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#include "rnmat.hh"
#include "adjtest.hh"
#include "cgnealg.hh"

using namespace RVL;
using namespace RVLAlg;
using namespace RVLUmin;

/** Umin Unit Test 1
    Purpose: basic CG alg - scalar type = float
*/

template<typename T>
void CGNEDiagTest(int rows, 
		  int cols, 
		  typename ScalarFieldTraits<T>::AbsType _nlvl, // noise level
		  int maxit, 
		  typename ScalarFieldTraits<T>::AbsType minsig, // max singular val
		  typename ScalarFieldTraits<T>::AbsType maxsig, // max singular val
		  typename ScalarFieldTraits<T>::AbsType epsilon,// nr error reduction
		  string testno, string datatype, string output, 
		  ostream & str) {

  typedef typename ScalarFieldTraits<T>::AbsType atype;

  try {
    str<<endl;
    str<<"/****************************************************"<<endl;
    str<<" *            BEGIN UMin UNIT TEST "<<testno<<endl;
    str<<" * Purpose: test CGNE alg scalar type ="<<datatype<<endl;
    str<<" *   noise level = "<<_nlvl<<endl;
    str<<" *   results reported in "<<output<<endl;
    str<<" ****************************************************/"<<endl; 
    str<<endl;

    // build output stream
    ofstream strout(output.c_str());
    strout<<scientific;

    str<<"1. Construct domain, range spaces"<<endl;
    RnSpace<T> dom(cols);
    RnSpace<T> rng(rows);
    str<<endl;


    str<<"2. Build LinearOp (GenMat), do adjoint test\n";
    GenMat<T> A(dom,rng);
    RVLRandomize<T> rnd;
    int n = min(cols,rows);
    atype one = ScalarFieldTraits<atype>::One();
    for (int i=0;i<n;i++) {
      atype t=((atype)i)/((atype)n);
      A.getElement(i,i)=sqrt((one-t)*minsig*minsig + t*maxsig*maxsig);
    }
    if (AdjointTest<T>(A,rnd,strout)) {
      str<<"*** adjoint test passed - result in "<<output<<"; proceed\n";
    }
    else {
      str<<"*** adjoint test failed - result in "<<output<<"; exit\n";
      return;
    }
    str<<endl;

    str<<"3. Build sol, rhs vectors\n";
    Vector<T> sol(dom);
    Vector<T> est(dom);
    // initialize exact solution to random vector
    sol.eval(rnd);
    // initialize estimated solution to zero
    est.zero();
    // create rhs, initialize to noisy version of exact sol image
    Vector<T> rhs(rng);
    A.applyOp(sol,rhs);
    atype rhsnorm = rhs.norm();
    Vector<T> err(rng);
    err.eval(rnd);
    T nlvl = _nlvl*rhs.norm()/err.norm();
    rhs.linComb(nlvl,err);
    Vector<T> nrhs(rng);
    A.applyAdjOp(rhs,nrhs);
    atype nrhsnorm = nrhs.norm();
    str<<endl;

    str<<"4. Build, run CGNE algorithm \n";
    str<<endl;    

    // allocate rnorm, nrnorm scalars
    atype rnorm = numeric_limits<atype>::max();
    atype nrnorm = numeric_limits<atype>::max();
    CGNEAlg<T> iter(est,A,rhs,rnorm,nrnorm,ScalarFieldTraits<atype>::Zero(),epsilon,maxit,numeric_limits<atype>::max(),strout);
    // run it
    iter.run();

    // display results
    atype snorm = sol.norm();
    atype enorm = est.norm();
    sol.linComb(-ScalarFieldTraits<atype>::One(),est);
    atype relerr=ScalarFieldTraits<atype>::One();
    if (ProtectedDivision<atype>(sol.norm(),snorm,relerr)) {
      RVLException e;
      e<<"a-oo-ga! a-oo-ga! solution was zero!!!\n";
      throw e;
    }
      
    Vector<T> ATb(A.getDomain());
    A.applyAdjOp(rhs,ATb);
    rhsnorm = ATb.norm();
    strout<<"*******************************************************"<<endl;
    strout<<"*        Test of CGNE iteration for Normal Eqns       *"<<endl;
    strout<<endl<<"****** Example Attributes  "<<endl;
    strout<<"max iterations               = "<<maxit<<endl;
    strout<<"data noise level             = "<<_nlvl<<endl;
    strout<<"min singular val             = "<<minsig<<endl;
    strout<<"max singular val             = "<<maxsig<<endl;
    strout<<"rcond for normal eqns        = "<<minsig*minsig/(maxsig*maxsig)<<endl;
    strout<<"target normal res redn       = "<<epsilon<<endl;

    strout<<endl<<"****** Iteration Summary "<<endl;
    strout<<"actual number of iterations  = "<<iter.getCount()<<endl;
    strout<<"norm of ATb                  = "<<nrhsnorm<<endl;
    strout<<"normal res norm              = "<<nrnorm<<endl;
    strout<<"actual normal res redn       = "<<nrnorm/nrhsnorm<<endl;
    strout<<"data relerr                  = "<<_nlvl<<endl;
    strout<<"data norm                    = "<<rhsnorm<<endl;
    strout<<"res norm                     = "<<rnorm<<endl;
    strout<<"actual res redn              = "<<rnorm/rhsnorm<<endl;
    strout<<"norm of exact solution       = "<<snorm<<endl;
    strout<<"norm of estimated solution   = "<<enorm<<endl;
    strout<<"relative error in solution   = "<<relerr<<endl;
    strout<<"final value of LS fcn        = ";
    Vector<T> val(A.getRange());
    A.applyOp(est,val);
    val.linComb(-1.0,rhs);
    strout<< 1.0/2.0*val.normsq()<<endl;
    strout<<"*******************************************************"<<endl;
    strout.close();
  }
  catch (RVLException & e) {
    e.write(str);
    exit(1);
  }
}

int main() {

  try {
    PlantSeeds(19490615);
    int cols=100;
    
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.1,1.0,0.001,
			 "0.0","double","./CGNEDiagdbl0.rpt",cout);
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.1,1.0,0.001,
			 "0.1","double","./CGNEDiagdbl1.rpt",cout);
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.01,1.0,0.001,
			 "0.2","double","./CGNEDiagdbl2.rpt",cout);
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.01,1.0,0.001,
			 "0.3","double","./CGNEDiagdbl3.rpt",cout);
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.0,1.0,0.001,
			 "0.4","double","./CGNEDiagdbl4.rpt",cout);
    CGNEDiagTest<double>(cols,cols,0.0,1000,0.0,1.0,0.001,
			 "0.5","double","./CGNEDiagdbl5.rpt",cout);
  }
  catch (RVLException & e) {
    e.write(cerr);
    exit(1);
  }
}