def test_ngram_9(self):
"""test _8 but longer; things happen before and after terminator"""
mi = mi_maker((V_IND, ), ('0,1', '0,2'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V'])
], mi)
mi = mi_maker((H_IND, ), ('1', '2'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': [('1', '2')],
'vertical': [('0,1', '0,2')],
'brackets': True,
'terminator': ['C']
}
expected = pandas.DataFrame([
pandas.Series(['[A Z] (a z) [B X]', '[D W] (d w) [E V]'],
index=[0, 3])
],
index=[['ngram.NGramIndexer'],
['0,1 0,2 : 1 2']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_21d(self):
"""tests that horizontal setting is set correctly when 'highest' is passed and there
are multiple vertical voice pairs. Also outputs results into multiple columns."""
mi = mi_maker((V_IND, ), ('0,1', '0,2', '1,2'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U'])
], mi)
mi = mi_maker((H_IND, ), ('0', '1', '2'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['a2', 'b2', 'c2', 'd2'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': 'highest',
'vertical': [('0,1', ), ('0,2', ), ('1,2', )],
'brackets': True,
}
mi = mi_maker(['ngram.NGramIndexer'],
['0,1 : 0', '0,2 : 0', '1,2 : 1'])
expected = df_maker([
pandas.Series(
['[A] (a) [B]', '[B] (b) [C]', '[C] (c) [D]', '[D] (d) [E]']),
pandas.Series(
['[Z] (a) [X]', '[X] (b) [Y]', '[Y] (c) [W]', '[W] (d) [V]']),
pandas.Series([
'[Q] (a2) [R]', '[R] (b2) [S]', '[S] (c2) [T]', '[T] (d2) [U]'
])
], mi)
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_21b(self):
"""tests that horizontal setting is set correctly when 'lowest' is passed and there
are multiple vertical voice pairs lumped in the same group. NB this is like tracking
the lowest voice of figured-bass sonorities."""
mi = mi_maker((V_IND, ), ('0,3', '1,3', '2,3'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U'])
], mi)
mi = mi_maker((H_IND, ), ('0', '1', '2', '3'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['a2', 'b2', 'c2', 'd2'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4]),
pandas.Series(['z2', 'x2', 'y2', 'w2'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': 'lowest',
'vertical': [('0,3', '1,3', '2,3')],
'brackets': True,
}
expected = pandas.DataFrame([
pandas.Series([
'[A Z Q] (z2) [B X R]', '[B X R] (x2) [C Y S]',
'[C Y S] (y2) [D W T]', '[D W T] (w2) [E V U]'
])
],
index=[['ngram.NGramIndexer'],
['0,3 1,3 2,3 : 3']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_16a(self):
"""test _9 but with three "vertical" parts and no terminator"""
mi = mi_maker((V_IND, ), ('0,1', '0,2', '0,3'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U'])
], mi)
mi = mi_maker((H_IND, ), ('2', '3'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': [('2', '3')],
'vertical': [('0,1', '0,2', '0,3')],
'brackets': True,
}
expected = pandas.DataFrame([
pandas.Series([
'[A Z Q] (a z) [B X R]', '[B X R] (b x) [C Y S]',
'[C Y S] (c y) [D W T]', '[D W T] (d w) [E V U]'
],
index=[0, 1, 2, 3])
],
index=[['ngram.NGramIndexer'],
['0,1 0,2 0,3 : 2 3']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_17(self):
"""test _16 but with four "vertical" parts"""
mi = mi_maker((V_IND, ), ('0,1', '0,2', '0,3', '0,4'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U']),
pandas.Series(['J', 'K', 'L', 'M', 'N'])
], mi)
mi = mi_maker((H_IND, ), ('3', '4'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': [('3', '4')],
'vertical': [('0,1', '0,2', '0,3', '0,4')],
'brackets': True,
}
expected = pandas.DataFrame([
pandas.Series([
'[A Z Q J] (a z) [B X R K]', '[B X R K] (b x) [C Y S L]',
'[C Y S L] (c y) [D W T M]', '[D W T M] (d w) [E V U N]'
],
index=[0, 1, 2, 3])
],
index=[['ngram.NGramIndexer'],
['0,1 0,2 0,3 0,4 : 3 4']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_6(self):
"""combination of tests _4a and _5a"""
mi = mi_maker((V_IND, ), ('0,1', '0,2'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D']),
pandas.Series(['Z', 'X', 'Y', 'W'])
], mi)
mi = mi_maker((H_IND, ), ('1', '2'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c'], index=[1, 2, 3]),
pandas.Series(['z', 'x', 'y'], index=[1, 2, 3])
], mi)
setts = {
'n': 2,
'horizontal': [('1', '2')],
'vertical': [('0,1', '0,2')],
'brackets': True
}
expected = pandas.DataFrame([
pandas.Series([
'[A Z] (a z) [B X]', '[B X] (b x) [C Y]', '[C Y] (c y) [D W]'
])
],
index=[['ngram.NGramIndexer'],
['0,1 0,2 : 1 2']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_18(self):
"""test _17 but with n=1"""
mi = mi_maker((V_IND, ), ('0,1', '0,2', '0,3', '0,4'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U']),
pandas.Series(['J', 'K', 'L', 'M', 'N'])
], mi)
setts = {
'n': 1,
'vertical': [('0,1', '0,2', '0,3', '0,4')],
'brackets': True,
}
expected = pandas.DataFrame([
pandas.Series([
'[A Z Q J]', '[B X R K]', '[C Y S L]', '[D W T M]', '[E V U N]'
],
index=[0, 1, 2, 3, 4])
],
index=[['ngram.NGramIndexer'],
['0,1 0,2 0,3 0,4']]).T
actual = ngram.NGramIndexer([vertical], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_19(self):
# test _0 with a "missing" vertical and horizontal thing
# Input:
# 0 1 2 3 4
# v: A B C D
# h: a b c
#
# Expected:
# 0: 'A a B'
# 1: 'B _ C'
# 2: 'C b C'
# 3: 'C c D'
# NB: this started as a regression test for issue 261, where missing values weren't filled
vertical = df_maker(
[pandas.Series(['A', 'B', 'C', 'D'], index=[0, 1, 2, 4])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 3, 4])],
HORIZ_DF.columns)
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a B', 'B _ C', 'C b C', 'C c D'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_21c(self):
"""tests that horizontal setting is set correctly when 'lowest' is passed and there
are multiple vertical voice pairs. Also outputs results into multiple columns."""
mi = mi_maker((V_IND, ), ('0,1', '0,2', '1,2'))
vertical = df_maker([
pandas.Series(['A', 'B', 'C', 'D', 'E']),
pandas.Series(['Z', 'X', 'Y', 'W', 'V']),
pandas.Series(['Q', 'R', 'S', 'T', 'U'])
], mi)
mi = mi_maker((H_IND, ), ('0', '1', '2'))
horizontal = df_maker([
pandas.Series(['a', 'b', 'c', 'd'], index=[1, 2, 3, 4]),
pandas.Series(['a2', 'b2', 'c2', 'd2'], index=[1, 2, 3, 4]),
pandas.Series(['z', 'x', 'y', 'w'], index=[1, 2, 3, 4])
], mi)
setts = {
'n': 2,
'horizontal': 'lowest',
'vertical': [('0,1', ), ('0,2', ), ('1,2', )],
'brackets': False,
}
mi = mi_maker(['ngram.NGramIndexer'],
['0,1 : 1', '0,2 : 2', '1,2 : 2'])
expected = df_maker([
pandas.Series(['A a2 B', 'B b2 C', 'C c2 D', 'D d2 E']),
pandas.Series(['Z z X', 'X x Y', 'Y y W', 'W w V']),
pandas.Series(['Q z R', 'R x S', 'S y T', 'T w U'])
], mi)
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_init_3(self):
"""that __init__() fails when 'n' is too short"""
# pylint: disable=protected-access
setts = {'n': 0, 'vertical': [('0,1', )]} # n is too short
self.assertRaises(RuntimeError, ngram.NGramIndexer, (VERT_DF, ), setts)
try:
ngram.NGramIndexer((VERT_DF, ), setts)
except RuntimeError as run_err:
self.assertEqual(ngram.NGramIndexer._N_VALUE_TOO_LOW,
run_err.args[0])
def test_init_1(self):
"""that __init__() works properly (only required settings given)"""
# pylint: disable=protected-access
setts = {'n': 1, 'vertical': [('0,1', )]}
actual = ngram.NGramIndexer((VERT_DF, ), setts)
for setting in ('n', 'vertical'):
self.assertEqual(setts[setting], actual._settings[setting])
for setting in ('horizontal', 'brackets', 'terminator', 'continuer'):
self.assertEqual(ngram.NGramIndexer.default_settings[setting],
actual._settings[setting])
def test_init_10(self):
"""That __init__() raises a RuntimeWarning when 'align' setting is improperly set."""
setts = {'n': 2, 'vertical': [('0,1', )], 'align': 'saperlipopette'}
self.assertRaises(RuntimeWarning, ngram.NGramIndexer, (VERT_DF, ),
setts)
try:
ngram.NGramIndexer((VERT_DF, ), setts)
except RuntimeWarning as run_warn:
self.assertEqual(ngram.NGramIndexer._WRONG_ALIGN_SETTING,
run_warn.args[0])
def test_init_4(self):
"""that __init__() fails when there are no 'vertical' events"""
# pylint: disable=protected-access
setts = {'n': 14, 'horizontal': [('1', )]} # no "vertical" parts
self.assertRaises(RuntimeError, ngram.NGramIndexer, 'a DataFrame',
setts)
try:
ngram.NGramIndexer('a DataFrame', setts)
except RuntimeError as run_err:
self.assertEqual(ngram.NGramIndexer._MISSING_SETTINGS,
run_err.args[0])
def test_init_9(self):
"""That __init__() raises a RuntimeError when 'horizontal' observations are provided but
no columns are specified in the settings['horizontal']."""
setts = {'n': 2, 'vertical': [('0,1', )], 'brackets': False}
self.assertRaises(RuntimeError, ngram.NGramIndexer,
(VERT_DF, HORIZ_DF), setts)
try:
ngram.NGramIndexer((VERT_DF, HORIZ_DF), setts)
except RuntimeError as run_err:
self.assertEqual(ngram.NGramIndexer._MISSING_HORIZONTAL_SETTING,
run_err.args[0])
def test_init_8b(self):
"""Same as test_init_8a but for horizontal observations. Note that there is only one
column in the HORIZ_DF DataFrame."""
setts = {'n': 2, 'horizontal': [('1', '2')], 'vertical': [('0,1', )]}
self.assertRaises(RuntimeError, ngram.NGramIndexer,
(VERT_DF, HORIZ_DF), setts)
try:
ngram.NGramIndexer((VERT_DF, HORIZ_DF), setts)
except RuntimeError as run_err:
self.assertEqual(ngram.NGramIndexer._HORIZONTAL_OUT_OF_RANGE,
run_err.args[0])
def test_init_8a(self):
"""That __init__() raises a RuntimeError when not all of the columns designated in the
'vertical' settings are found in the DataFrame of vertical observations. Note that there
is only one column in the VERT_DF DataFrame."""
setts = {'n': 2, 'vertical': [('0,1', '0,2')], 'open-ended': True}
self.assertRaises(RuntimeError, ngram.NGramIndexer, (VERT_DF, ), setts)
try:
ngram.NGramIndexer((VERT_DF, ), setts)
except RuntimeError as run_err:
self.assertEqual(ngram.NGramIndexer._VERTICAL_OUT_OF_RANGE,
run_err.args[0])
def test_init_7a(self):
"""that __init__() raises a RuntimeWarning when n (+1 if 'open-ended' setting is True) is
set higher than the number of observations in either of the passed dataframes."""
setts = {'n': 16, 'horizontal': [('1', )], 'vertical': [('0,1', )]}
self.assertRaises(RuntimeWarning, ngram.NGramIndexer,
(VERT_DF, HORIZ_DF), setts)
try:
ngram.NGramIndexer((VERT_DF, HORIZ_DF), setts)
except RuntimeWarning as run_warn:
self.assertEqual(ngram.NGramIndexer._N_VALUE_TOO_HIGH,
run_warn.args[0])
def test_ngram_15(self):
"""longer test, inspired by the first five measures of "Kyrie.krn" parts 1 and 3"""
setts = {
'n': 4,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'continuer': 'P1',
'terminator': 'Rest',
'brackets': True
}
actual = ngram.NGramIndexer([VERT_DF, HORIZ_DF], setts).run()
self.assertTrue(actual.equals(EXPECTED_DF))
def test_init_6b(self):
"""that __init__() manages the horizontal setting set to 'lowest' correctly."""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
mi = mi_maker((H_IND, ), ('1', '0'))
horizontal = df_maker(
[pandas.Series(['z', 'x', 'y']),
pandas.Series(['a', 'b', 'c'])], mi)
setts = {
'n': 2,
'horizontal': 'lowest',
'vertical': [('0,1', )],
'brackets': False
}
actual = ngram.NGramIndexer([vertical, horizontal], setts)
self.assertEqual([('1', )], actual._settings['horizontal'])
def test_init_5(self):
"""that __init__() fails when horizontal observations are provided and 'n' equals 1
and 'open-ended' is False."""
# pylint: disable=protected-access
setts = {
'n': 1,
'vertical': [('0,1', )],
'horizontal': [('1', )],
'open-ended': True
}
self.assertRaises(RuntimeError, ngram.NGramIndexer, (VERT_DF, ), setts)
try:
ngram.NGramIndexer((VERT_DF, HORIZ_DF), setts)
except RuntimeWarning as run_warn:
self.assertEqual(ngram.NGramIndexer._SUPERFLUOUS_HORIZONTAL_DATA,
run_warn.args[0])
def test_init_2(self):
"""that __init__() works properly (all settings given)"""
# pylint: disable=protected-access
setts = {
'n': 2,
'vertical': [('0,1', )],
'horizontal': [('1', )],
'brackets': True,
'terminator': 'RoboCop',
'continuer': 'Alex Murphy',
'open-ended': True
}
actual = ngram.NGramIndexer((VERT_DF, HORIZ_DF), setts)
for setting in ('n', 'vertical', 'horizontal', 'brackets',
'terminator', 'continuer', 'open-ended'):
self.assertEqual(setts[setting], actual._settings[setting])
def test_ngram_13(self):
"""test _1 with too few "vertical" things (last should be repeated)"""
vertical = df_maker([pandas.Series(['A', 'B', 'C'])], VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a B', 'B b C', 'C c C'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_2(self):
"""adds the grouping characters"""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': True
}
expected = pandas.DataFrame(
[pandas.Series(['[A] (a) [B]', '[B] (b) [C]', '[C] (c) [D]'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_3a(self):
"""test _1 but n=3"""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 3,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a B b C', 'B b C c D'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_12(self):
"""test _11 with one missing "horizontal" thing in the middle"""
vertical = pandas.concat([pandas.Series(['A', 'B', 'C', 'D'])], axis=1)
vertical.columns = VERT_DF.columns
horizontal = pandas.concat([pandas.Series(['a', 'z'], index=[1, 3])],
axis=1)
horizontal.columns = HORIZ_DF.columns
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a B', 'B _ C', 'C z D'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_14(self):
"""test _13 with one missing "vertical" thing in the middle"""
vertical = df_maker([pandas.Series(['A', 'B', 'C'], index=[0, 2, 3])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a A', 'A b B', 'B c C'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_10(self):
"""test _1 with too few "horizontal" things (should use "continuer" character)"""
vertical = pandas.concat([pandas.Series(['A', 'B', 'C', 'D'])], axis=1)
vertical.columns = VERT_DF.columns
horizontal = pandas.concat([pandas.Series(['a', 'b'], index=[1, 2])],
axis=1)
horizontal.columns = HORIZ_DF.columns
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a B', 'B b C', 'C _ D'])],
index=[['ngram.NGramIndexer'], ['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_1b(self):
"""like test _1a but with self._settings['open-ended'] set to True."""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 1,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': False,
'open-ended': True
}
expected = pandas.DataFrame([pandas.Series(['A a', 'B b', 'C c'])],
index=[['ngram.NGramIndexer'],
['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_7(self):
"""test _1 with a terminator; nothing should be picked up after terminator"""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
horizontal = df_maker(
[pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])],
HORIZ_DF.columns)
setts = {
'n': 2,
'horizontal': [('1', )],
'vertical': [('0,1', )],
'brackets': True,
'terminator': ['C']
}
expected = pandas.DataFrame([pandas.Series(['[A] (a) [B]'])],
index=[['ngram.NGramIndexer'],
['0,1 : 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
def test_ngram_5c(self):
"""test _1 but with two horizontals, and the order of 'horizontal' setting is important"""
vertical = df_maker([pandas.Series(['A', 'B', 'C', 'D'])],
VERT_DF.columns)
mi = mi_maker((H_IND, ), ('1', '0'))
horizontal = df_maker([
pandas.Series(['z', 'x', 'y'], index=[1, 2, 3]),
pandas.Series(['a', 'b', 'c'], index=[1, 2, 3])
], mi)
setts = {
'n': 2,
'horizontal': [('0', '1')],
'vertical': [('0,1', )],
'brackets': False
}
expected = pandas.DataFrame(
[pandas.Series(['A a z B', 'B b x C', 'C c y D'])],
index=[['ngram.NGramIndexer'], ['0,1 : 0 1']]).T
actual = ngram.NGramIndexer([vertical, horizontal], setts).run()
self.assertTrue(actual.equals(expected))
