\returns the distance of a point \a p to its projection onto the line \c *this. * \sa squaredDistance() */

Initialize with an operator and an initial vector

\returns the sparse triangular factor R. It is a sparse matrix */

\returns the matrix \b Z. */

Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero. * * This function does not free the currently allocated memo

Sets *this to the identity matrix. * This function also turns the matrix into compressed mode, and drop any reserved memory. */

allocate device memory

\returns the dimension of the kernel of the matrix of which *this is the LU decomposition. * * \note This method has to determine which pi

\brief Constructs the Hessenberg matrix H in the decomposition * * \returns expression object representing the matrix H * * \p

* \brief Set the number of rows and columns blocks */

\returns the spherical interpolation between \c *this and \a other using * parameter \a t. It is in fact equivalent to a linear interpolation.

Perform the solving operation \f$y=B^{-1}x\f$. \param x_in Pointer to the \f$x\f$ vector. \param y_out Pointer to the \f$y\f$ vector. y_out = inv(B