Jutho

I could probably provide a more efficient implementation with Strided.jl. Basis dependence just means that, if you have some contraction `X[a,b,c] = A[i,a]*B[i,b]*C[i,c]` this only holds in that particular basis...

Two remarks: 1) If you use the methods in TensorOperations.jl, you shouldn't be using the `@tensor` macro, so either ```julia ts_ctrct = tensorcontract(ts1, (1,2,3,4), ts2, (4,5,6,7)) ``` or ```julia @tensor...

I did some test myself: ``` Python 3.7.4 (default, Aug 13 2019, 15:17:50) Type 'copyright', 'credits' or 'license' for more information IPython 7.8.0 -- An enhanced Interactive Python. Type '?'...

I could add a `tensordot` function which behaves somewhat like the Python version.

Yes, contracting say the last axis of tensor 1 with the first axis of tensor 2 is exactly one of the tensor contractions that can directly be mapped to a...

In principle I am not opposed to other methods, I hardly ever use the method syntax. However, they do have to use Julia terminology, and not be just plain copies...

If you were to replace `A` with `A = view([1 2 3 1; 4 5 6 1; 7 8 9 1], 1:2, 1:3)` you would find that it works. The...

That would indeed be possible, a simple implementation based on loops could indeed be provided. The need for this was never very high. There are also some tricky (but not...

This package is mostly intended for big arrays with strided memory layout. In principle, the `@tensor` parsing and lowering part is reusable and can be made to work with any...

What should the ideal implementation for `StaticArrays` look like? Just plain loops, since sizes are typically small? I haven't used `StaticArrays` yet.