docstr: The initial_topics argument allows one to fit a model from a
  particular set of parameters.
docstr_tok: ["The","initial_topics","argument","allows","one","to","fit","a","model","from","a","particular","set","of","parameters","."]
code: def test_initialize(self):
      """
      The initial_topics argument allows one to fit a model from a
      particular set of parameters.
      """
  
      for m in self.models:
          start_docs = turicreate.SArray(self.docs.tail(3))
          m = topic_model.create(
              start_docs,
              num_topics=20,
              method="cgs",
              alpha=0.1,
              beta=0.01,
              num_iterations=1,
              print_interval=1,
          )
          start_topics = turicreate.SFrame(m.topics.head(100))
          m2 = topic_model.create(
              self.docs,
              num_topics=20,
              initial_topics=start_topics,
              method="cgs",
              alpha=0.1,
              beta=0.01,
              num_iterations=0,
              print_interval=1,
          )
  
          # Check that the vocabulary of the new model is the same as
          # the one we used to initialize the model.
          self.assertTrue(
              (
                  start_topics["vocabulary"] == m2.topics["vocabulary"]
              ).all()
          )
  
          # Check that the previously most probable word is still the most
          # probable after 0 iterations, i.e. just initialization.
          old_prob = start_topics["topic_probabilities"].vector_slice(0)
          new_prob = m2.topics["topic_probabilities"].vector_slice(0)
          self.assertTrue(
              np.argmax(list(old_prob)) == np.argmax(list(new_prob))
          )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import os
  import tempfile
  import shutil
  import unittest
  import turicreate
  from turicreate.toolkits._main import ToolkitError
  from turicreate.toolkits.topic_model import topic_model
  from turicreate.toolkits.text_analytics import parse_sparse
  from turicreate.toolkits.text_analytics import parse_docword
  from turicreate.toolkits.topic_model import perplexity
  from .None import util
  import time
  import random
  import numpy
  import itertools
label_desc: Use image node_id 11 for calling the BasicTest obj's underlying member method code with example usage: obj.test_initialize() without return types