scijit.optimize

scipy.optimize equivalents callable from inside numba.@njit code: MINPACK roots, L-BFGS-B / SLSQP / COBYLA / PRIMA minimizers, scalar root-finders and minimizers, and the global optimizers. Each name below links to a page generated from its docstring: parameters, returns, a runnable @njit example, and, where it applies, the ways it differs from scipy.

minimize	Minimize a scalar function of one or more variables.
minimize_scalar	Scalar minimizer dispatcher.
root	Find a root of a vector function.
root_scalar	Scalar root-finder dispatcher.
fsolve	Find the roots of a system of nonlinear equations.
leastsq	Minimize the sum of squares of a set of residuals.
curve_fit	Nonlinear least-squares curve fit.
nnls	Non-negative least squares.
lsq_linear	Bounded-variable linear least squares.
linear_sum_assignment	Solve the linear sum assignment problem.
fmin	Minimize a function using the Nelder-Mead simplex algorithm.
fmin_powell	Minimize a function using Powell's direction-set method.
fmin_cg	Minimize a function with the Polak-Ribiere+ conjugate gradient method.
fmin_bfgs	Minimize a function with the quasi-Newton BFGS method.
fmin_l_bfgs_b	Minimize a function of many variables subject to simple bounds.
fmin_slsqp	Minimize a function subject to equality, inequality and bound constraints.
fmin_cobyla	Minimize a function subject to nonlinear inequality constraints.
bisect	Bisection root-finder.
brentq	Brent's method with inverse quadratic interpolation.
brenth	Brent's method with hyperbolic extrapolation.
ridder	Ridders' method.
toms748	TOMS Algorithm 748 (Alefeld, Potra and Shi).
newton	Newton-Raphson, secant and Halley root-finder.
fixed_point	Scalar fixed point of f, a point where f(x) == x.
bracket	Bracket a minimum of func.
golden	Golden-section minimizer.
brent	Brent's parabolic-interpolation minimizer.
fminbound	Bounded scalar minimizer on a fixed interval.
brute	Brute-force grid search over a full Cartesian grid.
basinhopping	Basin-hopping global optimization by random restarts.
differential_evolution	Differential evolution, a population-based stochastic optimizer.
HessInv	The inverse-Hessian estimate a minimize result carries.
RootResults	Result of a scalar root find.
OptimizeResult	The result minimize, root and the other solvers return.
OptimizeWarning	Warning category for recoverable problems during optimization.