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Merge pull request #3 from 1oly/multithread
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Added multi-threading via the ThreadsX package
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@1oly
1oly authored Jun 1, 2022
2 parents 5aaa332 + 6051358 commit e834c50
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Showing 10 changed files with 67 additions and 66 deletions.
4 changes: 3 additions & 1 deletion Project.toml
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Expand Up @@ -4,7 +4,7 @@ keywords = ["AeroAcoustics"]
license = "MIT"
desc = "A package for post-processing of microphone array measurements"
authors = ["Oliver Lylloff <[email protected]>"]
version = "0.2.1"
version = "0.2.2"

[deps]
DSP = "717857b8-e6f2-59f4-9121-6e50c889abd2"
Expand All @@ -15,6 +15,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
NLsolve = "2774e3e8-f4cf-5e23-947b-6d7e65073b56"
Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
ThreadsX = "ac1d9e8a-700a-412c-b207-f0111f4b6c0d"

[compat]
DSP = "0.6.7"
Expand All @@ -23,6 +24,7 @@ FFTW = "1.1"
LazyArrays = "0.16"
NLsolve = "4.4"
Parameters = "0.12.3"
ThreadsX = "0.1.10"
julia = "1.6"

[extras]
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3 changes: 2 additions & 1 deletion docs/src/index.md
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Expand Up @@ -50,7 +50,8 @@ E = Environment(
Nx = 21,
Ny = 21,
xlim=(-0.5,0.5),
ylim=(-0.5,0.5)
ylim=(-0.5,0.5),
multi_thread = true # multi-threading can be enabled globally like this
)
```
Where the measurement distance `z0`, the microphone geometry `micgeom`, and the csm `CSM` are required variables.
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81 changes: 31 additions & 50 deletions examples/Quick_start.ipynb
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Expand Up @@ -2,18 +2,9 @@
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"┌ Warning: PyPlot is using tkagg backend, which is known to cause crashes on MacOS (#410); use the MPLBACKEND environment variable to request a different backend.\n",
"└ @ PyPlot /Users/oliver/.julia/packages/PyPlot/XaELc/src/init.jl:198\n"
]
}
],
"outputs": [],
"source": [
"using HDF5, AeroAcoustics, PyPlot"
]
Expand All @@ -27,7 +18,7 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": 4,
"metadata": {},
"outputs": [
{
Expand All @@ -36,7 +27,7 @@
"1.6"
]
},
"execution_count": 2,
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -53,7 +44,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -62,7 +53,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -74,13 +65,14 @@
" Nx = 21,\n",
" Ny = 21,\n",
" xlim=(-0.5,0.5),\n",
" ylim=(-0.5,0.5)\n",
" ylim=(-0.5,0.5),\n",
" multi_thread = true, # multi-threading can be enabled globally like this\n",
" );"
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -89,7 +81,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -98,7 +90,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 9,
"metadata": {},
"outputs": [
{
Expand All @@ -125,7 +117,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 10,
"metadata": {},
"outputs": [
{
Expand All @@ -134,7 +126,7 @@
"(0.1, -0.05)"
]
},
"execution_count": 8,
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -153,14 +145,14 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 4.742135 seconds (6.09 M allocations: 1.055 GiB, 5.72% gc time, 56.05% compilation time)\n"
" 4.762169 seconds (6.85 M allocations: 1.066 GiB, 6.01% gc time, 58.86% compilation time)\n"
]
}
],
Expand All @@ -170,7 +162,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 12,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -204,14 +196,14 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 2.603157 seconds (1.39 M allocations: 1.265 GiB, 11.42% gc time, 24.62% compilation time)\n"
" 2.377261 seconds (1.35 M allocations: 1.255 GiB, 12.46% gc time, 24.53% compilation time)\n"
]
}
],
Expand All @@ -221,7 +213,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 14,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -255,18 +247,14 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"breaking at iter = 42...\n",
"breaking at iter = 47...\n",
"breaking at iter = 71...\n",
"breaking at iter = 55...\n",
" 2.753007 seconds (5.40 M allocations: 345.352 MiB, 3.79% gc time)\n"
" 2.979043 seconds (5.47 M allocations: 328.361 MiB, 3.92% gc time, 98.86% compilation time)\n"
]
}
],
Expand All @@ -277,7 +265,7 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 16,
"metadata": {},
"outputs": [
{
Expand Down Expand Up @@ -311,7 +299,7 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -325,7 +313,7 @@
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 18,
"metadata": {},
"outputs": [
{
Expand All @@ -339,7 +327,7 @@
" 60.905 54.7118 54.8137 54.5308"
]
},
"execution_count": 21,
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -357,7 +345,7 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -366,7 +354,7 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 20,
"metadata": {},
"outputs": [
{
Expand All @@ -380,7 +368,7 @@
" 60.905 54.1891 54.7118 54.8137 54.5308"
]
},
"execution_count": 23,
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -395,26 +383,19 @@
"source": [
"The four methods `SPI`, `Clean-SC`, `DAMAS`, and `FISTA` now return very similar results of the source power for the 4 frequency bins defined in the environment (3000-4000 Hz)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.6.2",
"display_name": "Julia 1.7.2",
"language": "julia",
"name": "julia-1.6"
"name": "julia-1.7"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.6.2"
"version": "1.7.2"
}
},
"nbformat": 4,
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8 changes: 7 additions & 1 deletion src/AeroAcoustics.jl
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Expand Up @@ -7,6 +7,7 @@ using Parameters
using LazyArrays
using FFTW
import DSP
using ThreadsX

import Base.length,
Base.push!,
Expand Down Expand Up @@ -104,4 +105,9 @@ function DR(CSM::FreqArray)
return FreqArray(CSMd,CSM.fc)
end

end
function check_multithread(multi_thread)
_foreach = multi_thread ? ThreadsX.foreach : Base.foreach
return _foreach
end

end # Module
5 changes: 3 additions & 2 deletions src/beamforming.jl
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Expand Up @@ -25,10 +25,11 @@ end
Calculate frequency-domain beamforming using cross-spectral matrix `csm` and steering vector `v`
stored in Environment struct
"""
function beamforming(E::Environment)
function beamforming(E::Environment;multi_thread=E.multi_thread)
_foreach = AeroAcoustics.check_multithread(multi_thread)
@unpack CSM_s,w,steeringvec,M,N,Nf,fn = E
b = Array{Float64}(undef, N, Nf)
@views @inbounds for j in 1:Nf
@views @inbounds _foreach(1:Nf) do j
st = E.steeringvec.arr[:,:,j]
@. st = complex(w[:,j].*real(st), imag(st))
bf_col!(b[:,j],st,selectdim(CSM_s.arr, 3, j))
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5 changes: 3 additions & 2 deletions src/cleansc.jl
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Expand Up @@ -8,7 +8,8 @@ CLEAN-SC algorithm for source identification and quantification optionally setti
With inspiration from https://github.com/acoular/acoular/blob/66cba3cffb3bc72602c869f99347be76798f4ac1/acoular/fbeamform.py#L1496
"""
function cleanSC(E;maxiter=50,ϕ=0.5,stopn=10,peak_removal=false,trust_region=nothing)
function cleanSC(E;maxiter=50,ϕ=0.5,stopn=10,peak_removal=false,trust_region=nothing,multi_thread=E.multi_thread)
_foreach = AeroAcoustics.check_multithread(multi_thread)
@unpack CSM_s,steeringvec,M,N,Nf,fn = E
x = zeros(N,Nf)

Expand All @@ -20,7 +21,7 @@ function cleanSC(E;maxiter=50,ϕ=0.5,stopn=10,peak_removal=false,trust_region=no
trust_indices = LinearIndices((E.Nx,E.Ny))
end

@views @inbounds for j = 1:Nf
@views @inbounds _foreach(1:Nf) do j
_cleanSC!(x[:,j],steeringvec.arr[:,:,j],CSM_s.arr[:,:,j],maxiter,ϕ,stopn,peak_removal,trust_indices)
end
return FreqArray(x,E.fn)
Expand Down
2 changes: 1 addition & 1 deletion src/fista.jl
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Expand Up @@ -50,7 +50,7 @@ function _fista!(x,b,psf,gam;maxit=1000,tol=1e-6)
x .= max.(real.(y),0.0)
# stopping criterion
if norm(x_ex-x)/gam <= tol*(1+norm(x))
println("breaking at iter = $(it)...")
#println("breaking at iter = $(it)...")
break
end
end
Expand Down
5 changes: 3 additions & 2 deletions src/psf.jl
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Expand Up @@ -4,10 +4,11 @@
Calculate frequency-domain point spread function using the Environment struct to access
steeringvectors. Optionally, supply the index where the psf is centered, default is (N/2)+1.
"""
function psf(E::Environment,cent::Int64=floor(Int,E.N/2)+1)
function psf(E::Environment,cent::Int64=floor(Int,E.N/2)+1;multi_thread=false)
_foreach = AeroAcoustics.check_multithread(multi_thread)
@unpack steeringvec,M,N,Nf,fn = E
p = Array{Float64, 2}(undef, N, Nf)
@views @inbounds for j in 1:Nf
@views @inbounds _foreach(1:Nf) do j
AeroAcoustics.psf_col!(p[:,j],steeringvec.arr[:,:,j],cent)
end
return FreqArray(p,fn)
Expand Down
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@1oly 1oly commented on e834c50 Jun 1, 2022

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Registration pull request created: JuliaRegistries/General/61485

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.2.2 -m "<description of version>" e834c50165e64978ffda88b4a776edd1fb3d2447
git push origin v0.2.2

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