[原创]一道面试题
题目: 2n个数,一半奇数,一半偶数,设计一个程序让奇数位上的数是奇数,偶数位上的是偶数
要求:时空复杂度尽量低
看到群里发的这个题目,随手写了个一个答案:
def swap(a, i, j): a[i] = a[i] + a[j] a[j] = a[i] - a[j] a[i] = a[i] - a[j] def Fun(): the_list = [x for x in range(100)] print "orginal:", the_list random.shuffle(the_list) print "shuffled:", the_list i,j = 0,1 nSwap = 0 while nSwap < 50 and max(i,j) < 100: if the_list[i] % 2 != 0 and the_list[j] % 2 == 0 : swap(the_list,i,j) i += 2 j += 2 nSwap += 1 elif the_list[i] % 2 == 0 : i += 2 elif the_list[j] % 2 != 0 : j += 2 print "sorted:", the_list
经penny等群友的提醒,优化一下,第二版:
def Fun2(): the_list = [x for x in range(100)] print "orginal:", the_list random.shuffle(the_list) print "shuffled:", the_list for i,j in zip([pos for pos in range(0,100,2) if (the_list[pos] + pos) % 2 != 0], [pos for pos in range(1,100,2) if (the_list[pos] + pos) % 2 != 0]): the_list[i], the_list[j] = the_list[j], the_list[i] print "sorted:", the_list
附:penny发了一个点积的优化
A[]={<0,4>,<3,5>,<8,3>} B[]={<3,5>,<9,3>} C=A*B = {<3,25>} for(i=0,j=0;i<lenA&&j<lenB;) { k=0; if(A[i].index == B[j].index) { C[k].index = A[i].index; C[k].value = A[i].value * B[j].value k++ } else if(A[i].index < B[j].index) { i++; } else if(A[i].index > B[j].index ) { j++; } } A_I[]={0,3,8} B_I[]={3,9} A_V[]={4,5,9} B_V[]={5,3} for(i=0,j=0;i<lenA&&j<lenB;) { k=0; if(A_I[i] == B_I[j]) { C[k].index = A_I[i]; C[k].value = A_V[i]*B_V[j]; } else if(A_I[i] < B_I[j]) { i++; } else { j++; } } for(i=0,j=0;i<lenA&&j<lenB;) { k=0; i=0; j=0; bool equal = A_I[i] == B_I[j]; bool smaller= A_I[i] < B_I[j]; bool bigger = A_I[i] > B_I[j]; C[k].index = equal*A_I[i]; C[k].value = equal*A_V[i]*B_V[j]; k+=equal; i+=equal; j+=equal; i+=smaller; j+=biger; }
[原创]生成自描述的序列
给你10分钟时间,根据上排给出十个数,在其下排填出对应的十个数
要求下排每个数都是先前上排那十个数在下排出现的次数。
上排的十个数如下:
【0,1,2,3,4,5,6,7,8,9】
最省脑细胞的做法自然是盲搜:
def selfDescribableSeqence(arr): for guess in range(9*10**len(arr)): guess_list = (['0']*(10-len(str(guess)))) guess_list.extend(list(str(guess))) if isOK(arr, guess_list): return guess_list def isOK(top, bottom): def freq(val): return len(list(filter(lambda x: x == val, bottom))) return len(list(filter(lambda x: str(freq(x)) == bottom[int(x)], top))) == len(top) if __name__ == '__main__': print(selfDescribableSeqence(list(map(str, list(range(0,10))))))
显然,脑细胞是省下了,CPU就太浪费了,要判断解空间之外的很多分支。改成宽度优先:
def selfDescribableSeqence(): res = list(range(10)) while True: for pos in range(10): adjust(res, pos) if isOK(res): return res def freq(arr,val): return len(list(filter(lambda x: x == val, arr))) def adjust(arr, pos): the_freq = freq(arr, pos) if arr[pos] != the_freq: arr[pos] = the_freq pos = the_freq def isOK(arr): id_and_value = [(id, val) for (id,val) in enumerate(arr)] return len(list(filter(lambda x : freq(arr, x[0])==x[1], id_and_value))) == len(id_and_value) if __name__ == '__main__': print(selfDescribableSeqence())