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DimArrays.jl

This packages provides Julia arrays with named dimensions. Like the built-in Array type these are mutable objects, unlike NamedArrays and AxisArrays which are immutable.

The idea was to have a convenient way to gather results of calculations in a script or notebook, rather than for anything high-performance. For example, here I have a matrix of results at each iteration, and nest these into a 3-tensor, whose axis order I need not remember:

using DimArrays

list = [];
for i=1:33
    slowcalc = sqrt(i) .* randn(3,13) .+ i
    push!(list, DimArray(slowcalc, :a, :b, :c ))  # add labels for 1st and 2nd dimensions  
end

list3 = nest(list, :iter)   # now i is the 3rd index, and named "iter"

using Statistics

mean(list3, dims=:iter)     # equivalent to dropdims(mean(list3, dims=3), dims=3)

For quick plots, dimension names are used for axes and series:

using Plots

plot(selectdim(list3, :b, 1)' , legend=:bottomright)

Here selectdim(list3, :b, 1) == list3[:,1,:] in contents, but retains the labels.

Besides each dimension's name (which is a Symbol, strings will be converted) it can also store a function, which is used in plotting to scale the axes etc. (But only the output, getindex uses original integer indices). You can pass a number by which to scale the index, or a dictionary, instead of a function.

For example, this plots data saved every 4 iterations correctly over the above example:

saveevery = 4
list4 = DimArray([], :iter, saveevery);     # equivalent to function  i->4i
for i=1:33
    slowcalc = sqrt(i) .* randn(3,23) .+ i
    slownice = DimArray(slowcalc, [:a, :b], [Dict(1=>"one", 2=>"two", 3=>"three")], :stuff )
                                            # equivalent to  i->Dict(...)[i]
    rem(i,saveevery)==0 && push!(list4, slownice)
end
nest(list4)

plot!(mean(nest(list4), dims=:b)', s=:dash)

If you do not provide a name for a dimension (or give an empty string "") then you can still refer to it by default names like size(x, :row) == size(x,1) or maximum(y, :col) etc. However these defaults are not stored, and not manipulated by transpose(x) or kron(x,y).

For now, the list of functions supported is:

  • DimArray, DimVector, DimMatrix create one, taking names and functions for dimensions in the order given.
  • dictvector defines a DimVector whose function is a Dict.
  • nest converts arrays of arrays, and squeeze drops dimensions of size 1.

and these built-in functions:

  • selectdim, size understand a dimension's name.
  • sum, maximum, minimum, dropdims and Statistics.mean, std: all can be called with a dimension's name, in which case by default squeeze=true on that dimension, like mean(..., dims=:b) above. They can also be called with a list of dimensions: sum(x, dims=[1,:c]) etc.
  • push!, append!, hcat, vcat, transpose, ctranspose, permutedims.
  • Matrix multiplication * will warn (once) if you multiply along directions with mismatched names... which may be a terrible idea. And kronecker products produce new names like :a_b.
  • collect, implicitly used by comprehensions like [ sqrt(n) for n in DimVector(1:10, "int")' ] which thus inherit the names of the array being iterated over.

Since DimArray <: AbstractArray anything else will fall back on their methods, and forget the dimension labels.

See also:

ToDo:

  • Make things like x[:, 1:10:end] and hcat(a,b) update the functions correctly.
  • Figure out Julia 0.7's new broadcasting machinery.

Michael Abbott, January 2018, mostly (as I had a grant to write).

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Julia arrays with dimension labels, and scaling

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