// @Test
public void demoRnd1() {
TsData s = rnd;
TestFunction fn = new TestFunction(s);
ISsqFunctionMinimizer min = new LevenbergMarquardtMethod();
min.minimize(fn, new TestFunctionInstance(s));
TestFunctionInstance rslt = (TestFunctionInstance) min.getResult();
System.out.println("Rnd1");
printRslt(rslt);
}
// @Test
public void demo1() {
TsData s = Data.X.log();
TestFunction fn = new TestFunction(s);
ISsqFunctionMinimizer min =
new ec.tstoolkit.maths.realfunctions.levmar.LevenbergMarquardtMethod();
// ISsqFunctionMinimizer min = new
// ec.tstoolkit.maths.realfunctions.minpack.LevenbergMarquardtMinimizer();
// min.setConvergenceCriterion(1e-9);
min.setMaxIter(10);
min.minimize(fn, new TestFunctionInstance(s));
TestFunctionInstance rslt = (TestFunctionInstance) min.getResult();
double[] gradient = fn.getDerivatives(rslt).getGradient();
System.out.println("X");
printRslt(rslt);
}