Basic classes : array, matrix and vector and their views ================================================================= * The library provides several interoperable forms of arrays : * array : general (rectangular) `N`-dimensionnal array; models :ref:`HasImmutableArrayInterface` concept. * matrix : models the :ref:`MutableMatrix` concept. * vector : models the :ref:`MutableVector` concept. and the corresponding view classes : array_view, matrix_view, vector_view. * All these classes contains basically two things : * a *storage*, i.e. a (shared) pointer to the data in memory. * an *indexmap*, i.e. an object that encode the index systems and can map it to the memory. * They differ by their behaviour : * array, matrix, vector are *values* with value semantics, while the X_view classes are views, with reference semantics, see below. * array form an array algebra, where operation are done element-wise, while matrix and vector for the usual algebra and vector space of linear algebra. * These classes are largely interoperable, as explained below : it is easy and quick to take a matrix_view of an array, or vice versa. * The classes haves similar template parameters : .. code-block:: c typedef unsigned long long ull_t; template class array; template class array_view; template class matrix; template class matrix_view; template class vector; template class vector_view; where triqs::ull_t is the type defined by : .. code-block:: c typedef unsigned long long ull_t; Template parameters ---------------------------- ============================ ================================== ========================== ==================================================================== Template parameter Accepted type Access in the class Meaning ============================ ================================== ========================== ==================================================================== ValueType normally a scalar, but any default value_type The type of the element of the array constructible type (?). Rank int rank The rank of the array OptionsFlags unsigned long long Compile time options, see below. TraversalOrder unsigned long long Compile time options, see below. ============================ ================================== ========================== ==================================================================== * Rank is only present for array, since matrix have rank 2 and vector rank 1. * OptionFlags is a series of flags determining various options at compile time. The possible flags are accessible via a constexpr ull_t in triqs::arrays or a macro : ======================== ======================================= Macro constexpr equivalent ======================== ======================================= BOUND_CHECK triqs::arrays::BoundCheck TRAVERSAL_ORDER_C triqs::arrays::TraversalOrderC TRAVERSAL_ORDER_FORTRAN triqs::arrays::TraversalOrderFortran DEFAULT_INIT triqs::arrays::DefaultInit ======================== ======================================= Defaults can be modified with the macros : * `TRIQS_ARRAYS_ENFORCE_BOUNDCHECK` : enforce BoundCheck by default (slows down codes ! Use only for debugging purposes). * `TRIQS_ARRAYS_ENFORCE_INIT_DEFAULT` : init all arrays by default [ NOT IMPLEMENTED] * TraversalOrder is a coding of the optimal ordering of indices, given by a permutation evaluated at **compile time**. The traversal of the arrays (iterators, foreach loop) will be written and optimised for this order. The default (0) is understood as regular C-style ordering (slowest index first). Note that an array can use any index ordering in memory, and that decision is take at run time (this is necessary for interfacing with python numpy arrays, see below). The code will be correct for any order, but optimised for the TraversalOrder. For a few very specials operations (e.g. regrouping of indices), the indices ordering in memory and TraversalOrder must coincide. This will be explicitely said below. By default, it is not necessary. The permutation P encodes the position of the index : P[0] is the fastest index, P[rank - 1] the slowest index (see examples below). TraversalOrder is not present for vector since there is only one possibility in 1d. * Examples will be given in the next paragraph, with constructors.