# std::experimental::parallel::transform_reduce

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< cpp‎ | experimental

Defined in header `<experimental/numeric>` |  |
template<class InputIt, class UnaryOp, class T, class BinaryOp> T transform_reduce(InputIt first, InputIt last, UnaryOp unary_op, T init, BinaryOp binary_op); | (1) | (parallelism TS)
template<class ExecutionPolicy, class InputIt, class UnaryOp, class T, class BinaryOp> T transform_reduce(ExecutionPolicy&& policy, InputIt first, InputIt last, UnaryOp unary_op, T init, BinaryOp binary_op); | (2) | (parallelism TS)

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 `InputIterator`.

### 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)
transform | applies a function to a range of elements (function template)
reduce (parallelism TS) | similar to std::accumulate, except out of order (function template)

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