Good day all!
I use C# version of ALGLIB 3.14.0.
I had quite good results in working with
lsfitcreatef and
lsfitcreatefg. I worked with analytic functions before.
Now I have to work with vectos and have to find results for such task:
-------------------------------------------------------------------------------------------
v1, v2, v are vectors length N and
v = a1 * v1 + a2 * 2
a1 and a2 - are unknown parameters. Need to find tallies for a1 and a2.
In more general case
v1,v2,..,vk (they are not orthogonal)
v = a1 * v1 + a2 * 2 + .... + ak * vk. Need to find tallies for a1, a2, ..., ak.
In most general case
v1,v2,..,vk (they are not orthogonal)
v = a1 * F(v1,ak+1,...,an) + a2 * F(v2,ak+1,...,an) + ... + ak * F(vk,ak+1,...,an), where F(vi,ak+1,...,an) = vi* - transformed vector vi.
ak+1,...,an - parameters of transformation. The form of transformation is the same for all vectors. For example: vi -> vi^(ak+1)
Need to find tallies for a1, a2, ..., ak, ak+1,...,an.
--------------------------------------------------------------------------------------------------------------------------------------------------------
I have tried this code:
Code:
class Program
{
static void Main(string[] args)
{
double[] y = new double[] { 2, 2, 3, 3};
double[,] x = new double[y.Length, 1];
for (int i = 0; i < y.Length; i++)
{
x[i, 0] = (double)(i);
}
double[] s = new double[] {1, 1}; // scale
double[] c = new double[] {2.2, 1}; // start values
double[] bndl = new double[] {0.0, 0.0}; // lower bound
double[] bndu = new double[] {4.0, 4.0}; // upper bound
double epsx = 0.0001;
int maxits = 0;
int info;
alglib.lsfitstate state;
alglib.lsfitreport rep;
double diffstep = 0.01;
alglib.lsfitcreatef(x, y, c, diffstep, out state);
alglib.lsfitsetbc(state, bndl, bndu);
alglib.lsfitsetcond(state, epsx, maxits);
alglib.lsfitsetscale(state, s);
alglib.lsfitfit(state, function_cx_2_func, null, null);
alglib.lsfitresults(state, out info, out c, out rep);
int iterationscount = rep.iterationscount;
System.Console.WriteLine("{0}", info);
System.Console.WriteLine("iterationscount = " + iterationscount.ToString());
System.Console.WriteLine("{0}", alglib.ap.format(c, 7));
System.Console.ReadKey();
}
public static void function_cx_2_func(double[] c, double[] x, ref double func, object obj)
{
// vectors a and b
[b]double[] a = new double[] { 1, 1, 0, 0};
double[] b = new double[] { 0, 0, 1, 1};[/b]
func = func + c[0] * a[(int)x[0]] + c[1] * b[(int)x[0]];
}
}
Output:
2
iterationscount = 0
{2.1995969,0.9996091} While correct result {2.0, 3.0}.Most likely I was wrong somewhere in the code or in logic of lsfit subpackage.I solved this task through minlm subpackage:Code:
class Program
{
static void Main(string[] args)
{
//
// This example demonstrates minimization of F(x0,x1) = f0^2+f1^2 + .... fn^2
//
// using "V" mode of the Levenberg-Marquardt optimizer.
//
// Optimization algorithm uses:
// * function vector f[] = {f1,f2,...,fn^2}
//
// No other information (Jacobian, gradient, etc.) is needed.
//
double[] x = new double[] { 0, 0 };
double epsx = 0.0000000001;
int maxits = 100;
alglib.minlmstate state;
alglib.minlmreport rep;
double[] bndl = new double[] { 0, 0 };
double[] bndu = new double[] { +4, +4 };
alglib.minlmcreatev(4, x, 0.0001, out state);
alglib.minlmsetbc(state, bndl, bndu);
alglib.minlmsetcond(state, epsx, maxits);
alglib.minlmoptimize(state, function2_fvec, null, null);
alglib.minlmresults(state, out x, out rep);
System.Console.WriteLine("{0}", alglib.ap.format(x, 7));
System.Console.WriteLine("{0}", alglib.ap.format(rep.iterationscount, 7));
System.Console.ReadLine();
}
public static void function2_fvec(double[] x, double[] fi, object obj)
{
double[] array1 = new double[] { 1, 1, 0, 0 };
double[] array2 = new double[] { 0, 0, 1, 1};
double[] array3 = new double[] { 2, 2, 3, 3};
for (int i = 0; i < array1.Length; i++)
{
fi[i] = System.Math.Pow(array3[i] - x[0] * array1[i] - x[1] * array2[i], 2);
}
}
}
Output
{2.0000000,3.0000000}
44.0000000+0.0000000i
OK
Sergey, could you spare a little time for my problem, please?
I hoped use lsfit subpackage due to more compact form for function2_fvec as well as for uniformity of code in other similar tasks.
And second question: what is the differece between lsfit subpackage and minlm subpackage?
Is it possible to say that some package is better for NLS-fiting?
With the best regards
Dmitri
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