def find_median(array, left, right):
middle = left + ((right - left)/2)
elements = [(array[x], x) for x in set([left, middle, right])]
if len(elements) == 3:
# 'true' median is the middle element
median, index = sorted(elements)[1]
else:
# no median found, use minimum as pivot
median, index = min(elements)
# avoid overhead, skip debug logging
if log.level == logging.DEBUG:
debug_message = []
for x, y in elements:
is_median = median == x
msg = utils.array2str(array, y, mark=is_median, spacing=8)
debug_message.append(msg)
log.debug("\n" + "\n".join(debug_message))
return (median, index)
def find_pivot(array, left, right):
array_name = "pivot"
pivot = None
if __question__ == 1:
# Question 2.1 (pivot = first element)
pivot = left
elif __question__ == 2:
# Question 2.2 (pivot = final element)
pivot = right
elif __question__ == 3:
# Question 2.3 (Median of 3; left/right)
median, pivot = find_median(array, left, right)
if pivot is None or pivot < 0:
raise Exception("Failed to find pivot")
log.debug(utils.array2str(array, pivot, array_name))
swap(array, left, pivot)
return array[left]
for p in problems:
start = time.clock()
initial_state = shape(p)
s = Sudoku(initial_state)
s.random_fill()
final_state, steps, score = heuristics_options[args.heuristic](args, s)
x.append(steps)
y.append(score)
tclock = time.clock() - start
if args.verbose:
print("execution time:", tclock)
if args.heuristic == "sa":
data.append((p, args.heuristic, array2str(final_state.flatten()),
s.cost_function(final_state), len(steps), tclock))
else:
data.append((p, args.heuristic, array2str(final_state.flatten()),
score, steps, tclock))
output_csv(args, data)
plots_options = {
"hc": plot_2D_grid_hc,
"hcr": plot_2D_grid_hcr,
"sa": plot_2D_grid_sa
}
plots_options[args.heuristic](x, y, args.img_output_dir)