class_docstr: The constructor estimates the author-topic model parameters based on a training corpus.
class_docstr_tok: ["The","constructor","estimates","the","author-topic","model","parameters","based","on","a","training","corpus","."]
docstr: Get topic distribution for input `author_names`.
  
  Parameters
  ----------
  author_names : {str, list of str}
      Name(s) of the author for which the topic distribution needs to be estimated.
  eps : float, optional
      The minimum probability value for showing the topics of a given author, topics with probability < `eps`
      will be ignored.
  
  Returns
  -------
  list of (int, float) **or** list of list of (int, float)
      Topic distribution for the author(s), type depends on type of `author_names`.
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code: def __getitem__(self, author_names, eps=None):
      """Get topic distribution for input `author_names`.
  
      Parameters
      ----------
      author_names : {str, list of str}
          Name(s) of the author for which the topic distribution needs to be estimated.
      eps : float, optional
          The minimum probability value for showing the topics of a given author, topics with probability < `eps`
          will be ignored.
  
      Returns
      -------
      list of (int, float) **or** list of list of (int, float)
          Topic distribution for the author(s), type depends on type of `author_names`.
  
      """
      if isinstance(author_names, list):
          items = []
          for a in author_names:
              items.append(
                  self.get_author_topics(a, minimum_probability=eps)
              )
      else:
          items = self.get_author_topics(
              author_names, minimum_probability=eps
          )
  
      return items
  
imports: import logging
  from itertools import chain
  from copy import deepcopy
  from shutil import copyfile
  from os.path import isfile
  from os import remove
  import numpy
  from scipy.special import gammaln
  from gensim import utils
  from gensim.models import LdaModel
  from gensim.models.ldamodel import LdaState
  from gensim.matutils import dirichlet_expectation, mean_absolute_difference
  from gensim.corpora import MmCorpus
label_desc: Use image node_id 14 for calling the AuthorTopicModel obj's underlying member method code with example usage: obj.__getitem__(author_names, eps) and returns: items