C++ QMat::nRows方法代码示例

/**
 * \brief Construct a diagonal matrix 
 *
 * Use diagonal values to create a new diagonal matrix
 * @param d Matrix to get diagonal values
 * @return QMat new diagonal matrix
 */
QMat QMat::diagonal ( const QMat & d )
{
	QMat R ( d.nRows(),d.nRows() );
	for (int i=0; i<d.nRows(); i++)
	{
		for (int j=0; j<d.nCols(); j++)
		{
			R(i,j) = 0;
		}
	}
	for ( int i=0; i < d.nRows(); i++ )
		R ( i,i ) = d ( i );
	return R;
}

/**
 * \brief Matrix to matrix product operator; \f$ C = this * A \f$
 *
 * IPP coge (columnas, filas) en las llamadas
 * @param A matrix factor for operation
 * @return QMat New matrix result
 */
QMat QMat::operator * ( const QMat & A ) const
{
// 	printf("Operator *: (%d,%d) x (%d,%d)\n", rows, cols, A.rows, A.cols);
	QMat C=zeros( rows, A.nCols() );
	if ( cols != A.nRows())
	{
		QString ex= "QMat::operator* - a.cols!=b.rows";
		throw ex;
	}
	else
	{
#ifdef COMPILE_IPP
	ippmMul_mm_32f ( toDataConst(), cols*sizeof ( T ), sizeof ( T ), cols, rows, A.toDataConst(), A.nCols() *sizeof ( T ), sizeof ( T ), A.nCols(), A.nRows(), C.toData(), C.nCols() *sizeof ( T ), sizeof ( T ) );
#else
	for(int i=0;i<rows;i++)
	{
		for(int j=0;j<A.cols;j++)
		{
			C(i,j)=0;
			for(int k=0;k<cols;k++)
			{
				C(i,j) += operator()(i,k)*A(k,j);
			}
// 			printf("%f ", C(i,j));
		}
// 		printf("\n");
	}
#endif
	}
	return C;
}

/**
 * @brief Moves a virtual copy of the robot along the road checking for enough free space around it
 * 
 * @param innermodel ...
 * @param road ...
 * @param laserData ...
 * @param robotRadius ...
 * @return bool
 */
 bool ElasticBand::checkCollisionAlongRoad(InnerModel *innermodel, const RoboCompLaser::TLaserData& laserData, WayPoints &road,  WayPoints::const_iterator robot,
                                            WayPoints::const_iterator target, float robotRadius)
 {
	//Simplify laser polyline using Ramer-Douglas-Peucker algorithm
	std::vector<Point> points, res;
	QVec wd;
	for( auto &ld : laserData)
	{
		wd = innermodel->laserTo("world", "laser", ld.dist, ld.angle);      //OPTIMIZE THIS FOR ALL CLASS METHODS
		points.push_back(Point(wd.x(), wd.z()));
	}
	res = simPath.simplifyWithRDP(points, 70);
	qDebug() << __FUNCTION__ << "laser polygon after simp" << res.size();

	// Create a QPolygon so we can check if robot outline falls inside
	QPolygonF polygon;
	for (auto &p: res)
		polygon << QPointF(p.x, p.y);

	// Move the robot along the road
	QVec memo = innermodel->transform6D("world","robot");
	bool free = false;
	for( WayPoints::const_iterator it = robot; it != target; ++it)
	{
		if( it->isVisible == false)
			break;
		// compute orientation of the robot at the point

		innermodel->updateTransformValues("robot", it->pos.x(), it->pos.y(), it->pos.z(), 0, it->rot.y(), 0);
		//get Robot transformation matrix
		QMat m = innermodel->getTransformationMatrix("world", "robot");
		// Transform all points at one
		qDebug() << __FUNCTION__ << "hello2";
		m.print("m");
		pointsMat.print("pointsMat");
		QMat newPoints = m * pointsMat;
		qDebug() << __FUNCTION__ << "hello3";

		//Check if they are inside the laser polygon
		for( int i=0; i<newPoints.nRows(); i++)
			if( polygon.containsPoint(QPointF(pointsMat(i,0)/pointsMat(i,3), pointsMat(i,2)/pointsMat(i,3)), Qt::OddEvenFill ) == false)
			{
				free = false;
				break;
			}
		free = true;
	}
	 qDebug() << __FUNCTION__ << "hello";

	 // Set the robot back to its original state
	innermodel->updateTransformValues("robot", memo.x(), memo.y(), memo.z(), 0, memo.ry(), 0);
	return free ? true : false;
 }

int QMat::maxDim ( const QMat &A )
{
	return qMax ( A.nRows(), A.nCols() );
}

int QMat::minDim ( const QMat &A )
{
	return qMin ( A.nRows(), A.nCols() );
}

bool QMat::isSquare ( const QMat &A ) const
{
	return ( A.nRows() == A.nCols() );
}

bool RMat::QMat::is3ColumnVector(const QMat & A) const
{
	return (A.nRows() == 3 and A.nCols() == 1);
}