Ver 0.39.5

- Add new feature `rkyv`

Author: Axect

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "peroxide"
-version = "0.39.4"
+version = "0.39.5"
 authors = ["axect <[email protected]>"]
 edition = "2018"
 description = "Rust comprehensive scientific computation library contains linear algebra, numerical analysis, statistics and machine learning tools with farmiliar syntax"
@@ -47,6 +47,7 @@ pyo3 = { version = "0.22", optional = true, features = [
 blas = { version = "0.22", optional = true }
 lapack = { version = "0.19", optional = true }
 serde = { version = "1.0", features = ["derive"], optional = true }
+rkyv = { version = "0.8", optional = true }
 json = { version = "0.12", optional = true }
 arrow2 = { version = "0.18", features = [
   "io_parquet",

README.md

@@ -46,6 +46,7 @@ Peroxide provides various features.
 - `csv` - To handle csv file format with Matrix or DataFrame
 - `parquet` - To handle parquet file format with DataFrame
 - `serde` - serialization with [Serde](https://serde.rs/).
+- `rkyv` - serialization with [rkyv](https://rkyv.org).
 
 If you want to do high performance computation and more linear algebra, then choose `O3` feature.
 If you don't want to depend C/C++ or Fortran libraries, then choose `default` feature.

RELEASES.md

@@ -1,3 +1,8 @@
+# Release 0.39.5 (2025-04-21)
+
+- New feature `rkyv`
+  - Implement `rkyv::{Archive, Serialize, Deserialize}` for `Matrix`, `Polynomial`, `Spline`, `ODE`
+
 # Release 0.39.4 (2025-04-11)
 
 ## Optimize `integrate`

src/numerical/ode.rs

@@ -366,6 +366,7 @@ impl<BU: ButcherTableau> ODEIntegrator for BU {
 /// In MATLAB, it is called `ode3`.
 #[derive(Debug, Clone, Copy, Default)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct RALS3;
 
 impl ButcherTableau for RALS3 {
@@ -381,6 +382,7 @@ impl ButcherTableau for RALS3 {
 /// It calculates four intermediate values (k1, k2, k3, k4) to estimate the next step solution.
 #[derive(Debug, Clone, Copy, Default)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct RK4;
 
 impl ButcherTableau for RK4 {
@@ -395,6 +397,7 @@ impl ButcherTableau for RK4 {
 /// This fourth order method is known as minimum truncation error RK4.
 #[derive(Debug, Clone, Copy, Default)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct RALS4;
 
 impl ButcherTableau for RALS4 {
@@ -414,6 +417,7 @@ impl ButcherTableau for RALS4 {
 /// This integrator uses the 5th order Runge-Kutta method to numerically integrate the ODE system.
 #[derive(Debug, Clone, Copy, Default)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct RK5;
 
 impl ButcherTableau for RK5 {
@@ -473,6 +477,7 @@ impl ButcherTableau for RK5 {
 /// - `max_step_iter`: The maximum number of iterations per step.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct BS23 {
     pub tol: f64,
     pub safety_factor: f64,
@@ -554,6 +559,7 @@ impl ButcherTableau for BS23 {
 /// - `max_step_iter`: The maximum number of iterations per step.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct RKF45 {
     pub tol: f64,
     pub safety_factor: f64,
@@ -656,6 +662,7 @@ impl ButcherTableau for RKF45 {
 /// - `max_step_iter`: The maximum number of iterations per step.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct DP45 {
     pub tol: f64,
     pub safety_factor: f64,
@@ -777,6 +784,7 @@ impl ButcherTableau for DP45 {
 /// - Ch. Tsitouras, Comput. Math. Appl. 62 (2011) 770-780.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct TSIT45 {
     pub tol: f64,
     pub safety_factor: f64,
@@ -896,6 +904,7 @@ impl ButcherTableau for TSIT45 {
 /// Currently, there are two options: fixed-point iteration and Broyden's method.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub enum ImplicitSolver {
     FixedPoint,
     Broyden,
@@ -915,6 +924,7 @@ pub enum ImplicitSolver {
 /// - `max_step_iter`: The maximum number of iterations for the implicit solver per step.
 #[derive(Debug, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(serde::Serialize, serde::Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct GL4 {
     pub solver: ImplicitSolver,
     pub tol: f64,

src/numerical/spline.rs

@@ -441,6 +441,7 @@ pub fn cubic_hermite_spline(
 /// ```
 #[derive(Debug, Clone, Default)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct CubicSpline {
     polynomials: Vec<(Range<f64>, Polynomial)>,
 }
@@ -691,6 +692,7 @@ impl Calculus for CubicSpline {
 // =============================================================================
 #[derive(Debug, Clone, Default)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct CubicHermiteSpline {
     polynomials: Vec<(Range<f64>, Polynomial)>,
 }
@@ -917,6 +919,7 @@ fn quadratic_slopes(x: &[f64], y: &[f64]) -> Result<Vec<f64>> {
 /// [Wikipedia](https://en.wikipedia.org/wiki/Irwin%E2%80%93Hall_distribution#Special_cases)
 #[derive(Debug, Copy, Clone)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct UnitCubicBasis {
     pub x_min: f64,
     pub x_max: f64,
@@ -992,6 +995,7 @@ impl UnitCubicBasis {
 /// ```
 #[derive(Debug, Clone)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct CubicBSplineBases {
     pub ranges: Vec<Range<f64>>,
     pub bases: Vec<UnitCubicBasis>,
@@ -1089,6 +1093,7 @@ impl CubicBSplineBases {
 /// ```
 #[derive(Debug, Clone, Default)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct BSpline {
     pub degree: usize,
     pub knots: Vec<f64>,

src/statistics/stat.rs

@@ -555,7 +555,8 @@ pub fn cor(v1: &Vec<f64>, v2: &Vec<f64>) -> f64 {
 ///
 /// fn main() {
 ///     let a: Matrix = c!(1,2,3,4,5).into();
-///     let b: Matrix = &a + &Normal(0,1).sample(5).into();
+///     let noise: Matrix = Normal(0,1).sample(5).into();
+///     let b: Matrix = &a + &noise;
 ///     lm(&a, &b).print();
 ///
 ///     //        c[0]

src/structure/matrix.rs

@@ -657,6 +657,7 @@ pub type Perms = Vec<(usize, usize)>;
 /// ```
 #[derive(Default, Debug, PartialEq, Clone, Copy)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub enum Shape {
     #[default]
     Col,
@@ -690,6 +691,7 @@ impl fmt::Display for Shape {
 /// ```
 #[derive(Debug, Clone, Default)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Serialize, rkyv::Deserialize))]
 pub struct Matrix {
     pub data: Vec<f64>,
     pub row: usize,

src/structure/polynomial.rs

@@ -18,6 +18,7 @@ use std::ops::{Add, Div, Mul, Neg, Sub};
 /// Polynomial Structure
 #[derive(Debug, Clone, Default)]
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
+#[cfg_attr(feature = "rkyv", derive(rkyv::Archive, rkyv::Deserialize, rkyv::Serialize))]
 pub struct Polynomial {
     pub coef: Vec<f64>,
 }