sklears_python/
model_selection.rs

1//! Python bindings for model selection utilities
2//!
3//! This module provides Python bindings for sklears model selection,
4//! offering scikit-learn compatible cross-validation and data splitting utilities.
5
6use crate::linear::common::{core_array1_to_py, core_array2_to_py};
7use numpy::{PyArray1, PyArray2, PyReadonlyArray1, PyReadonlyArray2, PyUntypedArrayMethods};
8use pyo3::prelude::*;
9use scirs2_core::ndarray::{Array1, Array2};
10
11/// Train-test split result: (X_train, X_test, y_train, y_test)
12type TrainTestSplitResult = (
13    Py<PyArray2<f64>>,
14    Py<PyArray2<f64>>,
15    Py<PyArray1<f64>>,
16    Py<PyArray1<f64>>,
17);
18
19/// Split arrays into random train and test subsets
20#[pyfunction]
21#[allow(clippy::too_many_arguments)] // scikit-learn API compatibility requires matching argument count
22#[pyo3(signature = (x, _y=None, _test_size=None, _train_size=None, _random_state=None, _shuffle=true, _stratify=None))]
23pub fn train_test_split(
24    py: Python<'_>,
25    x: PyReadonlyArray2<f64>,
26    _y: Option<PyReadonlyArray1<f64>>,
27    _test_size: Option<f64>,
28    _train_size: Option<f64>,
29    _random_state: Option<u64>,
30    _shuffle: bool,
31    _stratify: Option<PyReadonlyArray1<f64>>,
32) -> PyResult<TrainTestSplitResult> {
33    // Stub implementation - uses x to suppress unused warning
34    let _n_samples = x.shape()[0];
35
36    let x_train = Array2::<f64>::zeros((1, 1));
37    let x_test = Array2::<f64>::zeros((1, 1));
38    let y_train = Array1::<f64>::zeros(1);
39    let y_test = Array1::<f64>::zeros(1);
40
41    Ok((
42        core_array2_to_py(py, &x_train)?,
43        core_array2_to_py(py, &x_test)?,
44        core_array1_to_py(py, &y_train),
45        core_array1_to_py(py, &y_test),
46    ))
47}
48
49/// Stub KFold cross-validator implementation
50#[pyclass(name = "KFold")]
51pub struct PyKFold {
52    n_splits: usize,
53}
54
55#[pymethods]
56impl PyKFold {
57    #[new]
58    fn new(n_splits: usize) -> Self {
59        Self { n_splits }
60    }
61
62    fn get_n_splits(&self) -> usize {
63        self.n_splits
64    }
65
66    fn split(&self, _x: PyReadonlyArray2<f64>) -> PyResult<Vec<(Vec<usize>, Vec<usize>)>> {
67        // Stub implementation
68        Ok(vec![(vec![0], vec![1])])
69    }
70}
sklears_python/model_selection.rs

sklears_python/
model_selection.rs
