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feat:add modes to conv function (#399) #403

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feat:add modes to conv function (#399) #403

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946464b
feat:add modes to conv function (#399)
Longhao-Chen Feb 22, 2021
cc81ca3
feat:Add :same and :valid support for Vector.
Longhao-Chen Feb 22, 2021
0584fbd
test:Add tests for :same and :valid modes of conv
Longhao-Chen Feb 22, 2021
54f0529
fix:Fix calculation errors.
Longhao-Chen Apr 28, 2021
07e3b01
test:Add tests for :same and :valid modes of conv-ND
Longhao-Chen Apr 30, 2021
5bdc1c2
Add modes to conv function.
Longhao-Chen Apr 30, 2021
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70 changes: 55 additions & 15 deletions src/dspbase.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -679,13 +679,31 @@ end

# May switch argument order
"""
conv(u,v)
conv(u,v; mode = :full)

Convolution of two arrays. Uses either FFT convolution or overlap-save,
depending on the size of the input. `u` and `v` can be N-dimensional arrays,
with arbitrary indexing offsets, but their axes must be a `UnitRange`.

:full — Return the full convolution.

:same — Return the central part of the convolution, which is the same size as u.

:valid — Return only parts of the convolution that are computed without zero-padded edges.
"""
function conv(u::AbstractArray{T, N},
function conv(u, v; mode::Symbol = :full)
if mode == :full
conv_full(u, v)
elseif mode == :same
conv_same(u, v)
elseif mode == :valid
conv_valid(u, v)
else
throw(ArgumentError("mode keyword argument must be :full or :same or :valid"))
end
end

function conv_full(u::AbstractArray{T, N},
v::AbstractArray{T, N}) where {T<:BLAS.BlasFloat, N}
su = size(u)
sv = size(v)
Expand All @@ -696,35 +714,57 @@ function conv(u::AbstractArray{T, N},
end
end

function conv(u::AbstractArray{<:BLAS.BlasFloat, N},
function conv_full(u::AbstractArray{<:BLAS.BlasFloat, N},
v::AbstractArray{<:BLAS.BlasFloat, N}) where N
fu, fv = promote(u, v)
conv(fu, fv)
conv_full(fu, fv)
end

conv(u::AbstractArray{<:Integer, N}, v::AbstractArray{<:Integer, N}) where {N} =
round.(Int, conv(float(u), float(v)))
conv_full(u::AbstractArray{<:Integer, N}, v::AbstractArray{<:Integer, N}) where {N} =
round.(Int, conv_full(float(u), float(v)))

conv(u::AbstractArray{<:Number, N}, v::AbstractArray{<:Number, N}) where {N} =
conv(float(u), float(v))
conv_full(u::AbstractArray{<:Number, N}, v::AbstractArray{<:Number, N}) where {N} =
conv_full(float(u), float(v))

function conv(u::AbstractArray{<:Number, N},
function conv_full(u::AbstractArray{<:Number, N},
v::AbstractArray{<:BLAS.BlasFloat, N}) where N
conv(float(u), v)
conv_full(float(u), v)
end

function conv(u::AbstractArray{<:BLAS.BlasFloat, N},
function conv_full(u::AbstractArray{<:BLAS.BlasFloat, N},
v::AbstractArray{<:Number, N}) where N
conv(u, float(v))
conv_full(u, float(v))
end

function conv(A::AbstractArray{<:Number, M},
function conv_full(A::AbstractArray{<:Number, M},
B::AbstractArray{<:Number, N}) where {M, N}
if (M < N)
conv(cat(A, dims=N)::AbstractArray{eltype(A), N}, B)
conv_full(cat(A, dims=N)::AbstractArray{eltype(A), N}, B)
else
@assert M > N
conv(A, cat(B, dims=M)::AbstractArray{eltype(B), M})
conv_full(A, cat(B, dims=M)::AbstractArray{eltype(B), M})
end
end

function conv_same(u::AbstractArray{T, N}, v::AbstractArray{T, N}) where {T, N}
su = size(u)
sv = size(v)
conv_res = conv_full(u, v)
if N != 1
conv_res[Int(floor.(sv[1]/2 + 1)):Int(floor.(sv[1]/2) + su[1]), Int(floor.(sv[2]/2 + 1)):Int(floor.(sv[2]/2) + su[2]), axes(conv_res)[3:end]...]
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Why only apply this to the first two dimensions?

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I always think that n-dimensional convolution only needs to be cut on the first two dimensions.

It may take me a few days to have free time to fix it.

else
conv_res[Int(floor.(sv[1]/2 + 1)):Int(floor.(sv[1]/2) + su[1])]
end
end

function conv_valid(u::AbstractArray{T, N}, v::AbstractArray{T, N}) where {T, N}
su = size(u)
sv = size(v)
conv_res = conv_full(u, v)
if N != 1
conv_res[sv[1]:su[1], sv[2]:su[2], axes(conv_res)[3:end]...]
else
conv_res[sv[1]:su[1]]
end
end

Expand Down
4 changes: 4 additions & 0 deletions test/dsp.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,8 @@ end
im_expectation = [1, 3, 6, 6, 5, 3]
a32 = convert(Array{Int32}, a)
@test conv(a, b) == expectation
@test conv(a, b, mode=:same) == expectation[2:5]
@test conv(a, b, mode=:valid) == expectation[3:4]
@test conv(a32, b) == expectation
fa = convert(Array{Float64}, a)
f32a = convert(Array{Float32}, a)
Expand Down Expand Up @@ -90,6 +92,8 @@ end
# Real Integers
a32 = convert(Array{Int32}, a)
@test conv(a, b) == expectation
@test conv(a, b, mode=:same) == expectation[2:4, 2:4]
@test conv(a, b, mode=:valid) == expectation[2:3, 2:3]
@test conv(a32, b) == expectation
# Floats
fa = convert(Array{Float64}, a)
Expand Down