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我正在尝试将单词列表（标记化字符串）分解为每个可能的子字符串。然后我想对每个子字符串运行一个 FreqDist，以找到最常见的子字符串。第一部分工作正常。但是，当我运行 FreqDist 时，出现错误：

TypeError: unhashable type: 'list'

这是我的代码：

import nltk

string = ['This','is','a','sample']
substrings = []

count1 = 0
count2 = 0

for word in string:
    while count2 <= len(string):
        if count1 != count2:
            temp = string[count1:count2]
            substrings.append(temp)
        count2 += 1
    count1 +=1
    count2 = count1

print substrings

fd = nltk.FreqDist(substrings)

print fd

的输出substrings很好。这里是：

[['This'], ['This', 'is'], ['This', 'is', 'a'], ['This', 'is', 'a', 'sample'], ['is'], ['is', 'a'], ['is', 'a', 'sample'], ['a'], ['a', 'sample'], ['sample']]

但是，我就是无法让 FreqDist 在其上运行。任何见解将不胜感激。在这种情况下，每个子字符串的 FreqDist 仅为 1，但该程序旨在在更大的文本样本上运行。

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1 回答 1

6

我不完全确定您想要什么，但错误消息是说它想要对列表进行哈希处理，这通常表明它正在将其放入集合中或将其用作字典键。我们可以通过给它元组来解决这个问题。

>>> import nltk
>>> import itertools
>>> 
>>> sentence = ['This','is','a','sample']
>>> contiguous_subs = [sentence[i:j] for i,j in itertools.combinations(xrange(len(sentence)+1), 2)]
>>> contiguous_subs
[['This'], ['This', 'is'], ['This', 'is', 'a'], ['This', 'is', 'a', 'sample'],
 ['is'], ['is', 'a'], ['is', 'a', 'sample'], ['a'], ['a', 'sample'],
 ['sample']]

但我们还有

>>> fd = nltk.FreqDist(contiguous_subs)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/nltk/probability.py", line 107, in __init__
    self.update(samples)
  File "/usr/local/lib/python2.7/dist-packages/nltk/probability.py", line 437, in update
    self.inc(sample, count=count)
  File "/usr/local/lib/python2.7/dist-packages/nltk/probability.py", line 122, in inc
    self[sample] = self.get(sample,0) + count
TypeError: unhashable type: 'list'

但是，如果我们将子序列制作成元组：

>>> contiguous_subs = [tuple(sentence[i:j]) for i,j in itertools.combinations(xrange(len(sentence)+1), 2)]
>>> contiguous_subs
[('This',), ('This', 'is'), ('This', 'is', 'a'), ('This', 'is', 'a', 'sample'), ('is',), ('is', 'a'), ('is', 'a', 'sample'), ('a',), ('a', 'sample'), ('sample',)]
>>> fd = nltk.FreqDist(contiguous_subs)
>>> print fd
<FreqDist: ('This',): 1, ('This', 'is'): 1, ('This', 'is', 'a'): 1, ('This', 'is', 'a', 'sample'): 1, ('a',): 1, ('a', 'sample'): 1, ('is',): 1, ('is', 'a'): 1, ('is', 'a', 'sample'): 1, ('sample',): 1>

那是你要找的吗？

于 2012-04-05T15:41:23.510 回答