程序应该做的是采取步骤和一个数字,然后输出给您多少个唯一的序列,它们精确地x为steps
来创建number
。
有人知道我可以如何节省一些内存-因为我应该在4秒内使这项工作适用于非常庞大的数字。
def IsaacRule(steps, number):
if number in IsaacRule.numbers:
return 0
else:
IsaacRule.numbers.add(number)
if steps == 0:
return 1
counter = 0
if ((number - 1) / 3) % 2 == 1:
counter += IsaacRule(steps-1, (number - 1) / 3)
if (number * 2) % 2 == 0:
counter += IsaacRule(steps-1, number*2)
return counter
IsaacRule.numbers = set()
print(IsaacRule(6, 2))
如果有人知道带有备忘的版本,我会很感激,现在可以使用,但是仍有改进的空间。
答案 0 :(得分:0)
基线:IsaacRule(50, 2)
花费6.96秒
这使代码花费了更长的时间,并给出了不同的最终结果
(number * 2) % 2 == 0
至True
IsaacRule(50, 2)
耗时0.679s。感谢Pm2Ring。
((number - 1) / 3) % 2 == 1
简化为number % 6 == 4
,并在可能的情况下使用楼层分割: IsaacRule(50, 2)
耗时0.499s
真值表:
| n | n-1 | (n-1)/3 | (n-1)/3 % 2 | ((n-1)/3)%2 == 1 |
|---|-----|---------|-------------|------------------|
| 1 | 0 | 0.00 | 0.00 | FALSE |
| 2 | 1 | 0.33 | 0.33 | FALSE |
| 3 | 2 | 0.67 | 0.67 | FALSE |
| 4 | 3 | 1.00 | 1.00 | TRUE |
| 5 | 4 | 1.33 | 1.33 | FALSE |
| 6 | 5 | 1.67 | 1.67 | FALSE |
| 7 | 6 | 2.00 | 0.00 | FALSE |
代码:
def IsaacRule(steps, number):
if number in IsaacRule.numbers:
return 0
else:
IsaacRule.numbers.add(number)
if steps == 0:
return 1
counter = 0
if number % 6 == 4:
counter += IsaacRule(steps-1, (number - 1) // 3)
counter += IsaacRule(steps-1, number*2)
return counter
IsaacRule(50, 2)
耗时0.381s
这使我们可以利用对集合所做的任何优化。基本上,我在这里进行广度优先搜索。
IsaacRule(50, 2)
耗时0.256s
我们只需要添加一个检查number != 1
即可打破唯一已知的周期。这样可以加快速度,但是如果您从1开始,则需要添加一个特殊情况。谢谢Paul的建议!
START = 2
STEPS = 50
# Special case since we broke the cycle
if START == 1:
START = 2
STEPS -= 1
current_candidates = {START} # set of states that can be reached in `step` steps
for step in range(STEPS):
# Get all states that can be reached from current_candidates
next_candidates = set(number * 2 for number in current_candidates if number != 1) | set((number - 1) // 3 for number in current_candidates if number % 6 == 4)
# Next step of BFS
current_candidates = next_candidates
print(len(next_candidates))