fafbseg.flywire.get_l2_dotprops¶
- fafbseg.flywire.get_l2_dotprops(root_ids, min_size=None, sample=False, omit_failures=None, progress=True, max_threads=10, *, dataset=None, **kwargs)[source]¶
Generate dotprops from L2 chunks.
L2 chunks not present in the L2 cache or without a pca attribute (happens for very small chunks) are silently ignored.
- Parameters:
root_ids (int | list of ints | NeuronCriteria) – Root ID(s) of the FlyWire neuron(s) you want to dotprops for.
min_size (int, optional) – Minimum size (in nm^3) for the L2 chunks. Smaller chunks will be ignored. This is useful to de-emphasise the finer terminal neurites which typically break into more, smaller chunks and are hence overrepresented. A good value appears to be around 1_000_000.
sample (float [0 > 1], optional) – If float, will create Dotprops based on a fractional sample of the L2 chunks. The sampling is random but deterministic.
omit_failures (bool, optional) –
Determine behaviour when dotprops generation fails (i.e. if the neuron has no L2 info):
None
(default) will raise an exceptionTrue
will skip the offending neuron (might result
in an empty
NeuronList
) -False
will return an emptyDotprops
progress (bool) – Whether to show a progress bar.
max_threads (int) – Number of parallel requests to make when fetching the L2 IDs (but not the L2 info).
dataset ("public" | "production" | "sandbox" | "flat_630", optional) – Against which FlyWire dataset to query. If
None
will fall back to the default dataset (seeset_default_dataset()
).**kwargs – Keyword arguments are passed through to the Dotprops initialization. Use to e.g. set extra properties.
- Returns:
dps – List of Dotprops.
- Return type:
navis.NeuronList
See also
fafbseg.flywire.get_l2_skeleton()
Fetch skeletons instead of dotprops using the L2 edges to infer connectivity.
fafbseg.flywire.skeletonize_neuron()
Skeletonize the full resolution mesh.
Examples
>>> from fafbseg import flywire >>> n = flywire.get_l2_dotprops(720575940614131061)