sc_neurocore_engine/bindings/
matrix_inputs.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 — PyO3 matrix-input conversion
8
9//! Shared matrix parsing and row reshaping for Python learning and solver bindings.
10
11use pyo3::exceptions::PyValueError;
12use pyo3::prelude::*;
13
14pub(crate) fn extract_matrix_f64(
15    data: &Bound<'_, PyAny>,
16    name: &str,
17) -> PyResult<(Vec<f64>, usize, usize)> {
18    if let Ok(rows) = data.extract::<Vec<Vec<f64>>>() {
19        if rows.is_empty() {
20            return Err(PyValueError::new_err(format!(
21                "{} must not be an empty matrix.",
22                name
23            )));
24        }
25        let row_count = rows.len();
26        let cols = rows[0].len();
27        if cols == 0 {
28            return Err(PyValueError::new_err(format!(
29                "{} must not have zero columns.",
30                name
31            )));
32        }
33        if rows.iter().any(|r| r.len() != cols) {
34            return Err(PyValueError::new_err(format!(
35                "{} must be a rectangular matrix.",
36                name
37            )));
38        }
39        let out = rows.into_iter().flatten().collect::<Vec<f64>>();
40        return Ok((out, row_count, cols));
41    }
42
43    if let Ok(flat) = data.extract::<Vec<f64>>() {
44        if flat.is_empty() {
45            return Err(PyValueError::new_err(format!(
46                "{} must not be an empty vector.",
47                name
48            )));
49        }
50        let cols = flat.len();
51        return Ok((flat, 1, cols));
52    }
53
54    Err(PyValueError::new_err(format!(
55        "{} must be a 1-D or 2-D float array.",
56        name
57    )))
58}
59
60pub(crate) fn reshape_flat_to_rows(flat: Vec<f64>, rows: usize, cols: usize) -> Vec<Vec<f64>> {
61    let mut out = Vec::with_capacity(rows);
62    for i in 0..rows {
63        out.push(flat[i * cols..(i + 1) * cols].to_vec());
64    }
65    out
66}
sc_neurocore_engine/bindings/matrix_inputs.rs

sc_neurocore_engine/bindings/
matrix_inputs.rs
