def test_loading_columns():
network = pg.read_network()
print('\nstart loading columns\n')
st = time()
pg.load_columns(network)
print('processing time of loading columns :{0: .2f}'.format(time() - st) +
's')
print('\nstart column generation\n')
st = time()
iter_num = 0
column_update_num = 10
pg.perform_network_assignment(1, iter_num, column_update_num, network)
print('processing time of column generation:{0: .2f}'.format(time() - st) +
's'
f' for {iter_num} assignment iterations and '
f'{column_update_num} iterations in column generation')
pg.output_columns(network)
pg.output_link_performance(network)
print('\npath finding results can be found in agent.csv')
def test_column_generation_py():
network = pg.read_network()
print('\nstart column generation\n')
st = time()
iter_num = 20
column_update_num = 20
pg.perform_network_assignment(1, iter_num, column_update_num, network)
print(f'processing time of column generation: {time()-st:.2f} s'
f' for {iter_num} assignment iterations and '
f'{column_update_num} iterations in column generation')
# if you do not want to include geometry info in the output file,
# use pg.output_columns(network, False)
pg.output_columns(network)
pg.output_link_performance(network)
def test_loading_columns():
network = pg.read_network()
print('\nstart loading columns\n')
st = time()
pg.load_columns(network)
print(f'processing time of loading columns: {time()-st:.2f} s')
print('\nstart column generation\n')
st = time()
iter_num = 0
column_update_num = 10
pg.perform_network_assignment(1, iter_num, column_update_num, network)
print(f'processing time of column generation: {time()-st:.2f} s'
f' for {iter_num} assignment iterations and '
f'{column_update_num} iterations in column generation')
pg.output_columns(network)
pg.output_link_performance(network)