def test_alpha_diversity_group_unknown_metric(self):
with patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['metric-a', 'metric-b']
metric = 'observed_otus'
with self.assertRaises(UnknownResource):
alpha_group(self.post_body,
alpha_metric=metric,
summary_statistics=False,
return_raw=True)
def test_alpha_diversity_group_unknown_sample(self):
# One ID not found (out of two)
with patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.side_effect = [True, False]
with self.assertRaises(UnknownID):
alpha_group(self.post_body, 'observed_otus')
# Multiple IDs do not exist
with patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.side_effect = [False, False]
with self.assertRaises(UnknownID):
alpha_group(self.post_body, 'observed_otus')
def test_alpha_diversity_group_return_summary_only(self):
with patch.object(AlphaRepo, 'get_alpha_diversity') as mock_method, \
patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.return_value = [True, True]
mock_method.return_value = pd.Series(
{
'sample-foo-bar': 7,
'sample-baz-bat': 9.5,
'sample-qux-quux': 7.5,
'sample-4': 8,
},
name='observed_otus')
metric = 'observed_otus'
response, code = alpha_group(
body={
'sample_ids': [
'sample-foo-bar',
'sample-baz-bat',
'sample-qux-quux',
'sample-4',
]
},
alpha_metric=metric,
summary_statistics=True,
percentiles=[100, 0, 50, 20],
return_raw=False,
)
exp = {
'alpha_metric': 'observed_otus',
'group_summary': {
'mean': 8,
'median': 7.75,
'std': sqrt(0.875),
'group_size': 4,
'percentile': [100, 0, 50, 20],
'percentile_values': [9.5, 7, 7.75, 7.3]
}
}
self.assertEqual(code, 200)
obs = json.loads(response.data)
self.assertCountEqual(exp.keys(), obs.keys())
self.assertCountEqual(exp['alpha_metric'], obs['alpha_metric'])
self.assertCountEqual(exp['group_summary'].keys(),
obs['group_summary'].keys())
gs_exp = exp['group_summary']
gs_obs = obs['group_summary']
npt.assert_array_almost_equal(gs_exp.pop('percentile'),
gs_obs.pop('percentile'))
npt.assert_array_almost_equal(gs_exp.pop('percentile_values'),
gs_obs.pop('percentile_values'))
# checks of the numerical parts of the expected and observed are
# almost the same
pdt.assert_series_equal(pd.Series(gs_exp),
pd.Series(gs_obs),
check_exact=False)
def test_alpha_diversity_group_return_raw_only_metadata_query_only(self):
post_body = {
'metadata_query': {
'some query': 'value'
},
}
with patch.object(AlphaRepo, 'get_alpha_diversity') as mock_method, \
patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo,
'available_metrics') as mock_metrics, \
patch.object(MetadataRepo,
'sample_id_matches') as mock_matches:
mock_metrics.return_value = ['observed_otus']
# first two values are used on checking requested ids, the other
# two are used for checking ids that match metadata query
mock_exists.side_effect = [True, True, True, True]
mock_method.return_value = pd.Series(
{
'sample-foo-bar': 8.25,
'sample-baz-bat': 9.01
},
name='observed_otus')
mock_matches.return_value = ['sample-foo-bar', 'sample-4']
metric = 'observed_otus'
response, code = alpha_group(post_body,
alpha_metric=metric,
summary_statistics=False,
return_raw=True)
self.assertEqual(code, 200)
args, kwargs = mock_method.call_args
self.assertCountEqual(args[0], ['sample-foo-bar', 'sample-4'])
def test_alpha_diversity_group_return_raw_only(self):
with patch.object(AlphaRepo, 'get_alpha_diversity') as mock_method, \
patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.return_value = [True, True]
mock_method.return_value = pd.Series(
{
'sample-foo-bar': 8.25,
'sample-baz-bat': 9.01
},
name='observed_otus')
metric = 'observed_otus'
response, code = alpha_group(self.post_body,
alpha_metric=metric,
summary_statistics=False,
return_raw=True)
exp = {
'alpha_metric': 'observed_otus',
'alpha_diversity': {
'sample-foo-bar': 8.25,
'sample-baz-bat': 9.01,
}
}
obs = json.loads(response.data)
self.assertDictEqual(exp, obs)
self.assertEqual(code, 200)
def test_alpha_diversity_improper_parameters(self):
with patch.object(AlphaRepo, 'get_alpha_diversity') as mock_method, \
patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.return_value = [True, True]
mock_method.return_value = pd.Series(
{
'sample-foo-bar': 8.25,
'sample-baz-bat': 9.01
},
name='observed_otus')
metric = 'observed_otus'
with self.assertRaises(IncompatibleOptions):
alpha_group(self.post_body,
alpha_metric=metric,
summary_statistics=False,
return_raw=False)
def test_alpha_diversity_group_percentiles_none(self):
with patch.object(AlphaRepo, 'get_alpha_diversity') as mock_method, \
patch.object(AlphaRepo, 'exists') as mock_exists, \
patch.object(AlphaRepo, 'available_metrics') as mock_metrics:
mock_metrics.return_value = ['observed_otus']
mock_exists.return_value = [True, True]
mock_method.return_value = pd.Series(
{
'sample-foo-bar': 7,
'sample-baz-bat': 9.5,
'sample-qux-quux': 7.5,
'sample-4': 8,
},
name='observed_otus')
metric = 'observed_otus'
response, code = alpha_group(
body={
'sample_ids': [
'sample-foo-bar',
'sample-baz-bat',
'sample-qux-quux',
'sample-4',
]
},
alpha_metric=metric,
summary_statistics=True,
percentiles=None,
return_raw=False,
)
self.assertEqual(code, 200)
obs = json.loads(response.data)
self.assertIn('group_summary', obs)
summary = obs['group_summary']
self.assertIn('percentile', summary)
perc = summary['percentile']
# check default value of percentiles is returned
npt.assert_array_almost_equal(perc, list(range(10, 91, 10)))