高效将gensim TransformedCorpus数据转换为数组

问题描述

与下面的逐行方法相比，从gensim.interfaces.TransformedCorpus对象获取主题概率数据到numpy数组(或熊猫数据框)中，是否有更直接或有效的方法?

Is there a more direct or efficient method for getting the topic probabilities data from a gensim.interfaces.TransformedCorpus object into a numpy array (or alternatively, pandas dataframe) than the by-row method below?

from gensim import models
import numpy as np

num_topics = 5
model = models.LdaMulticore(corpus, num_topics=num_topics, minimum_probability=0.0)

all_topics = model.get_document_topics(corpus)
num_docs = len(all_topics)

lda_scores = np.empty([num_docs, num_topics])

for i in range(0, num_docs):
    lda_scores[i] = np.array(all_topics[i]).transpose()[1]

推荐答案

可能为时已晚，但是gensim具有用于与numpy/scipy数组进行相互转换的辅助函数.

Might be too late, but gensim has a helper function for converting to and from numpy/scipy arrays.

您要寻找的是:

gensim.matutils.corpus2csc

然后，您可以根据需要将输出转换为numpy数组或pandas df.

You can then can convert the output to a numpy array or pandas df as you wish.

import gensim
import numpy as np

all_topics_csr = gensim.matutils.corpus2csc(all_topics)
all_topics_numpy = all_topics_csr.T.toarray()

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