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replace splat with Tuple #513

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merged 7 commits into from
Jan 22, 2024
Merged

replace splat with Tuple #513

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1425e0d
replace splat with Tuple
wheeheee Nov 26, 2023
b7b100a
use sum, replace manual loop unrolling
wheeheee Nov 27, 2023
c13663a
zeros(Int, N)
wheeheee Nov 28, 2023
a884537
remove let block
wheeheee Nov 28, 2023
ff57c22
`NTuple`, `fill!`, `copyto!`
wheeheee Nov 28, 2023
b5d5f4e
remove unnecessary `@inline`
wheeheee Nov 28, 2023
32a8298
NTuple{N,UnitRange{Int}}(border_range)
wheeheee Nov 28, 2023
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86 changes: 30 additions & 56 deletions src/unwrap.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ function unwrap!(y::AbstractArray{T,N}, m::AbstractArray{T,N}; dims=nothing, ran
dims = 1
end
if dims isa Integer
accumulate!(unwrap_kernel(range), y, m, dims=dims)
accumulate!(unwrap_kernel(range), y, m; dims=dims)
elseif dims == 1:N
unwrap_nd!(y, m; range=range, kwargs...)
else
Expand Down Expand Up @@ -113,7 +113,7 @@ end
function unwrap_nd!(dest::AbstractArray{T, N},
src::AbstractArray{T, N};
range::Number=2*convert(T, pi),
circular_dims::NTuple{N, Bool}=tuple(fill(false, N)...),
circular_dims::NTuple{N, Bool}=ntuple(_->false, Val(N)),
rng::AbstractRNG=GLOBAL_RNG) where {T, N}

range_T = convert(T, range)
Expand Down Expand Up @@ -235,18 +235,18 @@ function populate_edges!(edges, pixel_image::Array{T, N}, dim, connected, range)
size_img[dim] -= 1
idx_step = fill(0, N)
idx_step[dim] += 1
idx_step_cart = CartesianIndex{N}(idx_step...)
idx_size = CartesianIndex{N}(size_img...)
idx_step_cart = CartesianIndex{N}(NTuple{N,Int}(idx_step))
idx_size = CartesianIndex{N}(NTuple{N,Int}(size_img))
for i in CartesianIndices(idx_size)
push!(edges, Edge{N}(pixel_image, i, i+idx_step_cart, range))
end
if connected
idx_step = fill(0, N)
idx_step = fill!(idx_step, 0)
idx_step[dim] = -size_img[dim]
idx_step_cart = CartesianIndex{N}(idx_step...)
edge_begin = fill(1, N)
idx_step_cart = CartesianIndex{N}(NTuple{N,Int}(idx_step))
edge_begin = ones(Int, N)
edge_begin[dim] = size(pixel_image)[dim]
edge_begin_cart = CartesianIndex{N}(edge_begin...)
edge_begin_cart = CartesianIndex{N}(NTuple{N,Int}(edge_begin))
for i in CartesianIndices(ntuple(dim_idx -> edge_begin_cart[dim_idx]:size(pixel_image, dim_idx), N))
push!(edges, Edge{N}(pixel_image, i, i+idx_step_cart, range))
end
Expand All @@ -263,16 +263,22 @@ function calculate_reliability(pixel_image::AbstractArray{T, N}, circular_dims,
@inbounds pixel_image[i].reliability = calculate_pixel_reliability(pixel_image, i, pixel_shifts, range)
end

if !(true in circular_dims)
return
end

pixel_shifts_border = similar(pixel_shifts)
new_ps = zeros(Int, N)
for (idx_dim, connected) in enumerate(circular_dims)
if connected
# first border
pixel_shifts_border = copy(pixel_shifts)
copyto!(pixel_shifts_border, pixel_shifts)
for (idx_ps, ps) in enumerate(pixel_shifts_border)
# if the pixel shift goes out of bounds, we make the shift wrap
if ps[idx_dim] == 1
new_ps = fill(0, N)
fill!(new_ps, 0)
new_ps[idx_dim] = -size_img[idx_dim]+1
pixel_shifts_border[idx_ps] = CartesianIndex{N}(new_ps...)
pixel_shifts_border[idx_ps] = CartesianIndex{N}(NTuple{N,Int}(new_ps))
end
end
border_range = get_border_range(size_img, idx_dim, size_img[idx_dim])
Expand All @@ -284,9 +290,9 @@ function calculate_reliability(pixel_image::AbstractArray{T, N}, circular_dims,
for (idx_ps, ps) in enumerate(pixel_shifts_border)
# if the pixel shift goes out of bounds, we make the shift wrap, this time to the other side
if ps[idx_dim] == -1
new_ps = fill(0, N)
fill!(new_ps, 0)
new_ps[idx_dim] = size_img[idx_dim]-1
pixel_shifts_border[idx_ps] = CartesianIndex{N}(new_ps...)
pixel_shifts_border[idx_ps] = CartesianIndex{N}(NTuple{N,Int}(new_ps))
end
end
border_range = get_border_range(size_img, idx_dim, 1)
Expand All @@ -300,56 +306,24 @@ end
function get_border_range(size_img::NTuple{N, T}, border_dim, border_idx) where {N, T}
border_range = [2:(size_img[dim]-1) for dim=1:N]
border_range[border_dim] = border_idx:border_idx
return tuple(border_range...)
return NTuple{N,UnitRange{Int}}(border_range)
end

function calculate_pixel_reliability(pixel_image::AbstractArray{Pixel{T}, N}, pixel_index, pixel_shifts, range) where {T, N}
sum_val = zero(T)
for pixel_shift in pixel_shifts
@inbounds sum_val += wrap_val(pixel_image[pixel_index+pixel_shift].val - pixel_image[pixel_index].val, range)^2
end
function calculate_pixel_reliability(pixel_image::AbstractArray{Pixel{T},N}, pixel_index, pixel_shifts, range) where {T,N}
pix_val = pixel_image[pixel_index].val
rel_contrib(shift) = @inbounds wrap_val(pixel_image[pixel_index+shift].val - pix_val, range)^2
# for N=3, pixel_shifts[14] is null shift, can avoid if manually unrolling loop
sum_val = sum(rel_contrib, pixel_shifts)
return sum_val
end

# specialized pixel reliability calculations for different N
function calculate_pixel_reliability(pixel_image::AbstractArray{Pixel{T}, 2}, pixel_index, pixel_shifts, range) where T
@inbounds D1 = wrap_val(pixel_image[pixel_index+pixel_shifts[2]].val - pixel_image[pixel_index].val, range)
@inbounds D2 = wrap_val(pixel_image[pixel_index+pixel_shifts[4]].val - pixel_image[pixel_index].val, range)
@inbounds H = wrap_val(pixel_image[pixel_index+pixel_shifts[6]].val - pixel_image[pixel_index].val, range)
@inbounds V = wrap_val(pixel_image[pixel_index+pixel_shifts[8]].val - pixel_image[pixel_index].val, range)
@inbounds function calculate_pixel_reliability(pixel_image::AbstractArray{Pixel{T}, 2}, pixel_index, pixel_shifts, range) where T
D1 = wrap_val(pixel_image[pixel_index+pixel_shifts[2]].val - pixel_image[pixel_index].val, range)
D2 = wrap_val(pixel_image[pixel_index+pixel_shifts[4]].val - pixel_image[pixel_index].val, range)
H = wrap_val(pixel_image[pixel_index+pixel_shifts[6]].val - pixel_image[pixel_index].val, range)
V = wrap_val(pixel_image[pixel_index+pixel_shifts[8]].val - pixel_image[pixel_index].val, range)
return H*H + V*V + D1*D1 + D2*D2
end

function calculate_pixel_reliability(pixel_image::AbstractArray{Pixel{T}, 3}, pixel_index, pixel_shifts, range) where T
sum_val = zero(T)
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[1]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[2]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[3]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[4]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[5]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[6]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[7]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[8]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[9]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[10]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[11]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[12]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[13]].val - pixel_image[pixel_index].val, range))^2
# pixel_shifts[14] is null shift
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[15]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[16]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[17]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[18]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[19]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[20]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[21]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[22]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[23]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[24]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[25]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[26]].val - pixel_image[pixel_index].val, range))^2
@inbounds sum_val += (wrap_val(pixel_image[pixel_index+pixel_shifts[27]].val - pixel_image[pixel_index].val, range))^2
return sum_val
end

end
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