cols() [2/2]

template<Rank rank>

Index syten::Delinearise::cols ( Tensor< rank > const &  in, Index const  uncombinedLeg, Tensor< rank > &  p, Tensor< 2 > &  t, std::vector< Index >  leading_dimensions = std::vector<Index>(), bool  relax_if_necessary = false  )

inline

Column-based Delinearisation.

Parameters

[in]	in	input tensor to decompose into in → p t
[in]	uncombinedLeg	leg of in/p which is not combined and at which t attaches
[out]	p	output tensor with same rank as in
[out]	t	output tensor with rank 2
[in]	leading_dimensions	number of leading dimensions for threshold estimates
[in]	relax_if_necessary	Do a rank-revealing QR decomposition after each dense decomposition. If the resulting matrix is not full rank, relax the epsilon threshold to allow cancellation to zero and re-try.

Returns

the number of discarded vectors

References syten::Tensor< rank >::clear(), cols(), syten::DenseTensor< rank, Scalar >::dim(), syten::Tensor< rank >::dirs, syten::Tensor< rank >::empty(), syten::hasCGC(), syten::makeIdentity(), std::move(), syten::No, syten::partial_abs(), syten::Tensor< rank >::push_back(), std::vector< T >::push_back(), syten::rank(), syten::Tensor< rank >::reduce(), syten::Tensor< rank >::reserve(), std::vector< T >::size(), SYTEN_DELINEARISE_THRESHOLD, and syten::tensorSortBuckets().

Here is the call graph for this function: