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 <boost/iterator/zip_iterator.hpp>
 #include <boost/tuple.hpp>
 #include <experimental/execution_policy>
 #include <experimental/numeric>
 #include <functional>
 #include <iostream>
 #include <iterator>
 #include <vector>
 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 or folds 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)