The residual function to differentiate
Optionaloptions: NumericalDifferentiationOptionsOptional numerical differentiation settings
A Jacobian function that can be passed to optimization algorithms
import { gaussNewton, createFiniteDiffJacobian } from 'numopt-js';
// Define your residual function
const residualFn = (params) => {
// Return residuals for curve fitting, etc.
return new Float64Array([...]);
};
// Create a Jacobian function
const jacobianFn = createFiniteDiffJacobian(residualFn);
// Use it with an optimizer
const result = gaussNewton(
new Float64Array([1, 1]),
residualFn,
jacobianFn,
{ maxIterations: 100, tolerance: 1e-6 }
);
Creates a Jacobian function from a residual function using finite differences.
This is a convenience wrapper around finiteDiffJacobian that returns a Jacobian function suitable for use with optimization algorithms like gaussNewton.