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`kron`

ecker 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).

07/21/2018

about 2 years ago

6 commits