def run_nelder_mead(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method="nelder-mead") x, y, z = res.x return x, y, z, f((x, y, z))
def run_newton_cg(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method="Newton-CG", jac=J, hess=H) x, y, z = res.x return x, y, z, f((x, y, z))
def run_bfgs(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method="BFGS", jac=J) x, y, z = res.x return x, y, z, f((x, y, z))
def run_nelder_mead(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method = 'nelder-mead') x, y, z = res.x return x, y, z, f((x, y, z))
def run_newton_cg(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method = 'Newton-CG', jac = J, hess = H) x, y, z = res.x return x, y, z, f((x, y, z))
def run_bfgs(): xy0 = numpy.array([1.0, 1.0, 1.0]) res = minimize(f, xy0, method = 'BFGS', jac = J) x, y, z = res.x return x, y, z, f((x, y, z))