Can’t we just synthesize std::tuple_element from get? Jonathan Müller — @foonathanAdding structured bindings support to a custom tuple-like type template struct my_tuple { … }; Jonathan Jonathan Müller — @foonathan Can’t we just synthesize std::tuple_element from get? CppCon 2024-09-18 1Adding structured bindings support to a custom tuple-like type template struct my_tuple get(Tuple&& t) -> decltype(auto) { … } Jonathan Müller — @foonathan Can’t we just synthesize std::tuple_element from get? CppCon 2024-09-18 1Adding structured bindings support to a custom tuple-like type template

predefined types: GrB_PLUS_BOOL, GrB_PLUS_INT8, GrB_PLUS_UINT8, GrB_PLUS_INT16, GrB_PLUS_UINT16, GrB_PLUS_INT32, GrB_PLUS_UINT32, GrB_PLUS_INT64, GrB_PLUS_UINT64, GrB_PLUS_FP32, GrB_PLUS_FP64. - There are predefined types: GrB_PLUS_BOOL, GrB_PLUS_INT8, GrB_PLUS_UINT8, GrB_PLUS_INT16, GrB_PLUS_UINT16, GrB_PLUS_INT32, GrB_PLUS_UINT32, GrB_PLUS_INT64, GrB_PLUS_UINT64, GrB_PLUS_FP32, GrB_PLUS_FP64. - There are predefined types: GrB_PLUS_BOOL, GrB_PLUS_INT8, GrB_PLUS_UINT8, GrB_PLUS_INT16, GrB_PLUS_UINT16, GrB_PLUS_INT32, GrB_PLUS_UINT32, GrB_PLUS_INT64, GrB_PLUS_UINT64, GrB_PLUS_FP32, GrB_PLUS_FP64. - There are

| views::transform([](auto element) { auto [a, b] = element; return a * b; }); return reduce(par_unseq, z, 0, std::plus()); }Outline - Background (Ranges views::transform([](auto element) { auto [a, b] = element; return a * b; }); return reduce(par_unseq, z.begin(), z.end(), T(0), std::plus()); }Dot Product views::transform([](auto element) { auto [a, b] = element; return a * b; }); return reduce(par_unseq, z.begin(), z.end(), T(0), std::plus()); }Standard C++

Werterion std::cout << "vodd elems: "<< num << '\n' Jifind position of first element with odd value (retums iterator): auto Pos = std::find_if(coll.begin()，coll.end() ， jlrange isodd) on the fy) return elem 8 2 1 std: :cout << "vodd elems: "<< num << Na JWind position of first element with odd value: auto Pos = std::find_if(coll.begin() ，coll.end() ， jlrange (int elem) 1 Jicriterion Werterion std: :cout << "vodd elems: "<< num << Na Jind position of first element with odd value: auto Pos = std::find_if(coll.begin()，coll.end() ， Jirange isodad) ，

and each element is potentially a different size. How do we know where element N is? — Beyond this, each element is also potentially a different type! How do we know what type element N is? 17© std::vector vec {false, 1, 2.0, "three"}; vec[3] = "one plus two"; std::cout << std::get(vec[3]) << std::endl; } // => one plus two 46© 2024 Bloomberg Finance L.P. All rights reserved vv::vector; int main() { vector vec {false, 1, 2.0, "three"}; vec[3] = "one plus two"; std::cout << std::get(vec[3]) << std::endl; } // => three 49© 2024 Bloomberg

T> constexpr auto first_plus_last(T... values) -> T...[0] { return T...[0](values...[0] + values...[sizeof...(values)-1]); } 1 2 3 4 5 6 int main() { 7 //first_plus_last(); // ill formed 8 static_assert(first_plus_last(1, 2, 10) == 11); 9 } 10 24previously meta-programming complex code and slow compiles P2662 Pack indexing // syntax is name-of-a-pack ... [constant-expression] template T> constexpr auto first_plus_last(T... values) -> T...[0] { return T...[0](values...[0] + values...[sizeof...(values)-1]); } 1 2 3 4 5 6 int main() { 7 //first_plus_last(); // ill formed 8

numbers{ 1, 2, 3, 4, 5, 6, 7 }; std::accumulate( begin(numbers), end(numbers), 0 , std::plus<>{} ); Wait a second: Isn’t this the Command design pattern? 🤔An Example from the Standard Library numbers{ 1, 2, 3, 4, 5, 6, 7 }; std::accumulate( begin(numbers), end(numbers), 0 , std::plus<>{} );51The GoF’s Explanation 52 The Command Design Pattern ”Encapsulate a request as an object something should be done ➜ Strategy design patternCommand vs. Strategy 54 What should I do with each element? ➜ Command design pattern std::vector numbers{ 1, 2, 3, 4, 5, 6, 7 }; std::for_each( begin(numbers)

//... } 0 0.1 0 0 0 0 0.2 0 0 0 0 0 2 0.5 0 3 transition_rates 5 0 1 0 population element-wise multiplication weights 0 0.2 2 0 0 0.5 0 0 0 0 0 0 0 0 0 0 2 0.5 0 0Sample a position ForwardIt last, T init ); The generalized sum of init and the elements of [first, last) over std::plus<>(). cppreference.comParallel STL algorithm (average population) 15 // compute average population ForwardIt last, T init ); The generalized sum of init and the elements of [first, last) over std::plus<>(). Specify the execution policy of parallel algorithms cppreference.comParallel STL algorithm

(2009) • Blaze (2012) • Expression template-based libraries • Include the usual BLAS functionality plus decompositions and solvers • For more information on Blaze • CppCon 2016 talk by Klaus Iglberger org/dox/group__TutorialMatrixClass.html• The ∗ operator conveniently implements the matrix product • Not element-by-element multiplication using Eigen::MatrixXd; MatrixXd A { {1.0, 2.0, 3.0}, {1.5, 2.5 from a t-distribution using and the std::generate algorithm • And then apply std::max_element to find the maximum random value in the result #include #include // . .

C++17 Structured Bindings C++17 CTADauto solution2(auto v) { using namespace std::ranges; nth_element(v, std::begin(v) + 2, std::greater{}); transform(std::cbegin(v), std::cbegin(v) + 2, std::begin(v) std::begin(v) + 2, 0, std::plus{}); }C++20 Concepts C++14 Function Deduced Return Type C++17 CTAD C++20 Ranges auto solution3(auto v) { using namespace std::ranges; nth_element(v, std::begin(v) + 2 rv::chunk(2) | rv::transform([](auto rng) { return 1.0 / (rng[0] * rng[1]); }) | hs::accumulate(0.0, std::plus{})) * 8; }auto leibniz_pi_approximation(int n) { return (rv::iota(0, n) | rv::transform([](auto