Thanks Bradley, I'll take a look at the changes when I find some time.

I'm still working on my image library and dataframe library, but slowly.
I haven't found any other issues so far - SRFI 179 seems a good basis.

One thing I needed was a more general partial application rather than
curry, i.e. being able to specify just a middle dimension, but then I
realized that I could always permute the array first to achieve this.

On Sat, Sep 25, 2021 at 4:25 AM John Cowan <xxxxxx@ccil.org> wrote:
>
> 2) Add the word "transpose" and/or "transposition" to the explanation of array-permute; people who deal with matrices will think of a permutation matrix rather than a transpose operator.

I actually define a utility (array-transpose a [dim1 [dim2]]) which
just swaps the two dimensions, defaulting to 0 and 1.

> 3) (array-append k a1 a2 ...)
>
> 4) (array-laminate k a1 a2 ...)

Both of these are provided by (chibi math linalg):
https://github.com/ashinn/alschemist/blob/master/chibi/math/linalg.scm
For consistency with numpy, laminate is called stack, and the axis
refers to the result dimension so has the more natural domain [0,
res-dim).
They are fairly general and I agree should be in the base library
rather than a linear algebra library.

--
Alex