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dft_tools/doc/reference/c++/arrays_old/algebras.rst
Olivier Parcollet f2c7d449cc First commit : triqs libs version 1.0 alpha1
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.. highlight:: c
array and matrix/vector algebra
=======================================================
Arrays and matrices can be combined in formal algebraic expressions, which models the :ref:`HasImmutableArrayInterface` concept.
This algebraic expressions can therefore be used as RHS of assignment (SEE) or in array/matrix contructors.
.. warning::
To use this technique, you have to include the <arrays/expressions/array_algebra.hpp> or <arrays/expressions/matrix_algebra.hpp>
files.
For example ::
array<long,2> A (2,2), B(2,2),C;
C= A + 2*B;
array<long,2> D( A+ 2*B);
array<double,2> F( 0.5 * A); // Type promotion is automatic
The technique is called `expression templates`. It allows the elimination of temporaries, so that the clear
and readable code::
Z= A + 2*B + C/2;
is in fact rewritten by the compiler into ::
for (i,j,...) indices of A, B :
C(i,j) = A(i,j) + 2* B(i,j) + C(i,j)/2
instead of making a chain of temporaries (C/2, 2*B, 2*B + C/2...) that "ordinary" object-oriented programming would produce.
As a result, the produced code is as fast as if you were writing the loop yourself,
but with several advantages :
* It is more **compact** and **readable** : you don't have to write the loop, and he indices range are computed automatically.
* It is much better for **optimization** :
* What you want is to tell the compiler/library to compute this expression, not *how* to do it optimally on a given machine.
* For example, since the memory layout is decided at compile time, the library can traverse the data
in an optimal way, allowing machine-dependent optimization.
* The library can perform easy optimisations, e.g. for vector it will use blas if possible.
Arrays vs matrices
----------------------
Because their multiplication is not the same, arrays and matrices don't form the same algebra.
Mixing them in expression would therefore be meaningless and it is therefore not allowed ::
array<long,2> A;
matrix<long,2> M;
M + A; // --> ERROR
However, you can always make a matrix_view from a array of rank 2 ::
A + make_matrix_view(M); //--> OK.
.. note::
Making view is very cheap, it only copies the index systems.
Expressions are lazy
---------------------------
This means that constructing an expression is separated from evaluating it ::
auto e = A + 2*B; // expression, purely formal, no computation is done
cout<< e <<endl ; // prints the expression
cout<< e(1,2) <<endl ; // evaluates just at a point
cout<< e.domain() <<endl ; // just computes its domain
array<long,2> D(e); // now really makes the computation and store the result in D.
The expression type is complicated (the expression in stored in the C++ type), so we used here
the C++0x `auto` to make simple things simple...
FAQ
----------
Where can expressions be used ?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Expressions models :ref:`HasImmutableArrayInterface` concept, so they can used *anywhere*
an object modeling this concept is accepted, e.g. :
* array, matrix contruction
* operator =, +=, -=, ...
They behave like an immutable array : they have a domain, they can be evaluated.
When `C` is assigned to the expression in the previous example,
the compiler just needs to compute the new domain for `C`, resize it and fill it by evaluation of the expression.
What is the cost of this technique ?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Thanks to the Boost Proto library, this can be done :
* with an acceptable increase in compilation time (try it !).
* in about *2 pages of readable code* !