thrust::inclusive_scan_by_key
Defined in thrust/scan.h
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template<typename DerivedPolicy, typename InputIterator1, typename InputIterator2, typename OutputIterator, typename BinaryPredicate, typename AssociativeOperator>
 OutputIterator thrust::inclusive_scan_by_key(const thrust::detail::execution_policy_base<DerivedPolicy> &exec, InputIterator1 first1, InputIterator1 last1, InputIterator2 first2, OutputIterator result, BinaryPredicate binary_pred, AssociativeOperator binary_op)
- inclusive_scan_by_keycomputes an inclusive key-value or ‘segmented’ prefix sum operation. The term ‘inclusive’ means that each result includes the corresponding input operand in the partial sum. The term ‘segmented’ means that the partial sums are broken into distinct segments. In other words, within each segment a separate inclusive scan operation is computed. Refer to the code sample below for example usage.- This version of - inclusive_scan_by_keyuses the binary predicate- predto compare adjacent keys. Specifically, consecutive iterators- iand- i+1in the range- [first1, last1)belong to the same segment if- binary_pred(*i, *(i+1))is true, and belong to different segments otherwise.- This version of - inclusive_scan_by_keyuses the associative operator- binary_opto perform the prefix sum. When the input and output sequences are the same, the scan is performed in-place.- Results are not deterministic for pseudo-associative operators (e.g., addition of floating-point types). Results for pseudo-associative operators may vary from run to run. - The algorithm’s execution is parallelized as determined by - exec.- The following code snippet demonstrates how to use - inclusive_scan_by_keyusing the- thrust::hostexecution policy for parallelization:- #include <thrust/scan.h> #include <thrust/functional.h> #include <thrust/execution_policy.h> ... int data[10] = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; int keys[10] = {0, 0, 0, 1, 1, 2, 3, 3, 3, 3}; thrust::equal_to<int> binary_pred; thrust::plus<int> binary_op; thrust::inclusive_scan_by_key(thrust::host, keys, keys + 10, data, data, binary_pred, binary_op); // in-place scan // data is now {1, 2, 3, 1, 2, 1, 1, 2, 3, 4}; - See also - inclusive_scan - See also - exclusive_scan_by_key - Parameters
- exec – The execution policy to use for parallelization. 
- first1 – The beginning of the key sequence. 
- last1 – The end of the key sequence. 
- first2 – The beginning of the input value sequence. 
- result – The beginning of the output value sequence. 
- binary_pred – The binary predicate used to determine equality of keys. 
- binary_op – The associative operator used to ‘sum’ values. 
 
- Template Parameters
- DerivedPolicy – The name of the derived execution policy. 
- InputIterator1 – is a model of Input Iterator 
- InputIterator2 – is a model of Input Iterator and - InputIterator2's- value_typeis convertible to- OutputIterator's- value_type.
- OutputIterator – is a model of Output Iterator, and if - xand- yare objects of- OutputIterator's- value_type, then- binary_op(x,y)is defined.
- BinaryPredicate – is a model of Binary Predicate. 
- AssociativeOperator – The function’s return type must be convertible to - OutputIterator's- value_type.
 
- Returns
- The end of the output sequence. 
- Pre
- first1may equal- resultbut the range- [first1, last1)and the range- [result, result + (last1 - first1))shall not overlap otherwise.
- Pre
- first2may equal- resultbut the range- [first2, first2 + (last1 - first1)and the range- [result, result + (last1 - first1))shall not overlap otherwise.