new_contents: # ----------------------------------------------------------------------------
  # Copyright (c) 2016--,  Calour development team.
  #
  # Distributed under the terms of the Modified BSD License.
  #
  # The full license is in the file COPYING.txt, distributed with this software.
  # ----------------------------------------------------------------------------
  
  import unittest
  import pandas as pd
  from os.path import join
  import pandas.util.testing as pdt
  
  import calour as ca
  from calour.testing import Tests, assert_experiment_equal
  
  
  class TestSorting(Tests):
      def setUp(self):
          super().setUp()
          # load the simple experiment as sparse
          self.simple = ca.read(self.simple_table, self.simple_map)
          # load the complex experiment as sparse
          self.complex = ca.read(self.complex_table, self.complex_map)
  
      def test_sort_taxonomy(self):
          newexp = self.simple.sort_taxonomy()
          expected_taxonomy = pd.Series.from_csv(join(self.test_data_dir, 'test1.sorted.taxonomy.csv'))
          pdt.assert_series_equal(newexp.feature_metadata['taxonomy'], expected_taxonomy, check_names=False)
  
      def test_cluster_features(self):
          # no minimal filtering
          # simple experiment
          newexp = self.simple.cluster_features()
          expected_experiment = ca.read(join(self.test_data_dir, 'test1.clustered.features.biom'), join(self.test_data_dir, 'test1.map.txt'))
          assert_experiment_equal(newexp, expected_experiment, check_history=False, almost_equal=True)
          # complex experiment (timeseries)
          newexp = self.complex.cluster_features()
          expected_experiment = ca.read(join(self.test_data_dir, 'timeseries.clustered.features.biom'), join(self.test_data_dir, 'timeseries.map.txt'))
          assert_experiment_equal(newexp, expected_experiment, check_history=False, almost_equal=True)
  
  
  if __name__ == "__main__":
      unittest.main()
  
subject: add unit test for clustering simple experiment