Exemple #1
0
template<class _t, class _rt, class _it> _t rect<_t, _rt, _it>::width() {
	adjust_to_concept(); 
	return x1() - x0() + 1; 
}
Exemple #2
0
vector<double> CNelderMead::NelderMeadFunction(double (*f)(vector<double>, RMSEinputs rmsein), NMsettings nmset, vector<vector<double> > x)
{
	int NumIters = 0;
	int i,j;

	double MaxIters   = nmset.MaxIters;
	double tolerance  = nmset.tolerance;
	int N = nmset.N;
	RMSEinputs rmsein = nmset.RMSEinp;
	double S = rmsein.S;
	double T = rmsein.T;
	double r = rmsein.r;

	// Value of the function at the vertices
	vector<vector<double> > F(N+1, vector<double>(2));

	// Step 0.  Ordering and Best and Worst points
	// Order according to the functional values, compute the best and worst points
	step0:
	NumIters += 1;
	for (j=0; j<=N; j++){
		vector<double> z(N, 0.0);								// Create vector to contain
		for (i=0; i<=N-1; i++)
			z[i] = x[i][j];
		F[j][0] = f(z,rmsein);		       						// Function values
		F[j][1] = j;											// Original index positions
	}
	sort(F.begin(), F.end());

	// New vertices order first N best initial vectors and
	// last (N+1)st vertice is the worst vector
	// y is the matrix of vertices, ordered so that the worst vertice is last
	vector<vector<double> > y(N, vector<double>(N+1));
	for (j=0; j<=N; j++)
		for (i=0; i<=N-1; i++)
			y[i][j] = x[i][F[j][1]];

	//  First best vector y(1) and function value f1
	vector<double> x1(N, 0.0); for (i=0; i<=N-1; i++) x1[i] = y[i][0];
	double f1 = f(x1,rmsein);

	// Last best vector y(N) and function value fn
	vector<double> xn(N, 0.0); for (i=0; i<=N-1; i++) xn[i] = y[i][N-1];
	double fn = f(xn,rmsein);

	// Worst vector y(N+1) and function value fn1
	vector<double> xn1(N, 0.0); for (i=0; i<=N-1; i++) xn1[i] = y[i][N];
	double fn1 = f(xn1,rmsein);

	// z is the first N vectors from y, excludes the worst y(N+1)
	vector<vector<double> > z(N, vector<double>(N));
	for (j=0; j<=N-1; j++)
		for (i=0; i<=N-1; i++)
			z[i][j] = y[i][j];

	// Mean of best N values and function value fm
	vector<double> xm(N, 0.0); xm = CNelderMead::VMean(z,N);
	double fm = f(xm,rmsein);

	// Reflection point xr and function fr
	vector<double> xr(N, 0.0); xr = CNelderMead::VSub(VAdd(xm, xm), xn1);
	double fr = f(xr,rmsein);

	// Expansion point xe and function fe
	vector<double> xe(N, 0.0); xe = CNelderMead::VSub(VAdd(xr, xr), xm);
	double fe = f(xe,rmsein);

	// Outside contraction point and function foc
	vector<double> xoc(N, 0.0);	xoc = CNelderMead::VAdd(CNelderMead::VMult(xr, 0.5), VMult(xm, 0.5));
	double foc = f(xoc,rmsein);

	// Inside contraction point and function foc
	vector<double> xic(N, 0.0);	xic = CNelderMead::VAdd(CNelderMead::VMult(xm, 0.5), CNelderMead::VMult(xn1, 0.5));
	double fic = f(xic,rmsein);

	while ((NumIters <= MaxIters) && (abs(f1-fn1) >= tolerance))
	{
		// Step 1. Reflection Rule
		if ((f1<=fr) && (fr<fn)) {
			for (j=0; j<=N-1; j++)
				for (i=0; i<=N-1; i++)
					x[i][j] = y[i][j];
			for (i=0; i<=N-1; i++)
				x[i][N] = xr[i];
			goto step0;
		}

		// Step 2.  Expansion Rule
		if (fr<f1) {
			for (j=0; j<=N-1; j++) {
				for (i=0; i<=N-1; i++)  x[i][j] = y[i][j]; }
			if (fe<fr)
				for (i=0; i<=N-1; i++)	x[i][N] = xe[i];
			else
				for (i=0; i<=N-1; i++)	x[i][N] = xr[i];
			goto step0;
		}

		// Step 3.  Outside contraction Rule
		if ((fn<=fr) && (fr<fn1) && (foc<=fr)) {
			for (j=0; j<=N-1; j++) {
				for (i=0; i<=N-1; i++)  x[i][j] = y[i][j]; }
			for (i=0; i<=N-1; i++)	x[i][N] = xoc[i];
			goto step0;
		}

		// Step 4.  Inside contraction Rule
		if ((fr>=fn1) && (fic<fn1)) {
			for (j=0; j<=N-1; j++) {
				for (i=0; i<=N-1; i++)  x[i][j] = y[i][j]; }
			for (i=0; i<=N-1; i++)	x[i][N] = xic[i];
			goto step0;
		}

		// Step 5. Shrink Step
		for (i=0; i<=N-1; i++)
			x[i][0] = y[i][0];
		for (i=0; i<=N-1; i++) {
			for (j=1; j<=N; j++)
				x[i][j] = 0.5*(y[i][j] + x[i][0]);
		}
		goto step0;
	}

	// Output component
	// Return N parameter values, value of objective function, and number of iterations
	vector<double> out(N+2);
	for (i=0; i<=N-1; i++)
		out[i] = x1[i];
	out[N] = f1;
	out[N+1] = NumIters;
	return out;
}
// Private methods
// determine the slave/master pair in contact, and setup Vectors (N,T1,T2)
int ZeroLengthInterface2D::contactDetect(int s, int m1, int m2, int stage)
{
  //+--------------+-----------------+----------------+----------------+---------------+
  // NOTES: some methods to get displacements from nodes
  //+--------------+-----------------+----------------+----------------+---------------+
  // getDisp() :         get commit(k-1) disp, will be commit(k) after commit
  // getTrialDisp():     get Trial(k) disp
  // getIncrDisp():      get Trial(k)-Commit(k-1), will be 0 after commit
  // getIncrDeltaDisp(): get Trial(k)-Trial(k-1),  will be 0 after commit
  //+--------------+-----------------+----------------+----------------+--------------
  ////////////////////////////// for transient gap ///////////////////////////////////
  // DEFINE:
  // gap = (U_master-U_slave) / dot(ContactNormal),
  // defines overlapped normal distance, always keep positive (+) when contacted
  ///*
  // get current position and after trial displacement for (slave, master1, master2) nodes
  int i;
  const Vector &xs = nodePointers[s]->getCrds();
  const Vector &uxs = nodePointers[s]->getTrialDisp();
  const Vector &x1 = nodePointers[m1]->getCrds();
  const Vector &ux1= nodePointers[m1]->getTrialDisp();
  const Vector &x2 = nodePointers[m2]->getCrds();
  const Vector &ux2= nodePointers[m2]->getTrialDisp();
  
  Vector trial_slave(2), trial_master1(2), trial_master2(2);
  for (i = 0; i < 2; i++) {
    trial_slave(i) = xs(i) + uxs(i);
    trial_master1(i) = x1(i) + ux1(i);
    trial_master2(i) = x2(i) + ux2(i);
    //opserr << "trial_slave: " << trial_slave(i) << "\n";
    //opserr << "trial_master1: " << trial_master1(i) << "\n";
    //opserr << "trial_master2: " << trial_master2(i) << "\n";
  }
  
  // calculate normal gap for contact
  Vector diff(2);
  Vector ContactTangent(2);
  for (i = 0; i < 2; i++) {
    diff(i) = trial_master2(i) - trial_master1(i);
    //opserr << "diff: " << diff(i) << "\n";
  }
  double L  = diff.Norm();
  // tangent vector
  for (i = 0; i < 2; i++) ContactTangent(i) = (1/L) * (trial_master2(i) - trial_master1(i));
  // normal vector
  ContactNormal(0) = - ContactTangent(1);
  ContactNormal(1) = ContactTangent(0);
  
  normal_gap(s) = 0;
  double alpha = 0;
  double alpha_bar = 0;
  for (i = 0; i < 2; i++) {
    alpha += (1/L) * (trial_slave(i) - trial_master1(i)) * ContactTangent(i);
    normal_gap(s) += (trial_slave(i) - trial_master1(i)) * ContactNormal(i);
    diff(i) = x2(i) - x1(i);
  }
  
  double gapgap = normal_gap(s);
  
  double L_bar = diff.Norm();
  for (i = 0; i < 2; i++) alpha_bar += (1/L_bar) * (xs(i) - x1(i)) * ContactTangent(i);
  shear_gap(s) = (alpha - alpha_bar) * L_bar;
  /*
    /////////////////////////////// for transient gap ///////////////////////////////
    // we have another way to define the gap, can replace previous code block if want
    ////////////////////////////// for dynamic gap //////////////////////////////////
    const Vector   // get current trial incremental position
    &U_slave = nodePointers[0]->getCrds() + nodePointers[0]->getIncrDisp();
    const Vector
    &U_master= nodePointers[1]->getCrds() + nodePointers[1]->getIncrDisp();
    gap=0;
    int i;
    for (i=0; i<2; i++){
    gap += (U_master(i)-U_slave(i))* ContactNormal(i);
    }
    gap+=gap_n;
    ///////////////// for dynamic gap //////////////////////
    */
  // stage = 0 means searching slave nodes against master segments
  // stage = 1 means searching master nodes against slave segments
  if ((stage == 0  && normal_gap(s) >= 0 && alpha > 0 && alpha < 1) ||
      (stage == 1  && normal_gap(s) >= 0 && alpha >= 0 && alpha <= 1)) { // in contact
    N(0) = ContactNormal(0);
    N(1) = ContactNormal(1);
    N(2) = -(1 - alpha) * N(0);
    N(3) = -(1 - alpha) * N(1);
    N(4) = -(alpha) * N(0);
    N(5) = -(alpha) * N(1);
    
    T(0) = ContactTangent(0);
    T(1) = ContactTangent(1);
    T(2) = -(1-alpha) * T(0);
    T(3) = -(1-alpha) * T(1);
    T(4) = -(alpha) * T(0);
    T(5) = -(alpha) * T(1);
    
    return 1;
  } else {
    return 0; // Not in contact
  }
}
Exemple #4
0
long LatticeSolve(vec_ZZ& x, const mat_ZZ& A, const vec_ZZ& y, long reduce)
{
   long n = A.NumRows();
   long m = A.NumCols();

   if (y.length() != m)
      Error("LatticeSolve: dimension mismatch");

   if (reduce < 0 || reduce > 2)
      Error("LatticeSolve: bad reduce parameter");

   if (IsZero(y)) {
      x.SetLength(n);
      clear(x);
      return 1;
   }

   mat_ZZ A1, U1;
   ZZ det2;
   long im_rank, ker_rank;

   A1 = A;

   im_rank = image(det2, A1, U1);
   ker_rank = n - im_rank;

   mat_ZZ A2, U2;
   long new_rank;
   long i;

   A2.SetDims(im_rank + 1, m);
   for (i = 1; i <= im_rank; i++)
      A2(i) = A1(ker_rank + i);

   A2(im_rank + 1) = y;

   new_rank = image(det2, A2, U2);

   if (new_rank != im_rank ||
      (U2(1)(im_rank+1) != 1  && U2(1)(im_rank+1) != -1))
      return 0;

   vec_ZZ x1;
   x1.SetLength(im_rank);

   for (i = 1; i <= im_rank; i++)
      x1(i) = U2(1)(i);

   if (U2(1)(im_rank+1) == 1)
      negate(x1, x1);

   vec_ZZ x2, tmp;
   x2.SetLength(n);
   clear(x2);
   tmp.SetLength(n);

   for (i = 1; i <= im_rank; i++) {
      mul(tmp, U1(ker_rank+i), x1(i));
      add(x2, x2, tmp);
   }

   if (reduce == 0) {
      x = x2;
      return 1;
   }
   else if (reduce == 1) {
      U1.SetDims(ker_rank+1, n);
      U1(ker_rank+1) = x2;
      image(det2, U1);

      x = U1(ker_rank + 1);
      return 1;
   }
   else if (reduce == 2) {
      U1.SetDims(ker_rank, n);
      LLL(det2, U1);
      U1.SetDims(ker_rank+1, n);
      U1(ker_rank+1) = x2;
      image(det2, U1);

      x = U1(ker_rank + 1);
      return 1;
   }

   return 0;
}
Exemple #5
0
void benchmark_sort(
        const vex::Context &ctx, vex::profiler<> &prof
        )
{
    const size_t N = 16 * 1024 * 1024;
    const size_t M = 16;

    typedef typename std::conditional<
        std::is_same<float, real>::value, cl_uint, cl_ulong
        >::type key_type;

    std::default_random_engine rng( std::rand() );
    std::uniform_int_distribution<key_type> rnd;

    std::vector<key_type> x0(N);
    std::vector<key_type> x1(N);

    std::generate(x0.begin(), x0.end(), [&]() { return rnd(rng); });

    vex::vector<key_type> X0(ctx, x0);
    vex::vector<key_type> X1(ctx, N);

    X1 = X0;
    vex::sort(X1);

    double tot_time = 0;
    for(size_t i = 0; i < M; i++) {
        X1 = X0;
        ctx.finish();
        prof.tic_cpu("VexCL");
        vex::sort(X1);
        ctx.finish();
        tot_time += prof.toc("VexCL");
    }

    std::cout
        << "Sort (" << vex::type_name<key_type>() << ")\n"
        << "    VexCL:         " << N * M / tot_time << " keys/sec\n";

#ifdef HAVE_BOOST_COMPUTE
    X1 = X0;
    vex::compute::sort(X1);

    tot_time = 0;
    for(size_t i = 0; i < M; i++) {
        X1 = X0;
        ctx.finish();
        prof.tic_cpu("Boost.Compute");
        vex::compute::sort(X1);
        ctx.finish();
        tot_time += prof.toc("Boost.Compute");
    }

    std::cout
        << "    Boost.Compute: " << N * M / tot_time << " keys/sec\n";
#endif

#ifdef HAVE_CLOGS
    X1 = X0;
    vex::clogs::sort(X1);

    tot_time = 0;
    for(size_t i = 0; i < M; i++) {
        X1 = X0;
        ctx.finish();
        prof.tic_cpu("CLOGS");
        vex::clogs::sort(X1);
        ctx.finish();
        tot_time += prof.toc("CLOGS");
    }

    std::cout
        << "    CLOGS:         " << N * M / tot_time << " keys/sec\n";
#endif

    if (options.bm_cpu) {
        tot_time = 0;
        for(size_t i = 0; i < M; i++) {
            std::copy(x0.begin(), x0.end(), x1.begin());
            prof.tic_cpu("STL");
            std::sort(x1.begin(), x1.end());
            tot_time += prof.toc("STL");
        }

        std::cout << "    STL:           " << N * M / tot_time << " keys/sec\n";
    }

    std::cout << std::endl;
}
Exemple #6
0
static void tst_isolate_roots() {
    enable_trace("isolate_roots");
    unsynch_mpq_manager        qm;
    polynomial::manager        pm(qm);
    algebraic_numbers::manager am(qm);
    polynomial_ref x0(pm);
    polynomial_ref x1(pm);
    polynomial_ref x2(pm);
    polynomial_ref x3(pm);
    x0 = pm.mk_polynomial(pm.mk_var());
    x1 = pm.mk_polynomial(pm.mk_var());
    x2 = pm.mk_polynomial(pm.mk_var());
    x3 = pm.mk_polynomial(pm.mk_var());

    polynomial_ref p(pm);
    p = x3*x1 + 1;

    scoped_anum v0(am), v1(am), v2(am);

    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    am.set(v1, 1);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    am.set(v1, 2);
    am.root(v1, 2, v1);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 + x2)*x3 + 1;
    am.set(v2, v1);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 + x2)*x3 + x1*x2 + 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 + x2)*(x3^3) + x1*x2 + 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 + x2)*(x3^2) - x1*x2 - 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = x0*(x1 + x2)*(x3^2) - x0*x1*x2 - 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 - x2)*x3 + x1*x2 - 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x1 - x2)*(x3^3) + x1*x2 - 2;
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x3 - x0)*(x3 - x0 - x1);
    am.set(v0, 2);
    am.root(v0, 2, v0); // x2 -> sqrt(2)
    am.set(v1, 3);
    am.root(v1, 2, v1); // x1 -> sqrt(3)
    am.reset(v2);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x3 - x0)*((x3 - x0 - x1)^2);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);

    p = (x3 - x0)*(x3 - 2)*((x3 - 1)^2)*(x3 - x1);
    tst_isolate_roots(p, am, 0, v0, 1, v1, 2, v2);
}
Exemple #7
0
int main(int argc, char *argv[]) {

  Teuchos::GlobalMPISession mpiSession(&argc, &argv,0);
  Platform &platform = Tpetra::DefaultPlatform::getDefaultPlatform();
  Teuchos::RCP<const Teuchos::Comm<int> > comm = platform.getComm();

  int iprint = argc - 1;
  Teuchos::oblackholestream bhs; // outputs nothing
  std::ostream& outStream = (iprint > 0) ? std::cout : bhs;

  int errorFlag = 0;

  RealT errtol = ROL::ROL_THRESHOLD<RealT>();

  try {
    // Dimension of the optimization vector

    int dim = 10; 
  
    Teuchos::RCP<Map> map = Teuchos::rcp( new Map(dim,0,comm) );

    // Create Tpetra::MultiVectors (single vectors) 
    MVP x_rcp = Teuchos::rcp( new MV(map,1,true) ); 
    MVP y_rcp = Teuchos::rcp( new MV(map,1,true) ); 
    VP W_rcp = Teuchos::rcp( new V(map,true) );

    // Random elements
    //x_rcp->randomize();
    //y_rcp->randomize();
    x_rcp->putScalar(1.0);
    y_rcp->putScalar(1.0);

    // Set all values to 2
    W_rcp->putScalar(2.0);

    // Create ROL vectors
    ROL::PrimalScaledTpetraMultiVector<RealT,LO,GO,Node> x(x_rcp,W_rcp);
    ROL::DualScaledTpetraMultiVector<RealT,LO,GO,Node>   y(y_rcp,W_rcp);

//    const ROL::Vector<RealT> &g = x.dual();
//    const ROL::Vector<RealT> &h = x.dual();
//    RealT hnorm = h.norm();
//    RealT gnorm = g.norm();

    RealT xy = x.dot(y.dual());
    RealT yx = y.dot(x.dual());

    outStream << "\nAbsolute error between x.dot(y.dual()) and y.dot(x.dual()): "
              << std::abs(xy-yx) << "\n";
    outStream << "x.dot(y.dual()): " << xy << "\n";
    outStream << "y.dot(x.dual()): " << yx << "\n";
    if ( std::abs(xy-yx) > errtol ) {
      outStream << "---> POSSIBLE ERROR ABOVE!\n";
      errorFlag++;
    }

    RealT xx = std::sqrt(x.dot(x)), xnorm = x.norm();
    RealT yy = std::sqrt(y.dot(y)), ynorm = y.norm();

    outStream << "\nAbsolute error between sqrt(x.dot(x)) and x.norm(): "
              << std::abs(xx-xnorm) << "\n";
    outStream << "sqrt(x.dot(x)): " << xx << "\n";
    outStream << "x.norm():       " << xnorm << "\n";
    if ( std::abs(xx-xnorm) > errtol ) {
      outStream << "---> POSSIBLE ERROR ABOVE!\n";
      errorFlag++;
    }

    outStream << "\nAbsolute error between sqrt(y.dot(y)) and y.norm(): "
              << std::abs(yy-ynorm) << "\n";
    outStream << "sqrt(y.dot(y)): " << yy << "\n";
    outStream << "y.norm():       " << ynorm << "\n";
    if ( std::abs(yy-ynorm) > errtol ) {
      outStream << "---> POSSIBLE ERROR ABOVE!\n";
      errorFlag++;
    }

    // clone z from x, deep copy x into z, norm of z
    Teuchos::RCP<ROL::Vector<RealT> > z = x.clone();
    z->set(x);
    RealT znorm = z->norm();
    outStream << "\nNorm of ROL::Vector z (clone of x): " << znorm << "\n";
    if ( std::abs(xnorm - znorm) > errtol ) {
      outStream << "---> POSSIBLE ERROR ABOVE!\n";
      errorFlag++;
    }
    Teuchos::RCP<ROL::Vector<RealT> > w = y.clone();
    w = y.clone();
    w->set(y);
    RealT wnorm = w->norm();
    outStream << "\nNorm of ROL::Vector w (clone of y): " << wnorm << "\n";
    if ( std::abs(ynorm - wnorm) > errtol ) {
      outStream << "---> POSSIBLE ERROR ABOVE!\n";
      errorFlag++;
    }

    // Standard tests.
    // Create Tpetra::MultiVectors (single vectors) 
    MVP x1_rcp = Teuchos::rcp( new MV(map,1,true) ); 
    MVP y1_rcp = Teuchos::rcp( new MV(map,1,true) ); 
    MVP z1_rcp = Teuchos::rcp( new MV(map,1,true) ); 
    ROL::PrimalScaledTpetraMultiVector<RealT,LO,GO,Node> x1(x1_rcp,W_rcp);
    ROL::PrimalScaledTpetraMultiVector<RealT,LO,GO,Node> y1(y1_rcp,W_rcp);
    ROL::PrimalScaledTpetraMultiVector<RealT,LO,GO,Node> z1(z1_rcp,W_rcp);
    x1_rcp->randomize();
    y1_rcp->randomize();
    z1_rcp->randomize();

    std::vector<RealT> consistency = x1.checkVector(y1, z1, true, outStream);
    ROL::StdVector<RealT> checkvec(Teuchos::rcp(&consistency, false));
    if (checkvec.norm() > std::sqrt(errtol)) {
      errorFlag++;
    }

  }

  catch (std::logic_error err) {
    outStream << err.what() << "\n";
    errorFlag = -1000;
  }; // end try

  if (errorFlag != 0)
    std::cout << "End Result: TEST FAILED\n";
  else
    std::cout << "End Result: TEST PASSED\n";

  return 0;
}
Exemple #8
0
main(){
        X x1("1234");
        X x2(x1+1);
}
Exemple #9
0
 double yangle() const {
     double x=x1()-x0;
     double y=y1()-y0;
     double o=x<0?1:-1;
     return vangle(0,1,x,y)*o+M_PI;
 }
Exemple #10
0
Path SVGLineElement::toPathData() const
{
    return Path::createLine(FloatPoint(x1().value(this), y1().value(this)),
                            FloatPoint(x2().value(this), y2().value(this)));
}
Exemple #11
0
bool SVGLineElement::hasRelativeValues() const
{
    return (x1().isRelative() || y1().isRelative() ||
            x2().isRelative() || y2().isRelative());
}
Exemple #12
0
inline void
TrsvUN( UnitOrNonUnit diag, const DistMatrix<F>& U, DistMatrix<F>& x )
{
#ifndef RELEASE
    CallStackEntry entry("internal::TrsvUN");
    if( U.Grid() != x.Grid() )
        LogicError("{U,x} must be distributed over the same grid");
    if( U.Height() != U.Width() )
        LogicError("U must be square");
    if( x.Width() != 1 && x.Height() != 1 )
        LogicError("x must be a vector");
    const Int xLength = ( x.Width() == 1 ? x.Height() : x.Width() );
    if( U.Width() != xLength )
        LogicError("Nonconformal TrsvUN");
#endif
    const Grid& g = U.Grid();

    if( x.Width() == 1 )
    {
        // Matrix views 
        DistMatrix<F> U01(g),
                      U11(g);
        DistMatrix<F> 
            xT(g),  x0(g),
            xB(g),  x1(g),
                    x2(g);

        // Temporary distributions
        DistMatrix<F,STAR,STAR> U11_STAR_STAR(g);
        DistMatrix<F,STAR,STAR> x1_STAR_STAR(g);
        DistMatrix<F,MR,  STAR> x1_MR_STAR(g);
        DistMatrix<F,MC,  STAR> z_MC_STAR(g);

        // Views of z[MC,* ], which will store updates to x
        DistMatrix<F,MC,STAR> z0_MC_STAR(g),
                              z1_MC_STAR(g);

        z_MC_STAR.AlignWith( U );
        Zeros( z_MC_STAR, x.Height(), 1 );

        // Start the algorithm
        PartitionUp
        ( x, xT,
             xB, 0 );
        while( xT.Height() > 0 )
        {
            RepartitionUp
            ( xT,  x0,
                   x1,
             /**/ /**/
              xB,  x2 );

            const Int n0 = x0.Height();
            const Int n1 = x1.Height();
            LockedView( U01, U, 0,  n0, n0, n1 );
            LockedView( U11, U, n0, n0, n1, n1 );
            View( z0_MC_STAR, z_MC_STAR, 0,  0, n0, 1 );
            View( z1_MC_STAR, z_MC_STAR, n0, 0, n1, 1 );

            x1_MR_STAR.AlignWith( U01 );
            //----------------------------------------------------------------//
            if( x2.Height() != 0 )
                x1.SumScatterUpdate( F(1), z1_MC_STAR );

            x1_STAR_STAR = x1;
            U11_STAR_STAR = U11;
            Trsv
            ( UPPER, NORMAL, diag,
              U11_STAR_STAR.LockedMatrix(),
              x1_STAR_STAR.Matrix() );
            x1 = x1_STAR_STAR;

            x1_MR_STAR = x1_STAR_STAR;
            LocalGemv( NORMAL, F(-1), U01, x1_MR_STAR, F(1), z0_MC_STAR );
            //----------------------------------------------------------------//

            SlidePartitionUp
            ( xT,  x0,
             /**/ /**/
                   x1,
              xB,  x2 );
        }
    }
    else
    {
        // Matrix views 
        DistMatrix<F> U01(g),
                      U11(g);
        DistMatrix<F> 
            xL(g), xR(g),
            x0(g), x1(g), x2(g);

        // Temporary distributions
        DistMatrix<F,STAR,STAR> U11_STAR_STAR(g);
        DistMatrix<F,STAR,STAR> x1_STAR_STAR(g);
        DistMatrix<F,STAR,MR  > x1_STAR_MR(g);
        DistMatrix<F,MC,  MR  > z1(g);
        DistMatrix<F,MR,  MC  > z1_MR_MC(g);
        DistMatrix<F,STAR,MC  > z_STAR_MC(g);

        // Views of z[* ,MC]
        DistMatrix<F,STAR,MC> z0_STAR_MC(g), z1_STAR_MC(g);

        z_STAR_MC.AlignWith( U );
        Zeros( z_STAR_MC, 1, x.Width() );

        // Start the algorithm
        PartitionLeft( x,  xL, xR, 0 );
        while( xL.Width() > 0 )
        {
            RepartitionLeft
            ( xL,     /**/ xR,
              x0, x1, /**/ x2 );

            const Int n0 = x0.Width();
            const Int n1 = x1.Width();
            LockedView( U01, U, 0,  n0, n0, n1 );
            LockedView( U11, U, n0, n0, n1, n1 );
            View( z0_STAR_MC, z_STAR_MC, 0, 0,  1, n0 );
            View( z1_STAR_MC, z_STAR_MC, 0, n0, 1, n1 );

            x1_STAR_MR.AlignWith( U01 );
            z1.AlignWith( x1 );
            //----------------------------------------------------------------//
            if( x2.Width() != 0 )
            {
                z1_MR_MC.SumScatterFrom( z1_STAR_MC );
                z1 = z1_MR_MC;
                Axpy( F(1), z1, x1 );
            }

            x1_STAR_STAR = x1;
            U11_STAR_STAR = U11;
            Trsv
            ( UPPER, NORMAL, diag,
              U11_STAR_STAR.LockedMatrix(),
              x1_STAR_STAR.Matrix() );
            x1 = x1_STAR_STAR;

            x1_STAR_MR = x1_STAR_STAR;
            LocalGemv( NORMAL, F(-1), U01, x1_STAR_MR, F(1), z0_STAR_MC );
            //----------------------------------------------------------------//

            SlidePartitionLeft
            ( xL, /**/ xR,
              x0, /**/ x1, x2 );
        }
    }
}
Exemple #13
0
Eigen::MatrixXd RmullwlskCCsort2( const Eigen::Map<Eigen::VectorXd> & bw, const std::string kernel_type, const Eigen::Map<Eigen::MatrixXd> & tPairs, const Eigen::Map<Eigen::MatrixXd> & cxxn, const Eigen::Map<Eigen::VectorXd> & win,  const Eigen::Map<Eigen::VectorXd> & xgrid, const Eigen::Map<Eigen::VectorXd> & ygrid, const bool & bwCheck){ 
// Assumes the first row of tPairs is sorted in increasing order.
  // tPairs : xin (in MATLAB code)
  // cxxn : yin (in MATLAB code)
  // xgrid: out1 (in MATLAB code)
  // ygrid: out2 (in MATLAB code)
  // bwCheck : boolean/ cause the function to simply run the bandwidth check.

  const double invSqrt2pi=  1./(sqrt(2.*M_PI));

  // Map the kernel name so we can use switches  
  std::map<std::string,int> possibleKernels; 
  possibleKernels["epan"]    = 1;   possibleKernels["rect"]    = 2;
  possibleKernels["gauss"]   = 3;   possibleKernels["gausvar"] = 4; 
  possibleKernels["quar"]    = 5; 
   
  // The following test is here for completeness, we mightwant to move it up a 
  // level (in the wrapper) in the future. 

  // If the kernel_type key exists set KernelName appropriately
  int KernelName = 0;
  if ( possibleKernels.count( kernel_type ) != 0){ 
    KernelName = possibleKernels.find( kernel_type )->second; //Set kernel choice
  } else {
  // otherwise use "epan"as the kernel_type 
    //Rcpp::Rcout << "Kernel_type argument was not set correctly; Epanechnikov kernel used." << std::endl;
    Rcpp::warning("Kernel_type argument was not set correctly; Epanechnikov kernel used.");
    KernelName = possibleKernels.find( "epan" )->second;;
  }

  // Check that we do not have zero weights // Should do a try-catch here
  // Again this might be best moved a level-up. 
  if ( !(win.all()) ){  // 
    Rcpp::Rcout << "Cases with zero-valued windows are not yet implemented" << std::endl;
    return (tPairs);
  } 

  // ProfilerStart("sort.log");
  // Start the actual smoother here  
  const unsigned int xgridN = xgrid.size();  
  const unsigned int ygridN = ygrid.size();  
  const unsigned int n = tPairs.cols();
  
  // For sorted x1
  Eigen::VectorXd x1(tPairs.row(0).transpose());
  const double* tDat = x1.data();
  
  Eigen::MatrixXd mu(xgrid.size(), ygrid.size());
  mu.setZero();    


  for (unsigned int i = 0; i != xgridN; ++i) {  
    const double xl = xgrid(i) - bw(0) - 1e-6, 
                 xu = xgrid(i) + bw(0) + 1e-6;

    unsigned int indl = std::lower_bound(tDat, tDat + n, xl) - tDat,  
                 indu = std::upper_bound(tDat, tDat + n, xu) - tDat;

    // sort the y index
    std::vector<valIndPair> yval(indu - indl);
    for (unsigned int k = 0; k < yval.size(); ++k){
      yval[k] = std::make_pair(tPairs(1, k + indl), k + indl);
    }
    std::sort<std::vector<valIndPair>::iterator>(yval.begin(), yval.end(), compPair);

    std::vector<valIndPair>::iterator ylIt = yval.begin(), 
                                      yuIt = yval.begin();

    for (unsigned int j = 0; j != ygridN; ++j) { 
      const double yl = ygrid(j) - bw(1) - 1e-6, 
                   yu = ygrid(j) + bw(1) + 1e-6;

      //locating local window (LOL) (bad joke)
      std::vector <unsigned int> indx; 
      
      //if the kernel is not Gaussian
      if ( KernelName != 3) { 
      // Search the lower and upper bounds increasingly.
        ylIt = std::lower_bound(ylIt, yval.end(), valIndPair(yl, 0), compPair);
        yuIt = std::upper_bound(yuIt, yval.end(), valIndPair(yu, 0), compPair);

        // The following works nice for the Gaussian 
        //  but for very small samples it complains  
        //} else {
        //  ylIt = yval.begin();
        //  yuIt = yval.end();
        //}

        for (std::vector<valIndPair>::iterator y = ylIt; y != yuIt; ++y){ 
          indx.push_back(y->second);
        } 
      } else { //When we finally get c++11 we will use std::iota
        for( unsigned int y = 0; y != n; ++y){
          indx.push_back(y);
        }
      }

      // for (unsigned int y = 0; y != indx.size(); ++y){
      //  Rcpp::Rcout << "indx.at(y):  " << indx.at(y)<< ", ";
      //  }
      unsigned int indxSize = indx.size();
      Eigen::VectorXd lw(indxSize);  
      Eigen::VectorXd ly(indxSize);
      Eigen::MatrixXd lx(2,indxSize);

      for (unsigned int u = 0; u !=indxSize; ++u){ 
        lx.col(u) = tPairs.col(indx[u]); 
        lw(u) = win(indx[u]); 
        ly(u) = cxxn(indx[u]); 
      }

      // check enough points are in the local window 
      unsigned int meter=1;  
      for (unsigned int u =0; u< indxSize; ++u) { 
        for (unsigned int t = u + 1; t < indxSize; ++t) {
          if ( (lx(0,u) !=  lx(0,t) ) || (lx(1,u) != lx(1,t) ) ) {
            meter++;
          }
        }
        if (meter >= 3) { 
          break; 
        }
      }
    
      //computing weight matrix 
      if (meter >=  3 && !bwCheck) { 
        Eigen::VectorXd temp(indxSize);
        Eigen::MatrixXd llx(2, indxSize );  
        llx.row(0) = (lx.row(0).array() - xgrid(i))/bw(0);  
        llx.row(1) = (lx.row(1).array() - ygrid(j))/bw(1); 

        //define the kernel used 

        switch (KernelName){
          case 1: // Epan
            temp=  ((1-llx.row(0).array().pow(2))*(1- llx.row(1).array().pow(2))).array() * 
                   ((9./16)*lw).transpose().array(); 
            break;  
          case 2 : // Rect
            temp=(lw.array())*.25 ; 
            break;
          case 3 : // Gauss
            temp = ((-.5*(llx.row(1).array().pow(2))).exp()) * invSqrt2pi  *   
                   ((-.5*(llx.row(0).array().pow(2))).exp()) * invSqrt2pi  *
                   (lw.transpose().array()); 
            break;
          case 4 : // GausVar
            temp = (lw.transpose().array()) * 
		   ((-0.5 * llx.row(0).array().pow(2)).array().exp() * invSqrt2pi).array() *
                   ((-0.5 * llx.row(1).array().pow(2)).array().exp() * invSqrt2pi).array() * 
                   (1.25 - (0.25 * (llx.row(0).array().pow(2))).array())  * 
                   (1.50 - (0.50 * (llx.row(1).array().pow(2))).array()); 
            break;
          case 5 :  // Quar
              temp = (lw.transpose().array()) * 
                     ((1.-llx.row(0).array().pow(2)).array().pow(2)).array() *
                     ((1.-llx.row(1).array().pow(2)).array().pow(2)).array() * (225./256.);
            break;
        } 

        // make the design matrix
        Eigen::MatrixXd X(indxSize ,3);
        X.setOnes();    
        X.col(1) = lx.row(0).array() - xgrid(i);
        X.col(2) = lx.row(1).array() - ygrid(j); 
        Eigen::LDLT<Eigen::MatrixXd> ldlt_XTWX(X.transpose() * temp.asDiagonal() *X);
        // The solver should stop if the value is NaN. See the HOLE example in gcvlwls2dV2.
        Eigen::VectorXd beta = ldlt_XTWX.solve(X.transpose() * temp.asDiagonal() * ly);  
        mu(i,j)=beta(0); 
      } 
      // else if(meter < 3){
        // // Rcpp::Rcout <<"The meter value is:" << meter << std::endl;  
        // if (bwCheck) {
            // Eigen::MatrixXd checker(1,1);
            // checker(0,0) = 0.;
            // return(checker);
        // } else {
            // Rcpp::stop("No enough points in local window, please increase bandwidth.");
        // }
      // }
    }
  }

  if (bwCheck){
     Eigen::MatrixXd checker(1,1); 
     checker(0,0) = 1.; 
     return(checker);
  } 
      
// ProfilerStop();
  return ( mu ); 
}
Exemple #14
0
template<class _t, class _rt, class _it> _t rect<_t, _rt, _it>::center_x() {
	adjust_to_concept(); 
	return (x0() + x1()) / 2; 
}
Exemple #15
0
void MathPlot::setupSincScatterDemo(QCustomPlot *customPlot)
{

  customPlot->legend->setVisible(true);
  customPlot->legend->setFont(QFont("Helvetica",9));
  // set locale to english, so we get english decimal separator:
  customPlot->setLocale(QLocale(QLocale::English, QLocale::UnitedKingdom));
  // add confidence band graphs:
  customPlot->addGraph();
  QPen pen;
  pen.setStyle(Qt::DotLine);
  pen.setWidth(1);
  pen.setColor(QColor(180,180,180));
  customPlot->graph(0)->setName("Confidence Band 68%");
  customPlot->graph(0)->setPen(pen);
  customPlot->graph(0)->setBrush(QBrush(QColor(255,50,30,20)));
  customPlot->addGraph();
  customPlot->legend->removeItem(customPlot->legend->itemCount()-1); // don't show two confidence band graphs in legend
  customPlot->graph(1)->setPen(pen);
  customPlot->graph(0)->setChannelFillGraph(customPlot->graph(1));
  // add theory curve graph:
  customPlot->addGraph();
  pen.setStyle(Qt::DashLine);
  pen.setWidth(2);
  pen.setColor(Qt::red);
  customPlot->graph(2)->setPen(pen);
  customPlot->graph(2)->setName("Theory Curve");
  // add data point graph:
  customPlot->addGraph();
  customPlot->graph(3)->setPen(QPen(Qt::blue));
  customPlot->graph(3)->setLineStyle(QCPGraph::lsNone);
  customPlot->graph(3)->setScatterStyle(QCPScatterStyle(QCPScatterStyle::ssCross, 4));
  customPlot->graph(3)->setErrorType(QCPGraph::etValue);
  customPlot->graph(3)->setErrorPen(QPen(QColor(180,180,180)));
  customPlot->graph(3)->setName("Measurement");

  // generate ideal sinc curve data and some randomly perturbed data for scatter plot:
  QVector<double> x0(250), y0(250);
  QVector<double> yConfUpper(250), yConfLower(250);
  for (int i=0; i<250; ++i)
  {
    x0[i] = (i/249.0-0.5)*30+0.01; // by adding a small offset we make sure not do divide by zero in next code line
    y0[i] = sin(x0[i])/x0[i]; // sinc function
    yConfUpper[i] = y0[i]+0.15;
    yConfLower[i] = y0[i]-0.15;
    x0[i] *= 1000;
  }
  QVector<double> x1(50), y1(50), y1err(50);
  for (int i=0; i<50; ++i)
  {
    // generate a gaussian distributed random number:
    double tmp1 = rand()/(double)RAND_MAX;
    double tmp2 = rand()/(double)RAND_MAX;
    double r = sqrt(-2*log(tmp1))*cos(2*M_PI*tmp2); // box-muller transform for gaussian distribution
    // set y1 to value of y0 plus a random gaussian pertubation:
    x1[i] = (i/50.0-0.5)*30+0.25;
    y1[i] = sin(x1[i])/x1[i]+r*0.15;
    x1[i] *= 1000;
    y1err[i] = 0.15;
  }
  // pass data to graphs and let QCustomPlot determine the axes ranges so the whole thing is visible:
  customPlot->graph(0)->setData(x0, yConfUpper);
  customPlot->graph(1)->setData(x0, yConfLower);
  customPlot->graph(2)->setData(x0, y0);
  customPlot->graph(3)->setDataValueError(x1, y1, y1err);
  customPlot->graph(2)->rescaleAxes();
  customPlot->graph(3)->rescaleAxes(true);
  // setup look of bottom tick labels:
  customPlot->xAxis->setTickLabelRotation(30);
  customPlot->xAxis->setAutoTickCount(9);
  customPlot->xAxis->setNumberFormat("ebc");
  customPlot->xAxis->setNumberPrecision(1);
  customPlot->xAxis->moveRange(-10);
  // make top right axes clones of bottom left axes. Looks prettier:
  customPlot->axisRect()->setupFullAxesBox();
}
Exemple #16
0
	void ApplyNonMaximumSuppresion(std::vector< LkTracker* >& in_out_source, float in_nms_threshold)
	{
		if (in_out_source.empty())
			return;

		unsigned int size = in_out_source.size();

		std::vector<float> area(size);
		std::vector<float> scores(size);
		std::vector<int> x1(size);
		std::vector<int> y1(size);
		std::vector<int> x2(size);
		std::vector<int> y2(size);
		std::vector<unsigned int> indices(size);
		std::vector<bool> is_suppresed(size);

		for(unsigned int i = 0; i< in_out_source.size(); i++)
		{
			ObjectDetection tmp = in_out_source[i]->GetTrackedObject();
			area[i] = tmp.rect.width * tmp.rect.height;
			if (area[i]>0)
				is_suppresed[i] = false;
			else
			{
				is_suppresed[i] = true;
				in_out_source[i]->NullifyLifespan();
			}
			indices[i] = i;
			scores[i] = tmp.score;
			x1[i] = tmp.rect.x;
			y1[i] = tmp.rect.y;
			x2[i] = tmp.rect.width + tmp.rect.x;
			y2[i] = tmp.rect.height + tmp.rect.y;
		}

		Sort(area, indices);//returns indices ordered based on scores

		for(unsigned int i=0; i< size; i++)
		{

			for(unsigned int j= i+1; j< size; j++)
			{
				if(is_suppresed[indices[i]] || is_suppresed[indices[j]])
					continue;
				int x1_max = std::max(x1[indices[i]], x1[indices[j]]);
				int x2_min = std::min(x2[indices[i]], x2[indices[j]]);
				int y1_max = std::max(y1[indices[i]], y1[indices[j]]);
				int y2_min = std::min(y2[indices[i]], y2[indices[j]]);
				int overlap_width = x2_min - x1_max + 1;
				int overlap_height = y2_min - y1_max + 1;
				if(overlap_width > 0 && overlap_height>0)
				{
					float overlap_part = (overlap_width*overlap_height)/area[indices[j]];
					if(overlap_part > in_nms_threshold)
					{
						is_suppresed[indices[j]] = true;
						in_out_source[indices[j]]->NullifyLifespan();
						if (in_out_source[indices[j]]->GetFrameCount() > in_out_source[indices[i]]->GetFrameCount())
						{
							in_out_source[indices[i]]->object_id = in_out_source[indices[j]]->object_id;
						}

					}
				}
			}
		}
		return ;
	}
Exemple #17
0
void MathPlot::setupMultiAxisDemo(QCustomPlot *customPlot)
{
  customPlot->setInteractions(QCP::iRangeDrag | QCP::iRangeZoom);

  customPlot->setLocale(QLocale(QLocale::English, QLocale::UnitedKingdom)); // period as decimal separator and comma as thousand separator
  customPlot->legend->setVisible(true);
  QFont legendFont = font();  // start out with MainWindow's font..
  legendFont.setPointSize(9); // and make a bit smaller for legend
  customPlot->legend->setFont(legendFont);
  customPlot->legend->setBrush(QBrush(QColor(255,255,255,230)));
  // by default, the legend is in the inset layout of the main axis rect. So this is how we access it to change legend placement:
  customPlot->axisRect()->insetLayout()->setInsetAlignment(0, Qt::AlignBottom|Qt::AlignRight);

  // setup for graph 0: key axis left, value axis bottom
  // will contain left maxwell-like function
  customPlot->addGraph(customPlot->yAxis, customPlot->xAxis);
  customPlot->graph(0)->setPen(QPen(QColor(255, 100, 0)));
  customPlot->graph(0)->setBrush(QBrush(QPixmap("://skin/images/balboa.jpg"))); // fill with texture of specified image
  customPlot->graph(0)->setLineStyle(QCPGraph::lsLine);
  customPlot->graph(0)->setScatterStyle(QCPScatterStyle(QCPScatterStyle::ssDisc, 5));
  customPlot->graph(0)->setName("Left maxwell function");

  // setup for graph 1: key axis bottom, value axis left (those are the default axes)
  // will contain bottom maxwell-like function
  customPlot->addGraph();
  customPlot->graph(1)->setPen(QPen(Qt::red));
  customPlot->graph(1)->setBrush(QBrush(QPixmap("://skin/images/balboa.jpg"))); // same fill as we used for graph 0
  customPlot->graph(1)->setLineStyle(QCPGraph::lsStepCenter);
  customPlot->graph(1)->setScatterStyle(QCPScatterStyle(QCPScatterStyle::ssCircle, Qt::red, Qt::white, 7));
  customPlot->graph(1)->setErrorType(QCPGraph::etValue);
  customPlot->graph(1)->setName("Bottom maxwell function");

  // setup for graph 2: key axis top, value axis right
  // will contain high frequency sine with low frequency beating:
  customPlot->addGraph(customPlot->xAxis2, customPlot->yAxis2);
  customPlot->graph(2)->setPen(QPen(Qt::blue));
  customPlot->graph(2)->setName("High frequency sine");

  // setup for graph 3: same axes as graph 2
  // will contain low frequency beating envelope of graph 2
  customPlot->addGraph(customPlot->xAxis2, customPlot->yAxis2);
  QPen blueDotPen;
  blueDotPen.setColor(QColor(30, 40, 255, 150));
  blueDotPen.setStyle(Qt::DotLine);
  blueDotPen.setWidthF(4);
  customPlot->graph(3)->setPen(blueDotPen);
  customPlot->graph(3)->setName("Sine envelope");

  // setup for graph 4: key axis right, value axis top
  // will contain parabolically distributed data points with some random perturbance
  customPlot->addGraph(customPlot->yAxis2, customPlot->xAxis2);
  customPlot->graph(4)->setPen(QColor(50, 50, 50, 255));
  customPlot->graph(4)->setLineStyle(QCPGraph::lsNone);
  customPlot->graph(4)->setScatterStyle(QCPScatterStyle(QCPScatterStyle::ssCircle, 4));
  customPlot->graph(4)->setName("Some random data around\na quadratic function");

  // generate data, just playing with numbers, not much to learn here:
  QVector<double> x0(25), y0(25);
  QVector<double> x1(15), y1(15), y1err(15);
  QVector<double> x2(250), y2(250);
  QVector<double> x3(250), y3(250);
  QVector<double> x4(250), y4(250);
  for (int i=0; i<25; ++i) // data for graph 0
  {
    x0[i] = 3*i/25.0;
    y0[i] = exp(-x0[i]*x0[i]*0.8)*(x0[i]*x0[i]+x0[i]);
  }
  for (int i=0; i<15; ++i) // data for graph 1
  {
    x1[i] = 3*i/15.0;;
    y1[i] = exp(-x1[i]*x1[i])*(x1[i]*x1[i])*2.6;
    y1err[i] = y1[i]*0.25;
  }
  for (int i=0; i<250; ++i) // data for graphs 2, 3 and 4
  {
    x2[i] = i/250.0*3*M_PI;
    x3[i] = x2[i];
    x4[i] = i/250.0*100-50;
    y2[i] = sin(x2[i]*12)*cos(x2[i])*10;
    y3[i] = cos(x3[i])*10;
    y4[i] = 0.01*x4[i]*x4[i] + 1.5*(rand()/(double)RAND_MAX-0.5) + 1.5*M_PI;
  }

  // pass data points to graphs:
  customPlot->graph(0)->setData(x0, y0);
  customPlot->graph(1)->setDataValueError(x1, y1, y1err);
  customPlot->graph(2)->setData(x2, y2);
  customPlot->graph(3)->setData(x3, y3);
  customPlot->graph(4)->setData(x4, y4);
  // activate top and right axes, which are invisible by default:
  customPlot->xAxis2->setVisible(true);
  customPlot->yAxis2->setVisible(true);
  // set ranges appropriate to show data:
  customPlot->xAxis->setRange(0, 2.7);
  customPlot->yAxis->setRange(0, 2.6);
  customPlot->xAxis2->setRange(0, 3.0*M_PI);
  customPlot->yAxis2->setRange(-70, 35);
  // set pi ticks on top axis:
  QVector<double> piTicks;
  QVector<QString> piLabels;
  piTicks << 0  << 0.5*M_PI << M_PI << 1.5*M_PI << 2*M_PI << 2.5*M_PI << 3*M_PI;
  piLabels << "0" << QString::fromUtf8("½π") << QString::fromUtf8("π") << QString::fromUtf8("1½π") << QString::fromUtf8("2π") << QString::fromUtf8("2½π") << QString::fromUtf8("3π");
  customPlot->xAxis2->setAutoTicks(false);
  customPlot->xAxis2->setAutoTickLabels(false);
  customPlot->xAxis2->setTickVector(piTicks);
  customPlot->xAxis2->setTickVectorLabels(piLabels);
  // add title layout element:
  customPlot->plotLayout()->insertRow(0);
  customPlot->plotLayout()->addElement(0, 0, new QCPPlotTitle(customPlot, "Way too many graphs in one plot"));
  // set labels:
  customPlot->xAxis->setLabel("Bottom axis with outward ticks");
  customPlot->yAxis->setLabel("Left axis label");
  customPlot->xAxis2->setLabel("Top axis label");
  customPlot->yAxis2->setLabel("Right axis label");
  // make ticks on bottom axis go outward:
  customPlot->xAxis->setTickLength(0, 5);
  customPlot->xAxis->setSubTickLength(0, 3);
  // make ticks on right axis go inward and outward:
  customPlot->yAxis2->setTickLength(3, 3);
  customPlot->yAxis2->setSubTickLength(1, 1);
}
Exemple #18
0
    void IncNavierStokes::v_InitObject()
    {
        AdvectionSystem::v_InitObject();

        int i,j;
        int numfields = m_fields.num_elements();
        std::string velids[] = {"u","v","w"};

        // Set up Velocity field to point to the first m_expdim of m_fields; 
        m_velocity = Array<OneD,int>(m_spacedim);

        for(i = 0; i < m_spacedim; ++i)
        {
            for(j = 0; j < numfields; ++j)
            {
                std::string var = m_boundaryConditions->GetVariable(j);
                if(boost::iequals(velids[i], var))
                {
                    m_velocity[i] = j;
                    break;
                }

                ASSERTL0(j != numfields, "Failed to find field: " + var);
            }
        }

        // Set up equation type enum using kEquationTypeStr
        for(i = 0; i < (int) eEquationTypeSize; ++i)
        {
            bool match;
            m_session->MatchSolverInfo("EQTYPE",kEquationTypeStr[i],match,false);
            if(match)
            {
                m_equationType = (EquationType)i; 
                break;
            }
        }
        ASSERTL0(i != eEquationTypeSize,"EQTYPE not found in SOLVERINFO section");
        
        // This probably should to into specific implementations 
        // Equation specific Setups 
        switch(m_equationType)
        {
        case eSteadyStokes: 
        case eSteadyOseen: 
        case eSteadyNavierStokes:
        case eSteadyLinearisedNS: 
            break;
        case eUnsteadyNavierStokes:
        case eUnsteadyStokes:
            {
                m_session->LoadParameter("IO_InfoSteps", m_infosteps, 0);
                m_session->LoadParameter("IO_CFLSteps", m_cflsteps, 0);
                m_session->LoadParameter("SteadyStateSteps", m_steadyStateSteps, 0);
                m_session->LoadParameter("SteadyStateTol", m_steadyStateTol, 1e-6);
            
                // check to see if any user defined boundary condition is
                // indeed implemented
                
                for(int n = 0; n < m_fields[0]->GetBndConditions().num_elements(); ++n)
                {    
                    std::string type =m_fields[0]->GetBndConditions()[n]->GetUserDefined();
                    if(!type.empty())
                        // Time Dependent Boundary Condition (if no user
                        // defined then this is empty)
                        ASSERTL0 (boost::iequals(type,"Wall_Forces")   ||
                                  boost::iequals(type,"TimeDependent") ||
                                  boost::iequals(type,"MovingBody")    ||
                                  boost::iequals(type,"Radiation")     ||
                                  boost::iequals(type,"I")             ||
                                  boost::iequals(type,"HOutflow"),
                                  "Unknown USERDEFINEDTYPE boundary condition");
                }
            }
            break;
        case eNoEquationType:
        default:
            ASSERTL0(false,"Unknown or undefined equation type");
        }
        
        m_session->LoadParameter("Kinvis", m_kinvis);
        
        // Default advection type per solver
        std::string vConvectiveType;
        switch(m_equationType)
        {
            case eUnsteadyStokes:
                vConvectiveType = "NoAdvection";
                break;
            case eUnsteadyNavierStokes:
            case eSteadyNavierStokes:
                vConvectiveType = "Convective";
                break;
            case eUnsteadyLinearisedNS:
                vConvectiveType = "Linearised";
                break;
            default:
                break;
        }

        // Check if advection type overridden
        if (m_session->DefinesTag("AdvectiveType") && m_equationType != eUnsteadyStokes)
        {
            vConvectiveType = m_session->GetTag("AdvectiveType");
        }

        // Initialise advection
        m_advObject = SolverUtils::GetAdvectionFactory().CreateInstance(vConvectiveType, vConvectiveType);
        m_advObject->InitObject( m_session, m_fields);
        
        // Forcing terms
        m_forcing = SolverUtils::Forcing::Load(m_session, m_fields,
                                               v_GetForceDimension());

        // check to see if any Robin boundary conditions and if so set
        // up m_field to boundary condition maps;
        m_fieldsBCToElmtID  = Array<OneD, Array<OneD, int> >(numfields);
        m_fieldsBCToTraceID = Array<OneD, Array<OneD, int> >(numfields);
        m_fieldsRadiationFactor  = Array<OneD, Array<OneD, NekDouble> > (numfields);
        
        for (i = 0; i < m_fields.num_elements(); ++i)
        {
            bool Set = false;

            Array<OneD, const SpatialDomains::BoundaryConditionShPtr > BndConds;
            Array<OneD, MultiRegions::ExpListSharedPtr>  BndExp;
            int radpts = 0;
            
            BndConds = m_fields[i]->GetBndConditions();
            BndExp   = m_fields[i]->GetBndCondExpansions();
            for(int n = 0; n < BndConds.num_elements(); ++n)
            {    
                if(boost::iequals(BndConds[n]->GetUserDefined(),"Radiation"))
                {
                    ASSERTL0(BndConds[n]->GetBoundaryConditionType() == SpatialDomains::eRobin,
                             "Radiation boundary condition must be of type Robin <R>");
                    
                    if(Set == false)
                    {
                        m_fields[i]->GetBoundaryToElmtMap(m_fieldsBCToElmtID[i],m_fieldsBCToTraceID[i]);
                        Set = true;
                    }
                    radpts += BndExp[n]->GetTotPoints();
                }
            }

            m_fieldsRadiationFactor[i] = Array<OneD, NekDouble>(radpts);

            radpts = 0; // reset to use as a counter

            for(int n = 0; n < BndConds.num_elements(); ++n)
            {    
                if(boost::iequals(BndConds[n]->GetUserDefined(),"Radiation"))
                {
                    
                    int npoints    = BndExp[n]->GetNpoints();
                    Array<OneD, NekDouble> x0(npoints,0.0);
                    Array<OneD, NekDouble> x1(npoints,0.0);
                    Array<OneD, NekDouble> x2(npoints,0.0);
                    Array<OneD, NekDouble> tmpArray;

                    BndExp[n]->GetCoords(x0,x1,x2);
                    
                    LibUtilities::Equation coeff = 
                        boost::static_pointer_cast<
                    SpatialDomains::RobinBoundaryCondition
                        >(BndConds[n])->m_robinPrimitiveCoeff;
                    
                    coeff.Evaluate(x0,x1,x2,m_time, 
                                   tmpArray = m_fieldsRadiationFactor[i]+ radpts);
                    //Vmath::Neg(npoints,tmpArray = m_fieldsRadiationFactor[i]+ radpts,1);
                    radpts += npoints;
                }
            }
        }

        // Set up Field Meta Data for output files
        m_fieldMetaDataMap["Kinvis"] = boost::lexical_cast<std::string>(m_kinvis);
        m_fieldMetaDataMap["TimeStep"] = boost::lexical_cast<std::string>(m_timestep);
    }
void AdminWindow::addCustomPlot(QCustomPlot *customPlot)
{

    // generate some data:
    QVector<double> x1(101), y1(101); // initialize with entries 0..100
    for (int i=0; i<101; ++i)
    {
      x1[i] = i/50.0 - 1; // x goes from -1 to 1
      y1[i] = x1[i]*x1[i];  // let's plot a quadratic function
    }
//    // create graph and assign data to it:
//    customPlot->addGraph();
//    customPlot->graph(0)->setData(x, y);
//    // give the axes some labels:
//    customPlot->xAxis->setLabel("x");
//    customPlot->yAxis->setLabel("y");
//    // set axes ranges, so we see all data:
//    customPlot->xAxis->setRange(-1, 1);
//    customPlot->yAxis->setRange(0, 1);

    QCPGraph *graph1 = customPlot->addGraph();
    graph1->setData(x1, y1);
    graph1->setPen(Qt::NoPen);
    graph1->setBrush(QColor(70, 165, 255, 150));

    customPlot->addLayer("abovemain", customPlot->layer("main"), QCustomPlot::limAbove);
    customPlot->addLayer("belowmain", customPlot->layer("main"), QCustomPlot::limBelow);
    graph1->setLayer("abovemain");
    customPlot->xAxis->grid()->setLayer("belowmain");
    customPlot->yAxis->grid()->setLayer("belowmain");

    // set some pens, brushes and backgrounds:
    customPlot->xAxis->setBasePen(QPen(Qt::white, 1));
    customPlot->yAxis->setBasePen(QPen(Qt::white, 1));
    customPlot->xAxis->setTickPen(QPen(Qt::white, 1));
    customPlot->yAxis->setTickPen(QPen(Qt::white, 1));
    customPlot->xAxis->setSubTickPen(QPen(Qt::white, 1));
    customPlot->yAxis->setSubTickPen(QPen(Qt::white, 1));
    customPlot->xAxis->setTickLabelColor(Qt::white);
    customPlot->yAxis->setTickLabelColor(Qt::white);
    customPlot->xAxis->grid()->setPen(QPen(QColor(140, 140, 140), 1, Qt::DotLine));
    customPlot->yAxis->grid()->setPen(QPen(QColor(140, 140, 140), 1, Qt::DotLine));
    customPlot->xAxis->grid()->setSubGridPen(QPen(QColor(80, 80, 80), 1, Qt::DotLine));
    customPlot->yAxis->grid()->setSubGridPen(QPen(QColor(80, 80, 80), 1, Qt::DotLine));
    customPlot->xAxis->grid()->setSubGridVisible(true);
    customPlot->yAxis->grid()->setSubGridVisible(true);
    customPlot->xAxis->grid()->setZeroLinePen(Qt::NoPen);
    customPlot->yAxis->grid()->setZeroLinePen(Qt::NoPen);
    customPlot->xAxis->setUpperEnding(QCPLineEnding::esSpikeArrow);
    customPlot->yAxis->setUpperEnding(QCPLineEnding::esSpikeArrow);
    QLinearGradient plotGradient;
    plotGradient.setStart(0, 0);
    plotGradient.setFinalStop(0, 350);
    plotGradient.setColorAt(0, QColor(80, 80, 80));
    plotGradient.setColorAt(1, QColor(50, 50, 50));
    customPlot->setBackground(plotGradient);
    QLinearGradient axisRectGradient;
    axisRectGradient.setStart(0, 0);
    axisRectGradient.setFinalStop(0, 350);
    axisRectGradient.setColorAt(0, QColor(80, 80, 80));
    axisRectGradient.setColorAt(1, QColor(30, 30, 30));
    customPlot->axisRect()->setBackground(axisRectGradient);

    customPlot->rescaleAxes();
    customPlot->yAxis->setRange(0, 2);

}
	void EXPORT_API ProjectTetrasShapeMatchingJB(btVector3* initialPositions, btVector3* predPositions, float* invMasses, bool* posLocks, int* tetsPerVertex, Tetrahedron* tetras, btVector3* restCMs, float* invRestMat, int tetrasCount, float Ks_prime)
	{

		for (int i = 0; i < tetrasCount; i++)
		{
			Tetrahedron tetra = tetras[i];
			if (tetra.restVolume == 0.0f)
				continue;

			Eigen::Vector3f x1_0(initialPositions[tetra.idA].x(), initialPositions[tetra.idA].y(), initialPositions[tetra.idA].z());
			Eigen::Vector3f x2_0(initialPositions[tetra.idB].x(), initialPositions[tetra.idB].y(), initialPositions[tetra.idB].z());
			Eigen::Vector3f x3_0(initialPositions[tetra.idC].x(), initialPositions[tetra.idC].y(), initialPositions[tetra.idC].z());
			Eigen::Vector3f x4_0(initialPositions[tetra.idD].x(), initialPositions[tetra.idD].y(), initialPositions[tetra.idD].z());

			Eigen::Vector3f x1(predPositions[tetra.idA].x(), predPositions[tetra.idA].y(), predPositions[tetra.idA].z());
			Eigen::Vector3f x2(predPositions[tetra.idB].x(), predPositions[tetra.idB].y(), predPositions[tetra.idB].z());
			Eigen::Vector3f x3(predPositions[tetra.idC].x(), predPositions[tetra.idC].y(), predPositions[tetra.idC].z());
			Eigen::Vector3f x4(predPositions[tetra.idD].x(), predPositions[tetra.idD].y(), predPositions[tetra.idD].z());

			float w1 = posLocks[tetra.idA] ? 0.0f : invMasses[tetra.idA];
			float w2 = posLocks[tetra.idB] ? 0.0f : invMasses[tetra.idB];
			float w3 = posLocks[tetra.idC] ? 0.0f : invMasses[tetra.idC];
			float w4 = posLocks[tetra.idD] ? 0.0f : invMasses[tetra.idD];

			Eigen::Vector3f restCM(restCMs[i].x(), restCMs[i].y(), restCMs[i].z());
			Eigen::Matrix3f A;
			A(0, 0) = invRestMat[16 * i + 0]; A(0, 1) = invRestMat[16 * i + 1]; A(0, 2) = invRestMat[16 * i + 2];
			A(1, 0) = invRestMat[16 * i + 4]; A(1, 1) = invRestMat[16 * i + 5]; A(1, 2) = invRestMat[16 * i + 6];
			A(2, 0) = invRestMat[16 * i + 8]; A(2, 1) = invRestMat[16 * i + 9]; A(2, 2) = invRestMat[16 * i + 10];
			//
			//public float m00; 0
			//public float m01; 1
			//public float m02; 2
			//public float m03; 3

			//public float m10; 4
			//public float m11; 5
			//public float m12; 6
			//public float m13; 7

			//public float m20; 8
			//public float m21; 9
			//public float m22; 10
			//public float m23; 11

			//public float m30; 12
			//public float m31; 13
			//public float m32; 14
			//public float m33; 15
			//
			//A(0, 0) = invRestMat[16 * i + 0]; A(0, 1) = invRestMat[16 * i + 4]; A(0, 2) = invRestMat[16 * i + 8];
			//A(1, 0) = invRestMat[16 * i + 1]; A(1, 1) = invRestMat[16 * i + 5]; A(1, 2) = invRestMat[16 * i + 9];
			//A(2, 0) = invRestMat[16 * i + 2]; A(2, 1) = invRestMat[16 * i + 6]; A(2, 2) = invRestMat[16 * i + 10];

			//public float m00; 0
			//public float m10; 1
			//public float m20; 2
			//public float m30; 3
			//public float m01; 4
			//public float m11; 5
			//public float m21; 6
			//public float m31; 7
			//public float m02; 8
			//public float m12; 9
			//public float m22; 10
			//public float m32; 11
			//public float m03; 12
			//public float m13; 13
			//public float m23; 14
			//public float m33; 15


			Eigen::Vector3f x[4] = { x1, x2, x3, x4 };
			Eigen::Vector3f x0[4] = { x1_0, x2_0, x3_0, x4_0 };
			float w[4] = { w1, w2, w3, w4 };
			Eigen::Vector3f corr[4];


			bool res = PBD::PositionBasedDynamics::solveShapeMatchingConstraint(
				x0, x, w, 4,
				restCM,
				A,
				Ks_prime,
				false,
				corr);

			btVector3 dP1 = btVector3(corr[0].x(), corr[0].y(), corr[0].z());
			btVector3 dP2 = btVector3(corr[1].x(), corr[1].y(), corr[1].z());
			btVector3 dP3 = btVector3(corr[2].x(), corr[2].y(), corr[2].z());
			btVector3 dP4 = btVector3(corr[3].x(), corr[3].y(), corr[3].z());

			// Important: Divide position correction by the number of clusters which contain the vertex. 
			//corr1 = (1.0f / vTets[v1].m_numTets) * corr[0];
			//corr2 = (1.0f / vTets[v2].m_numTets) * corr[1];
			//corr3 = (1.0f / vTets[v3].m_numTets) * corr[2];
			//corr4 = (1.0f / vTets[v4].m_numTets) * corr[3];



			if (w1 != 0.0f) 
				predPositions[tetra.idA] += dP1 * (1.0f / (btScalar)tetsPerVertex[tetra.idA]);
			
			if (w2 != 0.0f) 
				predPositions[tetra.idB] += dP2 * (1.0f / (btScalar)tetsPerVertex[tetra.idB]);
			
			if (w3 != 0.0f) 
				predPositions[tetra.idC] += dP3 * (1.0f / (btScalar)tetsPerVertex[tetra.idC]);
			
			if (w4 != 0.0f) 
				predPositions[tetra.idD] += dP4 * (1.0f / (btScalar)tetsPerVertex[tetra.idD]);


		}


		

	}
Flux_Pts Rectang_Object::lmr_all_pts(INT dir) const
{
    Elise_Rect r = box();
    ASSERT_USER((r._dim == 1),"dim != 1 for lmr_all_pts(INT dir)");
    return line_map_rect(dir,x0(),x1());
}
Exemple #22
0
int main(int argc,char* argv[]) {
	if (argc < 4) {
		printf("./match_g2o pose_stamped.txt key.match map_point.txt\n");
		return 1;
	}
	srand(time(NULL));
	Rcl << 1,0,0,0,0,1,0,-1,0;
	Tcl << 0,0.06,0;

	//read pose file
	FILE* pose_stamped = fopen(argv[1],"r");
	if (!pose_stamped)
		return 1;
	char buffer[2048];
	std::vector<Mat3> rotations;
	std::vector<Eigen::Vector3d> translations;
	while (fgets(buffer,2048,pose_stamped)) {
		double t,x,y,z,qx,qy,qz,qw;
		if (sscanf(buffer,"%lf %lf %lf %lf %lf %lf %lf %lf",&t,&x,&y,&z,&qw,&qx,&qy,&qz)==8) {
			double r[9];
			quaternionToRotation(qx,qy,qz,qw,r);
			Mat3 Rwl;
			memcpy(Rwl.data(),r,9*sizeof(double));
			Eigen::Vector3d Twl(x,y,z);
			rotations.push_back(Rcl * Rwl.transpose());
			translations.push_back(- Rcl * Rwl.transpose() * Twl + Tcl);
		} else {
			printf("Error parsing: %s\n",buffer);
		}
	}
	fclose(pose_stamped);

	struct timespec start,end;
	clock_gettime(CLOCK_MONOTONIC,&start);
	int count_points = 0;
	double RMSE = 0;
	FILE* key_match = fopen(argv[2],"r");
	FILE* map_point = fopen(argv[3],"w");
	if (!(key_match && map_point))
		return 1;
	while (fgets(buffer,2048,key_match)) {
#if DEBUG_SINGLE
		printf("key.match: %s",buffer);
#endif
		int id;
		char* tok = strtok(buffer," ");
		std::vector<double> uc,vc;
		std::vector<int> index;
		while (tok) {
			id = atoi(tok);
			index.push_back(id);
			tok = strtok(NULL," \n");
			double u = atof(tok);
			tok = strtok(NULL," \n");
			double v = atof(tok);
			tok = strtok(NULL," \n");
			uc.push_back(u - cx);
			vc.push_back(cy - v);
		}

		//optimize
		Eigen::Vector3d bestEstimate, x1, x2;
		double leastError = -1;
		for (unsigned int i=0;i<index.size()-1;i++) {
			for (unsigned int j=i+1;j<index.size();j++) {
				double u1 = uc[i], v1 = vc[i];
				double u2 = uc[j], v2 = vc[j];
				Mat3 R1 = rotations[index[i]], R2 = rotations[index[j]];
				Eigen::Vector3d T1 = translations[index[i]], T2 = translations[index[j]];
				Mat3 Rcc = R2 * R1.transpose();
				Eigen::Vector3d Tcc = T1 - R1 * R2.transpose() * T2;
				Eigen::Vector3d r1 = Rcc.row(0), r2 = Rcc.row(1), r3 = Rcc.row(2);
				Eigen::Vector3d uv(-u1/fx,-v1/fy,1);
				Eigen::Vector3d mult_u = r1 + u2/fx * r3;
				Eigen::Vector3d mult_v = r2 + v2/fy * r3;
				double z_est[2] = {mult_u.dot(Tcc) / mult_u.dot(uv),
								mult_v.dot(Tcc) / mult_v.dot(uv) } ;
				for (int k=0;k<1;k++) {
					x1 << -u1*z_est[k]/fx, -v1*z_est[k]/fy, z_est[k];
					x2 = Rcc * (x1 - Tcc);
					if (x1(2) >= 0 || x2(2) >= 0)
						break;
					double u_est = -fx * x2(0) / x2(2);
					double v_est = -fy * x2(1) / x2(2);
					double error = (u_est-u2) * (u_est-u2) + (v_est-v2) * (v_est-v2);
					if (leastError < 0 || error < leastError) {
						leastError = error;
						bestEstimate = R1.transpose() * (x1 - T1);
					}
				}
			}
		}
		
		//record result
		RMSE += leastError;
#if DEBUG_SINGLE
		printf("reprojection: ");
		char* c = buffer;
		c += sprintf(c,"transformation:\n");
		for (unsigned int i=0;i<index.size();i++) {
			id = index[i];
			Eigen::Vector3d xc = rotations[id] * bestEstimate + translations[id];
			double u = - fx * xc(0) / xc(2);
			double v = - fy * xc(1) / xc(2);
			printf("%d %f %f ",id,u+cx,cy-v);
			c += sprintf(c,"%4.2f %4.2f %4.2f\n%4.2f %4.2f %4.2f\n%4.2f %4.2f %4.2f\n",
						rotations[id](0,0),rotations[id](0,1),rotations[id](0,2),
						rotations[id](1,0),rotations[id](1,1),rotations[id](1,2),
						rotations[id](2,0),rotations[id](2,1),rotations[id](2,2));
			c += sprintf(c,"[%4.2f %4.2f %4.2f]\n",translations[id](0),translations[id](1),translations[id](2));
		}
		printf("\n%s",buffer);
		printf("estimate: %f %f %f %lu %f\n",bestEstimate(0),bestEstimate(1),bestEstimate(2),index.size(),leastError);
#endif
		fprintf(map_point,"%f %f %f %lu %f\n",bestEstimate(0),bestEstimate(1),bestEstimate(2),index.size(),leastError);
		count_points++;
	}
	clock_gettime(CLOCK_MONOTONIC,&end);
	double dt = end.tv_sec - start.tv_sec + 0.000000001 * (end.tv_nsec - start.tv_nsec);
	RMSE = sqrt(RMSE / count_points);
	printf("Optimized %d map points (%fs, RMSE = %f)\n",count_points, dt, RMSE);
	fclose(key_match);
	fclose(map_point);

	return 0;
}
void vpTemplateTrackerMIInverseCompositional::trackNoPyr(const vpImage<unsigned char> &I)
{
  if(!CompoInitialised)
    std::cout<<"Compositionnal tracking no initialised\nUse InitCompInverse(vpImage<unsigned char> &I) function"<<std::endl;
  dW=0;

  if(blur)
    vpImageFilter::filter(I, BI,fgG,taillef);

  int Nbpoint=0;

  lambda=lambdaDep;
  double MI=0,MIprec=-1000;

  vpColVector p_avant_estimation;p_avant_estimation=p;
  MI_preEstimation=-getCost(I,p);
  NMI_preEstimation=-getNormalizedCost(I,p);

  //    std::cout << "MI avant: " << MI_preEstimation << std::endl;
  //    std::cout << "NMI avant: " << NMI_preEstimation << std::endl;

  initPosEvalRMS(p);

  vpColVector dpinv(nbParam);
  double alpha=2.;

  unsigned int iteration=0;

  //unsigned int bspline_ = (unsigned int) bspline;
  //unsigned int totParam = (bspline_ * bspline_)*(1+nbParam+nbParam*nbParam);

  vpMatrix Hnorm(nbParam,nbParam);

  do
  {
    Nbpoint=0;
    MIprec=MI;
    MI=0;

    zeroProbabilities();

    Warp->computeCoeff(p);

    {
      for(int point=0;point<(int)templateSize;point++)
      {
        vpColVector x1(2),x2(2);
        double i2,j2;
        double IW;
        int cr,ct;
        double er,et;

        x1[0]=(double)ptTemplate[point].x;
        x1[1]=(double)ptTemplate[point].y;

        Warp->computeDenom(x1,p); // A modif pour parallelisation mais ne pose pas de pb avec warp utilises dans DECSA
        Warp->warpX(x1,x2,p);

        j2=x2[0];
        i2=x2[1];

        if((i2>=0)&&(j2>=0)&&(i2<I.getHeight()-1)&&(j2<I.getWidth()-1))
        {

          //if(m_ptCurrentMask == NULL ||(m_ptCurrentMask->getWidth() == I.getWidth() && m_ptCurrentMask->getHeight() == I.getHeight() && (*m_ptCurrentMask)[(unsigned int)i2][(unsigned int)j2] > 128))
          {
            Nbpoint++;
            if(!blur)
              IW=(double)I.getValue(i2,j2);
            else
              IW=BI.getValue(i2,j2);

            ct=ptTemplateSupp[point].ct;
            et=ptTemplateSupp[point].et;
            double tmp = IW*(((double)Nc)-1.f)/255.f;
            cr=(int)tmp;
            er=tmp-(double)cr;

            if( (ApproxHessian==HESSIAN_NONSECOND||hessianComputation==vpTemplateTrackerMI::USE_HESSIEN_DESIRE) && (ptTemplateSelect[point] || !useTemplateSelect) )
            {
              vpTemplateTrackerMIBSpline::PutTotPVBsplineNoSecond(Prt, dPrt, cr, er, ct, et, Ncb, ptTemplate[point].dW, nbParam, bspline);
            }
            else if (ptTemplateSelect[point] || !useTemplateSelect)
            {
              if(bspline==3){
                vpTemplateTrackerMIBSpline::PutTotPVBspline3(Prt, dPrt, d2Prt, cr, er, ct, et, Ncb, ptTemplate[point].dW, nbParam);
              }
              else{
                vpTemplateTrackerMIBSpline::PutTotPVBspline4(Prt, dPrt, d2Prt, cr, er, ct, et, Ncb, ptTemplate[point].dW, nbParam);
              }
            }
            else{
              vpTemplateTrackerMIBSpline::PutTotPVBsplinePrt(Prt, cr, er, ct, et, Ncb,nbParam, bspline);
            }
          }

        }
      }
    }

    if(Nbpoint==0)
    {
      diverge=true;
      MI=0;
      deletePosEvalRMS();
      throw(vpTrackingException(vpTrackingException::notEnoughPointError, "No points in the template"));

    }
    else
    {
      //            computeProba(Nbpoint);

      unsigned int indd, indd2;
      indd = indd2 = 0;
      unsigned int Ncb_ = (unsigned int)Ncb;
      for(unsigned int i=0;i<Ncb_*Ncb_;i++){
        Prt[i]=Prt[i]/Nbpoint;
        for(unsigned int j=0;j<nbParam;j++){
          dPrt[indd]=dPrt[indd]/Nbpoint;
          indd++;
          for(unsigned int k=0;k<nbParam;k++){
            d2Prt[indd2]=d2Prt[indd2]/Nbpoint;
            indd2++;
          }
        }
      }

      computeMI(MI);

      if(hessianComputation!=vpTemplateTrackerMI::USE_HESSIEN_DESIRE){
        computeHessienNormalized(Hnorm);
        computeHessien(H);
      }
      computeGradient();

      vpMatrix::computeHLM(H,lambda,HLM);

      try
      {
        switch(hessianComputation)
        {
        case vpTemplateTrackerMI::USE_HESSIEN_DESIRE:
          dp=gain*HLMdesireInverse*G;
          break;
        case vpTemplateTrackerMI::USE_HESSIEN_BEST_COND:
          if(HLM.cond()>HLMdesire.cond())
            dp=gain*HLMdesireInverse*G;
          else
            dp=gain*0.2*HLM.inverseByLU()*G;
          break;
        default:
          dp=gain*0.2*HLM.inverseByLU()*G;
          break;
        }
      }
      catch(vpException &e)
      {
        //std::cerr<<"probleme inversion"<<std::endl;
        throw(e);
      }
    }

    switch(minimizationMethod)
    {
    case vpTemplateTrackerMIInverseCompositional::USE_LMA:
    {
      vpColVector dp_test_LMA(nbParam);
      vpColVector dpinv_test_LMA(nbParam);
      vpColVector p_test_LMA(nbParam);
      if(ApproxHessian==HESSIAN_NONSECOND)
        dp_test_LMA=-100000.1*dp;
      else
        dp_test_LMA=1.*dp;
      Warp->getParamInverse(dp_test_LMA,dpinv_test_LMA);
      Warp->pRondp(p,dpinv_test_LMA,p_test_LMA);

      MI=-getCost(I,p);
      double MI_LMA=-getCost(I,p_test_LMA);
      if(MI_LMA>MI)
      {
        dp=dp_test_LMA;
        lambda=(lambda/10.<1e-6)?lambda/10.:1e-6;
      }
      else
      {
        dp=0;
        lambda=(lambda*10.<1e6)?1e6:lambda*10.;
      }
    }
      break;
    case vpTemplateTrackerMIInverseCompositional::USE_GRADIENT:
      dp=-gain*0.3*G*20;
      break;

    case vpTemplateTrackerMIInverseCompositional::USE_QUASINEWTON:
    {
      double s_scal_y;
      if(iterationGlobale!=0)
      {
        vpColVector s_quasi=p-p_prec;
        vpColVector y_quasi=G-G_prec;
        s_scal_y=s_quasi.t()*y_quasi;
        //std::cout<<"mise a jour K"<<std::endl;
        /*if(s_scal_y!=0)//BFGS
                    KQuasiNewton=KQuasiNewton+0.01*(-(s_quasi*y_quasi.t()*KQuasiNewton+KQuasiNewton*y_quasi*s_quasi.t())/s_scal_y+(1.+y_quasi.t()*(KQuasiNewton*y_quasi)/s_scal_y)*s_quasi*s_quasi.t()/s_scal_y);*/
        //if(s_scal_y!=0)//DFP
        if(std::fabs(s_scal_y) > std::numeric_limits<double>::epsilon())//DFP
        {
          KQuasiNewton=KQuasiNewton+0.0001*(s_quasi*s_quasi.t()/s_scal_y-KQuasiNewton*y_quasi*y_quasi.t()*KQuasiNewton/(y_quasi.t()*KQuasiNewton*y_quasi));
          //std::cout<<"mise a jour K"<<std::endl;
        }
      }
      dp=gain*KQuasiNewton*G;
      //std::cout<<KQuasiNewton<<std::endl<<std::endl;
      p_prec=p;
      G_prec=G;
      //p-=1.01*dp;
    }
      break;

    default:
    {
      if(useBrent)
      {
        alpha=2.;
        computeOptimalBrentGain(I,p,-MI,dp,alpha);
        dp=alpha*dp;
      }
      if(ApproxHessian==HESSIAN_NONSECOND)
        dp=-1.*dp;

      break;
    }
    }

    Warp->getParamInverse(dp,dpinv);
    Warp->pRondp(p,dpinv,p);

    iteration++;
    iterationGlobale++;

    computeEvalRMS(p);

    //        std::cout << p.t() << std::endl;
  }
  while( (!diverge) && (std::fabs(MI-MIprec) > std::fabs(MI)*std::numeric_limits<double>::epsilon()) &&(iteration< iterationMax)&&(evolRMS>threshold_RMS) );
  //while( (!diverge) && (MI!=MIprec) &&(iteration< iterationMax)&&(evolRMS>threshold_RMS) );

  nbIteration=iteration;

  if(diverge)
  {
    if(computeCovariance){
      covarianceMatrix = vpMatrix(Warp->getNbParam(),Warp->getNbParam());
      covarianceMatrix = -1;
      MI_postEstimation = -1;
      NMI_postEstimation = -1;
    }
    deletePosEvalRMS();

    //        throw(vpTrackingException(vpTrackingException::badValue, "Tracking failed")) ;
  }
  else
  {
    MI_postEstimation=-getCost(I,p);
    NMI_postEstimation=-getNormalizedCost(I,p);
    //        std::cout << "MI apres: " << MI_postEstimation << std::endl;
    //        std::cout << "NMI apres: " << NMI_postEstimation << std::endl;
    if(MI_preEstimation>MI_postEstimation)
    {
      p=p_avant_estimation;
      MI_postEstimation = MI_preEstimation;
      NMI_postEstimation = NMI_preEstimation;
      covarianceMatrix = vpMatrix(Warp->getNbParam(),Warp->getNbParam());
      covarianceMatrix = -1;
    }

    deletePosEvalRMS();

    if(computeCovariance){
      try{
        covarianceMatrix = (-H).inverseByLU();
        //            covarianceMatrix = (-Hnorm).inverseByLU();
      }
      catch(...){
        covarianceMatrix = vpMatrix(Warp->getNbParam(),Warp->getNbParam());
        covarianceMatrix = -1;
        MI_postEstimation = -1;
        NMI_postEstimation = -1;
        deletePosEvalRMS();
      }
    }
  }
}
Exemple #24
0
void Ellipse_n::perform(){



    QVector<double> x(100*a*2+1), y(100*a*2+1); // initialize with entries 0..100

   double w = -a;
   int count = 0;
   for (int i=0; w<a; ++i)
   {

       x[i] = w;  // let's plot a quadratic function
       y[i] = b*sqrt((1) - ((x[i]*x[i]) / (a*a)));

count++;
   w+=0.01;

   }

   if (x[x.size()-1] != a){
   x[x.size()-1] = a;
   y[x.size()-1] = b*sqrt((1) - ((x[x.size()-1]*x[x.size()-1]) / (a*a)));

   }



   QVector<double> x1(100*a*2+1), y1(100*a*2+1); // initialize with entries 0..100

    w = -a;
   for (int i=0; w<a; ++i)
   {

       x1[i] = w;  // let's plot a quadratic function
       y1[i] = (-b)*sqrt((1) - ((x[i]*x[i]) / (a*a)));



   w+=0.01;

   }

   if (x1[x1.size()-1] != a){
   x1[x1.size()-1] = a;
   y1[x1.size()-1] = (-b)*sqrt((1) - ((x[x1.size()-1]*x[x1.size()-1]) / (a*a)));

   }


xg = x;
yg = y;



xg1 = x1;
yg1 = y1;


for (int i = 0; i<100*a*2 + 1; i ++){
xg[i] = xg[i] + Xc;

yg[i] = (yg[i] + Yc);

xg1[i] = xg1[i] + Xc;
yg1[i] = yg1[i] + Yc;



}



}
Exemple #25
0
void benchmark_scan(
        const vex::Context &ctx, vex::profiler<> &prof
        )
{
    const size_t N = 16 * 1024 * 1024;
    const size_t M = 16;

    typedef typename std::conditional<
        std::is_same<float, real>::value, cl_uint, cl_ulong
        >::type key_type;

    std::default_random_engine rng( std::rand() );
    std::uniform_int_distribution<key_type> rnd;

    std::vector<key_type> x0(N);
    std::vector<key_type> x1(N);

    std::generate(x0.begin(), x0.end(), [&]() { return rnd(rng); });

    vex::vector<key_type> X0(ctx, x0);
    vex::vector<key_type> X1(ctx, N);

    vex::exclusive_scan(X0, X1);

    ctx.finish();
    prof.tic_cpu("VexCL");

    for(size_t i = 0; i < M; i++)
        vex::exclusive_scan(X0, X1);

    ctx.finish();
    double tot_time = prof.toc("VexCL");

    std::cout
        << "Scan (" << vex::type_name<key_type>() << ")\n"
        << "    VexCL:         " << N * M / tot_time << " keys/sec\n";

#ifdef HAVE_BOOST_COMPUTE
    vex::compute::exclusive_scan(X0, X1);

    ctx.finish();
    prof.tic_cpu("Boost.Compute");

    for(size_t i = 0; i < M; i++)
        vex::compute::exclusive_scan(X0, X1);

    ctx.finish();
    tot_time = prof.toc("Boost.Compute");

    std::cout
        << "    Boost.Compute: " << N * M / tot_time << " keys/sec\n";
#endif

#ifdef HAVE_CLOGS
    vex::clogs::exclusive_scan(X0, X1);

    ctx.finish();
    prof.tic_cpu("CLOGS");

    for(size_t i = 0; i < M; i++)
        vex::clogs::exclusive_scan(X0, X1);

    ctx.finish();
    tot_time = prof.toc("CLOGS");

    std::cout
        << "    CLOGS:         " << N * M / tot_time << " keys/sec\n";
#endif

    if (options.bm_cpu) {
        prof.tic_cpu("CPU");
        for(size_t i = 0; i < M; i++) {
            key_type sum = key_type();
            for(size_t j = 0; j < N; ++j) {
                key_type next = sum + x0[j];
                x1[j] = sum;
                sum = next;
            }
        }
        tot_time = prof.toc("CPU");

        std::cout << "    CPU:           " << N * M / tot_time << " keys/sec\n";
    }

    std::cout << std::endl;
}
Exemple #26
0
int checkResults( bool trans,
		  Epetra_LinearProblemRedistor * redistor,
		  Epetra_LinearProblem * A,
		  Epetra_LinearProblem * R,
		  bool verbose) {

  int m = A->GetRHS()->MyLength();
  int n = A->GetLHS()->MyLength();
  assert( m == n ) ;

  Epetra_MultiVector *x = A->GetLHS() ;
  Epetra_MultiVector x1( *x ) ;
  //  Epetra_MultiVector Difference( x1 ) ;
  Epetra_MultiVector *b = A->GetRHS();
  Epetra_RowMatrix *matrixA = A->GetMatrix();
  assert( matrixA != 0 ) ;
  int iam = matrixA->Comm().MyPID();

  //  Epetra_Time timer(A->Comm());
  //  double start = timer.ElapsedTime();

  matrixA->Multiply(trans, *b, x1) ;   // x = Ab

  int M,N,nz;
  int *ptr, *ind;
  double *val, *rhs, *lhs;
  int Nrhs, ldrhs, ldlhs;

  redistor->ExtractHbData( M, N, nz, ptr, ind,
		    val, Nrhs, rhs, ldrhs,
		    lhs, ldlhs);

  assert( M == N ) ;
  if ( verbose ) {
    cout << " iam = " << iam
	 << " m = " << m  << " n = " << n  << " M = " << M << endl ;

    cout << " iam = " << iam << " ptr = " << ptr[0] << " "   << ptr[1] << " "  << ptr[2] << " "  << ptr[3] << " "  << ptr[4] << " " << ptr[5] << endl ;

    cout << " iam = " << iam << " ind = " << ind[0] << " "   << ind[1] << " "  << ind[2] << " "  << ind[3] << " "  << ind[4] << " " << ind[5] << endl ;

    cout << " iam = " << iam << " val = " << val[0] << " "   << val[1] << " "  << val[2] << " "  << val[3] << " "  << val[4] << " " << val[5] << endl ;
  }
  //  Create a serial map in case we end up needing it
  //  If it is created inside the else block below it would have to
  //  be with a call to new().
  int NumMyElements_ = 0 ;
  if (matrixA->Comm().MyPID()==0) NumMyElements_ = n;
  Epetra_Map SerialMap( n, NumMyElements_, 0, matrixA->Comm() );

  //  These are unnecessary and useless
  //  Epetra_Vector serial_A_rhs( SerialMap ) ;
  //  Epetra_Vector serial_A_lhs( SerialMap ) ;

  //  Epetra_Export exporter( matrixA->BlockRowMap(), SerialMap) ;

  //
  //  In each process, we will compute Rb putting the answer into LHS
  //


  for ( int k = 0 ; k < Nrhs; k ++ ) {
    for ( int i = 0 ; i < M ; i ++ ) {
      lhs[ i + k * ldlhs ] = 0.0;
    }
    for ( int i = 0 ; i < M ; i++ ) {
      for ( int l = ptr[i]; l < ptr[i+1]; l++ ) {
	int j = ind[l] ;
	if ( verbose && N < 40 ) {
	  cout << " i = " << i << " j = " << j ;
	  cout << " l = " << l << " val[l] = " << val[l] ;
	  cout << " rhs = " << rhs[ j + k * ldrhs ] << endl ;
	}
	lhs[ i + k * ldrhs ] += val[l] * rhs[ j + k * ldrhs ] ;
      }
    }

    if ( verbose && N < 40 ) {
      cout << " lhs = " ;
      for ( int j = 0 ; j < N ; j++ ) cout << " " << lhs[j] ;
      cout << endl ;
      cout << " rhs = " ;
      for ( int j = 0 ; j < N ; j++ ) cout << " " << rhs[j] ;
      cout << endl ;
    }

    const Epetra_Comm &comm = matrixA->Comm() ;
#ifdef HAVE_COMM_ASSERT_EQUAL
    //
    //  Here we double check to make sure that lhs and rhs are
    //  replicated.
    //
    for ( int j = 0 ; j < N ; j++ ) {
      assert( Comm_assert_equal( &comm, lhs[ j + k * ldrhs ] ) ) ;
      assert( Comm_assert_equal( &comm, rhs[ j + k * ldrhs ] ) ) ;
    }
#endif
  }

  //
  //  Now we have to redistribue them back
  //
  redistor->UpdateOriginalLHS( A->GetLHS() ) ;
  //
  //  Now we want to compare x and x1 which have been computed as follows:
  //  x = Rb
  //  x1 = Ab
  //

  double Norm_x1, Norm_diff ;
  EPETRA_CHK_ERR( x1.Norm2( &Norm_x1 ) ) ;

  //  cout << " x1 = " << x1 << endl ;
  //  cout << " *x = " << *x << endl ;

  x1.Update( -1.0, *x, 1.0 ) ;
  EPETRA_CHK_ERR( x1.Norm2( &Norm_diff ) ) ;

  //  cout << " diff, i.e. updated x1 = " << x1 << endl ;

  int ierr = 0;

  if ( verbose ) {
    cout << " Norm_diff = "  << Norm_diff << endl ;
    cout << " Norm_x1 = "  << Norm_x1 << endl ;
  }

  if ( Norm_diff / Norm_x1 > n * error_tolerance ) ierr++ ;

  if (ierr!=0 && verbose) cerr << "Status: Test failed" << endl;
  else if (verbose) cerr << "Status: Test passed" << endl;

  return(ierr);
}
void bi::DOPRI5IntegratorSSE<B,S,T1>::update(const T1 t1, const T1 t2,
    State<B,ON_HOST>& s) {
  /* pre-condition */
  BI_ASSERT(t1 < t2);

  typedef host_vector_reference<sse_real> vector_reference_type;
  typedef Pa<ON_HOST,B,host,host,sse_host,sse_host> PX;
  typedef DOPRI5VisitorHost<B,S,S,real,PX,sse_real> Visitor;
  static const int N = block_size<S>::value;
  const int P = s.size();

  #pragma omp parallel
  {
    sse_real buf[10*N];
    vector_reference_type x0(buf, N);
    vector_reference_type x1(buf + N, N);
    vector_reference_type x2(buf + 2*N, N);
    vector_reference_type x3(buf + 3*N, N);
    vector_reference_type x4(buf + 4*N, N);
    vector_reference_type x5(buf + 5*N, N);
    vector_reference_type x6(buf + 6*N, N);
    vector_reference_type err(buf + 7*N, N);
    vector_reference_type k1(buf + 8*N, N);
    vector_reference_type k7(buf + 9*N, N);

    sse_real e, e2;
    real t, h, logfacold, logfac11, fac, e2max;
    int n, id, p;
    bool k1in;
    PX pax;

    #pragma omp for
    for (p = 0; p < P; p += BI_SSE_SIZE) {
      t = t1;
      h = h_h0;
      logfacold = bi::log(BI_REAL(1.0e-4));
      k1in = false;
      n = 0;
      sse_host_load<B,S>(s, p, x0);

      /* integrate */
      while (t < t2 && n < h_nsteps) {
        if (BI_REAL(0.1)*bi::abs(h) <= bi::abs(t)*h_uround) {
          // step size too small
        }
        if (t + BI_REAL(1.01)*h - t2 > BI_REAL(0.0)) {
          h = t2 - t;
          if (h <= BI_REAL(0.0)) {
            t = t2;
            break;
          }
        }

        /* stages */
        Visitor::stage1(t, h, s, p, pax, x0.buf(), x1.buf(), x2.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), k1.buf(), err.buf(), k1in);
        k1in = true; // can reuse from previous iteration in future
        sse_host_store<B,S>(s, p, x1);

        Visitor::stage2(t, h, s, p, pax, x0.buf(), x2.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        sse_host_store<B,S>(s, p, x2);

        Visitor::stage3(t, h, s, p, pax, x0.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        sse_host_store<B,S>(s, p, x3);

        Visitor::stage4(t, h, s, p, pax, x0.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        sse_host_store<B,S>(s, p, x4);

        Visitor::stage5(t, h, s, p, pax, x0.buf(), x5.buf(), x6.buf(), err.buf());
        sse_host_store<B,S>(s, p, x5);

        Visitor::stage6(t, h, s, p, pax, x0.buf(), x6.buf(), err.buf());

        /* compute error */
        Visitor::stageErr(t, h, s, p, pax, x0.buf(), x6.buf(), k7.buf(), err.buf());

        /* determine largest error among trajectories */
        e2 = BI_REAL(0.0);
        for (id = 0; id < N; ++id) {
          e = err[id]*h/(bi::max(bi::abs(x0(id)), bi::abs(x6(id)))*h_rtoler + h_atoler);
          e2 += e*e;
        }
        #ifdef ENABLE_SINGLE
        e2max = bi::max(bi::max(e2.unpacked.a, e2.unpacked.b), bi::max(e2.unpacked.c, e2.unpacked.d));
        #else
        e2max = bi::max(e2.unpacked.a, e2.unpacked.b);
        #endif
        e2max /= N;

        if (e2max <= BI_REAL(1.0)) {
          /* accept */
          t += h;
          x0.swap(x6);
          k1.swap(k7);
        }
        sse_host_store<B,S>(s, p, x0);

        /* compute next step size */
        if (t < t2) {
          logfac11 = h_expo*bi::log(e2max);
          if (e2max > BI_REAL(1.0)) {
            /* step was rejected */
            h *= bi::max(h_facl, bi::exp(h_logsafe - logfac11));
          } else {
            /* step was accepted */
            fac = bi::exp(h_beta*logfacold + h_logsafe - logfac11); // Lund-stabilization
            fac = bi::min(h_facr, bi::max(h_facl, fac)); // bound
            h *= fac;
            logfacold = BI_REAL(0.5)*bi::log(bi::max(e2max, BI_REAL(1.0e-8)));
          }
        }

        ++n;
      }
    }
  }
}
Exemple #28
0
void bi::DOPRI5IntegratorHost<B,S,T1>::update(const T1 t1, const T1 t2,
    State<B,ON_HOST>& s) {
  /* pre-condition */
  BI_ASSERT(t1 < t2);

  typedef typename temp_host_vector<real>::type vector_type;
  typedef Pa<ON_HOST,B,host,host,host,host> PX;
  typedef DOPRI5VisitorHost<B,S,S,real,PX,real> Visitor;

  static const int N = block_size<S>::value;
  const int P = s.size();

#pragma omp parallel
  {
    vector_type x0(N), x1(N), x2(N), x3(N), x4(N), x5(N), x6(N), err(N), k1(
        N), k7(N);
    real t, h, e, e2, logfacold, logfac11, fac;
    int n, id, p;
    bool k1in;
    PX pax;

#pragma omp for
    for (p = 0; p < P; ++p) {
      t = t1;
      h = h_h0;
      logfacold = bi::log(BI_REAL(1.0e-4));
      k1in = false;
      n = 0;
      host_load<B,S>(s, p, x0);

      /* integrate */
      while (t < t2 && n < h_nsteps) {
        if (BI_REAL(0.1)*bi::abs(h) <= bi::abs(t)*h_uround) {
          // step size too small
        }
        if (t + BI_REAL(1.01)*h - t2 > BI_REAL(0.0)) {
          h = t2 - t;
          if (h <= BI_REAL(0.0)) {
            t = t2;
            break;
          }
        }

        /* stages */
        Visitor::stage1(t, h, s, p, pax, x0.buf(), x1.buf(), x2.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), k1.buf(), err.buf(), k1in);
        k1in = true;  // can reuse from previous iteration in future
        host_store<B,S>(s, p, x1);

        Visitor::stage2(t, h, s, p, pax, x0.buf(), x2.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        host_store<B,S>(s, p, x2);

        Visitor::stage3(t, h, s, p, pax, x0.buf(), x3.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        host_store<B,S>(s, p, x3);

        Visitor::stage4(t, h, s, p, pax, x0.buf(), x4.buf(), x5.buf(), x6.buf(), err.buf());
        host_store<B,S>(s, p, x4);

        Visitor::stage5(t, h, s, p, pax, x0.buf(), x5.buf(), x6.buf(), err.buf());
        host_store<B,S>(s, p, x5);

        Visitor::stage6(t, h, s, p, pax, x0.buf(), x6.buf(), err.buf());

        /* compute error */
        Visitor::stageErr(t, h, s, p, pax, x0.buf(), x6.buf(), k7.buf(), err.buf());
        e2 = 0.0;
        for (id = 0; id < N; ++id) {
          e = err(id)*h/(h_atoler + h_rtoler*bi::max(bi::abs(x0(id)), bi::abs(x6(id))));
          e2 += e*e;
        }
        e2 /= N;

        /* accept/reject */
        if (e2 <= BI_REAL(1.0)) {
          /* accept */
          t += h;
          x0.swap(x6);
          k1.swap(k7);
        }
        host_store<B,S>(s, p, x0);

        /* compute next step size */
        if (t < t2) {
          logfac11 = h_expo*bi::log(e2);
          if (e2 > BI_REAL(1.0)) {
            /* step was rejected */
            h *= bi::max(h_facl, bi::exp(h_logsafe - logfac11));
          } else {
            /* step was accepted */
            fac = bi::exp(h_beta*logfacold + h_logsafe - logfac11);  // Lund-stabilization
            fac = bi::min(h_facr, bi::max(h_facl, fac));// bound
            h *= fac;
            logfacold = BI_REAL(0.5)*bi::log(bi::max(e2, BI_REAL(1.0e-8)));
          }
        }

        ++n;
      }
    }
  }
}
Exemple #29
0
// ----------------------------------------------------------------------------
// Handles the action [id].
// Returns true if the action was handled, false otherwise
// ----------------------------------------------------------------------------
bool GfxEntryPanel::handleEntryPanelAction(std::string_view id)
{
	// We're only interested in "pgfx_" actions
	if (!StrUtil::startsWith(id, "pgfx_"))
		return false;

	// For pgfx_brush actions, the string after pgfx is a brush name
	if (StrUtil::startsWith(id, "pgfx_brush"))
	{
		gfx_canvas_->setBrush(SBrush::get(std::string{ id }));
		button_brush_->setIcon(StrUtil::afterFirst(id, '_'));
	}

	// Editing - drag mode
	else if (id == "pgfx_drag")
	{
		editing_ = false;
		gfx_canvas_->setEditingMode(GfxCanvas::EditMode::None);
	}

	// Editing - draw mode
	else if (id == "pgfx_draw")
	{
		editing_ = true;
		gfx_canvas_->setEditingMode(GfxCanvas::EditMode::Paint);
		gfx_canvas_->setPaintColour(cb_colour_->colour());
	}

	// Editing - erase mode
	else if (id == "pgfx_erase")
	{
		editing_ = true;
		gfx_canvas_->setEditingMode(GfxCanvas::EditMode::Erase);
	}

	// Editing - translate mode
	else if (id == "pgfx_magic")
	{
		editing_ = true;
		gfx_canvas_->setEditingMode(GfxCanvas::EditMode::Translate);
	}

	// Editing - set translation
	else if (id == "pgfx_settrans")
	{
		// Create translation editor dialog
		TranslationEditorDialog ted(
			theMainWindow, *theMainWindow->paletteChooser()->selectedPalette(), " Colour Remap", image());

		// Create translation to edit
		ted.openTranslation(edit_translation_);

		// Show the dialog
		if (ted.ShowModal() == wxID_OK)
		{
			// Set the translation
			edit_translation_.copy(ted.getTranslation());
			gfx_canvas_->setTranslation(&edit_translation_);
		}
	}

	// Editing - set brush
	else if (id == "pgfx_setbrush")
	{
		auto p = button_brush_->GetScreenPosition() -= GetScreenPosition();
		p.y += button_brush_->GetMaxHeight();
		PopupMenu(menu_brushes_, p);
	}

	// Mirror
	else if (id == "pgfx_mirror")
	{
		// Mirror X
		image()->mirror(false);

		// Update UI
		gfx_canvas_->updateImageTexture();
		gfx_canvas_->Refresh();

		// Update variables
		image_data_modified_ = true;
		setModified();
	}

	// Flip
	else if (id == "pgfx_flip")
	{
		// Mirror Y
		image()->mirror(true);

		// Update UI
		gfx_canvas_->updateImageTexture();
		gfx_canvas_->Refresh();

		// Update variables
		image_data_modified_ = true;
		setModified();
	}

	// Rotate
	else if (id == "pgfx_rotate")
	{
		// Prompt for rotation angle
		wxString angles[] = { "90", "180", "270" };
		int      choice   = wxGetSingleChoiceIndex("Select rotation angle", "Rotate", 3, angles, 0);

		// Rotate image
		switch (choice)
		{
		case 0: image()->rotate(90); break;
		case 1: image()->rotate(180); break;
		case 2: image()->rotate(270); break;
		default: break;
		}

		// Update UI
		gfx_canvas_->updateImageTexture();
		gfx_canvas_->Refresh();

		// Update variables
		image_data_modified_ = true;
		setModified();
	}

	// Translate
	else if (id == "pgfx_remap")
	{
		// Create translation editor dialog
		auto                    pal = MainEditor::currentPalette();
		TranslationEditorDialog ted(theMainWindow, *pal, " Colour Remap", &gfx_canvas_->image());

		// Create translation to edit
		ted.openTranslation(prev_translation_);

		// Show the dialog
		if (ted.ShowModal() == wxID_OK)
		{
			// Apply translation to image
			image()->applyTranslation(&ted.getTranslation(), pal);

			// Update UI
			gfx_canvas_->updateImageTexture();
			gfx_canvas_->Refresh();

			// Update variables
			image_data_modified_ = true;
			gfx_canvas_->updateImageTexture();
			setModified();
			prev_translation_.copy(ted.getTranslation());
		}
	}

	// Colourise
	else if (id == "pgfx_colourise")
	{
		auto               pal = MainEditor::currentPalette();
		GfxColouriseDialog gcd(theMainWindow, entry_, *pal);
		gcd.setColour(last_colour);

		// Show colourise dialog
		if (gcd.ShowModal() == wxID_OK)
		{
			// Colourise image
			image()->colourise(gcd.colour(), pal);

			// Update UI
			gfx_canvas_->updateImageTexture();
			gfx_canvas_->Refresh();

			// Update variables
			image_data_modified_ = true;
			Refresh();
			setModified();
		}
		last_colour = gcd.colour().toString(ColRGBA::StringFormat::RGB);
	}

	// Tint
	else if (id == "pgfx_tint")
	{
		auto          pal = MainEditor::currentPalette();
		GfxTintDialog gtd(theMainWindow, entry_, *pal);
		gtd.setValues(last_tint_colour, last_tint_amount);

		// Show tint dialog
		if (gtd.ShowModal() == wxID_OK)
		{
			// Tint image
			image()->tint(gtd.colour(), gtd.amount(), pal);

			// Update UI
			gfx_canvas_->updateImageTexture();
			gfx_canvas_->Refresh();

			// Update variables
			image_data_modified_ = true;
			Refresh();
			setModified();
		}
		last_tint_colour = gtd.colour().toString(ColRGBA::StringFormat::RGB);
		last_tint_amount = (int)(gtd.amount() * 100.0);
	}

	// Crop
	else if (id == "pgfx_crop")
	{
		auto          image = this->image();
		auto          pal   = MainEditor::currentPalette();
		GfxCropDialog gcd(theMainWindow, image, pal);

		// Show crop dialog
		if (gcd.ShowModal() == wxID_OK)
		{
			// Prompt to adjust offsets
			auto crop = gcd.cropRect();
			if (crop.tl.x > 0 || crop.tl.y > 0)
			{
				if (wxMessageBox(
						"Do you want to adjust the offsets? This will keep the graphic in the same relative "
						"position it was before cropping.",
						"Adjust Offsets?",
						wxYES_NO)
					== wxYES)
				{
					image->setXOffset(image->offset().x - crop.tl.x);
					image->setYOffset(image->offset().y - crop.tl.y);
				}
			}

			// Crop image
			image->crop(crop.x1(), crop.y1(), crop.x2(), crop.y2());

			// Update UI
			gfx_canvas_->updateImageTexture();
			gfx_canvas_->Refresh();

			// Update variables
			image_data_modified_ = true;
			Refresh();
			setModified();
		}
	}

	// alPh/tRNS
	else if (id == "pgfx_alph" || id == "pgfx_trns")
	{
		setModified();
		Refresh();
	}

	// Optimize PNG
	else if (id == "pgfx_pngopt")
	{
		// This is a special case. If we set the entry as modified, SLADE will prompt
		// to save it, rewriting the entry and cancelling the optimization done...
		if (EntryOperations::optimizePNG(entry_))
			setModified(false);
		else
			wxMessageBox(
				"Warning: Couldn't optimize this image, check console log for info",
				"Warning",
				wxOK | wxCENTRE | wxICON_WARNING);
		Refresh();
	}

	// Extract all
	else if (id == "pgfx_extract")
	{
		extractAll();
	}

	// Convert
	else if (id == "pgfx_convert")
	{
		GfxConvDialog gcd(theMainWindow);
		gcd.CenterOnParent();
		gcd.openEntry(entry_);

		gcd.ShowModal();

		if (gcd.itemModified(0))
		{
			// Get image and conversion info
			auto image  = gcd.itemImage(0);
			auto format = gcd.itemFormat(0);

			// Write converted image back to entry
			format->saveImage(*image, entry_data_, gcd.itemPalette(0));
			// This makes the "save" button (and the setModified stuff) redundant and confusing!
			// The alternative is to save to entry effectively (uncomment the importMemChunk line)
			// but remove the setModified and image_data_modified lines, and add a call to refresh
			// to get the PNG tRNS status back in sync.
			// entry->importMemChunk(entry_data);
			image_data_modified_ = true;
			setModified();

			// Fix tRNS status if we converted to paletted PNG
			int MENU_GFXEP_PNGOPT      = SAction::fromId("pgfx_pngopt")->wxId();
			int MENU_GFXEP_ALPH        = SAction::fromId("pgfx_alph")->wxId();
			int MENU_GFXEP_TRNS        = SAction::fromId("pgfx_trns")->wxId();
			int MENU_ARCHGFX_EXPORTPNG = SAction::fromId("arch_gfx_exportpng")->wxId();
			if (format->name() == "PNG")
			{
				ArchiveEntry temp;
				temp.importMemChunk(entry_data_);
				temp.setType(EntryType::fromId("png"));
				menu_custom_->Enable(MENU_GFXEP_ALPH, true);
				menu_custom_->Enable(MENU_GFXEP_TRNS, true);
				menu_custom_->Check(MENU_GFXEP_TRNS, EntryOperations::gettRNSChunk(&temp));
				menu_custom_->Enable(MENU_ARCHGFX_EXPORTPNG, false);
				menu_custom_->Enable(MENU_GFXEP_PNGOPT, true);
				toolbar_->enableGroup("PNG", true);
			}
			else
			{
				menu_custom_->Enable(MENU_GFXEP_ALPH, false);
				menu_custom_->Enable(MENU_GFXEP_TRNS, false);
				menu_custom_->Enable(MENU_ARCHGFX_EXPORTPNG, true);
				menu_custom_->Enable(MENU_GFXEP_PNGOPT, false);
				toolbar_->enableGroup("PNG", false);
			}

			// Refresh
			this->image()->open(entry_data_, 0, format->id());
			gfx_canvas_->Refresh();
		}
	}

	// Unknown action
	else
		return false;

	// Action handled
	return true;
}
Exemple #30
0
template<class _t, class _rt, class _it> _t rect<_t, _rt, _it>::center_x() const { 
	return (x0() + x1()) / 2; 
}