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https://github.com/paboyle/Grid.git
synced 2025-06-13 04:37:05 +01:00
Making sure I understand row-major vs column-major ordering
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@ -338,11 +338,11 @@ void DebugShowTensor(MyTensor &x, const char * n)
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// Initialise
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assert( d.size() == 3 );
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for( int i = 0 ; i < d[0] ; i++ )
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for( int j = 0 ; j < d[1] ; j++ )
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for( int k = 0 ; k < d[2] ; k++ ) {
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x(i,j,k) = std::complex<double>(SizeCalculated, -SizeCalculated);
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SizeCalculated--;
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}
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for( int j = 0 ; j < d[1] ; j++ )
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for( int k = 0 ; k < d[2] ; k++ ) {
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x(i,j,k) = std::complex<double>(SizeCalculated, -SizeCalculated);
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SizeCalculated--;
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}
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// Show raw data
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std::cout << "Data follow : " << std::endl;
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Complex * p = x.data();
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@ -496,7 +496,66 @@ public:
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inline value_type * end(void) { return m_p + N; }
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};
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bool DebugFelixTensorTest( void )
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template <int Options>
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void EigenSliceExample()
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{
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std::cout << "Eigen example, Options = " << Options << std::endl;
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using T2 = Eigen::Tensor<int, 2, Options>;
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T2 a(4, 3);
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a.setValues({{0, 100, 200}, {300, 400, 500},
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{600, 700, 800}, {900, 1000, 1100}});
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std::cout << "a\n" << a << std::endl;
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DumpMemoryOrder( a, "a" );
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Eigen::array<typename T2::Index, 2> offsets = {1, 0};
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Eigen::array<typename T2::Index, 2> extents = {2, 2};
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T2 slice = a.slice(offsets, extents);
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std::cout << "slice\n" << slice << std::endl;
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DumpMemoryOrder( slice, "slice" );
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std::cout << "\n========================================" << std::endl;
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}
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template <int Options>
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void EigenSliceExample2()
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{
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using TestScalar = std::complex<float>;
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using T3 = Eigen::Tensor<TestScalar, 3, Options>;
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using T2 = Eigen::Tensor<TestScalar, 2, Options>;
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T3 a(2,3,4);
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std::cout << "Initialising:a";
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float z = 0;
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for( int i = 0 ; i < a.dimension(0) ; i++ )
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for( int j = 0 ; j < a.dimension(1) ; j++ )
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for( int k = 0 ; k < a.dimension(2) ; k++ ) {
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TestScalar w{z, -z};
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a(i,j,k) = w;
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std::cout << " a(" << i << "," << j << "," << k << ")=" << w;
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z++;
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}
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std::cout << std::endl;
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//std::cout << "a initialised to:\n" << a << std::endl;
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DumpMemoryOrder( a, "a" );
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std::cout << "for_all(a):";
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for_all( a, [&](TestScalar c, typename T3::Index n, const std::size_t * pDims ){
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std::cout << " (" << pDims[0] << "," << pDims[1] << "," << pDims[2] << ")<" << n << ">=" << c;
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} );
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std::cout << std::endl;
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Eigen::array<typename T3::Index, 3> offsets = {0,1,1};
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Eigen::array<typename T3::Index, 3> extents = {1,2,2};
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T3 b;
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b = a.slice( offsets, extents );//.reshape(NewExtents);
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std::cout << "b = a.slice( offsets, extents ):\n" << b << std::endl;
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DumpMemoryOrder( b, "b" );
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T2 c(3,4);
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c = a.chip(0,1);
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std::cout << "c = a.chip(0,0):\n" << c << std::endl;
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DumpMemoryOrder( c, "c" );
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//T2 d = b.reshape(extents);
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//std::cout << "b.reshape(extents) is:\n" << d << std::endl;
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std::cout << "\n========================================" << std::endl;
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}
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void DebugFelixTensorTest( void )
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{
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unsigned int Nmom = 2;
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unsigned int Nt = 2;
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@ -509,25 +568,10 @@ bool DebugFelixTensorTest( void )
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using BaryonTensorMap = Eigen::TensorMap<BaryonTensorSet>;
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BaryonTensorMap BField4 (&Memory[0], Nmom,4,Nt,N_1,N_2,N_3);
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using TestScalar = std::complex<float>;
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//typedef Eigen::TensorFixedSize<TestScalar, Eigen::Sizes<9,4,2>, Eigen::StorageOptions::RowMajor> TestTensorFixed;
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using T3 = Eigen::Tensor<TestScalar, 3, Eigen::StorageOptions::RowMajor>;
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using T2 = Eigen::Tensor<TestScalar, 2, Eigen::StorageOptions::RowMajor>;
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T3 a(4,3,2);
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for_all( a, [&](TestScalar &c, float n, const std::size_t * pDims ){
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c = std::complex<float>{n,-n};
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} );
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std::cout << "a initialised to:\n" << a << std::endl;
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Eigen::array<int, 3> offsets = {0,0,0};
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Eigen::array<int, 3> extents = {1,3,2};
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T2 b(3,2);
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auto c = a.slice( offsets, extents).reshape(extents);
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std::cout << "c is:\n" << c << std::endl;
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b = a.chip(0,0);
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std::cout << "b is:\n" << b << std::endl;
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//b = c;
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return true;
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EigenSliceExample<Eigen::RowMajor>();
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EigenSliceExample<0>();
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EigenSliceExample2<Eigen::RowMajor>();
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EigenSliceExample2<0>();
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}
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bool DebugGridTensorTest( void )
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@ -561,7 +605,9 @@ bool DebugGridTensorTest( void )
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Start += Inc;
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}
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i = 0;
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for( auto x : toc7 ) std::cout << "toc7[" << i++ << "] = " << x << std::endl;
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std::cout << "toc7:";
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for( auto x : toc7 ) std::cout << " [" << i++ << "]=" << x;
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std::cout << std::endl;
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t2 o2;
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auto a2 = TensorRemove(o2);
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