From ead8c80e56fe3f66fa43f318b227108641b620a7 Mon Sep 17 00:00:00 2001
From: leo <wanderer@dotya.ml>
Date: Thu, 23 Feb 2023 18:05:18 +0100
Subject: [PATCH] algo: add DoCEC2020SOMAT3A func

---
 algo/algo.go | 84 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 84 insertions(+)

diff --git a/algo/algo.go b/algo/algo.go
index 94a7b6f..854adb4 100644
--- a/algo/algo.go
+++ b/algo/algo.go
@@ -582,3 +582,87 @@ func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex) {
 	stats.SaveTable(algoName, algoStats)
 	m.Unlock()
 }
+
+// DoCEC2020SOMAT3A performs a search using the SOMA T3A method.
+func DoCEC2020SOMAT3A(wg *sync.WaitGroup, m *sync.Mutex) {
+	defer wg.Done()
+
+	// funcCount is the number of bench functions available and tested.
+	funcCount := len(cec2020.Functions)
+	// stats for the current algo.
+	algoStats := make([][]stats.Stats, funcCount)
+	// ch serves as a way to get the actual computed output.
+	ch := make(chan []stats.Stats, funcCount)
+	chAlgoMeans := make(chan *stats.AlgoBenchMean, funcCount)
+
+	defer close(ch)
+	defer close(chAlgoMeans)
+
+	// somat3a params.
+	np := 50
+	k := 10
+	mSize := 10
+	n := 5
+	njumps := 7
+
+	for i := range algoStats {
+		somat3a := ga.NewSOMAT3A()
+
+		// params:
+		//  Generations, minimum bench iterations, initial population size,
+		//  leader candidates, migration candidates group size, number of
+		//  migrants, number of jumps each migrant performs, dimensions, bench
+		//  name and synchronisation channels.
+		//
+		//  -1 to disable generation limits,
+		//  n > 0 for minimum bench iterations,
+		//  np >= k+mSize as initial population size,
+		//  k, mSize, n and njumps >= 0.
+		err := somat3a.Init(-1, 30, np, k, mSize, n, njumps,
+			cec2020.Dimensions, cec2020.FuncNames[i],
+			ch, chAlgoMeans,
+		)
+		if err != nil {
+			log.Panicf("Failed to initialise SOMA T3A, error: %q", err)
+		}
+
+		go somat3a.Run()
+	}
+
+	// get results.
+	for i := range algoStats {
+		s := <-ch
+		aM := <-chAlgoMeans
+
+		algoStats[i] = s
+
+		saveAlgoMeans(*aM)
+	}
+
+	pCh := make(chan report.PicList, funcCount*len(cec2020.Dimensions))
+	pMeanCh := make(chan report.PicList, funcCount*len(cec2020.Dimensions))
+
+	for _, algoStat := range algoStats {
+		go plotAllDims(algoStat, "plot", ".pdf", pCh, pMeanCh)
+	}
+
+	pLs := []report.PicList{}
+	pLsMean := []report.PicList{}
+
+	for range algoStats {
+		pL := <-pCh
+		pLMean := <-pMeanCh
+
+		pLs = append(pLs, pL)
+		pLsMean = append(pLsMean, pLMean)
+	}
+
+	algoName := "SOMA T3A"
+
+	// protect access to shared data.
+	m.Lock()
+	report.SavePicsToFile(pLs, pLsMean, algoName)
+
+	stats.SaveTable(algoName, algoStats)
+	m.Unlock()
+}