content: # -*- coding: utf-8 -*-
  """
  Unit tests for the pandas bridge module.
  
  :copyright: Copyright 2014-2016 by the Elephant team, see AUTHORS.txt.
  :license: Modified BSD, see LICENSE.txt for details.
  """
  
  from __future__ import division, print_function
  
  import unittest
  from itertools import chain
  
  from neo.test.generate_datasets import fake_neo
  import numpy as np
  from numpy.testing import assert_array_equal
  import quantities as pq
  
  try:
      import pandas as pd
      from pandas.util.testing import assert_frame_equal, assert_index_equal
  except ImportError:
      HAVE_PANDAS = False
  else:
      import elephant.pandas_bridge as ep
      HAVE_PANDAS = True
  
  if HAVE_PANDAS:
      # Currying, otherwise the unittest will break with pandas>=0.16.0
      # parameter check_names is introduced in a newer versions than 0.14.0
      # this test is written for pandas 0.14.0
      def assert_index_equal(left, right):
          try:
              # pandas>=0.16.0
              return pd.util.testing.assert_index_equal(left, right,
                                                        check_names=False)
          except TypeError:
              # pandas older version
              return pd.util.testing.assert_index_equal(left, right)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class MultiindexFromDictTestCase(unittest.TestCase):
      def test__multiindex_from_dict(self):
          inds = {'test1': 6.5,
                  'test2': 5,
                  'test3': 'test'}
          targ = pd.MultiIndex(levels=[[6.5], [5], ['test']],
                               labels=[[0], [0], [0]],
                               names=['test1', 'test2', 'test3'])
          res0 = ep._multiindex_from_dict(inds)
          self.assertEqual(targ.levels, res0.levels)
          self.assertEqual(targ.names, res0.names)
          self.assertEqual(targ.labels, res0.labels)
  
  
  def _convert_levels(levels):
      """Convert a list of levels to the format pandas returns for a MultiIndex.
  
      Parameters
      ----------
  
      levels : list
               The list of levels to convert.
  
      Returns
      -------
  
      list
          The the level in `list` converted to values like what pandas will give.
  
      """
      levels = list(levels)
      for i, level in enumerate(levels):
          if hasattr(level, 'lower'):
              try:
                  level = unicode(level)
              except NameError:
                  pass
          elif hasattr(level, 'date'):
              levels[i] = pd.DatetimeIndex(data=[level])
              continue
          elif level is None:
              levels[i] = pd.Index([])
              continue
  
          # pd.Index around pd.Index to convert to Index structure if MultiIndex
          levels[i] = pd.Index(pd.Index([level]))
      return levels
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class ConvertValueSafeTestCase(unittest.TestCase):
      def test__convert_value_safe__float(self):
          targ = 5.5
          value = targ
  
          res = ep._convert_value_safe(value)
  
          self.assertIs(res, targ)
  
      def test__convert_value_safe__str(self):
          targ = 'test'
          value = targ
  
          res = ep._convert_value_safe(value)
  
          self.assertIs(res, targ)
  
      def test__convert_value_safe__bytes(self):
          targ = 'test'
          value = b'test'
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
  
      def test__convert_value_safe__numpy_int_scalar(self):
          targ = 5
          value = np.array(5)
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
          self.assertFalse(hasattr(res, 'dtype'))
  
      def test__convert_value_safe__numpy_float_scalar(self):
          targ = 5.
          value = np.array(5.)
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
          self.assertFalse(hasattr(res, 'dtype'))
  
      def test__convert_value_safe__numpy_unicode_scalar(self):
          targ = u'test'
          value = np.array('test', dtype='U')
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
          self.assertFalse(hasattr(res, 'dtype'))
  
      def test__convert_value_safe__numpy_str_scalar(self):
          targ = u'test'
          value = np.array('test', dtype='S')
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
          self.assertFalse(hasattr(res, 'dtype'))
  
      def test__convert_value_safe__quantity_scalar(self):
          targ = (10., 'ms')
          value = 10. * pq.ms
  
          res = ep._convert_value_safe(value)
  
          self.assertEqual(res, targ)
          self.assertFalse(hasattr(res[0], 'dtype'))
          self.assertFalse(hasattr(res[0], 'units'))
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class SpiketrainToDataframeTestCase(unittest.TestCase):
      def test__spiketrain_to_dataframe__parents_empty(self):
          obj = fake_neo('SpikeTrain', seed=0)
  
          res0 = ep.spiketrain_to_dataframe(obj)
          res1 = ep.spiketrain_to_dataframe(obj, child_first=True)
          res2 = ep.spiketrain_to_dataframe(obj, child_first=False)
          res3 = ep.spiketrain_to_dataframe(obj, parents=True)
          res4 = ep.spiketrain_to_dataframe(obj, parents=True,
                                            child_first=True)
          res5 = ep.spiketrain_to_dataframe(obj, parents=True,
                                            child_first=False)
          res6 = ep.spiketrain_to_dataframe(obj, parents=False)
          res7 = ep.spiketrain_to_dataframe(obj, parents=False, child_first=True)
          res8 = ep.spiketrain_to_dataframe(obj, parents=False,
                                            child_first=False)
  
          targvalues = pq.Quantity(obj.magnitude, units=obj.units)
          targvalues = targvalues.rescale('s').magnitude[np.newaxis].T
          targindex = np.arange(len(targvalues))
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True, child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
          self.assertEqual(1, len(res4.columns))
          self.assertEqual(1, len(res5.columns))
          self.assertEqual(1, len(res6.columns))
          self.assertEqual(1, len(res7.columns))
          self.assertEqual(1, len(res8.columns))
  
          self.assertEqual(len(obj), len(res0.index))
          self.assertEqual(len(obj), len(res1.index))
          self.assertEqual(len(obj), len(res2.index))
          self.assertEqual(len(obj), len(res3.index))
          self.assertEqual(len(obj), len(res4.index))
          self.assertEqual(len(obj), len(res5.index))
          self.assertEqual(len(obj), len(res6.index))
          self.assertEqual(len(obj), len(res7.index))
          self.assertEqual(len(obj), len(res8.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
          assert_array_equal(targvalues, res4.values)
          assert_array_equal(targvalues, res5.values)
          assert_array_equal(targvalues, res6.values)
          assert_array_equal(targvalues, res7.values)
          assert_array_equal(targvalues, res8.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
          assert_array_equal(targindex, res3.index)
          assert_array_equal(targindex, res4.index)
          assert_array_equal(targindex, res5.index)
          assert_array_equal(targindex, res6.index)
          assert_array_equal(targindex, res7.index)
          assert_array_equal(targindex, res8.index)
  
          self.assertEqual(['spike_number'], res0.index.names)
          self.assertEqual(['spike_number'], res1.index.names)
          self.assertEqual(['spike_number'], res2.index.names)
          self.assertEqual(['spike_number'], res3.index.names)
          self.assertEqual(['spike_number'], res4.index.names)
          self.assertEqual(['spike_number'], res5.index.names)
          self.assertEqual(['spike_number'], res6.index.names)
          self.assertEqual(['spike_number'], res7.index.names)
          self.assertEqual(['spike_number'], res8.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
          self.assertEqual(keys, res4.columns.names)
          self.assertEqual(keys, res5.columns.names)
          self.assertEqual(keys, res6.columns.names)
          self.assertEqual(keys, res7.columns.names)
          self.assertEqual(keys, res8.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res4.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res5.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res6.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res7.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res8.columns.levels):
              assert_index_equal(value, level)
  
      def test__spiketrain_to_dataframe__noparents(self):
          blk = fake_neo('Block', seed=0)
          obj = blk.list_children_by_class('SpikeTrain')[0]
  
          res0 = ep.spiketrain_to_dataframe(obj, parents=False)
          res1 = ep.spiketrain_to_dataframe(obj, parents=False,
                                            child_first=True)
          res2 = ep.spiketrain_to_dataframe(obj, parents=False,
                                            child_first=False)
  
          targvalues = pq.Quantity(obj.magnitude, units=obj.units)
          targvalues = targvalues.rescale('s').magnitude[np.newaxis].T
          targindex = np.arange(len(targvalues))
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=False,
                                             child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
  
          self.assertEqual(len(obj), len(res0.index))
          self.assertEqual(len(obj), len(res1.index))
          self.assertEqual(len(obj), len(res2.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
  
          self.assertEqual(['spike_number'], res0.index.names)
          self.assertEqual(['spike_number'], res1.index.names)
          self.assertEqual(['spike_number'], res2.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
  
      def test__spiketrain_to_dataframe__parents_childfirst(self):
          blk = fake_neo('Block', seed=0)
          obj = blk.list_children_by_class('SpikeTrain')[0]
          res0 = ep.spiketrain_to_dataframe(obj)
          res1 = ep.spiketrain_to_dataframe(obj, child_first=True)
          res2 = ep.spiketrain_to_dataframe(obj, parents=True)
          res3 = ep.spiketrain_to_dataframe(obj, parents=True, child_first=True)
  
          targvalues = pq.Quantity(obj.magnitude, units=obj.units)
          targvalues = targvalues.rescale('s').magnitude[np.newaxis].T
          targindex = np.arange(len(targvalues))
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True, child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
  
          self.assertEqual(len(obj), len(res0.index))
          self.assertEqual(len(obj), len(res1.index))
          self.assertEqual(len(obj), len(res2.index))
          self.assertEqual(len(obj), len(res3.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
          assert_array_equal(targindex, res3.index)
  
          self.assertEqual(['spike_number'], res0.index.names)
          self.assertEqual(['spike_number'], res1.index.names)
          self.assertEqual(['spike_number'], res2.index.names)
          self.assertEqual(['spike_number'], res3.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
  
      def test__spiketrain_to_dataframe__parents_parentfirst(self):
          blk = fake_neo('Block', seed=0)
          obj = blk.list_children_by_class('SpikeTrain')[0]
          res0 = ep.spiketrain_to_dataframe(obj, child_first=False)
          res1 = ep.spiketrain_to_dataframe(obj, parents=True, child_first=False)
  
          targvalues = pq.Quantity(obj.magnitude, units=obj.units)
          targvalues = targvalues.rescale('s').magnitude[np.newaxis].T
          targindex = np.arange(len(targvalues))
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True,
                                             child_first=False)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
  
          self.assertEqual(len(obj), len(res0.index))
          self.assertEqual(len(obj), len(res1.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
  
          self.assertEqual(['spike_number'], res0.index.names)
          self.assertEqual(['spike_number'], res1.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class EventToDataframeTestCase(unittest.TestCase):
      def test__event_to_dataframe__parents_empty(self):
          obj = fake_neo('Event', seed=42)
  
          res0 = ep.event_to_dataframe(obj)
          res1 = ep.event_to_dataframe(obj, child_first=True)
          res2 = ep.event_to_dataframe(obj, child_first=False)
          res3 = ep.event_to_dataframe(obj, parents=True)
          res4 = ep.event_to_dataframe(obj, parents=True, child_first=True)
          res5 = ep.event_to_dataframe(obj, parents=True, child_first=False)
          res6 = ep.event_to_dataframe(obj, parents=False)
          res7 = ep.event_to_dataframe(obj, parents=False, child_first=True)
          res8 = ep.event_to_dataframe(obj, parents=False, child_first=False)
  
          targvalues = obj.labels[:len(obj.times)][np.newaxis].T.astype('U')
          targindex = obj.times[:len(obj.labels)].rescale('s').magnitude
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True, child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
          self.assertEqual(1, len(res4.columns))
          self.assertEqual(1, len(res5.columns))
          self.assertEqual(1, len(res6.columns))
          self.assertEqual(1, len(res7.columns))
          self.assertEqual(1, len(res8.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res2.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res3.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res4.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res5.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res6.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res7.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res8.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
          assert_array_equal(targvalues, res4.values)
          assert_array_equal(targvalues, res5.values)
          assert_array_equal(targvalues, res6.values)
          assert_array_equal(targvalues, res7.values)
          assert_array_equal(targvalues, res8.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
          assert_array_equal(targindex, res3.index)
          assert_array_equal(targindex, res4.index)
          assert_array_equal(targindex, res5.index)
          assert_array_equal(targindex, res6.index)
          assert_array_equal(targindex, res7.index)
          assert_array_equal(targindex, res8.index)
  
          self.assertEqual(['times'], res0.index.names)
          self.assertEqual(['times'], res1.index.names)
          self.assertEqual(['times'], res2.index.names)
          self.assertEqual(['times'], res3.index.names)
          self.assertEqual(['times'], res4.index.names)
          self.assertEqual(['times'], res5.index.names)
          self.assertEqual(['times'], res6.index.names)
          self.assertEqual(['times'], res7.index.names)
          self.assertEqual(['times'], res8.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
          self.assertEqual(keys, res4.columns.names)
          self.assertEqual(keys, res5.columns.names)
          self.assertEqual(keys, res6.columns.names)
          self.assertEqual(keys, res7.columns.names)
          self.assertEqual(keys, res8.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res4.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res5.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res6.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res7.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res8.columns.levels):
              assert_index_equal(value, level)
  
      def test__event_to_dataframe__noparents(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Event')[0]
  
          res0 = ep.event_to_dataframe(obj, parents=False)
          res1 = ep.event_to_dataframe(obj, parents=False, child_first=False)
          res2 = ep.event_to_dataframe(obj, parents=False, child_first=True)
  
          targvalues = obj.labels[:len(obj.times)][np.newaxis].T.astype('U')
          targindex = obj.times[:len(obj.labels)].rescale('s').magnitude
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=False,
                                             child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res2.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
  
          self.assertEqual(['times'], res0.index.names)
          self.assertEqual(['times'], res1.index.names)
          self.assertEqual(['times'], res2.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
  
      def test__event_to_dataframe__parents_childfirst(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Event')[0]
  
          res0 = ep.event_to_dataframe(obj)
          res1 = ep.event_to_dataframe(obj, child_first=True)
          res2 = ep.event_to_dataframe(obj, parents=True)
          res3 = ep.event_to_dataframe(obj, parents=True, child_first=True)
  
          targvalues = obj.labels[:len(obj.times)][np.newaxis].T.astype('U')
          targindex = obj.times[:len(obj.labels)].rescale('s').magnitude
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True, child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res2.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res3.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
          assert_array_equal(targindex, res2.index)
          assert_array_equal(targindex, res3.index)
  
          self.assertEqual(['times'], res0.index.names)
          self.assertEqual(['times'], res1.index.names)
          self.assertEqual(['times'], res2.index.names)
          self.assertEqual(['times'], res3.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
  
      def test__event_to_dataframe__parents_parentfirst(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Event')[0]
          res0 = ep.event_to_dataframe(obj, child_first=False)
          res1 = ep.event_to_dataframe(obj, parents=True, child_first=False)
  
          targvalues = obj.labels[:len(obj.times)][np.newaxis].T.astype('U')
          targindex = obj.times[:len(obj.labels)].rescale('s').magnitude
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True,
                                             child_first=False)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.labels)),
                           len(res1.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
  
          assert_array_equal(targindex, res0.index)
          assert_array_equal(targindex, res1.index)
  
          self.assertEqual(['times'], res0.index.names)
          self.assertEqual(['times'], res1.index.names)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class EpochToDataframeTestCase(unittest.TestCase):
      def test__epoch_to_dataframe__parents_empty(self):
          obj = fake_neo('Epoch', seed=42)
  
          res0 = ep.epoch_to_dataframe(obj)
          res1 = ep.epoch_to_dataframe(obj, child_first=True)
          res2 = ep.epoch_to_dataframe(obj, child_first=False)
          res3 = ep.epoch_to_dataframe(obj, parents=True)
          res4 = ep.epoch_to_dataframe(obj, parents=True, child_first=True)
          res5 = ep.epoch_to_dataframe(obj, parents=True, child_first=False)
          res6 = ep.epoch_to_dataframe(obj, parents=False)
          res7 = ep.epoch_to_dataframe(obj, parents=False, child_first=True)
          res8 = ep.epoch_to_dataframe(obj, parents=False, child_first=False)
  
          minlen = min([len(obj.times), len(obj.durations), len(obj.labels)])
          targvalues = obj.labels[:minlen][np.newaxis].T.astype('U')
          targindex = np.vstack([obj.durations[:minlen].rescale('s').magnitude,
                                 obj.times[:minlen].rescale('s').magnitude])
          targvalues = targvalues[targindex.argsort()[0], :]
          targindex.sort()
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True,
                                             child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
          self.assertEqual(1, len(res4.columns))
          self.assertEqual(1, len(res5.columns))
          self.assertEqual(1, len(res6.columns))
          self.assertEqual(1, len(res7.columns))
          self.assertEqual(1, len(res8.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res2.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res3.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res4.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res5.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res6.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res7.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res8.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
          assert_array_equal(targvalues, res4.values)
          assert_array_equal(targvalues, res5.values)
          assert_array_equal(targvalues, res6.values)
          assert_array_equal(targvalues, res7.values)
          assert_array_equal(targvalues, res8.values)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
          self.assertEqual(keys, res4.columns.names)
          self.assertEqual(keys, res5.columns.names)
          self.assertEqual(keys, res6.columns.names)
          self.assertEqual(keys, res7.columns.names)
          self.assertEqual(keys, res8.columns.names)
  
          self.assertEqual([u'durations', u'times'], res0.index.names)
          self.assertEqual([u'durations', u'times'], res1.index.names)
          self.assertEqual([u'durations', u'times'], res2.index.names)
          self.assertEqual([u'durations', u'times'], res3.index.names)
          self.assertEqual([u'durations', u'times'], res4.index.names)
          self.assertEqual([u'durations', u'times'], res5.index.names)
          self.assertEqual([u'durations', u'times'], res6.index.names)
          self.assertEqual([u'durations', u'times'], res7.index.names)
          self.assertEqual([u'durations', u'times'], res8.index.names)
  
          self.assertEqual(2, len(res0.index.levels))
          self.assertEqual(2, len(res1.index.levels))
          self.assertEqual(2, len(res2.index.levels))
          self.assertEqual(2, len(res3.index.levels))
          self.assertEqual(2, len(res4.index.levels))
          self.assertEqual(2, len(res5.index.levels))
          self.assertEqual(2, len(res6.index.levels))
          self.assertEqual(2, len(res7.index.levels))
          self.assertEqual(2, len(res8.index.levels))
  
          assert_array_equal(targindex, res0.index.levels)
          assert_array_equal(targindex, res1.index.levels)
          assert_array_equal(targindex, res2.index.levels)
          assert_array_equal(targindex, res3.index.levels)
          assert_array_equal(targindex, res4.index.levels)
          assert_array_equal(targindex, res5.index.levels)
          assert_array_equal(targindex, res6.index.levels)
          assert_array_equal(targindex, res7.index.levels)
          assert_array_equal(targindex, res8.index.levels)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res4.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res5.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res6.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res7.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res8.columns.levels):
              assert_index_equal(value, level)
  
      def test__epoch_to_dataframe__noparents(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Epoch')[0]
  
          res0 = ep.epoch_to_dataframe(obj, parents=False)
          res1 = ep.epoch_to_dataframe(obj, parents=False, child_first=True)
          res2 = ep.epoch_to_dataframe(obj, parents=False, child_first=False)
  
          minlen = min([len(obj.times), len(obj.durations), len(obj.labels)])
          targvalues = obj.labels[:minlen][np.newaxis].T.astype('U')
          targindex = np.vstack([obj.durations[:minlen].rescale('s').magnitude,
                                 obj.times[:minlen].rescale('s').magnitude])
          targvalues = targvalues[targindex.argsort()[0], :]
          targindex.sort()
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=False,
                                             child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res2.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
  
          self.assertEqual([u'durations', u'times'], res0.index.names)
          self.assertEqual([u'durations', u'times'], res1.index.names)
          self.assertEqual([u'durations', u'times'], res2.index.names)
  
          self.assertEqual(2, len(res0.index.levels))
          self.assertEqual(2, len(res1.index.levels))
          self.assertEqual(2, len(res2.index.levels))
  
          assert_array_equal(targindex, res0.index.levels)
          assert_array_equal(targindex, res1.index.levels)
          assert_array_equal(targindex, res2.index.levels)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
  
      def test__epoch_to_dataframe__parents_childfirst(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Epoch')[0]
  
          res0 = ep.epoch_to_dataframe(obj)
          res1 = ep.epoch_to_dataframe(obj, child_first=True)
          res2 = ep.epoch_to_dataframe(obj, parents=True)
          res3 = ep.epoch_to_dataframe(obj, parents=True, child_first=True)
  
          minlen = min([len(obj.times), len(obj.durations), len(obj.labels)])
          targvalues = obj.labels[:minlen][np.newaxis].T.astype('U')
          targindex = np.vstack([obj.durations[:minlen].rescale('s').magnitude,
                                 obj.times[:minlen].rescale('s').magnitude])
          targvalues = targvalues[targindex.argsort()[0], :]
          targindex.sort()
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True, child_first=True)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
          self.assertEqual(1, len(res2.columns))
          self.assertEqual(1, len(res3.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res1.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res2.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res3.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
          assert_array_equal(targvalues, res2.values)
          assert_array_equal(targvalues, res3.values)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
          self.assertEqual(keys, res2.columns.names)
          self.assertEqual(keys, res3.columns.names)
  
          self.assertEqual([u'durations', u'times'], res0.index.names)
          self.assertEqual([u'durations', u'times'], res1.index.names)
          self.assertEqual([u'durations', u'times'], res2.index.names)
          self.assertEqual([u'durations', u'times'], res3.index.names)
  
          self.assertEqual(2, len(res0.index.levels))
          self.assertEqual(2, len(res1.index.levels))
          self.assertEqual(2, len(res2.index.levels))
          self.assertEqual(2, len(res3.index.levels))
  
          assert_array_equal(targindex, res0.index.levels)
          assert_array_equal(targindex, res1.index.levels)
          assert_array_equal(targindex, res2.index.levels)
          assert_array_equal(targindex, res3.index.levels)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res2.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res3.columns.levels):
              assert_index_equal(value, level)
  
      def test__epoch_to_dataframe__parents_parentfirst(self):
          blk = fake_neo('Block', seed=42)
          obj = blk.list_children_by_class('Epoch')[0]
  
          res0 = ep.epoch_to_dataframe(obj, child_first=False)
          res1 = ep.epoch_to_dataframe(obj, parents=True, child_first=False)
  
          minlen = min([len(obj.times), len(obj.durations), len(obj.labels)])
          targvalues = obj.labels[:minlen][np.newaxis].T.astype('U')
          targindex = np.vstack([obj.durations[:minlen].rescale('s').magnitude,
                                 obj.times[:minlen].rescale('s').magnitude])
          targvalues = targvalues[targindex.argsort()[0], :]
          targindex.sort()
  
          attrs = ep._extract_neo_attrs_safe(obj, parents=True,
                                             child_first=False)
          keys, values = zip(*sorted(attrs.items()))
          values = _convert_levels(values)
  
          self.assertEqual(1, len(res0.columns))
          self.assertEqual(1, len(res1.columns))
  
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res0.index))
          self.assertEqual(min(len(obj.times), len(obj.durations),
                               len(obj.labels)),
                           len(res1.index))
  
          assert_array_equal(targvalues, res0.values)
          assert_array_equal(targvalues, res1.values)
  
          self.assertEqual(keys, res0.columns.names)
          self.assertEqual(keys, res1.columns.names)
  
          self.assertEqual([u'durations', u'times'], res0.index.names)
          self.assertEqual([u'durations', u'times'], res1.index.names)
  
          self.assertEqual(2, len(res0.index.levels))
          self.assertEqual(2, len(res1.index.levels))
  
          assert_array_equal(targindex, res0.index.levels)
          assert_array_equal(targindex, res1.index.levels)
  
          for value, level in zip(values, res0.columns.levels):
              assert_index_equal(value, level)
          for value, level in zip(values, res1.columns.levels):
              assert_index_equal(value, level)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class MultiSpiketrainsToDataframeTestCase(unittest.TestCase):
      def setUp(self):
          if hasattr(self, 'assertItemsEqual'):
              self.assertCountEqual = self.assertItemsEqual
  
      def test__multi_spiketrains_to_dataframe__single(self):
          obj = fake_neo('SpikeTrain', seed=0, n=5)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=False)
          res2 = ep.multi_spiketrains_to_dataframe(obj, parents=True)
          res3 = ep.multi_spiketrains_to_dataframe(obj, child_first=True)
          res4 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=True)
          res5 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=True)
          res6 = ep.multi_spiketrains_to_dataframe(obj, child_first=False)
          res7 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=False)
          res8 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=False)
  
          targ = ep.spiketrain_to_dataframe(obj)
  
          keys = ep._extract_neo_attrs_safe(obj, parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = 1
          targlen = len(obj)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
          self.assertEqual(targwidth, len(res4.columns))
          self.assertEqual(targwidth, len(res5.columns))
          self.assertEqual(targwidth, len(res6.columns))
          self.assertEqual(targwidth, len(res7.columns))
          self.assertEqual(targwidth, len(res8.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
          self.assertEqual(targlen, len(res4.index))
          self.assertEqual(targlen, len(res5.index))
          self.assertEqual(targlen, len(res6.index))
          self.assertEqual(targlen, len(res7.index))
          self.assertEqual(targlen, len(res8.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
          self.assertCountEqual(keys, res4.columns.names)
          self.assertCountEqual(keys, res5.columns.names)
          self.assertCountEqual(keys, res6.columns.names)
          self.assertCountEqual(keys, res7.columns.names)
          self.assertCountEqual(keys, res8.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
          assert_array_equal(targ.values, res3.values)
          assert_array_equal(targ.values, res4.values)
          assert_array_equal(targ.values, res5.values)
          assert_array_equal(targ.values, res6.values)
          assert_array_equal(targ.values, res7.values)
          assert_array_equal(targ.values, res8.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
          assert_frame_equal(targ, res4)
          assert_frame_equal(targ, res5)
          assert_frame_equal(targ, res6)
          assert_frame_equal(targ, res7)
          assert_frame_equal(targ, res8)
  
      def test__multi_spiketrains_to_dataframe__unit_default(self):
          obj = fake_neo('Unit', seed=0, n=5)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
  
          objs = obj.spiketrains
  
          targ = [ep.spiketrain_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(targ.values, res0.values)
  
          assert_frame_equal(targ, res0)
  
      def test__multi_spiketrains_to_dataframe__segment_default(self):
          obj = fake_neo('Segment', seed=0, n=5)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
  
          objs = obj.spiketrains
  
          targ = [ep.spiketrain_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(targ.values, res0.values)
  
          assert_frame_equal(targ, res0)
  
      def test__multi_spiketrains_to_dataframe__block_noparents(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj, parents=False)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=True)
          res2 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=False)
  
          objs = obj.list_children_by_class('SpikeTrain')
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_spiketrains_to_dataframe__block_parents_childfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=True)
          res2 = ep.multi_spiketrains_to_dataframe(obj, child_first=True)
          res3 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=True)
  
          objs = obj.list_children_by_class('SpikeTrain')
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
          assert_array_equal(targ.values, res3.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_spiketrains_to_dataframe__block_parents_parentfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_spiketrains_to_dataframe(obj, child_first=False)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=False)
  
          objs = obj.list_children_by_class('SpikeTrain')
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_spiketrains_to_dataframe__list_noparents(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_spiketrains_to_dataframe(obj, parents=False)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=True)
          res2 = ep.multi_spiketrains_to_dataframe(obj, parents=False,
                                                   child_first=False)
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_spiketrains_to_dataframe__list_parents_childfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=True)
          res2 = ep.multi_spiketrains_to_dataframe(obj, child_first=True)
          res3 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=True)
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
          assert_array_equal(targ.values, res3.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_spiketrains_to_dataframe__list_parents_parentfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_spiketrains_to_dataframe(obj, child_first=False)
          res1 = ep.multi_spiketrains_to_dataframe(obj, parents=True,
                                                   child_first=False)
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.spiketrain_to_dataframe(iobj,
                                             parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_spiketrains_to_dataframe__tuple_default(self):
          obj = tuple(fake_neo('Block', seed=i, n=3) for i in range(3))
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.spiketrain_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(targ.values, res0.values)
  
          assert_frame_equal(targ, res0)
  
      def test__multi_spiketrains_to_dataframe__iter_default(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_spiketrains_to_dataframe(iter(obj))
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in obj)
          objs = list(chain.from_iterable(objs))
          targ = [ep.spiketrain_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(targ.values, res0.values)
  
          assert_frame_equal(targ, res0)
  
      def test__multi_spiketrains_to_dataframe__dict_default(self):
          obj = dict((i, fake_neo('Block', seed=i, n=3)) for i in range(3))
  
          res0 = ep.multi_spiketrains_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('SpikeTrain') for iobj in
                  obj.values())
          objs = list(chain.from_iterable(objs))
          targ = [ep.spiketrain_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = max(len(iobj) for iobj in objs)
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(targ.values, res0.values)
  
          assert_frame_equal(targ, res0)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class MultiEventsToDataframeTestCase(unittest.TestCase):
      def setUp(self):
          if hasattr(self, 'assertItemsEqual'):
              self.assertCountEqual = self.assertItemsEqual
  
      def test__multi_events_to_dataframe__single(self):
          obj = fake_neo('Event', seed=0, n=5)
  
          res0 = ep.multi_events_to_dataframe(obj)
          res1 = ep.multi_events_to_dataframe(obj, parents=False)
          res2 = ep.multi_events_to_dataframe(obj, parents=True)
          res3 = ep.multi_events_to_dataframe(obj, child_first=True)
          res4 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=True)
          res5 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=True)
          res6 = ep.multi_events_to_dataframe(obj, child_first=False)
          res7 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=False)
          res8 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          targ = ep.event_to_dataframe(obj)
  
          keys = ep._extract_neo_attrs_safe(obj, parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = 1
          targlen = min(len(obj.times), len(obj.labels))
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
          self.assertEqual(targwidth, len(res4.columns))
          self.assertEqual(targwidth, len(res5.columns))
          self.assertEqual(targwidth, len(res6.columns))
          self.assertEqual(targwidth, len(res7.columns))
          self.assertEqual(targwidth, len(res8.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
          self.assertEqual(targlen, len(res4.index))
          self.assertEqual(targlen, len(res5.index))
          self.assertEqual(targlen, len(res6.index))
          self.assertEqual(targlen, len(res7.index))
          self.assertEqual(targlen, len(res8.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
          self.assertCountEqual(keys, res4.columns.names)
          self.assertCountEqual(keys, res5.columns.names)
          self.assertCountEqual(keys, res6.columns.names)
          self.assertCountEqual(keys, res7.columns.names)
          self.assertCountEqual(keys, res8.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
          assert_array_equal(targ.values, res3.values)
          assert_array_equal(targ.values, res4.values)
          assert_array_equal(targ.values, res5.values)
          assert_array_equal(targ.values, res6.values)
          assert_array_equal(targ.values, res7.values)
          assert_array_equal(targ.values, res8.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
          assert_frame_equal(targ, res4)
          assert_frame_equal(targ, res5)
          assert_frame_equal(targ, res6)
          assert_frame_equal(targ, res7)
          assert_frame_equal(targ, res8)
  
      def test__multi_events_to_dataframe__segment_default(self):
          obj = fake_neo('Segment', seed=0, n=5)
  
          res0 = ep.multi_events_to_dataframe(obj)
  
          objs = obj.events
  
          targ = [ep.event_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
  
          assert_frame_equal(targ, res0)
  
      def test__multi_events_to_dataframe__block_noparents(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_events_to_dataframe(obj, parents=False)
          res1 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=True)
          res2 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=False)
  
          objs = obj.list_children_by_class('Event')
  
          targ = [ep.event_to_dataframe(iobj, parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_events_to_dataframe__block_parents_childfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_events_to_dataframe(obj)
          res1 = ep.multi_events_to_dataframe(obj, parents=True)
          res2 = ep.multi_events_to_dataframe(obj, child_first=True)
          res3 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=True)
  
          objs = obj.list_children_by_class('Event')
  
          targ = [ep.event_to_dataframe(iobj, parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res3.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_events_to_dataframe__block_parents_parentfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_events_to_dataframe(obj, child_first=False)
          res1 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          objs = obj.list_children_by_class('Event')
  
          targ = [ep.event_to_dataframe(iobj, parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_events_to_dataframe__list_noparents(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_events_to_dataframe(obj, parents=False)
          res1 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=True)
          res2 = ep.multi_events_to_dataframe(obj, parents=False,
                                              child_first=False)
  
          objs = (iobj.list_children_by_class('Event') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.event_to_dataframe(iobj, parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_events_to_dataframe__list_parents_childfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_events_to_dataframe(obj)
          res1 = ep.multi_events_to_dataframe(obj, parents=True)
          res2 = ep.multi_events_to_dataframe(obj, child_first=True)
          res3 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=True)
  
          objs = (iobj.list_children_by_class('Event') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.event_to_dataframe(iobj, parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res3.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_events_to_dataframe__list_parents_parentfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_events_to_dataframe(obj, child_first=False)
          res1 = ep.multi_events_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          objs = (iobj.list_children_by_class('Event') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.event_to_dataframe(iobj, parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_events_to_dataframe__tuple_default(self):
          obj = tuple(fake_neo('Block', seed=i, n=3) for i in range(3))
  
          res0 = ep.multi_events_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('Event') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.event_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
      def test__multi_events_to_dataframe__iter_default(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_events_to_dataframe(iter(obj))
  
          objs = (iobj.list_children_by_class('Event') for iobj in obj)
          objs = list(chain.from_iterable(objs))
          targ = [ep.event_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
      def test__multi_events_to_dataframe__dict_default(self):
          obj = dict((i, fake_neo('Block', seed=i, n=3)) for i in range(3))
  
          res0 = ep.multi_events_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('Event') for iobj in
                  obj.values())
          objs = list(chain.from_iterable(objs))
          targ = [ep.event_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.labels))]
                     for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class MultiEpochsToDataframeTestCase(unittest.TestCase):
      def setUp(self):
          if hasattr(self, 'assertItemsEqual'):
              self.assertCountEqual = self.assertItemsEqual
  
      def test__multi_epochs_to_dataframe__single(self):
          obj = fake_neo('Epoch', seed=0, n=5)
  
          res0 = ep.multi_epochs_to_dataframe(obj)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=False)
          res2 = ep.multi_epochs_to_dataframe(obj, parents=True)
          res3 = ep.multi_epochs_to_dataframe(obj, child_first=True)
          res4 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=True)
          res5 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=True)
          res6 = ep.multi_epochs_to_dataframe(obj, child_first=False)
          res7 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=False)
          res8 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          targ = ep.epoch_to_dataframe(obj)
  
          keys = ep._extract_neo_attrs_safe(obj, parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = 1
          targlen = min(len(obj.times), len(obj.durations), len(obj.labels))
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
          self.assertEqual(targwidth, len(res4.columns))
          self.assertEqual(targwidth, len(res5.columns))
          self.assertEqual(targwidth, len(res6.columns))
          self.assertEqual(targwidth, len(res7.columns))
          self.assertEqual(targwidth, len(res8.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
          self.assertEqual(targlen, len(res4.index))
          self.assertEqual(targlen, len(res5.index))
          self.assertEqual(targlen, len(res6.index))
          self.assertEqual(targlen, len(res7.index))
          self.assertEqual(targlen, len(res8.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
          self.assertCountEqual(keys, res4.columns.names)
          self.assertCountEqual(keys, res5.columns.names)
          self.assertCountEqual(keys, res6.columns.names)
          self.assertCountEqual(keys, res7.columns.names)
          self.assertCountEqual(keys, res8.columns.names)
  
          assert_array_equal(targ.values, res0.values)
          assert_array_equal(targ.values, res1.values)
          assert_array_equal(targ.values, res2.values)
          assert_array_equal(targ.values, res3.values)
          assert_array_equal(targ.values, res4.values)
          assert_array_equal(targ.values, res5.values)
          assert_array_equal(targ.values, res6.values)
          assert_array_equal(targ.values, res7.values)
          assert_array_equal(targ.values, res8.values)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
          assert_frame_equal(targ, res4)
          assert_frame_equal(targ, res5)
          assert_frame_equal(targ, res6)
          assert_frame_equal(targ, res7)
          assert_frame_equal(targ, res8)
  
      def test__multi_epochs_to_dataframe__segment_default(self):
          obj = fake_neo('Segment', seed=0, n=5)
  
          res0 = ep.multi_epochs_to_dataframe(obj)
  
          objs = obj.epochs
  
          targ = [ep.epoch_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
      def test__multi_epochs_to_dataframe__block_noparents(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_epochs_to_dataframe(obj, parents=False)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=True)
          res2 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=False)
  
          objs = obj.list_children_by_class('Epoch')
  
          targ = [ep.epoch_to_dataframe(iobj, parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_epochs_to_dataframe__block_parents_childfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_epochs_to_dataframe(obj)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=True)
          res2 = ep.multi_epochs_to_dataframe(obj, child_first=True)
          res3 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=True)
  
          objs = obj.list_children_by_class('Epoch')
  
          targ = [ep.epoch_to_dataframe(iobj, parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res3.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_epochs_to_dataframe__block_parents_parentfirst(self):
          obj = fake_neo('Block', seed=0, n=3)
  
          res0 = ep.multi_epochs_to_dataframe(obj, child_first=False)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          objs = obj.list_children_by_class('Epoch')
  
          targ = [ep.epoch_to_dataframe(iobj, parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_epochs_to_dataframe__list_noparents(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_epochs_to_dataframe(obj, parents=False)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=True)
          res2 = ep.multi_epochs_to_dataframe(obj, parents=False,
                                              child_first=False)
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.epoch_to_dataframe(iobj, parents=False, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=False,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
  
      def test__multi_epochs_to_dataframe__list_parents_childfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_epochs_to_dataframe(obj)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=True)
          res2 = ep.multi_epochs_to_dataframe(obj, child_first=True)
          res3 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=True)
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.epoch_to_dataframe(iobj, parents=True, child_first=True)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
          self.assertEqual(targwidth, len(res2.columns))
          self.assertEqual(targwidth, len(res3.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
          self.assertEqual(targlen, len(res2.index))
          self.assertEqual(targlen, len(res3.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
          self.assertCountEqual(keys, res2.columns.names)
          self.assertCountEqual(keys, res3.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res2.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res3.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
      def test__multi_epochs_to_dataframe__list_parents_parentfirst(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_epochs_to_dataframe(obj, child_first=False)
          res1 = ep.multi_epochs_to_dataframe(obj, parents=True,
                                              child_first=False)
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.epoch_to_dataframe(iobj, parents=True, child_first=False)
                  for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=False).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
          self.assertEqual(targwidth, len(res1.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
          self.assertEqual(targlen, len(res1.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
          self.assertCountEqual(keys, res1.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res1.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
  
      def test__multi_epochs_to_dataframe__tuple_default(self):
          obj = tuple(fake_neo('Block', seed=i, n=3) for i in range(3))
  
          res0 = ep.multi_epochs_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in obj)
          objs = list(chain.from_iterable(objs))
  
          targ = [ep.epoch_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
      def test__multi_epochs_to_dataframe__iter_default(self):
          obj = [fake_neo('Block', seed=i, n=3) for i in range(3)]
  
          res0 = ep.multi_epochs_to_dataframe(iter(obj))
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in obj)
          objs = list(chain.from_iterable(objs))
          targ = [ep.epoch_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
      def test__multi_epochs_to_dataframe__dict_default(self):
          obj = dict((i, fake_neo('Block', seed=i, n=3)) for i in range(3))
  
          res0 = ep.multi_epochs_to_dataframe(obj)
  
          objs = (iobj.list_children_by_class('Epoch') for iobj in
                  obj.values())
          objs = list(chain.from_iterable(objs))
          targ = [ep.epoch_to_dataframe(iobj) for iobj in objs]
          targ = ep._sort_inds(pd.concat(targ, axis=1), axis=1)
  
          keys = ep._extract_neo_attrs_safe(objs[0], parents=True,
                                            child_first=True).keys()
          keys = list(keys)
  
          targwidth = len(objs)
          targlen = [iobj.times[:min(len(iobj.times), len(iobj.durations),
                                     len(iobj.labels))] for iobj in objs]
          targlen = len(np.unique(np.hstack(targlen)))
  
          self.assertGreater(len(objs), 0)
  
          self.assertEqual(targwidth, len(targ.columns))
          self.assertEqual(targwidth, len(res0.columns))
  
          self.assertEqual(targlen, len(targ.index))
          self.assertEqual(targlen, len(res0.index))
  
          self.assertCountEqual(keys, targ.columns.names)
          self.assertCountEqual(keys, res0.columns.names)
  
          assert_array_equal(
              np.array(targ.values, dtype=np.float),
              np.array(res0.values, dtype=np.float))
  
          assert_frame_equal(targ, res0)
  
  
  @unittest.skipUnless(HAVE_PANDAS, 'requires pandas')
  class SliceSpiketrainTestCase(unittest.TestCase):
      def setUp(self):
          obj = [fake_neo('SpikeTrain', seed=i, n=3) for i in range(10)]
          self.obj = ep.multi_spiketrains_to_dataframe(obj)
  
      def test_single_none(self):
          targ_start = self.obj.columns.get_level_values('t_start').values
          targ_stop = self.obj.columns.get_level_values('t_stop').values
  
          res0 = ep.slice_spiketrain(self.obj)
          res1 = ep.slice_spiketrain(self.obj, t_start=None)
          res2 = ep.slice_spiketrain(self.obj, t_stop=None)
          res3 = ep.slice_spiketrain(self.obj, t_start=None, t_stop=None)
  
          res0_start = res0.columns.get_level_values('t_start').values
          res1_start = res1.columns.get_level_values('t_start').values
          res2_start = res2.columns.get_level_values('t_start').values
          res3_start = res3.columns.get_level_values('t_start').values
  
          res0_stop = res0.columns.get_level_values('t_stop').values
          res1_stop = res1.columns.get_level_values('t_stop').values
          res2_stop = res2.columns.get_level_values('t_stop').values
          res3_stop = res3.columns.get_level_values('t_stop').values
          targ = self.obj
  
          self.assertFalse(res0 is targ)
          self.assertFalse(res1 is targ)
          self.assertFalse(res2 is targ)
          self.assertFalse(res3 is targ)
  
          assert_frame_equal(targ, res0)
          assert_frame_equal(targ, res1)
          assert_frame_equal(targ, res2)
          assert_frame_equal(targ, res3)
  
          assert_array_equal(targ_start, res0_start)
          assert_array_equal(targ_start, res1_start)
          assert_array_equal(targ_start, res2_start)
          assert_array_equal(targ_start, res3_start)
  
          assert_array_equal(targ_stop, res0_stop)
          assert_array_equal(targ_stop, res1_stop)
          assert_array_equal(targ_stop, res2_stop)
          assert_array_equal(targ_stop, res3_stop)
  
      def test_single_t_start(self):
          targ_start = .0001
          targ_stop = self.obj.columns.get_level_values('t_stop').values
  
          res0 = ep.slice_spiketrain(self.obj, t_start=targ_start)
          res1 = ep.slice_spiketrain(self.obj, t_start=targ_start, t_stop=None)
  
          res0_start = res0.columns.get_level_values('t_start').unique().tolist()
          res1_start = res1.columns.get_level_values('t_start').unique().tolist()
  
          res0_stop = res0.columns.get_level_values('t_stop').values
          res1_stop = res1.columns.get_level_values('t_stop').values
  
          targ = self.obj.values
          targ[targ < targ_start] = np.nan
  
          self.assertFalse(res0 is targ)
          self.assertFalse(res1 is targ)
  
          assert_array_equal(targ, res0.values)
          assert_array_equal(targ, res1.values)
  
          self.assertEqual([targ_start], res0_start)
          self.assertEqual([targ_start], res1_start)
  
          assert_array_equal(targ_stop, res0_stop)
          assert_array_equal(targ_stop, res1_stop)
  
      def test_single_t_stop(self):
          targ_start = self.obj.columns.get_level_values('t_start').values
          targ_stop = .0009
  
          res0 = ep.slice_spiketrain(self.obj, t_stop=targ_stop)
          res1 = ep.slice_spiketrain(self.obj, t_stop=targ_stop, t_start=None)
  
          res0_start = res0.columns.get_level_values('t_start').values
          res1_start = res1.columns.get_level_values('t_start').values
  
          res0_stop = res0.columns.get_level_values('t_stop').unique().tolist()
          res1_stop = res1.columns.get_level_values('t_stop').unique().tolist()
  
          targ = self.obj.values
          targ[targ > targ_stop] = np.nan
  
          self.assertFalse(res0 is targ)
          self.assertFalse(res1 is targ)
  
          assert_array_equal(targ, res0.values)
          assert_array_equal(targ, res1.values)
  
          assert_array_equal(targ_start, res0_start)
          assert_array_equal(targ_start, res1_start)
  
          self.assertEqual([targ_stop], res0_stop)
          self.assertEqual([targ_stop], res1_stop)
  
      def test_single_both(self):
          targ_start = .0001
          targ_stop = .0009
  
          res0 = ep.slice_spiketrain(self.obj,
                                     t_stop=targ_stop, t_start=targ_start)
  
          res0_start = res0.columns.get_level_values('t_start').unique().tolist()
  
          res0_stop = res0.columns.get_level_values('t_stop').unique().tolist()
  
          targ = self.obj.values
          targ[targ < targ_start] = np.nan
          targ[targ > targ_stop] = np.nan
  
          self.assertFalse(res0 is targ)
  
          assert_array_equal(targ, res0.values)
  
          self.assertEqual([targ_start], res0_start)
  
          self.assertEqual([targ_stop], res0_stop)
  
  
  if __name__ == '__main__':
      unittest.main()
  