#include "amma/Num/NumOptimiseGrid.hh"
#include "amma/Num/NumOptimiseRandomUniform.hh"
#include "amma/Num/NumOptimiseDescent.hh"
#include "amma/Num/NumOptimiseGenetic.hh"
#include "amma/Num/NumMagnitudeEuclidean.hh"
#include "amma/Num/NumCostFunction.hh"
#include "amma/Num/NumModelPolynomial.hh"
#include "amma/Vector2d.hh"
#include <fstream.h>

// This is a test program and should NOT be considered as
// an example of how to use this code.

main ()
{
  // Setup Data
  VectorC min = Vector2dC (0,0);
  VectorC max = Vector2dC (2,2);
  VectorC mid = Vector2dC (1,1);
  NumVVDataSetC train;
  train.Append (min,max);
  train.Append (max,max);
  train.Append (mid,min);
  train.Append (Vector2dC(0,2), Vector2dC(1,-1));
  train.Append (Vector2dC(2,0), Vector2dC(-1,1));
  train.Append (Vector2dC(1,0), Vector2dC(0.5,-0.5));
  train.Append (Vector2dC(-1,0),Vector2dC(-0.5,0.5));
  train.Append (Vector2dC(0,1), Vector2dC(0.5,0.5));
  train.Append (Vector2dC(0,-1),Vector2dC(-0.5,-0.5));
  // Setup parabola model
  NumModelPolynomialC model (2);
  model.Fit (train);
  // Optimisers
  SArray1dC<NumOptimiseC> optimisers (4);
  optimisers[0] = NumOptimiseGridC ();
  optimisers[1] = NumOptimiseRandomUniformC (100);
  optimisers[2] = NumOptimiseDescentC (50);
  optimisers[3] = NumOptimiseGeneticC ();
  // Setup cost function
  NumMagnitudeEuclideanC magnitude;
  
  IntSArray1dC steps (2); steps.Fill (50);
  SArray1dC<IntSArray1dC> masks(3);
  masks[0] = IntSArray1dC (2); masks[0].Fill(1);
  masks[1] = IntSArray1dC (2); masks[1][0] = 0; masks[1][1] = 1;
  masks[2] = IntSArray1dC (2); masks[2][0] = 1; masks[2][1] = 0;
  VectorC Yd = Vector2dC (0.5,-0.5);
  NumParametersC parameters (min,max,steps);
  parameters.SetConstP (mid);                      // Specifies starting point
  
  // Save
  {
    ofstream out ("testNumOptimise.data");
    FOR_SARRAY1 (optimisers,i1)
      optimisers[i1].Save (out);
  }
  // Load again as optimiser
  ifstream in ("testNumOptimise.data");
  SArray1dC<NumOptimiseC> newOptimisers (4);
  FOR_SARRAY1 (newOptimisers,i2)
    in >> newOptimisers[i2];
  // Do optimisation
  FOR_SARRAY1 (masks,i0) {
    cout << "Using following parameters mask: " << masks[i0] << "\n";
    parameters.SetMask (masks[i0]);
    NumCostFunctionC cost (parameters,Yd,model,magnitude);
    FOR_SARRAY1 (newOptimisers,i1) {
      VectorC Xdmin = newOptimisers[i1].MinimalX (cost);
      VectorC Xdmax = newOptimisers[i1].MaximalX (cost);
      cout << newOptimisers[i1].GetInfo () << "\n";
      cout << "MinimalX = " << Xdmin << "\n";
      cout << "MaximalX = " << Xdmax << "\n";
    }
  }
}