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Merge branch 'hotfix' into dev
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Cargo.toml

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[package]
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name = "peroxide"
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version = "0.36.4"
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version = "0.37.0"
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authors = ["axect <[email protected]>"]
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edition = "2018"
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description = "Rust comprehensive scientific computation library contains linear algebra, numerical analysis, statistics and machine learning tools with farmiliar syntax"

README.md

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@@ -256,7 +256,7 @@ The example code demonstrates how Peroxide can be used to simulate the Lorenz at
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use peroxide::fuga::*;
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fn main() -> Result<(), Box<dyn Error>> {
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let rkf45 = RKF45::new(1e-4, 0.9, 1e-6, 1e-1, 100);
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let rkf45 = RKF45::new(1e-4, 0.9, 1e-6, 1e-2, 100);
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let basic_ode_solver = BasicODESolver::new(rkf45);
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let (_, y_vec) = basic_ode_solver.solve(
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&Lorenz,
@@ -309,7 +309,7 @@ How's that? Let me know if there's anything else you'd like me to improve!
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## Latest README version
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Corresponding to `0.36.0`
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Corresponding to `0.37.0`
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## Pre-requisite
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- In [examples](./examples) directory, there are some examples.
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- In [tests](./tests) directory, there are some useful tests.
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- More examples are in [Peroxide Gallery](https://github.com/Axect/Peroxide_Gallery).
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## Release Info
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To see [RELEASES.md](RELEASES.md)
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To see [RELEASES.md](./RELEASES.md)
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## Contributes Guide
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## TODO
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To see [TODO.md](./TODO.md)
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## Cite Peroxide
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Hey there!
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If you're using Peroxide in your research or project, you're not required to cite us.
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But if you do, we'd be really grateful! 😊
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To make citing Peroxide easy, we've created a DOI through Zenodo. Just click on this badge:
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[![DOI](https://zenodo.org/badge/130400565.svg)](https://zenodo.org/doi/10.5281/zenodo.10815823)
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This will take you to the Zenodo page for Peroxide.
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At the bottom, you'll find the citation information in various formats like BibTeX, RIS, and APA.
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So, if you want to acknowledge the work we've put into Peroxide, citing us would be a great way to do it! Thanks for considering it, we appreciate your support! 👍

TODO.md

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# TODO
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## 2021.01.14
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## 2024.04.14
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### Primary
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- [ ] Whole new Optimize (Trait based)
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- [ ] Pure Rust implementation of Linear Algebra
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- [x] LU (Completely Pivoting)
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- [x] LU (Partial Pivoting)
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- [ ] QR
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- [ ] SVD
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- [ ] Add more IO options for DataFrame
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- [x] CSV (`csv` feature)
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- [x] NetCDF (`nc` feature)
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- [ ] JSON
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- [ ] Arrow IPC
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- [ ] Parquet
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### Subs
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- [x] Student's t
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- [x] Uniform
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- [ ] Wishart
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- [x] Weighted Uniform
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- [ ] Implement special polynomial
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- [x] Legendre
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- [ ] Bessel
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- [ ] Hermite
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- [ ] Implement convenient structure of Neural Network
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- [ ] Documentized
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- [x] Vector
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- [x] Matrix
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- [x] Linear Algebra
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- [x] Functional Programming
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- [x] Statistics
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- [ ] Interpolation & Spline
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- [x] ODE
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- [ ] Macros
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- [ ] Machine Learning
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- [x] Optimize
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- [x] Automatic Differentiation
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- [x] DataFrame
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- [ ] Add Statistical regression
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- [ ] Gaussian Kernel
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- [ ] Logistic Kernel
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- [ ] Make or Use pure Rust plot library
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- [ ] Implement more Eigenvalue algorithms
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- [ ] Implement more spline algorithms
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- [ ] Complex matrix
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## Complete
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- [x] Replace `proc_macro` for `AD` with ordinary macro or Enum
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- [x] Make `csv` optional
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- [x] Remove `dual`, `hyperdual` and modify `Real`, `Number` (How to bind `f64` & `AD` effectively?)
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- [x] Add more IO options for DataFrame
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- [x] CSV (`csv` feature)
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- [x] NetCDF (`nc` feature)
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- [x] Parquet
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- [x] Documentized
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- [x] Vector
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- [x] Matrix
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- [x] Linear Algebra
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- [x] Functional Programming
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- [x] Statistics
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- [x] Interpolation & Spline
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- [x] ODE
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- [x] Macros
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- [x] Optimize
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- [x] Automatic Differentiation
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- [x] DataFrame
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- [x] Implement more spline algorithms
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- [x] Whole new ODE (trait based)
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- [x] Whole new root finding (trait based)

example_data/lorenz_rkf45.png

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example_data/rkf45_test.png

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example_data/test_plot.png

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examples/lorenz_rkf45.rs

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#[allow(unused_variables)]
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fn main() -> Result<(), Box<dyn Error>> {
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let rkf45 = RKF45::new(1e-4, 0.9, 1e-6, 1e-1, 100);
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let rkf45 = RKF45::new(1e-4, 0.9, 1e-6, 1e-2, 100);
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let basic_ode_solver = BasicODESolver::new(rkf45);
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let (_, y_vec) = basic_ode_solver.solve(
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&Lorenz,

src/util/plot.rs

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//! let y1 = x.fmap(|t| t.powi(2));
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//! let y2 = x.fmap(|t| t.powi(3));
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//!
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//! let mut rng = SmallRng::seed_from_u64(42);
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//! let normal = Normal(0f64, 0.1);
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//! let eps = normal.sample(100);
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//! let eps = normal.sample_with_rng(&mut rng, x.len());
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//! let y3 = y2.add_v(&eps);
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//!
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//! let mut plt = Plot2D::new();

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