div

auto eve::div = functor<div_t>

inlineconstexpr

Header file

#include <eve/module/core.hpp>

Callable Signatures

namespace eve
{
   // Regular overloads
   constexpr auto div(value auto x, value auto ... xs)                          noexcept; // 1
   constexpr auto div(kumi::non_empty_product_type auto const& tup)             noexcept; // 2
 
   // Lanes masking
   constexpr auto div[conditional_expr auto c](/*any of the above overloads*/)  noexcept; // 3
   constexpr auto div[logical_value auto m](/*any of the above overloads*/)     noexcept; // 3
 
   // Semantic exclusive options
   constexpr auto div[upward](/*any of the above overloads*/)                   noexcept; // 4
   constexpr auto div[downward](/*any of the above overloads*/)                 noexcept; // 4
   constexpr auto div[toward_zero](/*any of the above overloads*/)              noexcept; // 4
   constexpr auto div[to_nearest](/*any of the above overloads*/)               noexcept; // 4
   constexpr auto div[lower](/*any of the above overloads*/)                    noexcept; // 5
   constexpr auto div[upper](/*any of the above overloads*/)                    noexcept; // 6
   constexpr auto div[lower][srict](/*any of the above overloads*/)             noexcept; // 5
   constexpr auto div[upper][srict](/*any of the above overloads*/)             noexcept; // 6
 
   // Semantic options
   constexpr auto div[right](/*any of the above overloads*/)                    noexcept; // 1
   constexpr auto div[saturated](integral_value auto x, integral_value auto y)) noexcept; // 7
   constexpr auto div[left](/*any of the above overloads*/)                     noexcept; // 8
}

Parameters

• x, ...xs: real arguments.
• tup: non empty tuple of arguments.
• c: Conditional expression masking the operation.
• m: Logical value masking the operation.

Return value

1. If the arguments are \((x_i)_{0\le i\le n}\) The value of \(x/\prod_1^n x_i\) is returned.
2. equivalent to the call on the elements of the tuple.
3. The operation is performed conditionnaly
4. If z denotes the prduct of the xs, the call div[o](x, xs...) produces:
   • eve::trunc(div(x, z)), if d is toward_zero.
   • eve::floor(div(x, z)), if d is downward.
   • eve::ceil(div(x, z)), if d is upward.
   • eve::nearest(div(x, z)), if d is to_nearest.
5. The floating division is computed in a rounding mode such that the result is guaranted to be less or equal to the exact one (except for Nans).Combined with strict the option ensures generally faster computation, but strict inequality.
6. The floating division is computed in a rounding mode such that the result is guaranted to be greater or equal to the exact one (except for Nans). Combined with strict the option ensures generally faster computation, but strict inequality.
7. computes the saturated division of x by y. The result is always defined even if the denominator is 0.

8. div[left](a, b) is semantically equivalent to div(b, a)

   The relevant cases are just in fact the division by 0 for integral types in which case the result is eve::valmin(as(x)) or [valmax(as(x))](ref eve::valmax) according to the dividend sign, and the division of valmin(as(x)) by -1 that produces valmax(as(x)).

Note

• With two parameters, the call div(x, y) is equivalent to x / y if x or y is an simd value.
• Although the infix notation with / is supported for two parameters, the / operator on standard scalar types is the original one and so can lead to automatic promotion.

Example

// revision 1
#include <eve/module/core.hpp>
#include <iostream>
#include <iomanip>
 
int main()
{
  using wf_t = eve::wide<float, eve::fixed<4>>;
  wf_t pf = {3.2, 1.6, 3, 32700}, qf = {4.1, 2.345, 1, 100};
 
  std::cout << "---- simd" << std::setprecision(10) << '\n'
            << " <- pf                    = " << pf << '\n'
            << " <- qf                    = " << qf << '\n'
            << " -> div(pf, qf)           = " << eve::div(pf, qf) << '\n'
            << " -> pf / qf               = " << pf / qf << '\n'
            << " -> div[left](pf, qf)     = " << eve::div[eve::left](pf, qf) << "\n"
            << " -> div[upper](pf, qf)    = " << eve::div[eve::upper](pf, qf) << '\n'
            << " -> div[lower](pf, qf)    = " << eve::div[eve::lower](pf, qf) << '\n'
            << " -> div[pf> qf](pf, qf)   = " << eve::div[pf>qf](pf, qf) << '\n';
 
 
  wf_t rf = {3034, 200, 333, 32700}, sf = {4, 7, 13, 100};
 
  std::cout << "---- simd" << '\n'
            << " <- rf                       = " << rf << '\n'
            << " <- sf                       = " << sf << '\n'
            << " -> div[toward_zero](rf, sf) = " << eve::div[eve::toward_zero](rf, sf) << '\n'
            << " -> div[lower](rf, sf)       = " << eve::div[eve::lower](rf, sf)       << '\n'
            << " -> div[upper](rf, sf)       = " << eve::div[eve::upper](rf, sf)       << '\n'
            << " -> div[to_nearest](rf, sf)  = " << eve::div[eve::to_nearest](rf, sf)  << '\n';
 
  auto k = kumi::tuple{pf, pf, pf, 1};
  std::cout << "---- multi parameters" << '\n'
            << " -> div(k)                        = " << eve::div(k)                       << '\n'
            << " -> div(kumi::tuple{pf, pf})      = " << eve::div( kumi::tuple{pf, pf})    << '\n'
            << " -> div(kumi::tuple{pf, 1.0f)     = " << eve::div( kumi::tuple{pf, 1.0f})  << '\n'
            << " -> div(kumi::tuple{1.0f, pf)     = " << eve::div( kumi::tuple{1.0f, pf})  << '\n';
}