class_docstr: Online Non-Negative Matrix Factorization.
  
  `Renbo Zhao et al :"Online Nonnegative Matrix Factorization with Outliers" <https://arxiv.org/abs/1604.02634>`_
class_docstr_tok: ["Online","Non-Negative","Matrix","Factorization",".","`","Renbo","Zhao","et","al",":","''","Online","Nonnegative","Matrix","Factorization","with","Outliers","''","<","https",":","\/\/arxiv.org\/abs\/1604.02634",">","`","_"]
docstr: Get the term-topic matrix learned during inference.
  
  Parameters
  ----------
  normalize: bool or None, optional
      Whether to normalize the result. Allows for estimation of perplexity, coherence, e.t.c.
  
  Returns
  -------
  numpy.ndarray
      The probability for each word in each topic, shape (`num_topics`, `vocabulary_size`).
docstr_tok: ["Get","the","term-topic","matrix","learned","during","inference",".","Parameters","--","--","--","--","--","normalize",":","bool","or","None",",","optional","Whether","to","normalize","the","result",".","Allows","for","estimation","of","perplexity",",","coherence",",","e.t.c",".","Returns","--","--","--","-","numpy.ndarray","The","probability","for","each","word","in","each","topic",",","shape","(","`","num_topics","`",",","`","vocabulary_size","`",")","."]
code: def get_topics(self, normalize=None):
      """Get the term-topic matrix learned during inference.
  
      Parameters
      ----------
      normalize: bool or None, optional
          Whether to normalize the result. Allows for estimation of perplexity, coherence, e.t.c.
  
      Returns
      -------
      numpy.ndarray
          The probability for each word in each topic, shape (`num_topics`, `vocabulary_size`).
  
      """
      dense_topics = self._W.T
      if normalize is None:
          normalize = self.normalize
      if normalize:
          return dense_topics / dense_topics.sum(axis=1).reshape(-1, 1)
  
      return dense_topics
  
imports: import collections.abc
  import logging
  import numpy
  import scipy.sparse
  from scipy.stats import halfnorm
  from gensim import interfaces
  from gensim import matutils
  from gensim import utils
  from gensim.interfaces import TransformedCorpus
  from gensim.models import basemodel, CoherenceModel
  from gensim.models.nmf_pgd import solve_h
label_desc: Use image node_id 2 for calling the Nmf obj's underlying member method code with example usage: obj.get_topics(normalize) and returns: dense_topics, unknown