def test_two_iterations_with_metadata_were_values_are_unique(self):
# This should be identical to test_without_metadata_df_two_iterations,
# with just the `sample-id` replaced with `pet`.
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=columns,
index=['russ', 'milo', 'pea'])
counts = pd.DataFrame(data=[[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]],
columns=columns,
index=['russ', 'milo', 'pea'])
obs = _compute_summary(data, 'pet', counts=counts)
d = [
['russ', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['russ', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
['milo', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['milo', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
['pea', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['pea', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
]
exp = pd.DataFrame(data=d,
columns=[
'pet', 'depth', 'min', '2%', '9%', '25%', '50%',
'75%', '91%', '98%', 'max', 'count'
])
pdt.assert_frame_equal(exp, obs)
def test_two_iterations_with_metadata_were_values_are_unique(self):
# This should be identical to test_without_metadata_df_two_iterations,
# with just the `sample-id` replaced with `pet`.
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=columns, index=['russ', 'milo', 'pea'])
counts = pd.DataFrame(data=[[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]],
columns=columns, index=['russ', 'milo', 'pea'])
obs = _compute_summary(data, 'pet', counts=counts)
d = [
['russ', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['russ', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
['milo', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['milo', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
['pea', 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2., 1],
['pea', 200, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4., 1],
]
exp = pd.DataFrame(data=d, columns=['pet', 'depth', 'min', '2%', '9%',
'25%', '50%', '75%', '91%', '98%',
'max', 'count'])
pdt.assert_frame_equal(exp, obs)
def test_two_iterations_with_metadata_were_values_are_identical(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[3, 6, 9, 9]], columns=columns,
index=['milo'])
counts = pd.DataFrame(data=[[3, 3, 3, 3]], columns=columns,
index=['milo'])
obs = _compute_summary(data, 'pet', counts=counts)
d = [
['milo', 1, 3., 3.06, 3.27, 3.75, 4.5, 5.25, 5.73, 5.94, 6., 3],
['milo', 200, 9., 9., 9., 9., 9., 9., 9., 9., 9., 3],
]
exp = pd.DataFrame(data=d, columns=['pet', 'depth', 'min', '2%', '9%',
'25%', '50%', '75%', '91%', '98%',
'max', 'count'])
pdt.assert_frame_equal(exp, obs)
def test_two_iterations_no_metadata(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=columns, index=['S1', 'S2', 'S3'])
# No counts provided because no metadata
obs = _compute_summary(data, 'sample-id')
d = [['S1', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S1', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.],
['S2', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S2', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.],
['S3', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S3', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.]]
exp = pd.DataFrame(data=d, columns=['sample-id', 'depth', 'count',
'min', '2%', '9%', '25%', '50%',
'75%', '91%', '98%', 'max'])
pdt.assert_frame_equal(exp, obs)
def test_two_iterations_with_metadata_were_values_are_identical(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[3, 6, 9, 9]], columns=columns,
index=['milo'])
counts = pd.DataFrame(data=[[3, 3, 3, 3]], columns=columns,
index=['milo'])
obs = _compute_summary(data, 'pet', counts=counts)
d = [
['milo', 1, 3., 3.06, 3.27, 3.75, 4.5, 5.25, 5.73, 5.94, 6., 3],
['milo', 200, 9., 9., 9., 9., 9., 9., 9., 9., 9., 3],
]
exp = pd.DataFrame(data=d, columns=['pet', 'depth', 'min', '2%', '9%',
'25%', '50%', '75%', '91%', '98%',
'max', 'count'])
pdt.assert_frame_equal(exp, obs)
def test_two_iterations_no_metadata(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]],
columns=columns, index=['S1', 'S2', 'S3'])
# No counts provided because no metadata
obs = _compute_summary(data, 'sample-id')
d = [['S1', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S1', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.],
['S2', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S2', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.],
['S3', 1, 1, 1., 1.02, 1.09, 1.25, 1.5, 1.75, 1.91, 1.98, 2.],
['S3', 200, 1, 3., 3.02, 3.09, 3.25, 3.5, 3.75, 3.91, 3.98, 4.]]
exp = pd.DataFrame(data=d, columns=['sample-id', 'depth', 'count',
'min', '2%', '9%', '25%', '50%',
'75%', '91%', '98%', 'max'])
pdt.assert_frame_equal(exp, obs)
def test_three_iterations_no_metadata(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2, 3]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4, 5, 6], [1, 2, 3, 4, 5, 6],
[1, 2, 3, 4, 5, 6]],
columns=columns, index=['S1', 'S2', 'S3'])
# No counts provided because no metadata
obs = _compute_summary(data, 'sample-id')
d = [['S1', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S1', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.],
['S2', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S2', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.],
['S3', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S3', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.]]
exp = pd.DataFrame(data=d, columns=['sample-id', 'depth', 'count',
'min', '2%', '9%', '25%', '50%',
'75%', '91%', '98%', 'max'])
pdt.assert_frame_equal(exp, obs)
def test_three_iterations_no_metadata(self):
columns = pd.MultiIndex.from_product([[1, 200], [1, 2, 3]],
names=['depth', 'iter'])
data = pd.DataFrame(data=[[1, 2, 3, 4, 5, 6], [1, 2, 3, 4, 5, 6],
[1, 2, 3, 4, 5, 6]],
columns=columns, index=['S1', 'S2', 'S3'])
# No counts provided because no metadata
obs = _compute_summary(data, 'sample-id')
d = [['S1', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S1', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.],
['S2', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S2', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.],
['S3', 1, 1, 1., 1.04, 1.18, 1.5, 2., 2.5, 2.82, 2.96, 3.],
['S3', 200, 1, 4., 4.04, 4.18, 4.5, 5., 5.5, 5.82, 5.96, 6.]]
exp = pd.DataFrame(data=d, columns=['sample-id', 'depth', 'count',
'min', '2%', '9%', '25%', '50%',
'75%', '91%', '98%', 'max'])
pdt.assert_frame_equal(exp, obs)
