def test_run_2(self):
# ensure that run() properly gets "method" from self._settings (default value)
in_val = [mock.MagicMock(spec_set=pandas.Series)]
in_val[0].index = [0.0]
settings = {'quarterLength': 0.5}
ind = FilterByOffsetIndexer(in_val, settings)
ind.run()
in_val[0].reindex.assert_called_once_with(index=[0.0], method='ffill')
def test_offset_xparts_1(self):
# input is expected output; 2 parts
in_val = [
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5],
name=('N', '0')),
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5],
name=('N', '1'))
]
expected = {
'0': pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5]),
'1': pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5])
}
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values),
list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index),
list(actual[partname].index))
def test_offset_xparts_0b(self):
# 0 length, many parts, but one part has stuff
in_val = [
pandas.Series(name=('N', '0')),
pandas.Series(['a', 'b', 'c'],
name=('N', '1'),
index=[0.0, 0.5, 1.0]),
pandas.Series(name=('N', '2')),
pandas.Series(name=('N', '3'))
]
expected = {str(i): pandas.Series() for i in [0, 2, 3]}
#print(str(expected)) # DEBUG
expected['1'] = pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.0])
#print(str(expected)) # DEBUG
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values),
list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index),
list(actual[partname].index))
def test_offset_xparts_5(self):
# irregular offset interval to 1.0; 3 parts, same offsets, one much longer
in_val = [
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.4, 1.1, 2.9],
name=('N', '0')),
pandas.Series(['q', 'w', 'e', 'r'],
index=[0.0, 0.3, 1.4, 2.6],
name=('N', '1')),
pandas.Series(['t', 'a', 'l', 'l', 'o', 'r', 'd', 'e', 'r'],
name=('N', '2'),
index=[0.0, 0.2, 1.9, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0])
]
expected = {
'0':
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 1.0, 2.0, 3.0]),
'1':
pandas.Series(['q', 'w', 'e', 'r'], index=[0.0, 1.0, 2.0, 3.0]),
'2':
pandas.Series(['t', 'a', 'l', 'l', 'o', 'r', 'd', 'e', 'r'],
index=[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0])
}
expected = pandas.DataFrame(expected)
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values),
list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index),
list(actual[partname].index))
def test_offset_xparts_2(self):
# input is expected output; 10 parts
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5])]
expected = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5])]
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_xparts_2(self):
# input is expected output; 10 parts
letters = ['a', 'b', 'c', 'd']
offsets = [0.0, 0.5, 1.0, 1.5]
in_val = [
pandas.Series(letters, index=offsets, name=('N', str(_)))
for _ in range(10)
]
expected = {
str(i): pandas.Series(letters, index=offsets)
for i in range(10)
}
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values),
list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index),
list(actual[partname].index))
def test_offset_1part_0(self):
# 0 parts
in_val = []
expected = []
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
def test_offset_1part_9(self):
# targeted test for end-of-piece: when last thing lands on an observed offset
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.0])]
expected = pandas.Series(['a', 'b', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5, 2.0])
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values), list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index), list(actual.index)) # same index?
def test_offset_1part_4b(self):
# already regular offset interval to a very small one
in_val = [pandas.Series(['a', 'b'], index=[0.0, 0.5])]
expected = [pandas.Series(['a', 'a', 'a', 'a', 'b'], index=[0.0, 0.125, 0.25, 0.375, 0.5])]
offset_interval = 0.125
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_7(self):
# irregular offset interval to a large one
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.1])]
expected = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 1.0, 2.0, 3.0])]
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_5(self):
# already regular offset interval (but some missing) to larger one
in_val = [pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.5])]
expected = [pandas.Series(['a', 'b', 'c'], index=[0.0, 1.0, 2.0])]
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_7(self):
# irregular offset interval to a large one
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.1])]
expected = pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 1.0, 2.0, 3.0])
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values), list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index), list(actual.index)) # same index?
def test_offset_1part_9(self):
# targeted test for end-of-piece: when last thing lands on an observed offset
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.0])]
expected = [pandas.Series(['a', 'b', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5, 2.0])]
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_1(self):
# 0 length
in_val = [pandas.Series()]
expected = [pandas.Series()]
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_5(self):
# already regular offset interval (but some missing) to larger one
in_val = [pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.5])]
expected = pandas.Series(['a', 'b', 'c'], index=[0.0, 1.0, 2.0])
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values), list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index), list(actual.index)) # same index?
def test_offset_1part_4b(self):
# already regular offset interval to a very small one
in_val = [pandas.Series(['a', 'b'], index=[0.0, 0.5])]
expected = pandas.Series(['a', 'a', 'a', 'a', 'b'], index=[0.0, 0.125, 0.25, 0.375, 0.5])
offset_interval = 0.125
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values), list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index), list(actual.index)) # same index?
def test_offset_1part_2(self):
# input is expected output
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5])]
expected = pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5])
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values), list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index), list(actual.index)) # same index?
def test_offset_1part_1(self):
# 0 length
in_val = [pandas.Series()]
expected = pandas.Series()
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(in_val), len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertEqual(len(expected), len(actual)) # same number of rows?
self.assertEqual(list(expected.index), list(actual.index)) # same row names?
def test_offset_xparts_0a(self):
# 0 length, many parts
in_val = [pandas.Series(), pandas.Series(), pandas.Series(), pandas.Series()]
expected = pandas.DataFrame({str(i): pandas.Series() for i in xrange(4)})
offset_interval = 12.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values), list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index), list(actual[partname].index))
def test_offset_xparts_0b(self):
# 0 length, many parts, but one part has stuff
in_val = [pandas.Series(), pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.0]),
pandas.Series(), pandas.Series()]
expected = [pandas.Series(), pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.0]),
pandas.Series(), pandas.Series()]
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_1part_1(self):
# 0 length
in_val = [pandas.Series(name=('Indexer', '0'))]
expected = pandas.Series(name=('Indexer', '0'))
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(in_val),
len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertEqual(len(expected), len(actual)) # same number of rows?
self.assertEqual(list(expected.index),
list(actual.index)) # same row names?
def test_offset_xparts_4(self):
# irregular offset interval to 1.0; 3 parts, same offsets
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.9]),
pandas.Series(['q', 'w', 'e', 'r'], index=[0.0, 0.3, 1.4, 2.6]),
pandas.Series(['t', 'a', 'l', 'l'], index=[0.0, 0.2, 1.9, 2.555])]
expected = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 1.0, 2.0, 3.0]),
pandas.Series(['q', 'w', 'e', 'r'], index=[0.0, 1.0, 2.0, 3.0]),
pandas.Series(['t', 'a', 'l', 'l'], index=[0.0, 1.0, 2.0, 3.0])]
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()
self.assertEqual(len(expected), len(actual)) # same number of columns?
for i in xrange(len(expected)):
self.assertEqual(len(expected[i]), len(actual[i])) # same number of rows?
self.assertEqual(list(expected[i].index), list(actual[i].index)) # same row names?
def test_offset_xparts_2(self):
# input is expected output; 10 parts
letters = ['a', 'b', 'c', 'd']
offsets = [0.0, 0.5, 1.0, 1.5]
in_val = [pandas.Series(letters, index=offsets) for _ in xrange(10)]
expected = {str(i): pandas.Series(letters, index=offsets) for i in xrange(10)}
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values), list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index), list(actual[partname].index))
def test_offset_xparts_1(self):
# input is expected output; 2 parts
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5], name=('N', '0')),
pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5], name=('N', '1'))]
expected = {'0': pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5]),
'1':pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.5, 1.0, 1.5])}
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values), list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index), list(actual[partname].index))
def test_offset_xparts_0b(self):
# 0 length, many parts, but one part has stuff
in_val = [pandas.Series(), pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.0]),
pandas.Series(), pandas.Series()]
expected = {str(i): pandas.Series() for i in [0, 2, 3]}
#print(str(expected)) # DEBUG
expected['1'] = pandas.Series(['a', 'b', 'c'], index=[0.0, 0.5, 1.0])
#print(str(expected)) # DEBUG
expected = pandas.DataFrame(expected)
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values), list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index), list(actual[partname].index))
def test_offset_xparts_4(self):
# irregular offset interval to 1.0; 3 parts, same offsets
in_val = [pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 0.4, 1.1, 2.9]),
pandas.Series(['q', 'w', 'e', 'r'], index=[0.0, 0.3, 1.4, 2.6]),
pandas.Series(['t', 'a', 'l', 'l'], index=[0.0, 0.2, 1.9, 2.555])]
expected = {'0': pandas.Series(['a', 'b', 'c', 'd'], index=[0.0, 1.0, 2.0, 3.0]),
'1': pandas.Series(['q', 'w', 'e', 'r'], index=[0.0, 1.0, 2.0, 3.0]),
'2': pandas.Series(['t', 'a', 'l', 'l'], index=[0.0, 1.0, 2.0, 3.0])}
expected = pandas.DataFrame(expected)
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val, {u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values), list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index), list(actual[partname].index))
def test_offset_xparts_0a(self):
# 0 length, many parts
in_val = [pandas.Series(name=('N', str(i))) for i in range(4)]
expected = pandas.DataFrame(
{str(i): pandas.Series()
for i in range(4)})
offset_interval = 12.0
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(len(expected.columns), len(actual.columns))
expected = expected.fillna(value='None') # avoid having to use isnan()
actual = actual.fillna(value='None')
for partname in expected.columns:
self.assertSequenceEqual(list(expected[partname].values),
list(actual[partname].values))
self.assertSequenceEqual(list(expected[partname].index),
list(actual[partname].index))
def test_offset_1part_4b(self):
# already regular offset interval to a very small one
in_val = [
pandas.Series(['a', 'b'], index=[0.0, 0.5], name=('Indexer', '0'))
]
expected = pandas.Series(['a', 'a', 'a', 'a', 'b'],
name=('Indexer', '0'),
index=[0.0, 0.125, 0.25, 0.375, 0.5])
offset_interval = 0.125
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values),
list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index),
list(actual.index)) # same index?
def test_offset_1part_10(self):
# targeted test for end-of-piece: when last thing doesn't land on an observed offset
in_val = [
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.4, 1.1, 2.1],
name=('N', '0'))
]
expected = pandas.Series(['a', 'b', 'b', 'c', 'c', 'd'],
name=('N', '0'),
index=[0.0, 0.5, 1.0, 1.5, 2.0, 2.5])
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values),
list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index),
list(actual.index)) # same index?
def test_offset_1part_2(self):
# input is expected output
in_val = [
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5],
name=('Indexer', '0'))
]
expected = pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.5, 1.0, 1.5],
name=('Indexer', '0'))
offset_interval = 0.5
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values),
list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index),
list(actual.index)) # same index?
def test_offset_1part_7(self):
# irregular offset interval to a large one
in_val = [
pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 0.4, 1.1, 2.1],
name=('Indexer', '0'))
]
expected = pandas.Series(['a', 'b', 'c', 'd'],
index=[0.0, 1.0, 2.0, 3.0],
name=('Indexer', '0'))
offset_interval = 1.0
ind = FilterByOffsetIndexer(in_val,
{u'quarterLength': offset_interval})
actual = ind.run()['offset.FilterByOffsetIndexer']
self.assertEqual(1, len(actual.columns)) # same number of columns?
actual = actual['0']
self.assertSequenceEqual(list(expected.values),
list(actual.values)) # same rows?
self.assertSequenceEqual(list(expected.index),
list(actual.index)) # same index?
