# -*- 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
[docs] 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')
[docs]class MultiindexFromDictTestCase(unittest.TestCase):
[docs] 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')
[docs]class ConvertValueSafeTestCase(unittest.TestCase):
[docs] def test__convert_value_safe__float(self):
targ = 5.5
value = targ
res = ep._convert_value_safe(value)
self.assertIs(res, targ)
[docs] def test__convert_value_safe__str(self):
targ = 'test'
value = targ
res = ep._convert_value_safe(value)
self.assertIs(res, targ)
[docs] def test__convert_value_safe__bytes(self):
targ = 'test'
value = b'test'
res = ep._convert_value_safe(value)
self.assertEqual(res, targ)
[docs] 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'))
[docs] 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'))
[docs] 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'))
[docs] 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'))
[docs] 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')
[docs]class SpiketrainToDataframeTestCase(unittest.TestCase):
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class EventToDataframeTestCase(unittest.TestCase):
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class EpochToDataframeTestCase(unittest.TestCase):
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class MultiSpiketrainsToDataframeTestCase(unittest.TestCase):
[docs] def setUp(self):
if hasattr(self, 'assertItemsEqual'):
self.assertCountEqual = self.assertItemsEqual
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class MultiEventsToDataframeTestCase(unittest.TestCase):
[docs] def setUp(self):
if hasattr(self, 'assertItemsEqual'):
self.assertCountEqual = self.assertItemsEqual
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class MultiEpochsToDataframeTestCase(unittest.TestCase):
[docs] def setUp(self):
if hasattr(self, 'assertItemsEqual'):
self.assertCountEqual = self.assertItemsEqual
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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')
[docs]class SliceSpiketrainTestCase(unittest.TestCase):
[docs] def setUp(self):
obj = [fake_neo('SpikeTrain', seed=i, n=3) for i in range(10)]
self.obj = ep.multi_spiketrains_to_dataframe(obj)
[docs] 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)
[docs] 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)
[docs] 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)
[docs] 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()