我有一个训练有素的自定义LDA模型（希伯来语），并且我想使用pyLDAvis对其进行可视化。
我指的是文档和以下资源：
https://pyldavis.readthedocs.io/en/latest/modules/API.html#pyLDAvis.prepare
https://nbviewer.jupyter.org/github/bmabey/pyLDAvis/blob/master/notebooks/pyLDAvis_overview.ipynb
但是我仍然不明白prepare方法的输入是什么样子。
topic_term_dists:array-like, shape (n_topics, n_terms)
Matrix of topic-term probabilities. Where n_terms is len(vocab).
doc_topic_dists :array-like, shape (n_docs, n_topics)
Matrix of document-topic probabilities.
doc_lengths :array-like, shape n_docs
The length of each document, i.e. the number of words in each document. The order of the numbers should be consistent with the ordering of the docs in doc_topic_dists.
vocab :array-like, shape n_terms
List of all the words in the corpus used to train the model.
term_frequency :array-like, shape n_terms
The count of each particular term over the entire corpus. The ordering of these counts should correspond with vocab and topic_term_dists.
有人为这些输入提供示例吗？谢谢