sc_neurocore_engine/bindings/
fitzhugh_rinzel.rs

1// SPDX-License-Identifier: AGPL-3.0-or-later
2// Commercial license available
3// © Concepts 1996–2026 Miroslav Šotek. All rights reserved.
4// © Code 2020–2026 Miroslav Šotek. All rights reserved.
5// ORCID: 0009-0009-3560-0851
6// Contact: www.anulum.li | protoscience@anulum.li
7// SC-NeuroCore — FitzHugh-Rinzel PyO3 binding
8
9//! Python binding for the FitzHugh-Rinzel three-timescale bursting model.
10
11use numpy::{IntoPyArray, PyArray1};
12use pyo3::prelude::*;
13use pyo3::types::PyDict;
14
15use crate::neurons::FitzHughRinzelNeuron;
16
17py_neuron_default!("FitzHughRinzelNeuron", PyFitzHughRinzelNeuron, FitzHughRinzelNeuron, state v, state w, state y);
18
19/// Register the FitzHugh-Rinzel class and batch simulator.
20pub(super) fn register(module: &Bound<'_, PyModule>) -> PyResult<()> {
21    module.add_class::<PyFitzHughRinzelNeuron>()?;
22    module.add_function(wrap_pyfunction!(py_fitzhugh_rinzel_simulate, module)?)?;
23    Ok(())
24}
25
26/// Parity contract with
27/// `sc_neurocore.neurons.models.fitzhugh_rinzel.FitzHughRinzelNeuron.simulate`:
28/// for the same parameters and constant input the returned `v` trace, upward-
29/// crossing spike count, and final `(v, w, y)` state are bit-identical to the
30/// Python RK4 reference (the right-hand side is exact arithmetic — `v.powi(3)`
31/// = `v*v*v`, additions and multiplications, no transcendental functions).
32#[pyfunction]
33#[pyo3(signature = (v0, w0, y0, a, b, c, d, delta, mu, dt, v_threshold, n_steps, current))]
34#[allow(clippy::too_many_arguments)]
35fn py_fitzhugh_rinzel_simulate<'py>(
36    py: Python<'py>,
37    v0: f64,
38    w0: f64,
39    y0: f64,
40    a: f64,
41    b: f64,
42    c: f64,
43    d: f64,
44    delta: f64,
45    mu: f64,
46    dt: f64,
47    v_threshold: f64,
48    n_steps: usize,
49    current: f64,
50) -> (Bound<'py, PyArray1<f64>>, i64, f64, f64, f64) {
51    let mut neuron = FitzHughRinzelNeuron {
52        v: v0,
53        w: w0,
54        y: y0,
55        a,
56        b,
57        c,
58        d,
59        delta,
60        mu,
61        dt,
62        v_threshold,
63    };
64    let (trace, spikes) = neuron.simulate(n_steps, current);
65    (trace.into_pyarray(py), spikes, neuron.v, neuron.w, neuron.y)
66}
sc_neurocore_engine/bindings/fitzhugh_rinzel.rs

sc_neurocore_engine/bindings/
fitzhugh_rinzel.rs
