math-optim/run.go

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// Copyright 2023 wanderer <a_mirre at utb dot cz>
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// SPDX-License-Identifier: GPL-3.0-or-later
package main
import (
"flag"
"log"
"sync"
"git.dotya.ml/wanderer/math-optim/algo"
"git.dotya.ml/wanderer/math-optim/report"
)
var version = "development"
var (
doPrint = flag.Bool("printreport", true, "print report.tex to console")
generate = flag.Bool("generate", true, "run algos and generate plot pics/statistical tables (anew)")
rS = flag.Bool("randomsearch", false, "run Random Search algorithm")
sHC = flag.Bool("shc", false, "run Stochastic Hill Climbing algorithm")
n100 = flag.Bool("N100", false, "run the \"100 Neighbours\" variant of SHC")
// TODO(me): add flag for plot output format: -plotout=(svg,eps,pdf).
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jDE = flag.Bool("jde", false, "run Differential Evolution algorithm with parameter self adaptation")
// run CEC2020 jDE by default.
c2jDE = flag.Bool("c2jde", true, "run CEC2020 version of the Differential Evolution algorithm with parameter self adaptation")
)
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func run() {
log.Println("starting math-optim version", "'"+version+"'")
flag.Parse()
if *generate {
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if !*jDE && !*c2jDE && !*sHC && !*rS {
log.Println("at least one algo needs to be specified, exiting...")
return
}
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var wg sync.WaitGroup
var m sync.Mutex
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if *jDE {
wg.Add(1)
go algo.DojDE(&wg, &m)
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}
if *c2jDE {
wg.Add(1)
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go algo.DoCEC2020jDE(&wg, &m)
}
if *rS {
wg.Add(1)
go algo.DoRandomSearch(&wg, &m)
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}
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if *sHC {
wg.Add(1)
if *n100 {
go algo.DoStochasticHillClimbing100Neigh(&wg, &m)
} else {
go algo.DoStochasticHillClimbing(&wg, &m)
}
}
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wg.Wait()
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// pL, benchCount := algo.PrepComparisonOfMeans(&wg)
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// report.SaveComparisonOfMeans(*pL, benchCount)
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report.SaveTexAllPics()
report.SaveTexAllTables()
}
report.SaveAndPrint(*doPrint)
log.Println("looks like we're done")
log.Println("run an equivalent of `pdflatex -clean -shell-escape -interaction=nonstopmode ./report.tex` to get a pdf")
}