def test_get_from_uri_kgquery_simple(self, kg_client): # TODO: UPDATE STORED QUERY
uri = "https://nexus.humanbrainproject.org/v0/data/neuralactivity/experiment/patchedcell/v0.1.0/b813a2f7-5e87-4827-81cd-0008da041648"
cell = PatchedCell.from_uri(uri, kg_client, api="query", resolved=False)
assert isinstance(cell, PatchedCell)
assert cell.brain_location == [BrainRegion('5th cerebellar lobule'),
BrainRegion('6th cerebellar lobule'),
BrainRegion('7th cerebellar lobule'),
BrainRegion('8th cerebellar lobule')]
assert isinstance(cell.collection, KGQuery)
assert isinstance(cell.experiments, KGQuery)
def test_get_from_uri_nexus(self, kg_client):
uri = "https://nexus.humanbrainproject.org/v0/data/neuralactivity/experiment/patchedcell/v0.1.0/5ab24291-8dca-4a45-a484-8a8c28d396e2"
cell = PatchedCell.from_uri(uri, kg_client, api="nexus")
assert isinstance(cell, PatchedCell)
assert cell.id == uri
assert cell.brain_location == [BrainRegion('lobule 5 of the cerebellar vermis'),
BrainRegion('lobule 6 of the cerebellar vermis'),
BrainRegion('lobule 7 of the cerebellar vermis'),
BrainRegion('lobule 8 of the cerebellar vermis')]
assert isinstance(cell.collection, KGQuery)
assert isinstance(cell.experiments, KGQuery)
def get_parameters(self, parameter_type, parameter_value):
parameter = None
if parameter_type == 'species':
if parameter_value not in (None, '', "Undefined", "Other"):
parameter = Species(parameter_value, strict=True)
if parameter_type == 'brain_region':
if parameter_value not in (None, '', 'other'):
parameter = BrainRegion(parameter_value, strict=True)
if parameter_type == 'cell_type':
if parameter_value not in (None, '', 'other'):
parameter = CellType(parameter_value, strict=True)
if parameter_type == "abstraction_level":
if parameter_value not in (None, '', "other"):
parameter = AbstractionLevel(parameter_value, strict=True)
if parameter_type == "model_scope":
if parameter_value not in (None, '', 'other'):
parameter = ModelScope(parameter_value, strict=True)
if parameter_type == "age":
parameter = None # temporary
return parameter
def test_repr(self):
try:
unicode
except NameError:
cell = PatchedCell("example001",
brain_location=BrainRegion("primary auditory cortex"),
collection=None,
cell_type=CellType("pyramidal cell"),
experiments=None,
pipette_id=31,
seal_resistance=QuantitativeValue(1.2, "GΩ"),
pipette_resistance=QuantitativeValue(1.5, "MΩ"),
liquid_junction_potential=None,
labeling_compound="0.1% biocytin ",
reversal_potential_cl=None)
expected_repr = ("PatchedCell(name='example001', "
"brain_location=BrainRegion('primary auditory cortex', 'http://purl.obolibrary.org/obo/UBERON_0034751'), "
"cell_type=CellType('pyramidal cell', 'http://purl.obolibrary.org/obo/CL_0000598'), "
"pipette_id=31, seal_resistance=QuantitativeValue(1.2 'GΩ'), "
"pipette_resistance=QuantitativeValue(1.5 'MΩ'), "
"labeling_compound='0.1% biocytin ', id=None)")
assert repr(cell) == expected_repr
else:
pytest.skip(
"The remaining lifespan of Python 2 is too short to fix unicode representation errors")
def test_list_nexus(self, kg_client):
cells = PatchedCell.list(kg_client, api="nexus", size=50)
assert len(cells) == 30
assert cells[0].brain_location == BrainRegion("hippocampus CA1")
assert isinstance(cells[0].collection, KGQuery)
assert cells[0].cell_type == CellType("hippocampus CA1 pyramidal cell")
assert isinstance(cells[0].experiments, KGQuery)
assert cells[0].pipette_id is None
assert cells[0].seal_resistance is None
assert cells[0].pipette_resistance is None
assert cells[0].liquid_junction_potential is None
assert cells[0].labeling_compound is None
assert cells[0].reversal_potential_cl == QuantitativeValue(-16.0, unit_text="mV")
def test_round_trip(self, kg_client):
cell1 = PatchedCell("example001",
brain_location=BrainRegion("primary auditory cortex"),
collection=None,
cell_type=CellType("pyramidal cell"),
experiments=None,
pipette_id=31,
seal_resistance=QuantitativeValue(1.2, "GΩ"),
pipette_resistance=QuantitativeValue(1.5, "MΩ"),
liquid_junction_potential=QuantitativeValue(5.0, "mV"),
labeling_compound="0.1% biocytin ",
reversal_potential_cl=QuantitativeValue(-65, "mV"))
instance = Instance(PatchedCell.path, cell1._build_data(kg_client), Instance.path)
instance.data["@id"] = "http://fake_uuid_93f9cd9a9b"
instance.data["@type"] = PatchedCell.type
cell2 = PatchedCell.from_kg_instance(instance, kg_client)
for field in ("name", "brain_location", "cell_type",
"pipette_id", "seal_resistance", "pipette_resistance",
"liquid_junction_potential", "labeling_compound",
"reversal_potential_cl"):
assert getattr(cell1, field) == getattr(cell2, field)
def test_repr(self):
cell = PatchedCell(
"example001",
brain_location=BrainRegion("primary auditory cortex"),
collection=None,
cell_type=CellType("pyramidal cell"),
experiments=None,
pipette_id=31,
seal_resistance=QuantitativeValue(1.2, "GΩ"),
pipette_resistance=QuantitativeValue(1.5, "MΩ"),
liquid_junction_potential=None,
labeling_compound="0.1% biocytin ",
reversal_potential_cl=None)
expected_repr = (
"PatchedCell(name='example001', "
"brain_location=BrainRegion('primary auditory cortex', 'http://uri.interlex.org/ilx_0443027'), "
"cell_type=CellType('pyramidal cell', 'http://uri.interlex.org/ilx_0107385'), "
"pipette_id=31, seal_resistance=QuantitativeValue(1.2 'GΩ'), "
"pipette_resistance=QuantitativeValue(1.5 'MΩ'), "
"labeling_compound='0.1% biocytin ', id=None)")
assert repr(cell) == expected_repr
def test_list_with_filter(self, kg_client):
cells = PatchedCell.list(kg_client, api="nexus", brain_region=BrainRegion("hippocampus CA1"), size=50)
assert len(cells) == 26
def test_all():
## Search based on brain region
cells_in_ca1 = PatchedCell.list(
client, brain_region=BrainRegion("hippocampus CA1"))
pprint([cell.brain_location for cell in cells_in_ca1])
### Download the recorded data for one of these cells
example_cell = cells_in_ca1[3]
experiment = example_cell.experiments.resolve(client)
trace = experiment.traces.resolve(client)
print(trace.time_step)
print(trace.data_unit)
download_url = trace.data_location.location
print(download_url)
data = np.genfromtxt(BytesIO(requests.get(download_url).content))
### Plot the data
times = data[:, 0]
signals = data[:, 1:]
# plot the first 100 signals
plt.figure(figsize=(18, 16), dpi=80, facecolor='w', edgecolor='k')
xlim = (times.min(), times.max())
for i in range(1, 101):
plt.subplot(10, 10, i)
plt.plot(times, data[:, i], 'grey')
plt.xlim(*xlim)
plt.axis('off')
## Search based on species
cells_from_mouse = PatchedCell.list(client,
species=Species("Mus musculus"))
for cell in cells_from_mouse[:10]:
pprint(
cell.collection.resolve(client).slice.resolve(
client).slice.resolve(client).subject.resolve(client).species)
## Search based on cell type
pyramidal_neurons = PatchedCell.list(
client, cell_type=CellType("hippocampus CA1 pyramidal cell"))
pprint([pn.cell_type for pn in pyramidal_neurons[:10]])
# An activity dataset with minimal metadata
Dataset.set_strict_mode(False)
query = {
"path":
"minds:specimen_group / minds:subjects / minds:samples / minds:methods / schema:name",
"op":
"in",
"value": [
"Electrophysiology recording", "Voltage clamp recording",
"Single electrode recording",
"functional magnetic resonance imaging"
]
}
context = {
"schema": "http://schema.org/",
"minds": "https://schema.hbp.eu/minds/"
}
activity_datasets = KGQuery(Dataset, query, context).resolve(client)
for dataset in activity_datasets:
print("* " + getattr(dataset, "name", "unknown"))
dataset = activity_datasets[-1]
#dataset.owners[0].resolve(client)
#dataset.license.resolve(client)
## An activity dataset with extended metadata
dataset = client.by_name(
Dataset,
"sIPSCs from juvenile (P21-30) C57Bl6/J male mice from CA1 pyramidal neurons receiving input from PV+ interneurons"
)
query = {"path": "nsg:partOf", "op": "eq", "value": dataset.id}
context = {
"nsg":
"https://bbp-nexus.epfl.ch/vocabs/bbp/neurosciencegraph/core/v0.1.0/"
}
traces = KGQuery(Trace, query, context).resolve(client)
print(traces)
tr0 = traces[0]
print(tr0.name)
print(tr0.channel)
print(tr0.time_step)
print(tr0.data_unit)
print(tr0.data_location)
experiment = tr0.generated_by.resolve(client)
print(experiment.name)
cell = experiment.recorded_cell.resolve(client)
print(cell.brain_location)
print(cell.cell_type)
print(cell.reversal_potential_cl)