def test_min_frequency(self):
# no filtering
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=2)
expected = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=3)
expected = Table(np.array([[1, 1, 2]]),
['O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=5)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
def test_min_frequency(self):
# no filtering
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=2)
expected = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=3)
expected = Table(np.array([[1, 1, 2]]),
['O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
table = Table(np.array([[0, 1, 1], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, min_frequency=5)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
def test_where(self):
# no filtering
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes' OR SequencedGenome='no'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([[1, 3]]),
['O1'],
['S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes' AND SequencedGenome='no'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
# filter one -> exclude one
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes'"
actual = filter_features(table,
exclude_ids=True,
metadata=metadata,
where=where)
expected = Table(np.array([[1, 1, 2]]),
['O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
def test_where(self):
# no filtering
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes' OR SequencedGenome='no'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([[1, 3]]),
['O1'],
['S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes' AND SequencedGenome='no'"
actual = filter_features(table, metadata=metadata, where=where)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
# filter one -> exclude one
df = pd.DataFrame({'SequencedGenome': ['yes', 'no']},
index=pd.Index(['O1', 'O2'], name='feature-id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
where = "SequencedGenome='yes'"
actual = filter_features(table,
exclude_ids=True,
metadata=metadata,
where=where)
expected = Table(np.array([[1, 1, 2]]),
['O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
def test_feature_metadata(self):
# no filtering
df = pd.DataFrame({'SequencedGenome': ['yes', 'yes']},
index=pd.Index(['O1', 'O2'], name='id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, metadata=metadata)
expected = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
df = pd.DataFrame({'SequencedGenome': ['yes']},
index=pd.Index(['O1'], name='id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, metadata=metadata)
expected = Table(np.array([[1, 3]]), ['O1'], ['S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
df = pd.DataFrame({}, index=pd.Index(['foo'], name='id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, metadata=metadata)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
# exclude one
df = pd.DataFrame({'SequencedGenome': ['yes']},
index=pd.Index(['O1'], name='id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, metadata=metadata, exclude_ids=True)
expected = Table(np.array([[1, 1, 2]]), ['O2'], ['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# exclude all
df = pd.DataFrame({'SequencedGenome': ['yes', 'yes']},
index=pd.Index(['O1', 'O2'], name='id'))
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, metadata=metadata, exclude_ids=True)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
def test_filter_empty_samples(self):
# no filtering
table = Table(np.array([[0, 1, 1], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table,
min_frequency=2,
filter_empty_samples=False)
expected = Table(np.array([[0, 1, 1], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
table = Table(np.array([[0, 1, 1], [1, 1, 2]]), ['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table,
min_frequency=5,
filter_empty_samples=False)
self.assertTrue(actual.is_empty())
def test_feature_metadata(self):
# no filtering
df = pd.DataFrame({'SequencedGenome': ['yes', 'yes']},
index=['O1', 'O2'])
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, feature_metadata=metadata)
expected = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
self.assertEqual(actual, expected)
# filter one
df = pd.DataFrame({'SequencedGenome': ['yes']},
index=['O1'])
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, feature_metadata=metadata)
expected = Table(np.array([[1, 3]]),
['O1'],
['S2', 'S3'])
self.assertEqual(actual, expected)
# filter all
df = pd.DataFrame({})
metadata = qiime2.Metadata(df)
table = Table(np.array([[0, 1, 3], [1, 1, 2]]),
['O1', 'O2'],
['S1', 'S2', 'S3'])
actual = filter_features(table, feature_metadata=metadata)
expected = Table(np.array([]), [], [])
self.assertEqual(actual, expected)
