#include <algorithm> #include <iostream> #include <unordered_set> using namespace std; void printAllPermutationsFast(string s, string l) { if (s.length() < 1) { cout << l + s << endl; } unordered_set<char> uset; for (int i = 0; i < s.length(); i++) { if (uset.fin...
# permutations using library function fromitertoolsimportpermutations # Get all permutations of [1, 2, 3] perm = permutations([1,2,3]) # Print the obtained permutations foriinlist(perm): print(i) 输出: (1,2,3) (1,3,2) (2,1,3) (2,3,1) (3,1,2) (3,2,1) 它生成 n! 如果...
permutations('ABC', 2): print(i, end=" ") # 输出结果:('A', 'B') ('A', 'C') ('B', 'A') ('B', 'C') ('C', 'A') ('C', 'B') for i in itertools.combinations('ABC', 2): print(i, end=" ") # 输出结果:('A', 'B') ('A', 'C') ('B', 'C') for i...
使用itertools 模块进行排列组合: python -c "from itertools import permutations;print [''.join(i) for i in list(permutations(['a','b','c']))]" print([''.join(x) for x in itertools.product('ATCG', repeat=4)]) 52.解码16进制字符串:也可以直接 print 出来 >>> b='\xd1\xee\xba\...
[permutations[:train_size]] val_indices = known_mask.nonzero(as_tuple=True)[0][permutations[train_size:train_size + val_size]] test_indices = known_mask.nonzero(as_tuple=True)[0][permutations[train_size + val_size:]] data.train_mask[train_indices] = True data.val_mask[val_indices]...
permutations(range(8)) if 8 == len(set(vec[i]+i for i in range(8))) == len(set(vec[i]-i for i in range(8)))] (11)一行代码实现数组的flatten功能: 将多维数组转化为一维 代码语言:javascript 代码运行次数:0 运行 AI代码解释 flatten = lambda x: [y for l in x for y in ...
permutations(p,[,r]):从序列p中取出r个元素组成全排列,将排列得到的元组作为新迭代器的元素 combinations(p,r):从序列p中取出r个元素组成全组合,元素不允许重复,将组合得到的元组作为新迭代器的元素 conbinations_with_replacement(p,r):从序列p中取出r个元素组成全组合,元素允许重复,将组合得到的元组作为新迭...
比如，生成所有两位数的全排列：digits =[,1,2,3,4,5,6,7,8,9]permutations =[''.join(digits[i]for i in pair)for pair in itertools.permutations(range(10),2)]print(permutations[:10])# 输出：['01', '02', '03', '04', '05', '06', '07', '08', '09', '10']使用函数与...
my_dict = {i: i * i for i in xrange(100)} my_set = {i * 15 for i in xrange(100)} # There is only a difference of ':' in both # 两者的区别在于字典推导中有冒号 3. 强制浮点除法 from __future__ import division result = 1/2# print(result)# 0.5 ...
>>> z =zip(a, b) >>> z [(1,'a'), (2,'b'), (3,'c')]# Pivoting list of tuples>>>zip(*z) [(1,2,3), ('a','b','c')] ▍9、从iterables中获取最小值/最大值(具有/不具有特定功能) # Getting maximum from iterable>>> a = [1,2, -3] ...