circuit-rs 0.3.0

A library for doing efficient operations on neural circuits

rusted_circuits

Exposing useful operations to manipulate the neural circuits that can be derived from Flywire, a project which maps out the Drosophila brain.

In my research, I found myself repeatedly needing to find a minimal circuit (connectivity-wise) that contains the smallest subcircuit containing all paths between a set of source and sink neurons (nodes, whatever). The python code I used was too slow, even considering various biological priors (e.g. I think it's possible to traverse from most neurons to almost any other within 5 jumps, and if you can't then it's probably not possible).

Written in Rust, exposed in Python.

Design

We support two main "modes", where the user passes in edge information as a list of tuples [(pre_1, post_1, pre_1, post_2, ...)] and as a np.ndarray of 2 dimensions. Under the hood, both use the same code, but there is a shim layer as rust doesn't have function overloads.

Example

Smallest Subcircuit

Here is a simple working example, where we have a linear path from source (1) to sink (5)

edge_list = np.asarray([(1, 2), (2, 3), (3, 4), (4, 5)])
sources = {1}
sinks = {5}
max_depth = 10
max_paths = 100

# The nid_to_cidx_map is optional, and if it is not specified, we derive the mapping of the neuron-id-to-connectivity-matrix-index.
nid_to_cidx_map = {1: 10, 2: 20, 3: 30, 4: 40, 5: 50}

# Expected: all nodes on the path from source to sink
expected = {10, 20, 30, 40, 50}
actual_np = isolate_subcircuit_np_edgelist(edge_list, sources, sinks, max_depth, max_paths, nid_to_cidx_map)

# -OR-, from a list
actual_list = isolate_subcircuit(edge_list.tolist(), sources, sinks, max_depth, max_paths, nid_to_cidx_map)

Maintainers

1. Add whatever code using git add ...

2. Add a commit message e.g. git commit -m '...'

Note: replace VERSION_NUMBER below by an actual version number e.g. v0.1.0

3. git tag $VERSION_NUMBER

4. git push origin $VERSION_NUMBER