=============
Using CXXBLAS                                                           [TOC]
=============

FLENS matrix/vector types make iteraction with BLAS easy as you have access
to

- matrix/vector dimensions,
- storage order,
- leading dimensions and strides and
- data pointers.

In addition __CXXBLAS__ makes it easy to reuse the same code for different
element types like `float`, `double`, `std::complex<float>`,
`std::complex<double>` or any other type that "can be used like a `double`",
i.e. relevant operators (e.g. `+`, `*`, ...) are overloaded.

Toy Example
===========
Assume you want to compute $y = \beta y + \alpha\,A^T x + z$ where $\alpha,
\beta$ are scalars, $x, y, z$ are (dense) vectors and $A$ is a (general) matrix
(with full storage).

Using CXXBLAS for this task you will first call __gemv__ and subsequently
__axpy__.

Example Code
============
:import: flens/examples/tut02-page01-example.cc [stripped, downloadable]

Comments on Example Code
========================
:import: flens/examples/tut02-page01-example.cc [brief]


Compile and Run
===============

 *--[SHELL]-------------------------------------------------------------------*
 |                                                                            |
 |  cd flens/examples                                                         |
 |  g++ -Wall -std=c++11 -I../.. tut02-page01-example.cc                      |
 |  ./a.out                                                                   |
 |                                                                            |
 *----------------------------------------------------------------------------*


:links: __CXXBLAS__  -> dir:cxxblas/
        __axpy__     -> file:cxxblas/level1/axpy.h
        __gemv__     -> file:cxxblas/level2/gemv.h

:navigate: __up__    -> doc:flens/examples/tutorial
           __next__  -> doc:flens/examples/tut02-page02