W3cubDocs

std::transform_reduce

Defined in header `<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)	(since C++17)
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)	(since C++17)

Defined in header <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)

(since C++17)

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)

(since C++17)

1) 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.

2) Same as (1), but executed according to policy. This overload does not participate in overload resolution unless std::is_execution_policy_v<std::decay_t<ExecutionPolicy>> is true

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 to use. See execution policy for details.
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

The overloads with a template parameter named ExecutionPolicy report errors as follows:

If execution of a function invoked as part of the algorithm throws an exception, std::terminate is called.
If the algorithm fails to allocate memory, std::bad_alloc is thrown.

Notes

unary_op is not applied to init.

If the range is empty, init is returned, unmodified.

Example

transform_reduce can be used to parallelize std::inner_product:

#include <vector>
#include <iterator>
#include <functional>
#include <iostream>
#include <numeric>
#include <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::transform_reduce(
        std::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:

accumulate	sums up a range of elements (function template)
transform	applies a function to a range of elements (function template)
reduce (C++17)	similar to `std::accumulate`, except out of order (function template)