C++ DoubleMatrix::rows方法代码示例

void MatrixHeatImaging(const DoubleMatrix &m, double minimum, double maximum, QPixmap &pixmap, int width, int height)
{
    pixmap = QPixmap(QSize(width, height));
    pixmap.fill(Qt::white);
    QPainter painter(&pixmap);

    unsigned int rows = m.rows();
    unsigned int cols = m.cols();

    for (unsigned int j=0; j<rows; j++)
    {
        for (unsigned int i=0; i<cols; i++)
        {
            double u = m.at(j,i);
            double ratio = 0.0;
            if (minimum!=maximum)
                ratio = 2.0 * (u-minimum) / (maximum - minimum);
            int b = int(MAX(0, 255*(1 - ratio)));
            int r = int(MAX(0, 255*(ratio - 1)));
            int g = 255 - b - r;
            QColor c(r, g, b);
            painter.setPen(c);
            painter.drawPoint(i,height-j-1);
        }
    }
}

void HeatControl2Delta::write(const char *fileName, const DoubleMatrix& m)
{
    FILE* f = fopen(fileName, "w");
    for (unsigned int j=0; j<m.rows(); j++)
    {
        for (unsigned int i=0; i<m.cols(); i++)
        {
            if (i==0)
                fprintf(f, "%.10f", m[j][i]);
            else
                fprintf(f, " %.10f", m[j][i]);
        }
        fprintf(f, "\n");
    }
    fclose(f);
}

int main(int argc, char *argv[]) {

  string hdr = invocationHeader(argc, argv);
  cout << "# " << hdr << endl;
  parseArgs(argc, argv);

  DoubleMatrix eigvals;
  readAsciiMatrix(eigvals_name, eigvals);

  DoubleMatrix eigvecs;
  readAsciiMatrix(eigvecs_name, eigvecs);

  if (modes.empty())
    for (uint i=0; i<eigvals.rows(); ++i)
      modes.push_back(i);

  uint n = modes.size();
  uint m = eigvecs.rows();

  // V = m x n matrix of eigenvectors
  DoubleMatrix V(m, n);
  for (uint i=0; i<n; ++i)
    for (uint j=0; j<m; ++j)
      V(j, i) = eigvecs(j, modes[i]);

  // Make a copy and scale by the appropriate eigenvalue,
  // remembering that eigenvalues are inverted for ENM,
  // or squaring and not inverting in the case of PCA
  DoubleMatrix VS = V.copy();
  for (uint i=0; i<n; ++i) {
    double e = eigvals[modes[i]];
    double s = (pca_input) ? (scale * e * e): (scale / e);
    for (uint j=0; j<m; ++j)
      VS(j, i) *= s;
  }
  
  // U = Covariance matrix
  DoubleMatrix U = loos::Math::MMMultiply(VS,V,false,true);

  // B-factors come from trace of diagonal 3x3 superblocks
  vector<double> B;
  double prefactor = 8.0 *  M_PI * M_PI / 3.0;
  for (uint i=0; i<m; i += 3) {
    double b = prefactor * (U(i,i) + U(i+1, i+1) + U(i+2, i+2));
    B.push_back(b);
    cout << boost::format("%-8d %g\n") % (i/3) % b;
  }

  if (!pdb_name.empty()) {
    AtomicGroup model = createSystem(pdb_name);
    AtomicGroup subset = selectAtoms(model, selection);

    if ((unsigned int)subset.size() != B.size()) {
      cerr << boost::format("Error- selection has %d atoms, but %d were expected.\n") % subset.size() % B.size();
      exit(-10);
    }

    for (uint i=0; i<B.size(); ++i)
      subset[i]->bfactor(B[i]);

    PDB pdb = PDB::fromAtomicGroup(model);
    pdb.remarks().add(hdr);
    ofstream ofs(out_name.c_str());
    ofs << pdb;
  }

}

/*!
	Linear assignment problem solution
	[modifies matrix in-place.]
	matrix(row,col): row major format assumed.

	Assignments are remaining 0 values on 'matrix'
	(extra 0 values are replaced with -1)

	The correspondence results are stored in the variables
	row2colMap and col2rowMap s.t.

		row2colMap(r) = c means that col c is assigned to row r
		col2rowMap(c) = r means that row r is assigned to column c

	@param initMaps if true the row/col maps are init to invalid values,
	                which help check the mapping by calling CheckMapping()
*/
double Munkres::Solve(const DoubleMatrix& m, UIntVector* row2colMap, 
					UIntVector* col2rowMap) 
{
#ifdef MUNKRES_DEBUG
	std::cout << "Munkres input matrix:" << std::endl;

	for ( int row = 0 ; row < m.rows() ; row++ ) 
	{
		for ( int col = 0 ; col < m.columns() ; col++ ) {
			std::cout.width(8);
			std::cout << m(row,col) << ",";
		}
		std::cout << std::endl;
	}
	std::cout << std::endl;
#endif

	bool notdone = true;
	int step = 1;

	// Copy m, because it need to be modified
	matrix = m;

	// Z_STAR == 1 == starred, Z_PRIME == 2 == primed
	mask_matrix.set_size(matrix.rows(), matrix.columns());
	mask_matrix.fill(0);

	row_mask = new bool[matrix.rows()];
	col_mask = new bool[matrix.columns()];

	for ( unsigned i = 0 ; i < matrix.rows() ; i++ ) {
		row_mask[i] = false;
	}

	for ( unsigned i = 0 ; i < matrix.columns() ; i++ ) {
		col_mask[i] = false;
	}

	while ( notdone ) {
		switch ( step ) {
			case 0:
				notdone = false;
				break;
			case 1:
				step = step1();
				break;
			case 2:
				step = step2();
				break;
			case 3:
				step = step3();
				break;
			case 4:
				step = step4();
				break;
			case 5:
				step = step5();
				break;
		}
	}

	delete[] row_mask;
	delete[] col_mask;

	// Store results
	/*
	for ( unsigned row = 0 ; row < matrix.rows() ; row++ )
		for ( unsigned col = 0 ; col < matrix.columns() ; col++ )
			if ( mask_matrix(row,col) == Z_STAR )
				matrix(row,col) = 0;
			else
				matrix(row,col) = -1;
				
	#ifdef MUNKRES_DEBUG
		std::cout << "Munkres output matrix:" << std::endl;
		for ( int row = 0 ; row < matrix.rows() ; row++ ) {
			for ( int col = 0 ; col < matrix.columns() ; col++ ) {
				std::cout.width(1);
				std::cout << matrix(row,col) << ",";
			}
			std::cout << std::endl;
		}
		std::cout << std::endl;
//.........这里部分代码省略.........