def test_bad_filter(self):
bad_annotation_type = ImmutableMultiDict([("obs:tissue", "lung")])
with self.assertRaises(QueryStringError):
parse_filter(bad_annotation_type, self.schema)
bad_axis = ImmutableMultiDict([("xyz:n_genes", "100,1000")])
with self.assertRaises(QueryStringError):
parse_filter(bad_axis, self.schema)
def get(self):
accept_type = request.args.get("accept-type", None)
# request.args is immutable
args = request.args.copy()
args.pop("accept-type", None)
try:
filter_ = parse_filter(ImmutableMultiDict(args), current_app.data.schema["annotations"])
except QueryStringError as e:
return make_response(e.message, HTTPStatus.BAD_REQUEST)
# TODO support CSV
try:
# TODO store mime_type when more than one is supported
get_mime_type(
acceptable_types=["application/json"], query_param=accept_type, header=request.accept_mimetypes
)
except MimeTypeError as e:
return make_response(e.message, HTTPStatus.NOT_ACCEPTABLE)
try:
return make_response((jsonify(current_app.data.data_frame(filter_, axis=Axis.OBS))), HTTPStatus.OK)
except FilterError as e:
return make_response(e.message, HTTPStatus.BAD_REQUEST)
except ValueError as e:
# JSON encoding failure, usually due to bad data
warnings.warn(JSON_NaN_to_num_warning_msg)
return make_response(str(e), HTTPStatus.INTERNAL_SERVER_ERROR)
def test_boolean_filter(self):
schema = {"obs": [{"name": "bool_filter", "type": "boolean"}]}
filter_dict = ImmutableMultiDict([("obs:bool_filter", "false")])
filter_ = parse_filter(filter_dict, schema)
self.assertIn("obs", filter_)
self.assertEqual(filter_["obs"]["annotation_value"], [{
"name": "bool_filter",
"values": [False]
}])
def test_filter_contiunous(self):
filterMock = MagicMock()
filterMock.__iter__.return_value = iter(["n_genes"])
filterMock.getlist.return_value = ["0,100"]
query = parse_filter(filterMock, self.schema)
assert query == {
"n_genes": {
"variable_type": "continuous",
"value_type": "int",
"query": {
"min": 0,
"max": 100
}
}
}
filterMock.__iter__.return_value = iter(["n_genes"])
filterMock.getlist.return_value = ["*,100"]
query = parse_filter(filterMock, self.schema)
assert query == {
"n_genes": {
"variable_type": "continuous",
"value_type": "int",
"query": {
"min": None,
"max": 100
}
}
}
filterMock.__iter__.return_value = iter(["n_genes"])
filterMock.getlist.return_value = ["0,*"]
query = parse_filter(filterMock, self.schema)
assert query == {
"n_genes": {
"variable_type": "continuous",
"value_type": "int",
"query": {
"min": 0,
"max": None
}
}
}
def test_filter_categorical(self):
filterMock = MagicMock()
filterMock.__iter__.return_value = iter(["louvain"])
filterMock.getlist.return_value = ["B cells", "T cells"]
query = parse_filter(filterMock, self.schema)
assert query == {
"louvain": {
"variable_type": "categorical",
"value_type": "string",
"query": ["B cells", "T cells"]
}
}
filterMock.__iter__.return_value = iter(["cluster"])
filterMock.getlist.return_value = ["1", "2"]
query = parse_filter(filterMock, self.schema)
assert query == {
"cluster": {
"variable_type": "categorical",
"value_type": "int",
"query": [1, 2]
}
}
def get(self):
payload = {
"metadata": [],
"cellcount": 0,
"graph": [],
"ranges": {},
}
# get query params
cells_filter = parse_filter(request.args, current_app.data.schema)
filtered_data = current_app.data.filter_cells(cells_filter)
payload["metadata"] = current_app.data.metadata(filtered_data)
payload["ranges"] = current_app.data.metadata_ranges(filtered_data)
payload["graph"] = current_app.data.create_graph(filtered_data)
payload["cellcount"] = current_app.data.cell_count
return make_payload(payload)
def test_complex_filter(self):
filter_dict = ImmutableMultiDict([("obs:louvain", "NK cells"),
("obs:louvain", "CD8 T cells"),
("obs:n_counts", "3000,*")])
filter_ = parse_filter(filter_dict, self.schema)
self.assertIn("obs", filter_)
self.assertEqual(
filter_["obs"]["annotation_value"],
[
{
"name": "louvain",
"values": ["NK cells", "CD8 T cells"]
},
{
"name": "n_counts",
"max": None,
"min": 3000.0
},
],
)