def part_4(num_files):
out_file = open('data/part_4_data.csv','w')
writer = csv.writer(out_file)
# Header
writer.writerow(('maze_num','forward_exec_time','adaptive_exec_time','forward_expanded_states','adaptive_expanded_states'))
for i in range(0,num_files):
maze_file = "mazes/maze_{0}.csv".format(i)
grid, size = env.read_grid(maze_file)
start = Cell(0,0,size)
goal = Cell(100,100,size)
forward_expanded_states = 0
adaptive_expanded_states = 0
print "forward"
forward_start = datetime.datetime.now()
path, forward_expanded_states = algo.repeated_forward_a_star(start,goal,grid,0,forward_expanded_states)
forward_end = datetime.datetime.now()
print "reset grid"
# RE-INITIALIZE GRID
new_grid, size = env.read_grid(maze_file)
print "adaptive"
adaptive_start = datetime.datetime.now()
path, adaptive_expanded_states = algo.adaptive_a_star(start,goal,new_grid,0,adaptive_expanded_states)
adaptive_end = datetime.datetime.now()
forward_exec_time = forward_end - forward_start
adaptive_exec_time = adaptive_end - adaptive_start
forward_exec_time = forward_exec_time.total_seconds()
adaptive_exec_time = adaptive_exec_time.total_seconds()
print "{0},{1},{2},{3},{4}".format(i,forward_exec_time,adaptive_exec_time,forward_expanded_states,adaptive_expanded_states)
writer.writerow((i,forward_exec_time,adaptive_exec_time,forward_expanded_states,adaptive_expanded_states))
out_file.close()
def part_2(num_files):
# Compare run times for each maze using the two tie-break methods
out_file = open('data/part_2_data.csv','w')
writer = csv.writer(out_file)
# Header
writer.writerow(('maze_num','smaller_exec_time','larger_exec_time','smaller_expanded_states','larger_expanded_states'))
for i in range(0,num_files):
maze_file = "mazes/maze_{0}.csv".format(i)
grid, size = env.read_grid(maze_file)
start = Cell(0,0,size)
goal = Cell(100,100,size)
smaller_expanded_states = 0
larger_expanded_states = 0
print "start smaller"
smaller_break_start = datetime.datetime.now()
path, smaller_expanded_states = algo.repeated_forward_a_star(start,goal,grid,1,smaller_expanded_states)
smaller_break_end = datetime.datetime.now()
print "reset grid"
# RE-INITIALIZE GRID
new_grid, size = env.read_grid(maze_file)
print "start larger"
larger_break_start = datetime.datetime.now()
path, larger_expanded_states = algo.repeated_forward_a_star(start,goal,new_grid,0,larger_expanded_states)
larger_break_end = datetime.datetime.now()
smaller_exec_time = (smaller_break_end - smaller_break_start).total_seconds()
larger_exec_time = (larger_break_end - larger_break_start).total_seconds()
print "{0},{1},{2},{3},{4}".format(i,smaller_exec_time,larger_exec_time,smaller_expanded_states,larger_expanded_states)
writer.writerow((i,smaller_exec_time,larger_exec_time,smaller_expanded_states,larger_expanded_states))
out_file.close()
import environment as env import pprint import sys import algo from cell import Cell # import pdb if __name__ == '__main__': # Get rid of the .pyc files that get generated on each run sys.dont_write_bytecode = True pp = pprint.PrettyPrinter() if len(sys.argv) != 2: print "Format: python main.py <path to maze file>" sys.exit(1) else: maze_file = sys.argv[1] grid, size = env.read_grid(maze_file) start = Cell(0,0,101) goal = Cell(9,9,101) algo.print_grid(grid, start, goal) algo.a_star(start, goal, grid)
import environment as env
import pprint
import sys
import algo
from cell import Cell
# import pdb
if __name__ == '__main__':
# Get rid of the .pyc files that get generated on each run
sys.dont_write_bytecode = True
pp = pprint.PrettyPrinter()
if len(sys.argv) != 2:
print "Format: python main.py <path to maze file>"
sys.exit(1)
else:
maze_file = sys.argv[1]
grid, size = env.read_grid(maze_file)
start = Cell(0, 0, 101)
goal = Cell(9, 9, 101)
algo.print_grid(grid, start, goal)
algo.a_star(start, goal, grid)