In Julia 1.4.0, attempting to extract a row from an array returns a vector/column, and not a row. From array: N = [1 2;3 4] 2×2 Array{Int64,2}: 1 2 3 4 N[1,:] 2-element Array{Int64,1}: 1 2 It returns a column instead of a 1x2 array. It doesn’t even show the dimension. Like: C = [3 8] …

The quick way of obtaining what you want is: julia> N[[1],:] 1×2 Array{Int64,2}: 1 2 I,e. instead of giving a scalar index, pass a collection of indices for slicing, like when you do N[1:2,:] - although that collection has only one index. Longer explanation of why is it like that in a recent di…

Thank you. I’ll dig deeper into that - it doesn’t make sense yet - I’ll keep looking.

Among the different replies given in the linked discussion, I think that this one by Oscar Smith is the clearest, so perhaps it will make sense after reading it: [image] Trouble Understanding Slicing New to Julia The reason scalar indexing drops dimensions is a little mor…

[image] heliosdrm: N[[1],:] Without checking I would think that N[1:1, :] is better, since it won’t heap-allocate an array.

Yeah, I agree with DNF that N[1:1, :] is probably more idiomatic. One way to understand it is that a 1D Vector is not the same as an Nx1 Matrix (i.e. a column), even though they are often interchangeable. The indexing rules in Julia are agnostic to the dimensionality of the array, i.e. they work t…

This does make more sense to me, but it still seems like that should be taken care of internally without having to specify a range. If : only returns 1 value then it should be scalar, otherwise, it should have the dimensions of the piece that you’re looking for. I come from Python, so using : is han…

There’s often a consistency/convenience trade-off. Opinions definitely differ but I think consistency is usually a better target because what’s convenient for one application is often inconvenient for another. In this case it’s nice to know what the dimensionality of the output will be when you use…

The reason Julia doesn’t do this is a consequence of a very important idea in Julia which is type stability. Put simply, since Julia has multiple dispatch, good performance depends on the ability of the compiler to know what types your functions will output based on the types of their input. This a…

What should you get when you index a 1D array? That is, when you do a = [11,12,13] a[2] Should you get 12 or [12]?

The more I think about this, the more I think that this is a flaw in Julia. If A[:,1] returns an nx1 column (which it does), then A[1:n] should return a 1xn row (which it doesn’t, it returns something that looks like a column, but doesn’t have any dimension attached). It’s a question of consistency. …

Problem: extracting a row from an array, returns a column

General Usage

heliosdrm April 10, 2020, 12:52pm 4

Among the different replies given in the linked discussion, I think that this one by Oscar Smith is the clearest, so perhaps it will make sense after reading it:

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Problem: extracting a row from an array, returns a column

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