Crate peroxide

Expand description

peroxide is comprehensive numerical library for Rust.

§Components

peroxide has various components for scientific computation.

Linear Algebra (with BLAS & LAPACK)
- Matrix operations
  - +,-,*,/
  - LU Decomposition, Determinant, Inverse
  - QR Decomposition (O3 feature needed)
  - Singular Value Decomposition (O3 feature needed)
  - Cholesky Decomposition (O3 feature needed)
  - Reduced Row Echelon Form
- Vector operations
- Eigenvalue, Eigenvector algorithms
Statistics
- Statistical operations
  - mean, var, sd
  - factorial, P, C, H
  - Confusion Matrix & metrics
- Distributions
  - Bernoulli
  - Uniform
  - Binomial
  - Normal
  - Gamma
  - Beta
  - Student’s t
  - LogNormal
Special functions (Using puruspe crate)
- Gaussian
- Gamma
- Beta
- Error
- Incomplete Gamma
- Incomplete Beta
- Lambert W
Automatic Differentiation
- Taylor mode forward AD
Numerical Utils
Optimization
- Gradient Descent
- Levenberg-Marquardt
Root Finding
- Bisection
- False Position
- Secant
- Newton
- Broyden
Ordinary Differential Equations
- Explicit
  - Ralston’s 3rd order
  - Runge-Kutta 4th order
  - Ralston’s 4th order
  - Runge-Kutta 5th order
- Embedded
  - Bogacki-Shampine 3(2)
  - Runge-Kutta-Fehlberg 4(5)
  - Dormand-Prince 5(4)
  - Tsitouras 5(4)
  - Runge-Kutta-Fehlberg 7(8)
- Implicit
  - Gauss-Legendre 4th order
Communication with Python
- Plot with matplotlib
DataFrame
- Read & Write with parquet or netcdf or csv format
Macros

And all these things are built on mathematical traits.

Traits

§Quick Start

§Cargo.toml

Run below commands in your project directory

Default
```
cargo add peroxide
```
OpenBLAS
```
cargo add peroxide --features O3
```
Plot
```
cargo add peroxide --features plot
```
NetCDF dependency for DataFrame
```
cargo add peroxide --features nc
```
CSV dependency for DataFrame
```
cargo add peroxide --features csv
```
Parquet dependency for DataFrame
```
cargo add peroxide --features parquet
```

All features

cargo add peroxide --features "O3 plot nc csv parquet"

§Import all at once

Peroxide has two options.

prelude : To simple use
fuga : To control numerical algorithms

To see differences, follow above two links.

You can import all functions & structures at once

prelude

#[macro_use]
extern crate peroxide;
use peroxide::prelude::*;

fn main() {
    // Write what you want
}

fuga

#[macro_use]
extern crate peroxide;
use peroxide::fuga::*;

fn main() {
    // Write what you want
}

§Useful tips for features

If you want to use QR, SVD, or Cholesky Decomposition, you should use the O3 feature. These decompositions are not implemented in the default feature.
If you want to save your numerical results, consider using the parquet or nc features, which correspond to the parquet and netcdf file formats, respectively. These formats are much more efficient than csv and json.
For plotting, it is recommended to use the plot feature. However, if you require more customization, you can use the parquet or nc feature to export your data in the parquet or netcdf format and then use Python to create the plots.
- To read parquet files in Python, you can use the pandas and pyarrow libraries.
- A template for Python code that works with netcdf files can be found in the Socialst repository.

Modules§

complex
fuga: Choose what you want.
macros: Useful macros
ml: Machine learning tools
numerical: Differential equations & Numerical Analysis tools
prelude: Do not disturbed. Just use.
special: Special functions module
statistics: Statistical Modules
structure: Main structures for peroxide
traits
util: Utility - plot, print, pickle and etc.

Macros§

bisection: High level macro for bisection
c: R like concatenate (Type: Vec<f64>)
cbind: R like cbind
dnorm: R like dnorm
dt: R like dt
eye: MATLAB like eye - identity matrix
false_position: High level macro for false position
hstack
linspace: MATLAB like linspace
lm: R like lm
matrix: More R like Matrix constructor (Macro)
newton: High level macro for newton (using Automatic differentiation)
pnorm: R like pnorm
pt: R like pt
rand: MATLAB like rand - random matrix
rbind: R like rbind
rnorm: R like random normal
rt: R like random Student’s t
runif: R like random uniform
secant: High level macro for secant
seq: R like seq macro
single_derivative: Macro for single derivative
single_function: Macro for single function
vstack
zeros: MATLAB like zeros - zero matrix