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你好：只是一个简单的问题.. 我希望。我正在尝试使用该程序从语料库中生成随机文本..在这种情况下是一本书的一部分。

我有一个文本文件是我的语料库：（这是介绍，不会在这里发布整个内容）

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接下来我有我正在尝试使用的课程：

import random

class Markov(object):

    def __init__(self, open_file):
        self.cache = {}
        self.open_file = open_file
        self.words = self.file_to_words()
        self.word_size = len(self.words)
        self.database()


def file_to_words(self):
    self.open_file.seek(0)
    data = self.open_file.read()
    words = data.split()
    return words


def triples(self):
    """ Generates triples from the given data string. So if our string were
            "What a lovely day", we'd generate (What, a, lovely) and then
            (a, lovely, day).
    """

    if len(self.words) < 3:
        return

    for i in range(len(self.words) - 2):
        yield (self.words[i], self.words[i+1], self.words[i+2])

def database(self):
    for w1, w2, w3 in self.triples():
        key = (w1, w2)
        if key in self.cache:
            self.cache[key].append(w3)
        else:
            self.cache[key] = [w3]

def generate_markov_text(self, size=25):
    seed = random.randint(0, self.word_size-3)
    seed_word, next_word = self.words[seed], self.words[seed+1]
    w1, w2 = seed_word, next_word
    gen_words = []
    for i in xrange(size):
        gen_words.append(w1)
        w1, w2 = w2, random.choice(self.cache[(w1, w2)])
    gen_words.append(w2)
    return ' '.join(gen_words)

最后给出错误的主要内容：“'Markov'对象没有属性'file_to_words'”

import Class
file_ = open('derp.txt')
markov = Class.Markov(file_)
markov.generate_markov_text()

这里出了什么问题？谢谢。

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2 回答 2

2

您需要缩进该file_to_words方法，使其成为 Markov 类的一部分。您目前拥有它的方式是函数中的模块级Class函数。将file_to_words方法中的所有内容（包括def行）向右移动 4 个空格。

更新：所有其他方法也是如此。Python 使用空格/缩进来表示范围。

于 2012-11-24T03:09:01.383 回答
1

从您发布的代码中，除了 init 之外的所有方法都不属于 Markov 类，因为缩进。

于 2012-11-24T03:09:28.607 回答