I don't like NumPy

It seems the main complaint is about confusing shapes / dimensions. Xarray has already be mentioned, but this is a broader concept, called named dimensions, sometimes also named tensors, named axes, labeled tensors, etc, which has often been proposed before, and many implementations exists.

https://nlp.seas.harvard.edu/NamedTensor

https://namedtensor.github.io/

https://docs.pytorch.org/docs/stable/named_tensor.html

https://github.com/JuliaArrays/AxisArrays.jl

https://github.com/ofnote/tsalib

https://github.com/google-deepmind/tensor_annotations

https://github.com/google-deepmind/penzai

https://github.com/tensorflow/mesh/

https://github.com/facebookresearch/torchdim

https://xarray.dev/

https://returnn.readthedocs.io/en/latest/getting_started/dat... (that's my own development; unfortunately the doc is very much outdated on that)

Someone just need to write a new named multi-dimentional array processing library in Dlang with Mir since it's more intuitive and faster than venerable Fortran library that's being widely used by array languages including Matlab, Julia, etc [1], based the implementation on the methodology presented in the seminal book by Hart [2], problem solved.

[1] Numeric age for D: Mir GLAS is faster than OpenBLAS and Eigen (2016):

http://blog.mir.dlang.io/glas/benchmark/openblas/2016/09/23/...

[2] Multidimensional Analysis: Algebras and Systems for Science and Engineering (1993):

https://link.springer.com/book/10.1007/978-1-4612-4208-6