python – BFS,想要找到节点之间最长的路径,减少了findchildren方法

我已经打开了另一个主题正是这个主题,但我认为我发布了太多的代码,我不知道我的问题在哪里,现在我觉得我有更好的想法,但仍然需要帮助.我们所拥有的是一个包含3个字母单词的文本文件,只有3个字母单词.我还有一个Word(节点)和队列类.我的findchildren方法应该为一个单词找到所有孩子这个词,让我说我进入“粉丝”,然后我应该得到类似[“kan”,“man”….等等].代码目前看起来像这样：

def findchildren(mangd,parent): 
    children=set()
    lparent=list(parent)
    mangd.remove(parent)
    for word in mangd:
        letters=list(word)
        count=0
        i=0
        for a in letters:
            if a==lparent[i]:
                count+=1
                i+=1
            else:
                i+=1
            if count==2:
                if word not in children:
                    children.add(word)
            if i>2:
                break
    return children

上面的代码,对于findchildren目前工作正常,但是,当我将它用于我的其他方法(实现bfs-search)时,一切都会花费太长时间,因此,我想收集所有的孩子在字典中包含孩子的列表.感觉这个任务现在不属于我的联盟,但这可能吗？我试图创建这样的东西：

def findchildren2(mangd):
    children=[]
    for word in mangd:
        lparent=list(word)
        mangd.remove(word)
        letters=list(word)
        count=0
        i=0
        for a in letters:
            if a==lparent[i]:
                count+=1
                i+=1
            else:
                i+=1
            if count==2:
                if word not in children:
                    children.append(word)
            if i>2:
                break
    return children

我想我的最后一次尝试只是垃圾,我得到错误消息“使用迭代设置更改大小”.

def findchildren3(mangd,parent):
    children=defaultdict(list)
    lparent=list(parent)
    mangd.remove(parent)
    for word in mangd:
        letters=list(word)
        count=0
        i=0
        for a in letters:
            if a==lparent[i]:
                count+=1
                i+=1
            else:
                i+=1
            if count==2:
                children[0].append(word)
            if i>2:
                break
    return children

解决方法

有更有效的方法来做到这一点(下面是O(n ^ 2)所以不是很好)但这里是一个简单的算法,让你开始：

import itertools
from collections import defaultdict

words = ['abc','def','adf','adc','acf','dec']
bigrams = {k: {''.join(x) for x in itertools.permutations(k,2)} for k in words}
result = defaultdict(list)
for k,v in bigrams.iteritems():
    for word in words:
        if k == word:
            continue
        if len(bigrams[k] & bigrams[word]):
            result[k].append(word)
print result

生产：

defaultdict(<type 'list'>,{'abc': ['adc','acf'],'acf': ['abc','adc'],'adf': ['def','adc': ['abc','dec'],'dec': ['def','def': ['adf','dec']})

这是一个更高效的版本,带有一些评论：

import itertools
from collections import defaultdict

words = ['abc','dec']

# Build a map of {word: {bigrams}} i.e. {'abc': {'ab','ba','bc','cb','ac','ca'}}
bigramMap = {k: {''.join(x) for x in itertools.permutations(k,2)} for k in words}

# 'Invert' the map so it is {bigram: {words}} i.e. {'ab': {'abc','bad'},'bc': {...}}
wordMap = defaultdict(set)
for word,bigramSet in bigramMap.iteritems():
    for bigram in bigramSet:
        wordMap[bigram].add(word)

# Create a final map of {word: {words}} i.e. {'abc': {'abc','bad': {'abc','bad'}}
result = defaultdict(set)
for k,v in wordMap.iteritems():
    for word in v:
        result[word] |= v ^ {word}

# display all 'childen' of each word from the original list
for word in words:
    print "The 'children' of word {} are {}".format(word,result[word])

生产：

The 'children' of word abc are set(['acf','adc'])
The 'children' of word def are set(['adf','dec'])
The 'children' of word adf are set(['adc','acf'])
The 'children' of word adc are set(['adf','abc','dec','acf'])
The 'children' of word acf are set(['adf','adc'])
The 'children' of word dec are set(['adc','def'])