Implement argmin and argmax

[willow-ahrens]

The idea is to first use minby to compute the argmin, then return just the coordinates of the minimum. In python, we only need to handle a single axis (https://numpy.org/doc/2.1/reference/generated/numpy.argmin.html). In Julia, there may be multiple axes, in which case the index used is an e.g. CartesianIndex(i, j) (https://docs.julialang.org/en/v1/base/collections/#Base.argmin). The minby function is described here: https://finch-tensor.github.io/Finch.jl/stable/docs/user-defined_functions/#Finch.minby

An example of a one-dimensional argmin is:

A = Scalar((Inf, 0))
@finch begin
    A .= (Inf, 0)
    for i = _
      A[] <<minby>>= tuple(B[i], i)
   end
end
result = A[][2]

An example of a similar function exists here: hhttps://github.com/finch-tensor/Finch.jl/blob/2e89d2228a777a8238eccd145cfa6a7b405eb76c/src/interface/compare.jl#L1-L28

You may find some of these docs to be helpful:
https://finch-tensor.github.io/Finch.jl/stable/docs/internals/virtualization/