sc_neurocore_engine/bindings/
hindmarsh_rose.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 — Hindmarsh-Rose PyO3 binding
8
9//! Python binding for the Hindmarsh-Rose three-state bursting model.
10
11use numpy::{IntoPyArray, PyArray1};
12use pyo3::prelude::*;
13use pyo3::types::PyDict;
14
15use crate::neurons::HindmarshRoseNeuron;
16
17py_neuron_default!("HindmarshRoseNeuron", PyHindmarshRoseNeuron, HindmarshRoseNeuron, state x, state y, state z);
18
19/// Register the Hindmarsh-Rose class and batch simulator.
20pub(super) fn register(module: &Bound<'_, PyModule>) -> PyResult<()> {
21    module.add_class::<PyHindmarshRoseNeuron>()?;
22    module.add_function(wrap_pyfunction!(py_hindmarsh_rose_simulate, module)?)?;
23    Ok(())
24}
25
26/// Parity contract with
27/// `sc_neurocore.neurons.models.hindmarsh_rose.HindmarshRoseNeuron.simulate`:
28/// for the same parameters and constant input the returned `x` trace, upward-
29/// crossing spike count, and final `(x, y, z)` state are bit-identical to the
30/// Python RK4 reference (the right-hand side is exact arithmetic — `x.powi(3)`
31/// = `x*x*x`, `x.powi(2)` = `x*x`, no transcendental functions — so even the
32/// chaotic bursting trace reproduces exactly).
33#[pyfunction]
34#[pyo3(signature = (x0, y0, z0, b, r, s, x_rest, dt, x_threshold, n_steps, current))]
35#[allow(clippy::too_many_arguments)]
36fn py_hindmarsh_rose_simulate<'py>(
37    py: Python<'py>,
38    x0: f64,
39    y0: f64,
40    z0: f64,
41    b: f64,
42    r: f64,
43    s: f64,
44    x_rest: f64,
45    dt: f64,
46    x_threshold: f64,
47    n_steps: usize,
48    current: f64,
49) -> (Bound<'py, PyArray1<f64>>, i64, f64, f64, f64) {
50    let mut neuron = HindmarshRoseNeuron {
51        x: x0,
52        y: y0,
53        z: z0,
54        b,
55        r,
56        s,
57        x_rest,
58        dt,
59        x_threshold,
60    };
61    let (trace, spikes) = neuron.simulate(n_steps, current);
62    (trace.into_pyarray(py), spikes, neuron.x, neuron.y, neuron.z)
63}
sc_neurocore_engine/bindings/hindmarsh_rose.rs

sc_neurocore_engine/bindings/
hindmarsh_rose.rs
