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Numerical methods in pure Go (CGO=0): optimisation and root finding, quadrature and ODE solvers, special functions — on go-ndarray.
Each library ports reference algorithms (MINPACK, L-BFGS-B, QUADPACK, the
Runge–Kutta, Radau and BDF solvers, Cephes and Boost.Math) statement by
statement, and its tests replay recorded answers: SciPy 1.18.1 runs for
optimize and integrate, with the netlib Fortran as a second oracle, and
mpmath at high precision for special, with SciPy
measured on the same points. Where the Go code is slower than the reference,
the documentation says so.
r, err := integrate.Quad(func(x float64) float64 { return math.Log(x) / math.Sqrt(x) }, 0, 1, nil)
// r.Value = -4, r.AbsErr = 2.3e-13, r.NEval = 315
root, _ := optimize.Brentq(func(x float64) float64 { return x*x*x - 2*x - 5 }, 2, 3, nil)
// root.Root = 2.094551481542…, 7 iterations
fmt.Println(special.Erfc(10)) // 2.088487583762545e-45| Repo | What it is |
|---|---|
| optimize | minimisation (Nelder–Mead, Powell, CG, BFGS, Newton-CG, L-BFGS-B), scalar and system roots, nonlinear least squares, curve fitting with covariance, linear programming |
| integrate | adaptive quadrature (QUADPACK), fixed and sample rules, multiple integrals, initial value problems (RK45, RK23, DOP853, Radau, BDF, stiffness switching) |
| special | gamma, beta, error and normal functions, incomplete gamma and beta and their inverses, Bessel, zeta, elliptic integrals, with an element-wise layer over go-ndarray |
| docs | the documentation site (Hugo + Hextra), served at /docs/ |
| go-numerics.github.io | the landing page (Hugo) |
| brand | logo, icons and social images |
Every library needs Go 1.27.2 or later. It is part of an ecosystem with go-ndarray (N-dimensional arrays), go-plot (figures), go-dataframe (labelled tables) and go-notebook (Go notebooks).