std::experimental::parallel::transform_reduce(3)

NAME
std::experimental::parallel::transform_reduce - std::experimental::parallel::transform_reduce

Synopsis
   Defined in header <experimental/numeric>
   template<class InputIt, class UnaryOp, class T, class BinaryOp>
   T transform_reduce(InputIt first, InputIt last, (1) (parallelism TS)
   UnaryOp unary_op, T init, BinaryOp binary_op);
   template<class ExecutionPolicy,
   class InputIt, class UnaryOp, class T, class BinaryOp>
   T transform_reduce(ExecutionPolicy&& policy, (2) (parallelism TS)
   InputIt first, InputIt last,
   UnaryOp unary_op, T init, BinaryOp binary_op);
   Applies unary_op to each element in the range [first; last) and reduces the results
   (possibly permuted and aggregated in unspecified manner) along with the initial
   value init over binary_op.
   The behavior is non-deterministic if binary_op is not associative or not
   commutative.
   The behavior is undefined if unary_op or binary_op modifies any element or
   invalidates any iterator in [first; last).

Parameters
   first, last - the range of elements to apply the algorithm to
   init - the initial value of the generalized sum
   policy - the execution policy
   unary_op - unary FunctionObject that will be applied to each element of the input
                 range. The return type must be acceptable as input to binary_op
   binary_op - binary FunctionObject that will be applied in unspecified order to the
                 results of unary_op, the results of other binary_op and init.

Type requirements
   -
   InputIt must meet the requirements of LegacyInputIterator.

Return value
   Generalized sum of init and unary_op(*first), unary_op(*(first+1)), ...
   unary_op(*(last-1)) over binary_op,
   where generalized sum GSUM(op, a
   1, ..., a
   N) is defined as follows:
     * if N=1, a
       1
     * if N > 1, op(GSUM(op, b
       1, ..., b
       K), GSUM(op, b
       M, ..., b
       N)) where
              * b
                1, ..., b
                N may be any permutation of a1, ..., aN and
              * 1 < K+1 = M ≤ N
   in other words, the results of unary_op may be grouped and arranged in arbitrary
   order.

Complexity
   O(last - first) applications each of unary_op and binary_op.

Exceptions
     * If execution of a function invoked as part of the algorithm throws an exception,
              * if policy is parallel_vector_execution_policy, std::terminate is called
              * if policy is sequential_execution_policy or parallel_execution_policy,
                the algorithm exits with an exception_list containing all uncaught
                exceptions. If there was only one uncaught exception, the algorithm may
                rethrow it without wrapping in exception_list. It is unspecified how
                much work the algorithm will perform before returning after the first
                exception was encountered.
              * if policy is some other type, the behavior is implementation-defined
     * If the algorithm fails to allocate memory (either for itself or to construct an
       exception_list when handling a user exception), std::bad_alloc is thrown.

Notes
   unary_op is not applied to init
   If the range is empty, init is returned, unmodified
     * If policy is an instance of sequential_execution_policy, all operations are
       performed in the calling thread.
     * If policy is an instance of parallel_execution_policy, operations may be
       performed in unspecified number of threads, indeterminately sequenced with each
       other
     * If policy is an instance of parallel_vector_execution_policy, execution may be
       both parallelized and vectorized: function body boundaries are not respected and
       user code may be overlapped and combined in arbitrary manner (in particular,
       this implies that a user-provided Callable must not acquire a mutex to access a
       shared resource)

Example
   transform_reduce can be used to parallelize std::inner_product: // Run this code
 #include <vector>
 #include <iterator>
 #include <functional>
 #include <iostream>
 #include <experimental/numeric>
 #include <experimental/execution_policy>
 #include <boost/iterator/zip_iterator.hpp>
 #include <boost/tuple.hpp>
 int main()
 {
     std::vector<double> xvalues(10007, 1.0), yvalues(10007, 1.0);
     double result = std::experimental::parallel::transform_reduce(
         std::experimental::parallel::par,
         boost::iterators::make_zip_iterator(
             boost::make_tuple(std::begin(xvalues), std::begin(yvalues))),
         boost::iterators::make_zip_iterator(
             boost::make_tuple(std::end(xvalues), std::end(yvalues))),
         [](auto r) { return boost::get<0>(r) * boost::get<1>(r); }
         0.0,
         std::plus<>()
     );
     std::cout << result << '\n';
 }

Output:
 10007

See also
   accumulate sums up a range of elements
                    (function template)
                    applies a function to a range of elements, storing results in a
   transform destination range
                    (function template)
   reduce similar to std::accumulate, except out of order
   (parallelism TS) (function template)