def _get_alpha_info(alpha_metric, matching_ids, percentiles, sample_id):
alpha_repo = AlphaRepo()
# retrieve the alpha diversity for each sample
alpha_series = alpha_repo.get_alpha_diversity(
matching_ids,
alpha_metric,
)
alpha_ = Alpha(alpha_series, percentiles=percentiles)
alpha_summary = alpha_.get_group(name='').to_dict()
if sample_id:
sample_diversity, = alpha_repo.get_alpha_diversity(
sample_id, alpha_metric)
else:
sample_diversity = None
return alpha_summary, sample_diversity
def alpha_group(body,
alpha_metric,
summary_statistics=True,
percentiles=None,
return_raw=False):
if not (summary_statistics or return_raw):
# swagger does not account for parameter dependencies, so we should
# give a bad request error here
return jsonify(error=400,
text='Either `summary_statistics`, `return_raw`, '
'or both are required to be true.'), 400
sample_ids = body['sample_ids']
alpha_repo = AlphaRepo()
# figure out if the user asked for a metric we have data on
available_metrics = alpha_repo.available_metrics()
type_ = 'metric'
missing_metric = validate_resource(available_metrics, alpha_metric, type_)
if missing_metric:
return missing_metric
# make sure all of the data the samples the user asked for have values
# for the given metric
missing_ids = [
id_ for id_ in sample_ids if not alpha_repo.exists(id_, alpha_metric)
]
missing_ids_msg = check_missing_ids(missing_ids, alpha_metric, type_)
if missing_ids_msg:
return missing_ids_msg
# retrieve the alpha diversity for each sample
alpha_series = alpha_repo.get_alpha_diversity(
sample_ids,
alpha_metric,
)
alpha_ = Alpha(alpha_series, percentiles=percentiles)
alpha_data = dict()
if return_raw:
# not using name right now, so give it a placeholder name
alpha_values = alpha_.get_group_raw(name='').to_dict()
del alpha_values['name']
alpha_data.update(alpha_values)
if summary_statistics:
# not using name right now, so give it a placeholder name
alpha_summary = alpha_.get_group(name='').to_dict()
del alpha_summary['name']
alpha_data.update({'alpha_metric': alpha_summary.pop('alpha_metric')})
alpha_data.update({'group_summary': alpha_summary})
response = jsonify(alpha_data)
return response, 200
def get_alpha(sample_id, alpha_metric):
alpha_repo = AlphaRepo()
if not all(alpha_repo.exists([sample_id], alpha_metric)):
return jsonify(error=404, text="Sample ID not found."), \
404
alpha_series = alpha_repo.get_alpha_diversity([sample_id], alpha_metric)
alpha_ = Alpha(alpha_series)
alpha_data = alpha_.get_group_raw().to_dict()
ret_val = {
'sample_id': sample_id,
'alpha_metric': alpha_data['alpha_metric'],
'data': alpha_data['alpha_diversity'][sample_id],
}
return jsonify(ret_val), 200
class TestAlphaRepoWithResources(TempfileTestCase, ConfigTestCase):
def setUp(self):
ConfigTestCase.setUp(self)
TempfileTestCase.setUp(self)
self.no_resources_repo = AlphaRepo()
resource_filename1 = self.create_tempfile(suffix='.qza').name
resource_filename2 = self.create_tempfile(suffix='.qza').name
test_series1 = pd.Series({
'sample1': 7.15,
'sample2': 9.04
},
name='chao1')
test_series2 = pd.Series(
{
'sample3': 7.24,
'sample2': 9.04,
'sample4': 8.25
},
name='faith_pd')
imported_artifact = Artifact.import_data("SampleData[AlphaDiversity]",
test_series1)
imported_artifact.save(resource_filename1)
imported_artifact = Artifact.import_data("SampleData[AlphaDiversity]",
test_series2)
imported_artifact.save(resource_filename2)
config.resources.update({
'alpha_resources': {
'chao1': resource_filename1,
'faith_pd': resource_filename2,
}
})
resources.update(config.resources)
self.repo = AlphaRepo()
def tearDown(self):
TempfileTestCase.tearDown(self)
ConfigTestCase.tearDown(self)
def test_available_metrics(self):
exp = ['chao1', 'faith_pd']
obs = self.repo.available_metrics()
self.assertCountEqual(exp, obs)
def test_get_alpha_diversity(self):
# group tests
obs = self.repo.get_alpha_diversity(['sample2', 'sample1'], 'chao1')
exp_series = pd.Series([9.04, 7.15],
index=['sample2', 'sample1'],
name='chao1')
assert_series_equal(obs, exp_series)
def test_get_alpha_diversity_single_sample(self):
# single sample tests
obs = self.repo.get_alpha_diversity('sample2', 'chao1')
exp_series = pd.Series([9.04], index=['sample2'], name='chao1')
assert_series_equal(obs, exp_series)
def test_exists(self):
# group tests
sample_list = ['sample2', 'sample1', 'sample2', 'blah', 'sample4']
obs = self.repo.exists(sample_list, 'chao1')
exp = [True, True, True, False, False]
self.assertListEqual(obs, exp)
obs = self.repo.exists(sample_list, 'faith_pd')
exp = [True, False, True, False, True]
self.assertListEqual(obs, exp)
def test_exists_single_sample(self):
# single sample tests
obs = self.repo.exists('sample1', 'chao1')
self.assertTrue(obs)
obs = self.repo.exists('sample1', 'faith_pd')
self.assertFalse(obs)