// Copyright 2023 wanderer <a_mirre at utb dot cz>
// 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).

	// run jDE by default.
	jDE = flag.Bool("jde", true, "run Differential Evolution algorithm with parameter self adaptation")
)

func run() {
	log.Println("starting math-optim version", "'"+version+"'")

	flag.Parse()

	if *generate {
		if !*jDE && !*sHC && !*rS {
			log.Println("at least one algo needs to be specified, exiting...")

			return
		}

		var wg sync.WaitGroup

		var m sync.Mutex

		switch {
		case *jDE:
			wg.Add(1)

			go algo.DojDE(&wg, &m)

		case *rS:
			wg.Add(1)

			go algo.DoRandomSearch(&wg, &m)

		case *sHC:
			wg.Add(1)

			if *n100 {
				go algo.DoStochasticHillClimbing100Neigh(&wg, &m)
			} else {
				go algo.DoStochasticHillClimbing(&wg, &m)
			}
		}

		wg.Wait()

		// pL, benchCount := algo.PrepComparisonOfMeans(&wg)

		// report.SaveComparisonOfMeans(*pL, benchCount)
		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")
}