ParallelRaContainerKernel.h

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/*
Copyright 2007-2025. Algoryx Simulation AB.
 
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tutorials, scene files and technical white papers, are copyrighted, proprietary
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valid commercial license from Algoryx Simulation AB.
 
Algoryx Simulation AB disclaims all responsibilities for loss or damage caused
from using this software, unless otherwise stated in written agreements with
Algoryx Simulation AB.
*/
 
#pragma once
 
#include <agx/Kernel.h>
 
namespace agx
{
  template<typename T, typename argument_type = typename T::const_reference>
  class ParallelRaContainerKernel : public agx::LambdaKernel
  {
    public:
      virtual void doExecute( const T* container );
 
    protected:
      ParallelRaContainerKernel( const agx::Name& name );
 
      agx::UInt getNumElements() const;
 
      const T* getContainer() const;
 
    protected:
      virtual void onPreExecute();
 
      virtual void onElement( agx::UInt index, argument_type element ) = 0;
 
      virtual void onPostExecute();
 
    private:
      ParallelRaContainerKernel( const ParallelRaContainerKernel<T>& ) = delete;
      ParallelRaContainerKernel<T>& operator=( const ParallelRaContainerKernel<T>& ) = delete;
 
      using agx::LambdaKernel::execute;
 
      void executeJob( const agx::RangeJob& job );
 
    private:
      const T* m_container;
  };
 
  template<typename T, typename argument_type>
  ParallelRaContainerKernel<T, argument_type>::ParallelRaContainerKernel( const agx::Name& name )
    : LambdaKernel( name,
                    std::bind( &ParallelRaContainerKernel<T, argument_type>::executeJob, this, std::placeholders::_1 ),
                    std::bind( &ParallelRaContainerKernel<T, argument_type>::getNumElements, this ) ),
      m_container( nullptr )
  {
  }
 
  template<typename T, typename argument_type>
  agx::UInt ParallelRaContainerKernel<T, argument_type>::getNumElements() const
  {
    return m_container != nullptr ? agx::UInt( m_container->size() ) : agx::UInt( 0 );
  }
 
  template<typename T, typename argument_type>
  const T* ParallelRaContainerKernel<T, argument_type>::getContainer() const
  {
    return m_container;
  }
 
  template<typename T, typename argument_type>
  void ParallelRaContainerKernel<T, argument_type>::onPreExecute()
  {
  }
 
  template<typename T, typename argument_type>
  void ParallelRaContainerKernel<T, argument_type>::doExecute( const T* container )
  {
    m_container = container;
    if ( m_container != nullptr ) {
      onPreExecute();
      agx::LambdaKernel::execute();
      onPostExecute();
    }
    m_container = nullptr;
  }
 
  template<typename T, typename argument_type>
  void ParallelRaContainerKernel<T, argument_type>::onPostExecute()
  {
  }
 
  template<typename T, typename argument_type>
  void ParallelRaContainerKernel<T, argument_type>::executeJob( const agx::RangeJob& job )
  {
    for ( agx::UInt i = job.range().begin(), end = job.range().end(); i != end; ++i )
      onElement( i, const_cast<T&>(*m_container)[ i ] );
  }
}