My wishlist for the next version of Julia

[lmiq]

@leon

Creating a m x n sized NaN should be as simple as NaN(m, n). Right now, I have to do this:
A = fill!(Array{Float64}(undef, m, n), NaN);

julia> fill(NaN,(3,4))

3×4 Matrix{Float64}:
 NaN  NaN  NaN  NaN
 NaN  NaN  NaN  NaN
 NaN  NaN  NaN  NaN

@leon

If I have two 1-column data with the same size, A and B, I should be able to get an Index by Ind = A>3 && B<15 . Right now, I would have to use map function to broadcast first:

You are lucky, that will be possible in V1.7 already:

julia> A = rand(3,4); B = rand(3,4);

julia> inds =  A .> 0.5 .&& B .> 0.5
3×4 BitMatrix:
 0  0  0  0
 0  1  1  0
 0  0  1  1

Currently you can already do this:

julia> A = rand(3,4); B = rand(3,4);

julia> (A .> 0.5) .& (B .> 0.5)
3×4 BitMatrix:
 0  0  0  0
 0  1  1  1
 0  0  1  0

(and I don’t see any immediate harm in that, with the parenthesis, maybe someone can correct me)

@leon

I should be able to initialize an array as A=[] , and then append to it as simple as A = [A; b]; Right now, Julia will complain that I can not append a 0 sized array with a m x n sized array.

If you are just pushing to A for the first time, just do A = b.

@leon

Automatically handle the conversion between vector and array for Index values, instead of relying on users to decide when to use A and when to use vec(A) .

The difference between vectors and matrices is a feature, actually, and the old julia and matlab users have discussed many times the advantages of that here.

@leon

Function should allow us to define the outcome of the function like: function [A, B] = f1(x, y, z) , instead of requiring us to use return function at the end of the function to return the results.

that can be done:

julia> f(x) = 2
f (generic function with 1 method)

julia> f(1)
2

(but you need to learn the syntax first).

@leon

I should be able to use a sortrows function, by B = sortrows(A, Index). Instead of having to find the Index using sortperm first.

I’m not sure what you want to do here, but isn’t this just this? (edit: or more likely, one of the options here: Sort matrix based on the elements of a specific column - #5 by nicolas - a function that sorts the matrix as a function of one row may exist, I’m not sure)

julia> A = rand(3,4);

julia> sort(A, dims=2)
3×4 Matrix{Float64}:
 0.0518517  0.055554  0.248347  0.992392
 0.168324   0.318615  0.857768  0.864286
 0.0809794  0.541194  0.724404  0.911751