def main() :
graph_stater = GraphStat()
timer = TimeStat()
for vertex_num in VERTEX_NUM_LIST :
logging.info('random generate connected graph ( vertex %d)' % vertex_num)
vertex , adj_matrix = generate_random_connected_graph(vertex_num , False)
logging.info('generate graph done .')
graph_stater.add_stat_graph(vertex , adj_matrix)
timer.add_stat_vertex_num(vertex_num)
# dfs
logging.info('using dfs to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_dfs = find_hamiltonian_in_dfs(vertex , adj_matrix , timer)
timer.end_time_stat()
timer.add_stat_dfs_timecost(timer.get_time_cost())
graph_stater.add_stat_dfs_path(hamiltonian_path_in_dfs)
logging.info('dfs done .')
print_path_in_console(hamiltonian_path_in_dfs)
# bfs
logging.info('using bfs to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_bfs = find_hamiltonian_in_bfs(vertex , adj_matrix , timer)
timer.end_time_stat()
timer.add_stat_bfs_timecost(timer.get_time_cost())
graph_stater.add_stat_bfs_path(hamiltonian_path_in_bfs)
logging.info('bfs done .')
print_path_in_console(hamiltonian_path_in_bfs)
#hill climbing
logging.info('using hillclimbing to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_hillclimbing = find_hamiltonian_in_hillclimbing(vertex , adj_matrix , timer)
timer.end_time_stat()
timer.add_stat_hillclimbing_timecost(timer.get_time_cost())
graph_stater.add_stat_hill_climbing_path(hamiltonian_path_in_hillclimbing)
logging.info('hillclimbing done .')
print_path_in_console(hamiltonian_path_in_hillclimbing)
# Min Hamiltonian
# it is different from previous
logging.info('generate a complete random weighted graph')
vertex , cost_matrix = generate_random_weighted_complete_graph(vertex_num,False)
logging.info('done .')
logging.info('using branch and bound to find minimum halmiltonian')
graph_stater.add_stat_complete_graph(vertex , cost_matrix)
timer.start_time_stat()
min_hamiltonian = find_min_hamiltonian_in_branch_and_bound(vertex , cost_matrix)
timer.end_time_stat()
timer.add_stat_branch_and_bound_timecout(timer.get_time_cost())
graph_stater.add_stat_branch_and_bound_path(min_hamiltonian)
print_path_in_console(min_hamiltonian)
logging.info('branch and bound done .')
graph_stater.draw_stat()
timer.print_time_cost()
timer.draw_stat()
plot.show()
map_matrix[i + 1][j + 1] = map_matrix[i][j] + 1
if map_matrix[i + 1][j + 1] > m_max:
m_max = map_matrix[i + 1][j + 1]
position = i + 1
'''
print(' ' + ' '.join(list(string_2)))
for idx, i in enumerate(map_matrix):
if idx == 0:
print(' ', i)
else:
print(string_1[idx - 1], i)
'''
return string_1[position - m_max:position], int(m_max)
if __name__ == '__main__':
import time
from time_stat import TimeStat
lcs_dp = LongestCommonStringDynamicProgramming()
string_1 = '123456778'
string_2 = '129834567486782'
max_iter = 10000
with TimeStat() as ts:
for i in range(max_iter):
res = lcs_dp(string_1, string_2, flag=False)
with TimeStat() as ts:
for i in range(max_iter):
res = lcs_dp(string_1, string_2, flag=True)
def main():
graph_stater = GraphStat()
timer = TimeStat()
for vertex_num in VERTEX_NUM_LIST:
logging.info('random generate connected graph ( vertex %d)' %
vertex_num)
vertex, adj_matrix = generate_random_connected_graph(vertex_num, False)
logging.info('generate graph done .')
graph_stater.add_stat_graph(vertex, adj_matrix)
timer.add_stat_vertex_num(vertex_num)
# dfs
logging.info('using dfs to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_dfs = find_hamiltonian_in_dfs(
vertex, adj_matrix, timer)
timer.end_time_stat()
timer.add_stat_dfs_timecost(timer.get_time_cost())
graph_stater.add_stat_dfs_path(hamiltonian_path_in_dfs)
logging.info('dfs done .')
print_path_in_console(hamiltonian_path_in_dfs)
# bfs
logging.info('using bfs to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_bfs = find_hamiltonian_in_bfs(
vertex, adj_matrix, timer)
timer.end_time_stat()
timer.add_stat_bfs_timecost(timer.get_time_cost())
graph_stater.add_stat_bfs_path(hamiltonian_path_in_bfs)
logging.info('bfs done .')
print_path_in_console(hamiltonian_path_in_bfs)
#hill climbing
logging.info('using hillclimbing to find hamiltonian')
timer.start_time_stat()
hamiltonian_path_in_hillclimbing = find_hamiltonian_in_hillclimbing(
vertex, adj_matrix, timer)
timer.end_time_stat()
timer.add_stat_hillclimbing_timecost(timer.get_time_cost())
graph_stater.add_stat_hill_climbing_path(
hamiltonian_path_in_hillclimbing)
logging.info('hillclimbing done .')
print_path_in_console(hamiltonian_path_in_hillclimbing)
# Min Hamiltonian
# it is different from previous
logging.info('generate a complete random weighted graph')
vertex, cost_matrix = generate_random_weighted_complete_graph(
vertex_num, False)
logging.info('done .')
logging.info('using branch and bound to find minimum halmiltonian')
graph_stater.add_stat_complete_graph(vertex, cost_matrix)
timer.start_time_stat()
min_hamiltonian = find_min_hamiltonian_in_branch_and_bound(
vertex, cost_matrix)
timer.end_time_stat()
timer.add_stat_branch_and_bound_timecout(timer.get_time_cost())
graph_stater.add_stat_branch_and_bound_path(min_hamiltonian)
print_path_in_console(min_hamiltonian)
logging.info('branch and bound done .')
graph_stater.draw_stat()
timer.print_time_cost()
timer.draw_stat()
plot.show()
def main() :
timer = TimeStat()
pntStater = PointStat()
pnt_nums = PNT_NUM_LIST
logging_format = "{method_name}-{pnt_num} done ."
for pnt_num in pnt_nums :
pnts = generate_pnts_in_random(pnt_num , is_static_random=False)
pntStater.add_stat_pnts(pnts)
timer.add_stat_pnt_num(pnt_num)
# brute force
method_name = "brute force"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_bruteforce(pnts)
#print convex_hull_pnts
plot_pnts = ready_plot_pnts_bruteforce(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_brute_force_timecost(timer.get_time_cost())
pntStater.add_stat_bruteforce_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()) )
# graham scan
method_name = "gramham scan"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_grahamscan(pnts)
plot_pnts = ready_plot_pnts_grahamscan(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_graham_scan_timecost(timer.get_time_cost())
pntStater.add_stat_graham_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()) )
# divide conquer
method_name = "divide conquer"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_dc(pnts)
plot_pnts = ready_plot_pnts_dc(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_dc_timecost(timer.get_time_cost())
pntStater.add_stat_dc_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()) )
timer.print_time_cost()
pntStater.draw_stat(convex_hull_pnt_plot_config)
timer.draw_stat()
plot.show()
def main():
timer = TimeStat()
pntStater = PointStat()
pnt_nums = PNT_NUM_LIST
logging_format = "{method_name}-{pnt_num} done ."
for pnt_num in pnt_nums:
pnts = generate_pnts_in_random(pnt_num, is_static_random=False)
pntStater.add_stat_pnts(pnts)
timer.add_stat_pnt_num(pnt_num)
# brute force
method_name = "brute force"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_bruteforce(pnts)
#print convex_hull_pnts
plot_pnts = ready_plot_pnts_bruteforce(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_brute_force_timecost(timer.get_time_cost())
pntStater.add_stat_bruteforce_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()))
# graham scan
method_name = "gramham scan"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_grahamscan(pnts)
plot_pnts = ready_plot_pnts_grahamscan(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_graham_scan_timecost(timer.get_time_cost())
pntStater.add_stat_graham_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()))
# divide conquer
method_name = "divide conquer"
timer.start_time_stat()
convex_hull_pnts = find_convex_hull_dc(pnts)
plot_pnts = ready_plot_pnts_dc(convex_hull_pnts)
timer.end_time_stat()
timer.add_stat_dc_timecost(timer.get_time_cost())
pntStater.add_stat_dc_convex_hull(plot_pnts)
logging.info(logging_format.format(**locals()))
timer.print_time_cost()
pntStater.draw_stat(convex_hull_pnt_plot_config)
timer.draw_stat()
plot.show()
