old_contents: from __future__ import absolute_import
  
  import logging
  
  from topik.tests import test_data_path
  
  class Termite(object):
      """A Bokeh Termite Visualization for LDA results analysis.
  
      Parameters
      ----------
      input_file: string
          A csv file from an LDA output containing columns "word", "topic" and "weight".
      title: string
          The title for your termite plot
  
      >>> termite = Termite("{}/termite.csv".format(test_data_path),
      ...                   "My lda results")
      >>> termite.plot('my_termite.html')
  
      """
      def __init__(self, input_file, title):
          self.input_file = input_file
          self.title = title
  
      def plot(self, output_file="termite.html"):
          import blaze as blz
          from odo import into
          import pandas as pd
          import bokeh.plotting as plt
          from bokeh.models.sources import ColumnDataSource
  
          t = blz.Data(self.input_file)
  
          MAX = blz.compute(t.weight.max())
          MIN = blz.compute(t.weight.min())
  
          # Create a size variable to define the size of the the circle for the plot.
          t = blz.transform(t, size=blz.sqrt((t.weight - MIN)/(MAX - MIN))*50)
  
          WORDS = t['word'].distinct()
          WORDS = into(list, WORDS)
          topics = t['topic'].distinct()
          topics = into(list, topics)
          # Convert topics to strings
          TOPICS = [str(i) for i in topics]
  
          source = into(pd.DataFrame, t)
  
          plt.output_file(output_file)
  
          data_source = ColumnDataSource(source)
  
          p = plt.figure(x_range=TOPICS, y_range=WORDS,
                         plot_width=1000, plot_height=1700,
                         title=self.title)
  
          p.circle(x="topic", y="word", size="size", fill_alpha=0.6, source=data_source)
          logging.info("generating termite plot for file %s" % self.input_file)
          plt.show(p)
  
  def plot_lda_vis(model_data):
      """Designed to work with to_py_lda_vis() in the model classes."""
      from pyLDAvis import prepare, show
      model_vis_data = prepare(**model_data)
      show(model_vis_data)
  
new_contents: from __future__ import absolute_import
  
  import logging
  
  from topik.tests import test_data_path
  
  class Termite(object):
      """A Bokeh Termite Visualization for LDA results analysis.
  
      Parameters
      ----------
      input_file : str or pandas DataFrame
          A pandas dataframe from a topik model get_termite_data() containing columns "word", "topic" and "weight".
          May also be a string, in which case the string is a filename of a csv file with the above columns.
      title : str
          The title for your termite plot
  
      Examples
      --------
      >>> termite = Termite("{}/termite.csv".format(test_data_path),
      ...                   "My lda results")
      >>> termite.plot('my_termite.html')
  
      """
      def __init__(self, input_file, title):
          self.input_file = input_file
          self.title = title
  
      def plot(self, output_file="termite.html"):
          import blaze as blz
          from odo import into
          import pandas as pd
          import bokeh.plotting as plt
          from bokeh.models.sources import ColumnDataSource
  
          t = blz.Data(self.input_file)
  
          MAX = blz.compute(t.weight.max())
          MIN = blz.compute(t.weight.min())
  
          # Create a size variable to define the size of the the circle for the plot.
          t = blz.transform(t, size=blz.sqrt((t.weight - MIN)/(MAX - MIN))*50)
  
          WORDS = t['word'].distinct()
          WORDS = into(list, WORDS)
          topics = t['topic'].distinct()
          topics = into(list, topics)
          # Convert topics to strings
          TOPICS = [str(i) for i in topics]
  
          source = into(pd.DataFrame, t)
  
          plt.output_file(output_file)
  
          data_source = ColumnDataSource(source)
  
          p = plt.figure(x_range=TOPICS, y_range=WORDS,
                         plot_width=1000, plot_height=1700,
                         title=self.title)
  
          p.circle(x="topic", y="word", size="size", fill_alpha=0.6, source=data_source)
          logging.info("generating termite plot for file %s" % self.input_file)
          plt.show(p)
  
  def plot_lda_vis(model_data):
      """Designed to work with to_py_lda_vis() in the model classes."""
      from pyLDAvis import prepare, show
      model_vis_data = prepare(**model_data)
      show(model_vis_data)
  
subject: fix docstrings in viz.py