def __setitem__(self, key, spec):
assert isinstance(key, ArrayKey) or isinstance(key, GraphKey), \
f"Only ArrayKey or GraphKey (not {type(key).__name__} are " \
"allowed as key for ProviderSpec, "
if isinstance(key, ArrayKey):
if isinstance(spec, Roi):
spec = ArraySpec(roi=spec)
assert isinstance(spec, ArraySpec), \
f"Only ArraySpec (not {type(spec).__name__}) can be set for " \
"ArrayKey"
self.array_specs[key] = spec.copy()
else:
if isinstance(spec, Roi):
spec = GraphSpec(roi=spec)
assert isinstance(spec, GraphSpec), \
f"Only GraphSpec (not {type(spec).__name__}) can be set for " \
"GraphKey"
self.graph_specs[key] = spec.copy()
class DaCapoArraySource(gp.BatchProvider):
"""A DaCapo Array source node
Args:
Array (Array):
The DaCapo Array to pull data from
key (``gp.ArrayKey``):
The key to provide data into
"""
def __init__(self, array: Array, key: gp.ArrayKey):
self.array = array
self.array_spec = ArraySpec(roi=self.array.roi,
voxel_size=self.array.voxel_size)
self.key = key
def setup(self):
self.provides(self.key, self.array_spec.copy())
def provide(self, request):
output = gp.Batch()
timing_provide = Timing(self, "provide")
timing_provide.start()
spec = self.array_spec.copy()
spec.roi = request[self.key].roi
data = self.array[spec.roi]
if "c" not in self.array.axes:
# add a channel dimension
data = np.expand_dims(data, 0)
if np.any(np.isnan(data)):
raise ValueError("INPUT DATA CAN'T BE NAN")
output[self.key] = gp.Array(data, spec=spec)
timing_provide.stop()
output.profiling_stats.add(timing_provide)
return output
