import {dot, weightedSum} from "./blas1";


/// searches along line 'pk' for a point that satifies the wolfe conditions
/// See 'Numerical Optimization' by Nocedal and Wright p59-60
/// f : objective function
/// pk : search direction
/// current: object containing current gradient/loss
/// next: output: contains next gradient/loss
/// returns a: step size taken
export function wolfeLineSearch(f, pk, current, next, a, c1, c2) {
    var phi0 = current.fx, phiPrime0 = dot(current.fxprime, pk),
        phi = phi0, phi_old = phi0,
        phiPrime = phiPrime0,
        a0 = 0;

    a = a || 1;
    c1 = c1 || 1e-6;
    c2 = c2 || 0.1;

    function zoom(a_lo, a_high, phi_lo) {
        for (var iteration = 0; iteration < 16; ++iteration) {
            a = (a_lo + a_high)/2;
            weightedSum(next.x, 1.0, current.x, a, pk);
            phi = next.fx = f(next.x, next.fxprime);
            phiPrime = dot(next.fxprime, pk);

            if ((phi > (phi0 + c1 * a * phiPrime0)) ||
                (phi >= phi_lo)) {
                a_high = a;

            } else  {
                if (Math.abs(phiPrime) <= -c2 * phiPrime0) {
                    return a;
                }

                if (phiPrime * (a_high - a_lo) >=0) {
                    a_high = a_lo;
                }

                a_lo = a;
                phi_lo = phi;
            }
        }

        return 0;
    }

    for (var iteration = 0; iteration < 10; ++iteration) {
        weightedSum(next.x, 1.0, current.x, a, pk);
        phi = next.fx = f(next.x, next.fxprime);
        phiPrime = dot(next.fxprime, pk);
        if ((phi > (phi0 + c1 * a * phiPrime0)) ||
            (iteration && (phi >= phi_old))) {
            return zoom(a0, a, phi_old);
        }

        if (Math.abs(phiPrime) <= -c2 * phiPrime0) {
            return a;
        }

        if (phiPrime >= 0 ) {
            return zoom(a, a0, phi);
        }

        phi_old = phi;
        a0 = a;
        a *= 2;
    }

    return a;
}