Totsu (凸 in Japanese) means convex.
This crate for Rust provides a first-order conic linear program solver.
A common target problem is continuous scalar convex optimization such as LP, QP, QCQP, SOCP and SDP. Each of those problems can be represented as a conic linear program.
The author combines the two papers [1] [2] so that the homogeneous self-dual embedding matrix in [2] is formed as a linear operator in [1].
See documentation for more details.
This crate can be used without the standard library (#![no_std]
).
Use this in Cargo.toml
:
toml
[dependencies.totsu]
version = "0.7.0"
default-features = false
features = ["nostd"]
Some module and structs are not availale in this case.
Changelog is available in CHANGELOG.md.
```rust use floateq::assertfloat_eq; use totsu::prelude::*; use totsu::operator::MatBuild; use totsu::problem::ProbQP;
type LA = FloatGeneric
let n = 2; // x0, x1 let m = 1; let p = 0;
// (1/2)(x - a)^2 + const let mut symp = AMatBuild::new(MatType::SymPack(n)); symp[(0, 0)] = 1.; sym_p[(1, 1)] = 1.;
let mut vecq = AMatBuild::new(MatType::General(n, 1)); vecq[(0, 0)] = -(-1.); // -a0 vec_q[(1, 0)] = -(-2.); // -a1
// 1 - x0/b0 - x1/b1 <= 0 let mut matg = AMatBuild::new(MatType::General(m, n)); matg[(0, 0)] = -1. / 2.; // -1/b0 mat_g[(0, 1)] = -1. / 3.; // -1/b1
let mut vech = AMatBuild::new(MatType::General(m, 1)); vech[(0, 0)] = -1.;
let mat_a = AMatBuild::new(MatType::General(p, n));
let vec_b = AMatBuild::new(MatType::General(p, 1));
let s = ASolver::new().par(|p| { p.maxiter = Some(100000); }); let mut qp = AProbQP::new(symp, vecq, matg, vech, mata, vecb, s.par.eps_zero); let rslt = s.solve(qp.problem(), NullLogger).unwrap();
assertfloateq!(rslt.0[0..2], [2., 0.].asref(), absall <= 1e-3); ```
You can find other tests of pre-defined solvers. More practical examples are also available.