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Commit 22fe779d authored by Theo Guyard's avatar Theo Guyard
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Small modifs. Still need to add citations to the README

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README.md
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− 18
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......@@ -4,19 +4,15 @@ This repository contains numerical procedures linked to the paper
**> ADD CITATION**
If you encounter a bug or something unexpected, please let me know by raising an issue on the project page or by contacting me by email at `theo.guyard@insa-rennes.fr`.
If you encounter a bug or something unexpected, please let me know by raising an issue on the project page or by contacting me by [mail](mailto:theo.guyard@insa-rennes.fr).
## Requirements
This repository works with Julia v1.5+. Please refer to the [Julia download page](https://julialang.org/downloads/) for install instructions.
Dependencies :
* [JuMP.jl](https://github.com/jump-dev/JuMP.jl)
* [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl)
* [Distributions.jl](https://github.com/JuliaStats/Distributions.jl)
* [StatsBase](https://github.com/JuliaStats/StatsBase.jl)
**Dependencies :** [JuMP.jl](https://github.com/jump-dev/JuMP.jl), [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl), [Distributions.jl](https://github.com/JuliaStats/Distributions.jl), [StatsBase.jl](https://github.com/JuliaStats/StatsBase.jl)
Our code works with the CPLEX solver through [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl). You cannot use CPLEX without having purchased and installed a copy of CPLEX Optimization Studio from [IBM](https://www.ibm.com). However, CPLEX is available for free to [academics and students](https://community.ibm.com/community/user/datascience/blogs/xavier-nodet1/2020/07/09/cplex-free-for-students). We recommend to follow carefully the install instructions described at [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl).
Our code works with the [CPLEX](https://www.ibm.com/fr-fr/analytics/cplex-optimizer) solver through [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl). You cannot use CPLEX without having purchased and installed a copy of CPLEX Optimization Studio from [IBM](https://www.ibm.com). However, CPLEX is available for free to [academics and students](https://community.ibm.com/community/user/datascience/blogs/xavier-nodet1/2020/07/09/cplex-free-for-students). We recommend you to follow carefully the install instructions described at [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl) to install the package.
## Install instructions
......@@ -25,7 +21,7 @@ Our code works with the CPLEX solver through [CPLEX.jl](https://github.com/jump-
git clone https://gitlab.insa-rennes.fr/Theo.Guyard/bnb-screening.git
```
2. Enter in the project folder
2. Enter in the project root folder
```bash
cd bnb-screening
```
......@@ -39,27 +35,32 @@ julia -v
4. Install dependencies using [Julia's Pkg](https://docs.julialang.org/en/v1/stdlib/Pkg/) in REPL mode
```julia
(@v1.5) pkg> activate .
(@v1.5) pkg> add JuMP
(@v1.5) pkg> add CPLEX
(@v1.5) pkg> add Distributions
(@v1.5) pkg> add StatsBase
(bnb-screening) pkg> instantiate
```
It is possible that you also have to build [CPLEX.jl](https://github.com/jump-dev/CPLEX.jl) manually with the command
```julia
(bnb-screening) pkg> build CPLEX
```
## ICASSP experiments
Experiments presented in the paper corresponding to this repository are located in the folder `bnb-screening/exp/ICASSP/`. The available experiment are
* `performances.jl` corresponding to table 1
Experiments presented in the paper submitted to [ICASSP 2022](https://2022.ieeeicassp.org) are located in the folder `bnb-screening/exp/ICASSP/`. The available experiments are
* `performances.jl` corresponding to results of table 1
Run experiments directly from the project root folder :
Run experiments directly from the project root folder as follows.
```bash
julia --project=. -t 1 exp/ICASSP/performances.jl
```
The `--project=.` argument installs package dependencies if needed. The flag `-t 1` restricts computations to only 1 CPU core in order to avoid bias due to parallelization capabilities. Logs are saved in the same folder as `performances.jl`. You can edit the experimental setup directly in the script, which is well commented.
The `--project=.` flag installs and build dependencies if needed. The `-t 1` flag restricts computations to only 1 CPU core in order to avoid bias due to parallelization capabilities. Logs of the experiment are saved in the same folder as `performances.jl`. You can edit the experimental setup directly in the script, which is well commented.
## Running demo examples
The `example` folder contains portions of code explaining how to use our package.
The `bnb-screening/examples/` folder contains portions of code explaining how to use our package. You can run these scripts as follows.
```bash
julia --project=. examples/solve_bnb.jl
julia --project=. examples/solve_mip.jl
```
## Licence
......@@ -69,4 +70,4 @@ This software is distributed under the [MIT Licence](https://mit-license.org).
If you use this package for your own work, please consider citing it as :
**ADD CITATION**
**> ADD CITATION**
examples/solve_bnb.jl
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......@@ -28,12 +28,5 @@ bnbparams = BnbParams(
showevery=1, # If verbosity=true, number of nodes between two displays
)
# Solve the problem using the BnB algorithm
result_bnb = solve_bnb(A,y,λ,M,bnbparams=BnbParams(verbosity=false))
# Display BnB results and statistics
println("BnB")
println(" Status : $(result_bnb.termination_status)")
println(" Objective : $(result_bnb.objective_value)")
println(" Nodes : $(result_bnb.node_count)")
println(" Timer : $(result_bnb.solve_time)")
\ No newline at end of file
# Solve the problem using the BnB algorithm with appropriate parameters
result_bnb = solve_bnb(A,y,λ,M,bnbparams=bnbparams)
examples/solve_mip.jl
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......@@ -16,11 +16,11 @@ mipparams = MipParams(
silent = false, # Toogle solver verbosity
)
# Solve the problem using a MIP solver
result_mip = solve_mip(A,y,λ,M)
# Solve the problem using a MIP solver with appropriate parameters
result_mip = solve_mip(A,y,λ,M,mipparams=mipparams)
# Display solver results and statistics
println("MIP")
println("\nMIP")
println(" Status : $(result_mip.termination_status)")
println(" Objective : $(result_mip.objective_value)")
println(" Nodes : $(result_mip.node_count)")
......
exp/ICASSP/performances.jl
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− 62
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......@@ -8,17 +8,22 @@ using StatsBase
# This is the only part of code you may have to edit
setup = "toeplitz" # Setup to use : "gaussian" or "toeplitz"
k = 7 # Sparsity level
k = 5 # Sparsity level
m, n = 500, 300 # Dictionnary dimension
snr = 10. * log10(10.) # SNR of the observation noise
maxtime = 1000 # Maximum solution time (in second) allowed
maxiter = 1000 # Maximum Active-Set iterations allowed per relaxation resolution
tol = 1.e-8 # Integer tolerance (ie, |x|<tol <=> x=0)
repeats = 100 # Number of repeats in the experiment
repeats = 10 # Number of repeats in the experiment
################################## Experiment ##################################
function print_and_log(s::String, f::IOStream)
print(s)
write(f,s)
end
function precompilation(
setup::String,
k::Int,
......@@ -29,7 +34,7 @@ function precompilation(
maxiter::Int,
tol::Float64,
)
println("Precomiling methods ...")
print_and_log("Precompiling methods ...\n",logfile)
try
if setup == "gaussian"
A, y, λ, M = data_gaussian(k,m,n,snr)
......@@ -42,10 +47,12 @@ function precompilation(
result_bnb = solve_bnb(A,y,λ,M,bnbparams=BnbParams(maxtime=maxtime,maxiter=maxiter,tol=tol,verbosity=false))
result_bnbs = solve_bnb(A,y,λ,M,bnbparams=BnbParams(maxtime=maxtime,maxiter=maxiter,tol=tol,verbosity=false,screening=true))
catch e
e == InterruptException() && rethrow(e)
println("Precompilation failed with the following error")
throw(e)
print_and_log("Precompilation failed with the following error\n",logfile)
print_and_log("$e\n",logfile)
print_and_log("Stopping experiment\n",logfile)
rethrow(e)
end
print_and_log("\n",logfile)
return nothing
end
......@@ -57,29 +64,18 @@ logfile_name = string(
)
logfile = open(logfile_name, "w")
println("--------------------------------")
println("ICASSP experiment - Performances\n")
println("Configuration")
println(" setup : $(setup)")
println(" k : $(k)")
println(" m, n : $(m), $(n)")
println(" snr : $(snr)")
println(" maxtime : $(maxtime)")
println(" maxiter : $(maxiter)")
println(" tol : $(tol)")
println(" repeats : $(repeats)")
println()
write(logfile,"ICASSP experiment - Performances\n\n")
write(logfile,"Configuration\n")
write(logfile," setup : $(setup)\n")
write(logfile," k : $(k)\n")
write(logfile," m, n : $(m), $(n)\n")
write(logfile," snr : $(snr)\n")
write(logfile," maxtime : $(maxtime)\n")
write(logfile," maxiter : $(maxiter)\n")
write(logfile," tol : $(tol)\n")
write(logfile," repeats : $(repeats)\n")
print_and_log("--------------------------------\n",logfile)
print_and_log("ICASSP experiment - Performances\n\n",logfile)
print_and_log("Configuration\n",logfile)
print_and_log(" setup : $(setup)\n",logfile)
print_and_log(" k : $(k)\n",logfile)
print_and_log(" m, n : $(m), $(n)\n",logfile)
print_and_log(" snr : $(snr)\n",logfile)
print_and_log(" maxtime : $(maxtime)\n",logfile)
print_and_log(" maxiter : $(maxiter)\n",logfile)
print_and_log(" tol : $(tol)\n",logfile)
print_and_log(" repeats : $(repeats)\n",logfile)
print_and_log("\n",logfile)
fail_mip = Vector{Union{Bool,Missing}}(missing,repeats)
fail_bnb = Vector{Union{Bool,Missing}}(missing,repeats)
......@@ -94,7 +90,7 @@ time_bnbs = Vector{Union{Float64,Missing}}(missing,repeats)
precompilation(setup,k,m,n,snr,maxtime,maxiter,tol)
for i in 1:repeats
println("Repeat $i/$repeats")
print_and_log("Repeat $i/$repeats\n",logfile)
try
# Generate data
if setup == "gaussian"
......@@ -130,42 +126,48 @@ for i in 1:repeats
else
fail_bnbs[i] = true
end
# Log results
print_and_log(" Fails\n",logfile)
print_and_log(" MIP : $(fail_mip[i])\n",logfile)
print_and_log(" BnB : $(fail_bnb[i])\n",logfile)
print_and_log(" SBnB : $(fail_bnbs[i])\n",logfile)
print_and_log(" Node count\n",logfile)
print_and_log(" MIP : $(node_mip[i])\n",logfile)
print_and_log(" BnB : $(node_bnb[i])\n",logfile)
print_and_log(" SBnB : $(node_bnbs[i])\n",logfile)
print_and_log(" Solve time\n",logfile)
print_and_log(" MIP : $(round(time_mip[i],digits=3)) seconds\n",logfile)
print_and_log(" BnB : $(round(time_bnb[i],digits=3)) seconds\n",logfile)
print_and_log(" SBnB : $(round(time_bnbs[i],digits=3)) seconds\n",logfile)
catch e
e == InterruptException() && rethrow(e)
println("warning : Repeat $i failed with the following error")
println(e)
if e == InterruptException()
close(logfile)
rethrow(e)
end
print_and_log("warning : Repeat $i failed with the following error\n",logfile)
print_and_log("$e\n",logfile)
print_and_log("Skipping this repeat\n",logfile)
end
end
################################### Results ####################################
println()
println("Fails")
println(" MIP : $(100 * mean(skipmissing(fail_mip)))%")
println(" BnB : $(100 * mean(skipmissing(fail_bnb)))%")
println(" SBnB : $(100 * mean(skipmissing(fail_bnbs)))%")
println("Node count")
println(" MIP : $(mean(skipmissing(node_mip)))")
println(" BnB : $(mean(skipmissing(node_bnb)))")
println(" SBnB : $(mean(skipmissing(node_bnbs)))")
println("Solve time")
println(" MIP : $(round(mean(skipmissing(time_mip)),digits=3)) seconds")
println(" BnB : $(round(mean(skipmissing(time_bnb)),digits=3)) seconds")
println(" SBnB : $(round(mean(skipmissing(time_bnbs)),digits=3)) seconds")
println("\n--------------------------------")
write(logfile,"\n")
write(logfile,"Fails\n")
write(logfile," MIP : $(100 * mean(skipmissing(fail_mip)))%\n")
write(logfile," BnB : $(100 * mean(skipmissing(fail_bnb)))%\n")
write(logfile," SBnB : $(100 * mean(skipmissing(fail_bnbs)))%\n")
write(logfile,"Node count\n")
write(logfile," MIP : $(mean(skipmissing(node_mip)))\n")
write(logfile," BnB : $(mean(skipmissing(node_bnb)))\n")
write(logfile," SBnB : $(mean(skipmissing(node_bnbs)))\n")
write(logfile,"Solve time\n")
write(logfile," MIP : $(round(mean(skipmissing(time_mip)),digits=3)) seconds\n")
write(logfile," BnB : $(round(mean(skipmissing(time_bnb)),digits=3)) seconds\n")
write(logfile," SBnB : $(round(mean(skipmissing(time_bnbs)),digits=3)) seconds\n")
close(logfile)
\ No newline at end of file
print_and_log("\n",logfile)
print_and_log("Results\n",logfile)
print_and_log(" Fails (mean over $repeats repeats)\n",logfile)
print_and_log(" MIP : $(100 * mean(skipmissing(fail_mip)))%\n",logfile)
print_and_log(" BnB : $(100 * mean(skipmissing(fail_bnb)))%\n",logfile)
print_and_log(" SBnB : $(100 * mean(skipmissing(fail_bnbs)))%\n",logfile)
print_and_log(" Node count (mean over $repeats repeats)\n",logfile)
print_and_log(" MIP : $(mean(skipmissing(node_mip)))\n",logfile)
print_and_log(" BnB : $(mean(skipmissing(node_bnb)))\n",logfile)
print_and_log(" SBnB : $(mean(skipmissing(node_bnbs)))\n",logfile)
print_and_log(" Solve time (mean over $repeats repeats)\n",logfile)
print_and_log(" MIP : $(round(mean(skipmissing(time_mip)),digits=3)) seconds\n",logfile)
print_and_log(" BnB : $(round(mean(skipmissing(time_bnb)),digits=3)) seconds\n",logfile)
print_and_log(" SBnB : $(round(mean(skipmissing(time_bnbs)),digits=3)) seconds\n",logfile)
print_and_log("--------------------------------",logfile)
close(logfile)
src/data.jl
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......@@ -9,6 +9,8 @@ function validate_data(
M > 0 || throw(ArgumentError("M must be positive"))
end
# ============================================================================ #
"""
data_gaussian(
k::Int=5,
......
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