def _neuroglancer_link(self):
options = Options.instance()
store_path = Path(options.runs_base_dir).expanduser()
viewer = neuroglancer.Viewer()
with viewer.txn() as s:
train_layers = {}
for i, dataset in enumerate(self.train):
train_layers.update(
dataset._neuroglancer_layers(
exclude_layers=set(train_layers.keys())))
validate_layers = {}
if self.validate is not None:
for i, dataset in enumerate(self.validate):
validate_layers.update(
dataset._neuroglancer_layers(
exclude_layers=set(validate_layers.keys())))
for layer_name, (layer, kwargs) in itertools.chain(
train_layers.items(), validate_layers.items()):
s.layers.append(
name=layer_name,
layer=layer,
**kwargs,
)
s.layout = neuroglancer.row_layout([
neuroglancer.LayerGroupViewer(
layers=list(train_layers.keys())),
neuroglancer.LayerGroupViewer(
layers=list(validate_layers.keys())),
])
return f"http://neuroglancer-demo.appspot.com/#!{json.dumps(viewer.state.to_json())}"
def create_array_store():
"""Create an array store based on the global DaCapo options."""
options = Options.instance()
# currently, only the LocalArrayStore is supported
base_dir = Path(options.runs_base_dir).expanduser()
return LocalArrayStore(base_dir)
def options(request, tmp_path):
# TODO: Clean up this fixture. Its a bit clunky to use.
# Maybe just write the dacapo.yaml file instead of assigning to Options._instance
kwargs_from_file = {}
if request.param == "mongo":
options_from_file = Options.instance()
kwargs_from_file.update({
"mongo_db_host": options_from_file.mongo_db_host,
"mongo_db_name": "dacapo_tests",
})
Options._instance = None
options = Options.instance(type=request.param,
runs_base_dir=f"{tmp_path}",
**kwargs_from_file)
yield options
if request.param == "mongo":
client = pymongo.MongoClient(host=options.mongo_db_host)
client.drop_database("dacapo_tests")
Options._instance = None
def mongo_db_available():
try:
options = Options.instance()
client = pymongo.MongoClient(host=options.mongo_db_host,
serverSelectionTimeoutMS=1000)
Options._instance = None
except RuntimeError:
# cannot find a dacapo config file, mongodb is not available
Options._instance = None
return False
try:
client.admin.command("ping")
return True
except pymongo.errors.ConnectionFailure:
return False
def create_stats_store():
"""Create a statistics store based on the global DaCapo options."""
options = Options.instance()
try:
store_type = options.type
except RuntimeError:
store_type = "mongo"
if store_type == "mongo":
db_host = options.mongo_db_host
db_name = options.mongo_db_name
return MongoStatsStore(db_host, db_name)
elif store_type == "files":
store_path = Path(options.runs_base_dir).expanduser()
return FileStatsStore(store_path / "stats")
def _neuroglancer_source(self):
source_type = "n5" if self.file_name.name.endswith(".n5") else "zarr"
options = Options.instance()
base_dir = Path(options.runs_base_dir).expanduser()
try:
relpath = self.file_name.relative_to(base_dir)
except ValueError:
relpath = str(self.file_name.absolute())
symlink_path = f"data_symlinks/{relpath}"
# Check if data is symlinked to a servable location
if not (base_dir / symlink_path).exists():
if not (base_dir / symlink_path).parent.exists():
(base_dir / symlink_path).parent.mkdir(parents=True)
(base_dir / symlink_path).symlink_to(Path(self.file_name))
dataset = self.dataset
parent_attributes_path = (base_dir / symlink_path /
self.dataset).parent / "attributes.json"
if parent_attributes_path.exists():
dataset_parent_attributes = json.loads(
open(
(base_dir / symlink_path / self.dataset).parent /
"attributes.json",
"r",
).read())
if "scales" in dataset_parent_attributes:
dataset = "/".join(self.dataset.split("/")[:-1])
file_server = options.file_server
try:
file_server = file_server.format(username=options.file_server_user,
password=options.file_server_pass)
except RuntimeError as e:
# if options doesn't have a file_server user or password simply continue
# without authentications
pass
source = {
"url": f"{source_type}://{file_server}/{symlink_path}/{dataset}",
"transform": {
"matrix": self._transform_matrix(),
"outputDimensions": self._output_dimensions(),
},
}
logger.warning(source)
return source