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Finalising traits
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@ -101,6 +101,20 @@ void ioTest(const std::string &filename, const O &object, const std::string &nam
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}
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#ifdef DEBUG
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template <typename T>
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//typename std::enable_if<EigenIO::is_tensor<T>::value, void>::type
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void dump_tensor(T & t)
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{
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using Traits = typename EigenIO::Traits<typename T::Scalar>;
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for_all( t, [&](typename Traits::scalar_type &c, typename T::Index index, const std::size_t * pDims ){
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std::cout << " ";
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for( int i = 0 ; i < t.NumDimensions + Traits::rank_non_trivial; i++ )
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std::cout << "[" << pDims[i] << "]";
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std::cout << " = " << c << std::endl;
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} );
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std::cout << "========================================" << std::endl;
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}
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//typedef int TestScalar;
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typedef std::complex<double> TestScalar;
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typedef Eigen::Tensor<iMatrix<TestScalar,1>, 6> TestTensorSingle;
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@ -145,6 +159,8 @@ bool EigenIOTest(void) {
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Val += Inc;
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}
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ioTest<Hdf5Writer, Hdf5Reader, TestTensor>("iotest_tensor.h5", t, "eigen_tensor_instance_name");
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std::cout << "t:";
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dump_tensor(t);
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// Now serialise a fixed size tensor
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using FixedTensor = Eigen::TensorFixedSize<TestScalar, Eigen::Sizes<8,4,3>>;
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@ -157,7 +173,9 @@ bool EigenIOTest(void) {
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Val += Inc;
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}
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ioTest<Hdf5Writer, Hdf5Reader, FixedTensor>("iotest_tensor_fixed.h5", tf, "eigen_tensor_fixed_name");
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std::cout << "tf:";
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dump_tensor(tf);
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ETSerClass o;
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ioTest<Hdf5Writer, Hdf5Reader, ETSerClass>("iotest_object.h5", o, "ETSerClass_object_instance_name");
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@ -174,14 +192,8 @@ bool EigenIOTest(void) {
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Val += Inc;
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}
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ioTest<Hdf5Writer, Hdf5Reader, LSCTensor>("iotest_LSCTensor.h5", l, "LSCTensor_object_instance_name");
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std::cout << "t:";
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for_all( l, [](std::complex<double> &c, LSCTensor::Index index, const std::size_t * pDims ){
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std::cout << " ";
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for( int i = 0 ; i < 5; i++ )
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std::cout << "[" << pDims[i] << "]";
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std::cout << " = " << c << std::endl;
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} );
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std::cout << std::endl;
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std::cout << "l:";
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dump_tensor(l);
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// Tensor of spin colour
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LCMTensor l2;
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@ -467,13 +467,13 @@ bool DebugEigenTest()
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template <typename T>
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void DebugGridTensorTest_print( int i )
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{
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std::cout << i << " : " << is_grid_tensor<T>::value
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<< ", depth " << grid_tensor_att<T>::depth
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<< ", rank " << grid_tensor_att<T>::rank
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<< ", rank_non_trivial " << grid_tensor_att<T>::rank_non_trivial
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<< ", count " << grid_tensor_att<T>::count
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<< ", scalar_size " << grid_tensor_att<T>::scalar_size
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<< ", size " << grid_tensor_att<T>::size
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std::cout << i << " : " << EigenIO::is_tensor<T>::value
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<< ", depth " << EigenIO::Traits<T>::depth
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<< ", rank " << EigenIO::Traits<T>::rank
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<< ", rank_non_trivial " << EigenIO::Traits<T>::rank_non_trivial
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<< ", count " << EigenIO::Traits<T>::count
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<< ", scalar_size " << EigenIO::Traits<T>::scalar_size
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<< ", size " << EigenIO::Traits<T>::size
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<< std::endl;
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}
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@ -494,8 +494,24 @@ 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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{
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unsigned int Nmom = 2;
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unsigned int Nt = 2;
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unsigned int N_1 = 2;
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unsigned int N_2 = 2;
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unsigned int N_3 = 2;
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using BaryonTensorSet = Eigen::Tensor<Complex, 6, Eigen::RowMajor>;
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BaryonTensorSet BField3(Nmom,4,Nt,N_1,N_2,N_3);
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std::vector<Complex> Memory(Nmom * Nt * N_1 * N_2 * N_3 * 2);
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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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return true;
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}
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bool DebugGridTensorTest( void )
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{
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DebugFelixTensorTest();
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typedef Complex t1;
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typedef iScalar<t1> t2;
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typedef iVector<t1, Ns> t3;
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