C++ MatrixXf::fill方法代码示例

/**
 * Create the augmented knots vector and fill in matrix Xt with the spline basis vectors
 */
void basis_splines_endreps_local_v2(float *knots, int n_knots, int order, int *boundaries, int n_boundaries,  Eigen::MatrixXf &Xt) {
  assert(n_boundaries == 2 && boundaries[0] < boundaries[1]);
  int n_rows = boundaries[1] - boundaries[0]; // this is frames so evaluate at each frame we'll need
  int n_cols = n_knots + order;  // number of basis vectors we'll have at end 
  Xt.resize(n_cols, n_rows); // swapped to transpose later. This order lets us use it as a scratch space
  Xt.fill(0);
  int n_std_knots = n_knots + 2 * order;
  float std_knots[n_std_knots];

  // Repeat the boundary knots on there to ensure linear out side of knots
  for (int i = 0; i < order; i++) {
    std_knots[i] = boundaries[0];
  }
  // Our original boundary knots here
  for (int i = 0; i < n_knots; i++) {
    std_knots[i+order] = knots[i];
  }
  // Repeat the boundary knots on there to ensure linear out side of knots
  for (int i = 0; i < order; i++) {
    std_knots[i+order+n_knots] = boundaries[1];
  }
  // Evaluate our basis splines at each frame.
  for (int i = boundaries[0]; i < boundaries[1]; i++) {
    int idx = -1;
    // find index such that i >= knots[idx] && i < knots[idx+1]
    float *val = std::upper_bound(std_knots, std_knots + n_std_knots - 1, 1.0f * i);
    idx = val - std_knots - 1;
    assert(idx >= 0);
    float *f = Xt.data() + i * n_cols + idx - (order - 1); //column offset
    basis_spline_xi_v2(std_knots, n_std_knots, order, idx, i, f);
  }
  // Put in our conventional format where each column is a basis vector
  Xt.transposeInPlace();
}

void PixelMapper::mergeProjections(Eigen::MatrixXf& depthImage, Eigen::MatrixXi& indexImage,
				   Eigen::MatrixXf* depths, Eigen::MatrixXi* indices, int numImages){
  assert (numImages>0);
  int rows=depths[0].rows();
  int cols=depths[0].cols();
  depthImage.resize(indexImage.rows(), indexImage.cols());
  depthImage.fill(std::numeric_limits<float>::max());
  indexImage.resize(rows, cols);
  indexImage.fill(-1);

  #pragma omp parallel for
  for (int c=0; c<cols; c++){
    int* destIndexPtr = &indexImage.coeffRef(0,c);
    float* destDepthPtr = &depthImage.coeffRef(0,c);
    int* srcIndexPtr[numImages];
    float* srcDepthPtr[numImages];
    for (int i=0; i<numImages; i++){
      srcIndexPtr[i] = &indices[i].coeffRef(0,c);
      srcDepthPtr[i] = &depths[i].coeffRef(0,c);
    }
    for (int r=0; r<rows; r++){
      for (int i=0; i<numImages; i++){
	if (*destDepthPtr>*srcDepthPtr[i]){
	  *destDepthPtr = *srcDepthPtr[i];
	  *destIndexPtr = *srcIndexPtr[i];
	}
	srcDepthPtr[i]++;
	srcIndexPtr[i]++;
      }
      destDepthPtr++;
      destIndexPtr++;
    }
  }

}

void DenseCRF::stepInference( Eigen::MatrixXf & Q, Eigen::MatrixXf & tmp1, Eigen::MatrixXf & tmp2 ) const{
	tmp1.resize( Q.rows(), Q.cols() );
	tmp1.fill(0);
	if( unary_ )
		tmp1 -= unary_->get();
	
	// Add up all pairwise potentials
	for( unsigned int k=0; k<pairwise_.size(); k++ ) {
		pairwise_[k]->apply( tmp2, Q );
		tmp1 -= tmp2;
	}
	
	// Exponentiate and normalize
	expAndNormalize( Q, tmp1 );
}

void PointProjector::project(Eigen::MatrixXi &indexImage, 
			     Eigen::MatrixXf &depthImage, 
			     const HomogeneousPoint3fVector &points) const {
  depthImage.resize(indexImage.rows(), indexImage.cols());
  depthImage.fill(std::numeric_limits<float>::max());
  indexImage.fill(-1);
  const HomogeneousPoint3f* point = &points[0];
  for (size_t i=0; i<points.size(); i++, point++){
    int x, y;
    float d;
    if (!project(x, y, d, *point) ||
	x<0 || x>=indexImage.rows() ||
	y<0 || y>=indexImage.cols()  )
      continue;
    float& otherDistance=depthImage(x,y);
    int&   otherIndex=indexImage(x,y);
    if (otherDistance>d) {
      otherDistance = d;
      otherIndex = i;
    }
  }
}