def test_check_object_field_error(self):
er = ExternalResources('terms')
data = Data(name="species", data=['H**o sapiens', 'Mus musculus'])
er._check_object_field(data, '')
er._add_object(data, '', '')
with self.assertRaises(ValueError):
er._check_object_field(data, '')
def test_piecewise_add(self):
er = ExternalResources('terms')
# this is the term the user wants to use. They will need to specify this
key = er._add_key('mouse')
resource1 = er._add_resource(resource='resource0', uri='resource_uri0')
# the user will have to supply this info as well. This is the information
# needed to retrieve info about the controled term
er._add_entity(key, resource1, '10090', 'uri')
# The user can also pass in the container or it can be wrapped up under NWBFILE
obj = er._add_object('object', 'species')
# This could also be wrapped up under NWBFile
er._add_object_key(obj, key)
self.assertEqual(er.keys.data, [('mouse', )])
self.assertEqual(er.entities.data, [(0, 0, '10090', 'uri')])
self.assertEqual(er.objects.data, [('object', 'species')])
def test_to_dataframe(self):
# Setup complex external resources with keys reused across objects and
# multiple resources per key
er = ExternalResources(name='example')
# Add a species dataset with 2 keys
data1 = Data(name='data_name',
data=np.array([('Mus musculus', 9, 81.0),
('H**o sapiens', 3, 27.0)],
dtype=[('species', 'U14'), ('age', 'i4'),
('weight', 'f4')]))
k1, r1, e1 = er.add_ref(
container=data1,
field='species',
key='Mus musculus',
resource_name='NCBI_Taxonomy',
resource_uri='https://www.ncbi.nlm.nih.gov/taxonomy',
entity_id='NCBI:txid10090',
entity_uri=
'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=10090'
)
k2, r2, e2 = er.add_ref(
container=data1,
field='species',
key='H**o sapiens',
resource_name='NCBI_Taxonomy',
resource_uri='https://www.ncbi.nlm.nih.gov/taxonomy',
entity_id='NCBI:txid9606',
entity_uri=
'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9606')
# Add a second species dataset that uses the same keys as the first dataset and add an additional key
data2 = Data(name="species",
data=['H**o sapiens', 'Mus musculus', 'Pongo abelii'])
o2 = er._add_object(data2, relative_path='', field='')
er._add_object_key(o2, k1)
er._add_object_key(o2, k2)
k2, r2, e2 = er.add_ref(
container=data2,
field='',
key='Pongo abelii',
resource_name='NCBI_Taxonomy',
resource_uri='https://www.ncbi.nlm.nih.gov/taxonomy',
entity_id='NCBI:txid9601',
entity_uri=
'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9601')
# Add a third data object, this time with 2 entities for a key
data3 = Data(name="genotypes", data=['Rorb'])
k3, r3, e3 = er.add_ref(
container=data3,
field='',
key='Rorb',
resource_name='MGI Database',
resource_uri='http://www.informatics.jax.org/',
entity_id='MGI:1346434',
entity_uri='http://www.informatics.jax.org/marker/MGI:1343464')
_ = er.add_ref(
container=data3,
field='',
key=k3,
resource_name='Ensembl',
resource_uri='https://uswest.ensembl.org/index.html',
entity_id='ENSG00000198963',
entity_uri=
'https://uswest.ensembl.org/Homo_sapiens/Gene/Summary?db=core;g=ENSG00000198963'
)
# Convert to dataframe and compare against the expected result
result_df = er.to_dataframe()
expected_df_data = \
{'objects_idx': {0: 0, 1: 0, 2: 1, 3: 1, 4: 1, 5: 2, 6: 2},
'object_id': {0: data1.object_id, 1: data1.object_id,
2: data2.object_id, 3: data2.object_id, 4: data2.object_id,
5: data3.object_id, 6: data3.object_id},
'field': {0: 'species', 1: 'species', 2: '', 3: '', 4: '', 5: '', 6: ''},
'keys_idx': {0: 0, 1: 1, 2: 0, 3: 1, 4: 2, 5: 3, 6: 3},
'key': {0: 'Mus musculus', 1: 'H**o sapiens', 2: 'Mus musculus', 3: 'H**o sapiens',
4: 'Pongo abelii', 5: 'Rorb', 6: 'Rorb'},
'resources_idx': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 1, 6: 2},
'resource': {0: 'NCBI_Taxonomy', 1: 'NCBI_Taxonomy', 2: 'NCBI_Taxonomy', 3: 'NCBI_Taxonomy',
4: 'NCBI_Taxonomy', 5: 'MGI Database', 6: 'Ensembl'},
'resource_uri': {0: 'https://www.ncbi.nlm.nih.gov/taxonomy', 1: 'https://www.ncbi.nlm.nih.gov/taxonomy',
2: 'https://www.ncbi.nlm.nih.gov/taxonomy', 3: 'https://www.ncbi.nlm.nih.gov/taxonomy',
4: 'https://www.ncbi.nlm.nih.gov/taxonomy', 5: 'http://www.informatics.jax.org/',
6: 'https://uswest.ensembl.org/index.html'},
'entities_idx': {0: 0, 1: 1, 2: 0, 3: 1, 4: 2, 5: 3, 6: 4},
'entity_id': {0: 'NCBI:txid10090', 1: 'NCBI:txid9606', 2: 'NCBI:txid10090', 3: 'NCBI:txid9606',
4: 'NCBI:txid9601', 5: 'MGI:1346434', 6: 'ENSG00000198963'},
'entity_uri': {0: 'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=10090',
1: 'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9606',
2: 'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=10090',
3: 'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9606',
4: 'https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=9601',
5: 'http://www.informatics.jax.org/marker/MGI:1343464',
6: 'https://uswest.ensembl.org/Homo_sapiens/Gene/Summary?db=core;g=ENSG00000198963'}}
expected_df = pd.DataFrame.from_dict(expected_df_data)
pd.testing.assert_frame_equal(result_df, expected_df)
# Convert to dataframe with categories and compare against the expected result
result_df = er.to_dataframe(use_categories=True)
cols_with_categories = [('objects', 'objects_idx'),
('objects', 'object_id'), ('objects', 'field'),
('keys', 'keys_idx'), ('keys', 'key'),
('resources', 'resources_idx'),
('resources', 'resource'),
('resources', 'resource_uri'),
('entities', 'entities_idx'),
('entities', 'entity_id'),
('entities', 'entity_uri')]
expected_df_data = {
c: expected_df_data[c[1]]
for c in cols_with_categories
}
expected_df = pd.DataFrame.from_dict(expected_df_data)
pd.testing.assert_frame_equal(result_df, expected_df)