帮我写一个textRANK算法代码

好的，以下是一个简单的textRANK算法的Python代码：

import jieba
import numpy as np

class TextRank:
    def __init__(self, text, window=5, alpha=0.85, eps=1e-4):
        self.text = text
        self.window = window
        self.alpha = alpha
        self.eps = eps
        self.words = list(jieba.cut(text))
        self.word_set = list(set(self.words))
        self.word_index = {w: i for i, w in enumerate(self.word_set)}
        self.word_count = len(self.word_set)
        self.graph = np.zeros((self.word_count, self.word_count))
        self.weights = np.zeros(self.word_count)
        self.scores = np.ones(self.word_count)

    def build_graph(self):
        for i in range(len(self.words)):
            for j in range(i - self.window, i + self.window + 1):
                if j < 0 or j >= len(self.words) or i == j:
                    continue
                self.graph[self.word_index[self.words[i]]][self.word_index[self.words[j]]] += 1

    def calculate_weights(self):
        for i in range(self.word_count):
            self.weights[i] = np.sum(self.graph[i])

    def update_scores(self):
        new_scores = np.zeros(self.word_count)
        for i in range(self.word_count):
            for j in range(self.word_count):
                if self.graph[j][i] != 0:
                    new_scores[i] += self.alpha * self.scores[j] / self.weights[j]
            new_scores[i] += 1 - self.alpha
        if np.sum(np.abs(new_scores - self.scores)) < self.eps:
            return False
        self.scores = new_scores
        return True

    def get_top_keywords(self, k=10):
        for i in range(100):
            if not self.update_scores():
                break
        top_indices = np.argsort(-self.scores)[:k]
        return [self.word_set[i] for i in top_indices]

text = "这是一段测试文本，用于测试textRank算法的效果。"
tr = TextRank(text)
tr.build_graph()
tr.calculate_weights()
keywords = tr.get_top_keywords()
print(keywords)

这个算法可以用于提取文本中的关键词，它基于图论的思想，将文本中的词语看作图中的节点，词语之间的共现关系看作边，通过迭代计算每个节点的权重，最终得到文本中的关键词。