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131 lines
3.5 KiB
ReStructuredText
131 lines
3.5 KiB
ReStructuredText
.. highlight:: c
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.. _arr_map_fold:
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Functional constructs : map & fold
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###########################################
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Two standard functional constructs are provided :
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* *map* that promotes a function of the array element to a function of the array,
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element by element.
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* *fold* is the reduction of a function on the array.
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.. _map:
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map
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========================================================
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* **Purpose** :
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map promotes any function into an `array function`, acting term by term.
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* **Synopsis** ::
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template<class F> auto map (F f);
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If `f` is a function, or a function object ::
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ValueType2 f(ValueType1)
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Then map(f) is a function::
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template<ImmutableCuboidArray A> auto map(f) (A const &)
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with :
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* A::value_type == ValueType1
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* The returned type of map(f) models the :ref:`ImmutableCuboidArray` concept
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* with the same domain as A
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* with value_type == ValueType2
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* N.B. : Some cases require explicit cast, e.g. for the standard abs function (already defined in arrays/mapped_function.hpp) ,
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or the compiler does not know which std::abs you are talking about ::
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auto Abs = map( std::function<double(double)>(static_cast< double (*)(double)> (std::abs)) );
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* TO DO : clarify the F f or F const & : check code and put an example with std::ref.
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* **Example** :
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.. compileblock::
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#include <triqs/arrays.hpp>
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using triqs::arrays::matrix; using triqs::arrays::make_matrix; using triqs::clef::placeholder;
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int main() {
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// declare and init a matrix
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placeholder<0> i_; placeholder<1> j_;
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matrix<int> A (2,2); A(i_,j_) << i_ + j_ ;
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// the mapped function
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auto F = triqs::arrays::map([](int i) { return i*2.5;});
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std::cout<< "A = " << A << std::endl;
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std::cout<< "F(A) = " << F(A) << std::endl; // oops no computation done
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std::cout<< "F(A) = " << make_matrix(F(A)) << std::endl;
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std::cout<< "3*F(2*A) = " << make_matrix(3*F(2*A)) << std::endl;
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}
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fold
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========================================================
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* **Purpose** :
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fold implements the folding (or reduction) on the array.
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* **Syntax** :
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If `f` is a function, or a function object of synopsis (T, R being 2 types) ::
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R f ( T, R )
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then ::
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auto F = fold(f);
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is a callable object which can fold any array of value_type T.
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So, if
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* A is a type which models the :ref:`ImmutableCuboidArray` concept
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(e.g. an array , a matrix, a vector, an expression, ...)
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* A::value_type is T
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then ::
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fold (f) ( A, R init = R() ) = f( f( f( ... f( a(0,1), f(a(0,0), init)))))
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Note that :
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* The order of traversal is the same as foreach.
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* The precise return type of fold is an implementation detail, depending on the precise type of f,
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use auto to keep it.
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* The function f will be inlined if possible, leading to efficient algorithms.
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* fold is implemented using a foreach loop, hence it is efficient.
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* **Example** :
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Many algorithms can be written in form of map/fold.
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The function :ref:`arr_fnt_sum` which returns the sum of all the elements of the array is implemented as ::
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template <class A>
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typename A::value_type sum(A const & a) { return fold ( std::plus<typename A::value_type>()) (a); }
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Note in this example :
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* the simplicity of the code
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* the genericity : it is valid for any dimension of array.
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* internally, the library will rewrite it as a series of for loop, ordered in the TraversalOrder of the array
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and inline the plus operator.
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