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Filtering (filt) across columns of arrays and method signature tweaks #7560

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merged 3 commits into from
Jul 11, 2014

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@mbauman mbauman commented Jul 10, 2014

Here are yet two more patches for filt and filt! following #7513.

1. Enable filtering (filt) across columns of arrays.

When passed a multidimensional array, simply iterate over its columns, independently filtering each one. The starting filter state may be given as a vector (in which case it is common across all columns) or an array with the same number of columns as the input. This is a pretty common feature and is very handy.

cf. JuliaDSP/DSP.jl#58 (comment)

2. Relax filt signatures to allow heterogeneous types

Previously, filt[!] methods were only defined for arguments of all the same type T<:Number. This relaxes that restriction, allowing one to, for example, filter an array of Float32s by Float64 coefficients. Instead of defining many type parameters (T<:Number, S<:Number, R<:…), filt now simply trusts that the eltype of the arrays have methods for basic arithmetic. By default, the output of filt will be determined by promote_type of all arguments.

I needed this second change to simplify filtering of arrays of Float32s. It should generally be more forgiving.

cc: @simonster, @timholy, @codles

When passed a multidimensional array, simply iterate over its columns, independently filtering each one.  The starting filter state may be given as a vector (in which case it is common across all columns) or an array with the same number of columns as the input.
Previously, filt[!] methods were only defined for arguments of all the same type T<:Number. This relaxes that restriction, allowing one to, for example, filter an array of Float32s by Float64 coefficients.

By default, the output of filt will be the determined by promote_type of all arguments.

Instead of defining many type parameters (T<:Number, S<:Number, ...), filt now simply trusts that the eltype of the arrays have methods for basic arithmetic.
function filt!{T<:Number}(b::Union(AbstractVector{T}, T), a::Union(AbstractVector{T}, T), x::AbstractVector{T};
si::AbstractVector{T}=zeros(T, max(length(a), length(b))-1), out::AbstractVector{T}=x)
function filt!{T}(b::Union(AbstractVector, Number), a::Union(AbstractVector, Number), x::AbstractArray{T};
si::AbstractArray=_zerosi(b,a,T), out::AbstractArray=x)
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This may have the type inference issue I mentioned here if called with keyword arguments, since out is a keyword argument but determines the return type.

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Argh. I think you're right. That's frustrating. The same will be true for si in filt above since it's a part of the type promotion. That one is easier to make a positional argument, but filt! would ideally have two optional arguments, and with one in front it'd be ambiguous with positional args.

Any suggestions?

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Short of fixing type inference, I like the general pattern of having output arguments be first (they're closer to the left-hand side, which is where outputs usually go). You could make out a required argument for filt!, forcing the user to say filt!(x, b, a, x) when you want to filter in-place.

Because we're back to only one optional element for both `filt` and `filt!` (the initial state), I figure it's simpler to just use a positional argument in both cases.  So now the API is:

    filt(b, a, x, [si])
    filt!(out, b, a, x, [si])
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mbauman commented Jul 11, 2014

Alright, yet another API change to fix the type instability. Sorry @codles!

Because we're back to only one optional element for both filt and filt! (the initial state), I figure it's simpler to just use a positional argument in both cases. So now the API is:

filt(b, a, x, [si])
filt!(out, b, a, x, [si])

This will still leave room in the future for a 3-argument version of filt! with keywords if the inference improves. I think it should be a good stable place to start. (Just for reference, the only other argument SciPy supports is an axis, but I think Julia would be better off not supporting such a thing.)

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timholy commented Jul 11, 2014

Actually, I was already wondering if this should (someday) be generalized to perform filtering across any dimension, which is what I presume axis means. In julia there are many examples of such functions (see sum, maximum, fft, etc). It's usually called dim, dims, or region; I actually think axis/axes might be the clearer terminology. But I don't need it now, and if you don't either then might as well wait until there's call to implement it. axis wouldn't affect inference at all, so that could be a keyword if/when someone needs this.

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timholy commented Jul 11, 2014

I'm good with this. @simonster, if you like it, merge.

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mbauman commented Jul 11, 2014

Hah, fair enough. I probably shouldn't make such grand, sweeping statements. I don't need this, and I don't want to be responsible for maintaining the additional complexity. :)

Thanks again, gentlemen. I know it takes time for you to review these things, but your feedback is invaluable as I continue learning.

simonster added a commit that referenced this pull request Jul 11, 2014
Filtering (filt) across columns of arrays and method signature tweaks
@simonster simonster merged commit fdfccd7 into JuliaLang:master Jul 11, 2014
@mbauman mbauman deleted the filtarray branch July 11, 2014 14:58
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3 participants