {} / {}'.format(i+1, input_cons.run_num))
# chain.generate(chain_num, funs, randomChain=True)
# chain.user_generatore(0, input_cons.chains_random_path + input_cons.chains_random_name + str(chain_num) + '_' + str(i) + '.json', forEachChain=True)
chain.read(input_cons.chains_random_path + input_cons.chains_random_name + str(chain_num) + '_' + str(i) + '.json')
user_num = chain.num()
for k in input_cons.k_path_num:
for alpha in input_cons.alpha:
print('#######')
print('number of chains: {}/ number of users: {} / KSP: {} / alpha:{} / bathc size: {} / epoch: {}/{}'.format(chain_num, chain_num, k, alpha, batch_size, i+1, input_cons.run_num))
plot.run(input_cons.approaches, graph, chain, funs, k, alpha, batch_size, user_num)
user_list.append(user_num)
chain_list.append(chain_num)
# print(graph.node_list[0].cap_cpu)
#print(graph.node_list[1].cap_cpu)
#plot.box_plot_save(input_cons.approaches, user_num, k, alpha, batch_size, versus_chain=True, versus_user=False, show=False, fomat_list=input_cons.format)
#plot.curve(input_cons.approaches, alpha, batch_size, k, user_list, chain_list, 0, 0, format_list=input_cons.format, show=False, versus_chain=True, versus_user=False)
user_list = []
chain_list = []
