diff --git a/.Rbuildignore b/.Rbuildignore
index 9238dee..548f11c 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -4,4 +4,4 @@ matlab
 CHANGELOG.md
 CITATION.cff
 .travis.yml
-data/ExamplesDataFormatting
\ No newline at end of file
+inst/ext/ExamplesDataFormatting
\ No newline at end of file
diff --git a/DESCRIPTION b/DESCRIPTION
index e7e0081..aa9e85a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: rBAPS
 Title: Bayesian Analysis of Population Structure
-Version: 0.0.0.9000
-Date: 2020-01-14
+Version: 0.0.0.9001
+Date: 2020-11-09
 Authors@R:
     c(
         person(
@@ -30,14 +30,14 @@ Description: Partial R implementation of the BAPS software
     Corander et al. 2008b <doi:10.1007/s00180-007-0072-x>;
     Tang et al. 2009 <doi:10.1371/journal.pcbi.1000455>;
     Cheng et al. 2011 <doi:10.1186/1471-2105-12-302>,
-    available at <http://www.helsinki.fi/bsg/software/BAPS/Z>), provides a 
-    computationally-efficient method for the identification of admixture events 
+    available at <http://www.helsinki.fi/bsg/software/BAPS/Z>), provides a
+    computationally-efficient method for the identification of admixture events
     in genetic population history.
 License: GPL-3
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.1.1
-Suggests: 
+Suggests:
     testthat (>= 2.1.0)
 Imports:
     methods
diff --git a/NAMESPACE b/NAMESPACE
index 2dd1c5e..42b0063 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -23,7 +23,6 @@ export(linkage)
 export(logml2String)
 export(lueGenePopData)
 export(lueNimi)
-export(min_MATLAB)
 export(noIndex)
 export(ownNum2Str)
 export(poistaLiianPienet)
diff --git a/R/addAlleles.R b/R/addAlleles.R
index 33d0f38..6dd1c08 100644
--- a/R/addAlleles.R
+++ b/R/addAlleles.R
@@ -20,8 +20,8 @@ addAlleles <- function(data, ind, line, divider) {
 	k <- 1
 	merkki <- substring(line, k, k)
 	while (merkki != ',') {
-	   k <- k + 1
-	   merkki <- substring(line, k, k)
+		k <- k + 1
+		merkki <- substring(line, k, k)
 	}
 	line <- substring(line, k + 1)
 	# clear k; clear merkki;
diff --git a/R/addToSummary.R b/R/addToSummary.R
new file mode 100644
index 0000000..4affbe9
--- /dev/null
+++ b/R/addToSummary.R
@@ -0,0 +1,18 @@
+addToSummary <- function(logml, partitionSummary, worstIndex) {
+	# Tiedet��n, ett� annettu logml on isompi kuin huonoin arvo
+	# partitionSummary taulukossa. Jos partitionSummary:ss� ei viel� ole
+	# annettua logml arvoa, niin lis�t��n worstIndex:in kohtaan uusi logml ja
+	# nykyist� partitiota vastaava nclusters:in arvo. Muutoin ei tehd� mit��n.
+
+	apu <- find(abs(partitionSummary[, 2] - logml) < 1e-5)
+	if (isempty(apu)) {
+		# Nyt l�ydetty partitio ei ole viel� kirjattuna summaryyn.
+		npops <- length(unique(PARTITION))
+		partitionSummary[worstIndex, 1] <- npops
+		partitionSummary[worstIndex, 2] <- logml
+		added <- 1
+	} else {
+		added <- 0
+	}
+	return(list(partitionSummary = partitionSummary, added = added))
+}
\ No newline at end of file
diff --git a/R/admixture_initialization.R b/R/admixture_initialization.R
new file mode 100644
index 0000000..4d9f6c8
--- /dev/null
+++ b/R/admixture_initialization.R
@@ -0,0 +1,20 @@
+#' @title Seuraavat kolme funktiota liittyvat alkupartition muodostamiseen.
+#' @param data_matrix data_matrix
+#' @param nclusters ncluster
+#' @param Z Z
+
+admixture_initialization <- function (data_matrix, nclusters, Z) {
+	size_data <- size(data_matrix)
+	nloci <- size_data[2] - 1
+	n <- max(data_matrix[, end])
+	T <- cluster_own(Z, nclusters)
+	initial_partition <- zeros(size_data[1], 1)
+	for (i in 1:n) {
+		kori <- T[i]
+		here <- find(data_matrix[,end] == i)
+		for (j in 1:length(here)) {
+			initial_partition[here[j], 1] <- kori
+		}
+	}
+	return(initial_partition)
+}
\ No newline at end of file
diff --git a/R/clearGlobalVars.R b/R/clearGlobalVars.R
index 1d77d9c..abc59fb 100644
--- a/R/clearGlobalVars.R
+++ b/R/clearGlobalVars.R
@@ -1,7 +1,8 @@
 clearGlobalVars <- function() {
-	COUNTS <- SUMCOUNTS <- PARTITION <- POP_LOGML <- vector() # placeholders
+	# COUNTS <- SUMCOUNTS <- PARTITION <- POP_LOGML <- vector() # placeholders
 	COUNTS <<- vector()
 	SUMCOUNTS <<- vector()
 	PARTITION <<- vector()
 	POP_LOGML <<- vector()
+	LOGDIFF <<- vector()
 }
\ No newline at end of file
diff --git a/R/cluster_own.R b/R/cluster_own.R
new file mode 100644
index 0000000..b94b7b8
--- /dev/null
+++ b/R/cluster_own.R
@@ -0,0 +1,51 @@
+cluster_own <- function(Z, nclust) {
+	true <- logical(1)
+	false <- logical(0)
+	maxclust <- nclust
+	# % Start of algorithm
+	m <- size(Z, 1) + 1
+	T <- zeros(m, 1)
+	# % maximum number of clusters based on inconsistency
+	if (m <= maxclust) {
+		T = t((1:m))
+	} else if (maxclust == 1) {
+		T <- ones(m, 1)
+	} else {
+		clsnum <- 1
+		for (k in (m - maxclust + 1):(m - 1)) {
+			i = Z(k, 1) # left tree
+			if (i <= m) { # original node, no leafs
+				T(i) = clsnum
+				clsnum = clsnum + 1
+			} else if (i < (2 * m - maxclust + 1)) { # created before cutoff, search down the tree
+				T <- clusternum(Z, T, i - m, clsnum)
+				clsnum <- clsnum + 1
+			}
+			i <- Z(k, 2) # right tree
+			if (i <= m) { # original node, no leafs
+				T[i] <- clsnum
+				clsnum <- clsnum + 1
+			} else if (i < (2 * m - maxclust + 1)) { # created before cutoff, search down the tree
+				T <- clusternum(Z, T, i - m, clsnum)
+				clsnum <- clsnum + 1
+			}
+		}
+	}
+	return(T)
+}
+
+clusternum <- function(X, T, k, c) {
+	m <- size(X, 1) + 1
+	while (!isempty(k)) {
+		# Get the children of nodes at this level
+		children <- X[k, 1:2]
+		children <- children
+
+		# Assign this node number to leaf children
+		t <- (children <= m)
+		T[children[t]] <- c
+		# Move to next level
+		k <- children(!t) - m
+	}
+	return(T)
+}
\ No newline at end of file
diff --git a/R/computeDiffInCounts.R b/R/computeDiffInCounts.R
new file mode 100644
index 0000000..de19e30
--- /dev/null
+++ b/R/computeDiffInCounts.R
@@ -0,0 +1,17 @@
+computeDiffInCounts <- function(rows, max_noalle, nloci, data) {
+	# % Muodostaa max_noalle*nloci taulukon, jossa on niiden alleelien
+	# % lukum��r�t (vastaavasti kuin COUNTS:issa), jotka ovat data:n
+	# % riveill� rows. rows pit�� olla vaakavektori.
+
+	diffInCounts <- zeros(max_noalle, nloci)
+	for (i in rows) {
+		row <- data[i, ]
+		notEmpty <- find(row>=0)
+
+		if (length(notEmpty) > 0) {
+			diffInCounts(row(notEmpty) + (notEmpty - 1) * max_noalle) <-
+				diffInCounts(row(notEmpty) + (notEmpty - 1) * max_noalle) + 1
+		}
+	}
+	return(diffInCounts)
+}
diff --git a/R/computePopulationLogml.R b/R/computePopulationLogml.R
new file mode 100644
index 0000000..bf9782d
--- /dev/null
+++ b/R/computePopulationLogml.R
@@ -0,0 +1,24 @@
+computePopulationLogml <- function(pops, adjprior, priorTerm) {
+	# Palauttaa length(pops)*1 taulukon, jossa on laskettu korikohtaiset
+
+	x <- size(COUNTS, 1)
+	y <- size(COUNTS, 2)
+	z <- length(pops)
+
+	popLogml <- squeeze(
+		sum(
+			sum(
+				reshape(
+					lgamma(
+						repmat(adjprior, c(1, 1, length(pops))) +
+							COUNTS[, , pops]
+					),
+					c(x, y, z)
+				),
+				1
+			),
+			2
+		)
+	) - sum(lgamma(1 + SUMCOUNTS[pops, ]), 2) - priorTerm
+	return(popLogml)
+}
\ No newline at end of file
diff --git a/R/findEmptyPop.R b/R/findEmptyPop.R
new file mode 100644
index 0000000..e62b5e3
--- /dev/null
+++ b/R/findEmptyPop.R
@@ -0,0 +1,12 @@
+findEmptyPop <- function(npops) {
+	# % Palauttaa ensimm�isen tyhj�n populaation indeksin. Jos tyhji�
+	# % populaatioita ei ole, palauttaa -1:n.
+	pops <- t(unique(PARTITION))
+	if (length(pops) == npops) {
+		emptyPop <- -1
+	} else {
+		popDiff <- diff(c(0, pops, npops + 1))
+		emptyPop <- min(find(popDiff > 1))
+	}
+	return(list(emptyPop = emptyPop, pops = pops))
+}
diff --git a/R/greedyMix.R b/R/greedyMix.R
index ef91b17..7b0004e 100644
--- a/R/greedyMix.R
+++ b/R/greedyMix.R
@@ -11,10 +11,11 @@ greedyMix <- function(
 	savePreProcessed = NULL,
 	filePreProcessed = NULL
 ) {
-	# ASK: graphical components. Remove?
+	# ASK: Unclear when fixedk == TRUE. Remove?
 	# check whether fixed k mode is selected
 	# h0 <- findobj('Tag','fixk_menu')
 	# fixedK = get(h0, 'userdata');
+	fixedK <- FALSE
 
 	# if fixedK
 	# 	if ~(fixKWarning == 1) % call function fixKWarning
@@ -22,9 +23,11 @@ greedyMix <- function(
 	# 	end
 	# end
 
+	# ASK: ditto
 	# % check whether partition compare mode is selected
 	# h1 = findobj('Tag','partitioncompare_menu');
 	# partitionCompare = get(h1, 'userdata');
+	partitionCompare <- FALSE
 
 	if (is(tietue, "list") | is(tietue, "character")) {
 		# ----------------------------------------------------------------------
@@ -244,13 +247,15 @@ greedyMix <- function(
 	}
 
 	# ==========================================================================
-	# Declaring global variables
+	# Declaring global variables and changing environment of children functions
 	# ==========================================================================
 	PARTITION       <- vector()
 	COUNTS          <- vector()
 	SUMCOUNTS       <- vector()
 	POP_LOGML       <- vector()
-	clearGlobalVars <- vector()
+	clearGlobalVars()
+
+	environment(writeMixtureInfo) <- environment()
 	# ==========================================================================
 	c             <- list()
 	c$data        <- data
@@ -265,6 +270,7 @@ greedyMix <- function(
 	ekat   <- t(seq(1, ninds, rowsFromInd) * rowsFromInd)
 	c$rows <- c(ekat, ekat + rowsFromInd - 1)
 
+	# ASK remove?
 	# partition compare
 	# if (!is.null(partitionCompare)) {
 	# 	nsamplingunits <- size(c$rows, 1)
@@ -291,17 +297,22 @@ greedyMix <- function(
 	# 	}
 	# 	# return the logml result
 	# 	partitionCompare$logmls <- partitionLogml
-	# 	# set(h1, 'userdata', partitionCompare) # ASK remove?
+	# 	# set(h1, 'userdata', partitionCompare)
 	# 	return()
 	# }
 
-	# ASK remove (graphical part)?
-	# if (fixedK) {
-	# 	#logml_npops_partitionSummary <- indMix_fixK(c) # ASK translate?
-	# } else {
-	# 	#logml_npops_partitionSummary <- indMix(c) # ASK translate?
-	# }
-	# if (logml_npops_partitionSummary$logml == 1) return()
+	if (fixedK) {
+		# logml_npops_partitionSummary <- indMix_fixK(c) # TODO: translate
+		# logml <- logml_npops_partitionSummary$logml
+		# npops <- logml_npops_partitionSummary$npops
+		# partitionSummary <- logml_npops_partitionSummary$partitionSummary
+	} else {
+		logml_npops_partitionSummary <- indMix(c) # TODO: translate
+		logml <- logml_npops_partitionSummary$logml
+		npops <- logml_npops_partitionSummary$npops
+		partitionSummary <- logml_npops_partitionSummary$partitionSummary
+	}
+	if (logml_npops_partitionSummary$logml == 1) return()
 
 	data <- data[, seq_len(ncol(data) - 1)]
 
@@ -310,8 +321,9 @@ greedyMix <- function(
 	# inp = get(h0,'String');
 	# h0 = findobj('Tag','filename2_text')
 	# outp = get(h0,'String');
+	inp <- vector()
+	outp <- vector()
 
-	browser() # TEMP
 	changesInLogml <- writeMixtureInfo(
 		logml, rowsFromInd, data, adjprior, priorTerm, outp, inp,
 		popnames, fixedK
diff --git a/R/indMix.R b/R/indMix.R
new file mode 100644
index 0000000..6b11bf9
--- /dev/null
+++ b/R/indMix.R
@@ -0,0 +1,567 @@
+indMix <- function(c, npops, dispText) {
+	# Greedy search algorithm with unknown number of classes for regular
+	# clustering.
+	# Input npops is not used if called by greedyMix or greedyPopMix.
+
+	logml <- 1
+	clearGlobalVars()
+
+	noalle <- c$noalle
+	rows <- c$rows
+	data <- c$data
+
+	adjprior <- c$adjprior
+	priorTerm <- c$priorTerm
+	rowsFromInd <- c$rowsFromInd
+
+	if (isfield(c, 'dist')) {
+		dist <- c$dist
+		Z <- c$Z
+	}
+
+	rm(c)
+	nargin <- length(as.list(match.call())) - 1
+
+	if (nargin < 2) {
+		dispText <- 1
+		npopstext <- matrix()
+		ready <- FALSE
+		teksti <- 'Input upper bound to the number of populations (possibly multiple values)'
+		while (!ready) {
+			npopstextExtra <- inputdlg(
+				teksti,
+				1,
+				'20'
+			)
+			if (isempty(npopstextExtra)) { # Painettu Cancel:ia
+				return()
+			}
+			npopstextExtra <- npopstextExtra[1]
+			if (length(npopstextExtra)>=255) {
+				npopstextExtra <- npopstextExtra[1:255]
+				npopstext <- c(npopstext, ' ', npopstextExtra)
+				teksti <- 'The input field length limit (255 characters) was reached. Input more values: '
+			} else {
+				npopstext <- c(npopstext, ' ', npopstextExtra)
+				ready <- TRUE
+			}
+		}
+		rm(ready, teksti)
+		if (isempty(npopstext) | length(npopstext) == 1) {
+			return()
+		} else {
+			npopsTaulu <- as.numeric(npopstext)
+			ykkoset <- find(npopsTaulu == 1)
+			npopsTaulu(ykkoset) <- list() # Mik�li ykk�si� annettu yl�rajaksi, ne poistetaan.
+			if (isempty(npopsTaulu)) {
+				logml <- 1
+				partitionSummary <- 1
+				npops <- 1
+				return()
+			}
+			rm(ykkoset)
+		}
+	} else {
+		npopsTaulu <- npops
+	}
+
+	nruns <- length(npopsTaulu)
+
+	initData <- data
+	data <- data[,1:(end - 1)]
+
+	logmlBest <- -1e50
+	partitionSummary <- -1e50 * ones(30, 2) # Tiedot 30 parhaasta partitiosta (npops ja logml)
+	partitionSummary[,1] <- zeros(30, 1)
+	worstLogml <- -1e50
+	worstIndex <- 1
+	for (run in 1:nruns) {
+		npops <- npopsTaulu(run)
+		if (dispText) {
+			dispLine()
+			print(
+				paste0(
+					'Run ', num2str(run), '/', num2str(nruns),
+					', maximum number of populations ', num2str(npops), '.'
+				)
+			)
+		}
+		ninds <- size(rows, 1)
+
+		initialPartition <- admixture_initialization(initData, npops, Z) # TODO: translate
+		sumcounts_counts_logml = initialCounts(
+			initialPartition, data, npops, rows, noalle, adjprior
+		) # TODO: translate
+		sumcounts <- sumcounts_counts_logml$sumcounts
+		counts <- sumcounts_counts_logml$counts
+		logml <- sumcounts_counts_logml$logml
+
+		PARTITION <- zeros(ninds, 1)
+		for (i in 1:ninds) {
+			apu <- rows[i]
+			PARTITION[i] <- initialPartition(apu[1])
+		}
+
+		COUNTS <- counts
+		SUMCOUNTS <- sumcounts
+		POP_LOGML <- computePopulationLogml(1:npops, adjprior, priorTerm) # TODO: translate
+		LOGDIFF <- repmat(-Inf, c(ninds, npops))
+		rm(initialPartition, counts, sumcounts)
+
+		# PARHAAN MIXTURE-PARTITION ETSIMINEN
+		nRoundTypes <- 7
+		kokeiltu <- zeros(nRoundTypes, 1)
+		roundTypes <- c(1, 1)  # Ykk�svaiheen sykli kahteen kertaan.
+		ready <- 0
+		vaihe <- 1
+
+		if (dispText) {
+			print(' ')
+			print(
+				paste0(
+					'Mixture analysis started with initial',
+					num2str(npops),
+					'populations.'
+				)
+			)
+		}
+
+		while (ready != 1) {
+			muutoksia <- 0
+
+			if (dispText) {
+				print(paste('Performing steps:', num2str(roundTypes)))
+			}
+
+			for (n in 1:length(roundTypes)) {
+
+				round <- roundTypes[n]
+				kivaluku <- 0
+
+				if (kokeiltu(round) == 1) { #Askelta kokeiltu viime muutoksen j�lkeen
+
+				} else if (round == 0 | round == 1) { #Yksil�n siirt�minen toiseen populaatioon.
+					inds <- 1:ninds
+					aputaulu <- c(t(inds), rand(ninds, 1))
+					aputaulu <- sortrows(aputaulu, 2)
+					inds <- t(aputaulu[, 1])
+					muutosNyt <- 0
+
+					for (ind in inds) {
+						i1 <- PARTITION[ind]
+						muutokset_diffInCounts = laskeMuutokset(
+							ind, rows, data, adjprior, priorTerm
+						)
+						muutokset <- muutokset_diffInCounts$muutokset
+						diffInCounts <- muutokset_diffInCounts$diffInCounts
+
+						if (round == 1) {
+							maxMuutos <- max_MATLAB(muutokset)[[1]]
+							i2 <- max_MATLAB(muutokset)[[2]]
+						}
+
+						if (i1 != i2 & maxMuutos > 1e-5) {
+							# Tapahtui muutos
+							muutoksia <- 1
+							if (muutosNyt == 0) {
+								muutosNyt <- 1
+								if (dispText) {
+									print('Action 1')
+								}
+							}
+							kokeiltu <- zeros(nRoundTypes, 1)
+							kivaluku <- kivaluku + 1
+							updateGlobalVariables(
+								ind, i2, diffInCounts, adjprior, priorTerm
+							)
+							logml <- logml+maxMuutos
+							if (logml > worstLogml) {
+								partitionSummary_added = addToSummary(
+									logml, partitionSummary, worstIndex
+								)
+								partitionSummary_added <- partitionSummary_added$partitionSummary
+								added <- partitionSummary_added$added
+								if (added == 1) {
+									worstLogml <- min_MATLAB(partitionSummary[, 2])[[1]]
+									worstIndex <- min_MATLAB(partitionSummary[, 2])[[2]]
+								}
+							}
+						}
+					}
+
+					if (muutosNyt == 0) {
+						kokeiltu[round] <- 1
+					}
+
+				} else if (round == 2) { # Populaation yhdist�minen toiseen.
+					maxMuutos <- 0
+					for (pop in 1:npops) {
+						muutokset_diffInCounts <- laskeMuutokset2(
+							pop, rows, data, adjprior, priorTerm
+						)
+						muutokset <- muutokset_diffInCounts$muutokset
+						diffInCounts <- muutokset_diffInCounts$diffInCounts
+						isoin <- max_MATLAB(muutokset)[[1]]
+						indeksi <- max_MATLAB(muutokset)[[2]]
+						if (isoin > maxMuutos) {
+							maxMuutos <- isoin
+							i1 <- pop
+							i2 <- indeksi
+							diffInCountsBest <- diffInCounts
+						}
+					}
+
+					if (maxMuutos > 1e-5) {
+						muutoksia <- 1
+						kokeiltu <- zeros(nRoundTypes, 1)
+						updateGlobalVariables2(
+							i1, i2, diffInCountsBest, adjprior, priorTerm
+						)
+						logml <- logml + maxMuutos
+						if (dispText) {
+							print('Action 2')
+						}
+						if (logml > worstLogml) {
+							partitionSummary_added <- addToSummary(
+								logml, partitionSummary, worstIndex
+							)
+							partitionSummary <- partitionSummary_added$partitionSummary
+							added <- partitionSummary_added$added
+							if (added==1) {
+								worstLogml <- min_MATLAB(partitionSummary[, 2])[[1]]
+								worstIndex <- min_MATLAB(partitionSummary[, 2])[[2]]
+							}
+						}
+					} else {
+						kokeiltu[round] <- 1
+					}
+
+
+				} else if (round == 3 || round == 4) { #Populaation jakaminen osiin.
+					maxMuutos <- 0
+					ninds <- size(rows, 1)
+					for (pop in 1:npops) {
+						inds2 <- find(PARTITION == pop)
+						ninds2 <- length(inds2)
+						if (ninds2 > 2) {
+							dist2 <- laskeOsaDist(inds2, dist, ninds)
+							Z2 <- linkage(t(dist2))
+							if (round == 3) {
+								npops2 <- max(min(20, floor(ninds2 / 5)), 2)
+							} else if (round == 4) {
+								npops2 <- 2 # Moneenko osaan jaetaan
+							}
+							T2 <- cluster_own(Z2, npops2)
+							muutokset <- laskeMuutokset3(
+								T2, inds2, rows, data, adjprior, priorTerm, pop
+							)
+							isoin <- max_MATLAB(muutokset)[[1]]
+							indeksi <- max_MATLAB(muutokset)[[2]]
+							if (isoin > maxMuutos) {
+								maxMuutos <- isoin
+								muuttuvaPop2 <- indeksi %% npops2
+								if (muuttuvaPop2==0) muuttuvaPop2 <- npops2
+								muuttuvat <- inds2[find(T2 == muuttuvaPop2)]
+								i2 <- ceiling(indeksi / npops2)
+							}
+						}
+					}
+					if (maxMuutos > 1e-5) {
+						muutoksia <- 1
+						kokeiltu <- zeros(nRoundTypes, 1)
+						rivit <- list()
+						for (i in 1:length(muuttuvat)) {
+							ind <- muuttuvat[i]
+							lisa <- rows[ind, 1]:rows[ind, 2]
+							rivit <- rbind(rivit, t(lisa))
+						}
+						diffInCounts <- computeDiffInCounts(
+							t(rivit), size(COUNTS, 1), size(COUNTS, 2), data
+						)
+						i1 <- PARTITION(muuttuvat[1])
+						updateGlobalVariables3(
+							muuttuvat, diffInCounts, adjprior, priorTerm, i2
+						)
+						logml <- logml + maxMuutos
+						if (dispText) {
+							if (round == 3) {
+								print('Action 3')
+							} else {
+								print('Action 4')
+							}
+						}
+						if (logml > worstLogml) {
+							partitionSummary_added <- addToSummary(
+								logml, partitionSummary, worstIndex
+							)
+							partitionSummary <- partitionSummary_added$partitionSummary
+							added <- partitionSummary_added$added
+							if (added==1) {
+								worstLogml <- min_MATLAB(partitionSummary[, 2])[[1]]
+								worstIndex <- min_MATLAB(partitionSummary[, 2])[[2]]
+							}
+						}
+
+					} else {
+						kokeiltu[round] <- 1
+					}
+				} else if (round == 5 || round == 6) {
+					j <- 0
+					muutettu <- 0
+					poplogml <- POP_LOGML
+					partition <- PARTITION
+					counts <- COUNTS
+					sumcounts <- SUMCOUNTS
+					logdiff <- LOGDIFF
+
+					pops <- sample(npops)
+					while (j < npops & muutettu == 0) {
+						j <- j + 1
+						pop <- pops[j]
+						totalMuutos <- 0
+						inds <- find(PARTITION == pop)
+						if (round == 5) {
+							aputaulu <- c(inds, rand(length(inds), 1))
+							aputaulu <- sortrows(aputaulu, 2)
+							inds <- t(aputaulu[, 1])
+						} else if (round == 6) {
+							inds <- returnInOrder(
+								inds, pop, rows, data, adjprior, priorTerm
+							)
+						}
+
+						i <- 0
+
+						while (length(inds) > 0 & i < length(inds)) {
+							i <- i + 1
+							ind <- inds[i]
+
+							muutokset_diffInCounts <- laskeMuutokset(
+								ind, rows, data, adjprior, priorTerm
+							)
+							muutokset <- muutokset_diffInCounts$muutokset
+							diffInCounts <- muutokset_diffInCounts$diffInCounts
+
+							muutokset[pop] <- -1e50 # Varmasti ei suurin!!!
+							maxMuutos <- max_MATLAB(muutokset)[[1]]
+							i2 <- max_MATLAB(muutokset)[[2]]
+							updateGlobalVariables(
+								ind, i2, diffInCounts, adjprior, priorTerm
+							)
+
+							totalMuutos <- totalMuutos+maxMuutos
+							logml <- logml + maxMuutos
+							if (round == 6) {
+								# Lopetetaan heti kun muutos on positiivinen.
+								if (totalMuutos > 1e-5) {
+									i <- length(inds)
+								}
+							}
+						}
+
+						if (totalMuutos > 1e-5) {
+							kokeiltu <- zeros(nRoundTypes, 1)
+							muutettu <- 1
+							if (muutoksia == 0) {
+								muutoksia <- 1  # Ulompi kirjanpito.
+								if (dispText) {
+									if (round == 5) {
+										print('Action 5')
+									} else {
+										print('Action 6')
+									}
+								}
+							}
+							if (logml > worstLogml) {
+								partitionSummary_added <- addToSummary(
+									logml, partitionSummary, worstIndex
+								)
+								partitionSummary <- partitionSummary_added$partitionSummary
+								added <- partitionSummary_added$added
+								if (added==1) {
+									worstLogml <- min_MATLAB(partitionSummary[, 2])[[1]]
+									worstIndex <- min_MATLAB(partitionSummary[, 2])[[2]]
+								}
+							}
+						} else {
+							# Miss��n vaiheessa tila ei parantunut.
+							# Perutaan kaikki muutokset.
+							PARTITION <- partition
+							SUMCOUNTS <- sumcounts
+							POP_LOGML <- poplogml
+							COUNTS <- counts
+							logml <- logml - totalMuutos
+							LOGDIFF <- logdiff
+							kokeiltu[round] <- 1
+						}
+					}
+					rm(partition, sumcounts, counts, poplogml)
+
+				} else if (round == 7) {
+					emptyPop <- findEmptyPop(npops)
+					j <- 0
+					pops <- sample(npops)
+					muutoksiaNyt <- 0
+					if (emptyPop == -1) {
+						j <- npops
+					}
+					while (j < npops) {
+						j <- j + 1
+						pop <- pops[j]
+						inds2 <- find(PARTITION == pop)
+						ninds2 <- length(inds2)
+						if (ninds2 > 5) {
+							partition <- PARTITION
+							sumcounts <- SUMCOUNTS
+							counts <- COUNTS
+							poplogml <- POP_LOGML
+							logdiff <- LOGDIFF
+
+							dist2 <- laskeOsaDist(inds2, dist, ninds);
+							Z2 <- linkage(t(dist2))
+							T2 <- cluster_own(Z2, 2)
+							muuttuvat <- inds2[find(T2 == 1)]
+
+							muutokset <- laskeMuutokset3(
+								T2, inds2, rows, data, adjprior, priorTerm, pop
+							)
+							totalMuutos <- muutokset(1, emptyPop)
+
+							rivit <- list()
+							for (i in 1:length(muuttuvat)) {
+								ind <- muuttuvat[i]
+								lisa <- rows[ind, 1]:rows[ind, 2]
+								rivit <- c(rivit, lisa)
+							}
+							diffInCounts <- computeDiffInCounts(
+								rivit, size(COUNTS, 1), size(COUNTS, 2), data
+							)
+
+							updateGlobalVariables3(
+								muuttuvat, diffInCounts, adjprior, priorTerm,
+								emptyPop
+							)
+
+							muutettu <- 1
+							while (muutettu == 1) {
+								muutettu <- 0
+								# Siirret��n yksil�it� populaatioiden v�lill�
+								muutokset <- laskeMuutokset5(
+									inds2, rows, data, adjprior, priorTerm,
+									pop, emptyPop
+								)
+
+								maxMuutos <- indeksi <- max_MATLAB(muutokset)
+
+								muuttuva <- inds2(indeksi)
+								if (PARTITION(muuttuva) == pop) {
+									i2 <- emptyPop
+								} else {
+									i2 <- pop
+								}
+
+								if (maxMuutos > 1e-5) {
+									rivit <- rows[muuttuva, 1]:rows[muuttuva, 2]
+									diffInCounts <- computeDiffInCounts(
+										rivit, size(COUNTS, 1), size(COUNTS, 2),
+										data
+									)
+									updateGlobalVariables3(
+										muuttuva,diffInCounts, adjprior,
+										priorTerm, i2
+									)
+									muutettu <- 1
+									totalMuutos <- totalMuutos + maxMuutos
+								}
+							}
+							if (totalMuutos > 1e-5) {
+								muutoksia <- 1
+								logml <- logml + totalMuutos
+								if (logml > worstLogml) {
+									partitionSummary_added = addToSummary(
+										logml, partitionSummary, worstIndex
+									)
+									partitionSummary_added <- partitionSummary_added$partitionSummary
+									added <- partitionSummary_added$added
+									if (added == 1) {
+										worstLogml <- min_MATLAB(partitionSummary[, 2])[[1]]
+										worstIndex <- min_MATLAB(partitionSummary[, 2])[[2]]
+									}
+								}
+								if (muutoksiaNyt == 0) {
+									if (dispText) {
+										print('Action 7')
+									}
+									muutoksiaNyt <- 1
+								}
+								kokeiltu <- zeros(nRoundTypes, 1)
+								j <- npops
+							} else {
+								# palutetaan vanhat arvot
+								PARTITION <- partition
+								SUMCOUNTS <- sumcounts
+								COUNTS <- counts
+								POP_LOGML <- poplogml
+								LOGDIFF <- logdiff
+							}
+						}
+
+					}
+
+					if (muutoksiaNyt == 0) {
+						kokeiltu[round] <- 1
+					}
+
+				}
+			}
+
+			if (muutoksia == 0) {
+				if (vaihe <= 4) {
+					vaihe <= vaihe + 1
+				} else if (vaihe == 5) {
+					ready <- 1
+				}
+			} else {
+				muutoksia <- 0
+			}
+
+			if (ready == 0) {
+				if (vaihe == 1) {
+					roundTypes <- c(1)
+				} else if (vaihe == 2) {
+					roundTypes <- c(2, 1)
+				} else if (vaihe == 3) {
+					roundTypes <- c(5, 5, 7)
+				} else if (vaihe == 4) {
+					roundTypes = c(4, 3, 1)
+				} else if (vaihe == 5) {
+					roundTypes <- c(6, 7, 2, 3, 4, 1)
+				}
+			}
+		}
+
+		# TALLENNETAAN
+
+		npops <- poistaTyhjatPopulaatiot(npops)
+		POP_LOGML <- computePopulationLogml(1:npops, adjprior, priorTerm)
+		if (dispText) {
+			print(paste('Found partition with', num2str(npops), 'populations.'))
+			print(paste('Log(ml) =', as.character(logml)))
+			print(' ')
+		}
+
+		if (logml > logmlBest) {
+			# P�ivitet��n parasta l�ydetty� partitiota.
+			logmlBest <- logml
+			npopsBest <- npops
+			partitionBest <- PARTITION
+			countsBest <- COUNTS
+			sumCountsBest <- SUMCOUNTS
+			pop_logmlBest <- POP_LOGML
+			logdiffbest <- LOGDIFF
+		}
+	}
+	return(
+		list(logml = logml, npops = npops, partitionSummary = partitionSummary)
+	)
+}
diff --git a/R/initialPopCounts.R b/R/initialPopCounts.R
new file mode 100644
index 0000000..2cb4806
--- /dev/null
+++ b/R/initialPopCounts.R
@@ -0,0 +1,20 @@
+initialPopCounts <- function(data, npops, rows, noalle, adjprior) {
+	nloci <- size(data, 2)
+	counts <- zeros(max(noalle), nloci, npops)
+	sumcounts <- zeros(npops, nloci)
+
+	for (i in 1:npops) {
+		for (j in 1:nloci) {
+			i_rivit <- rows(i, 1):rows(i, 2)
+			havainnotLokuksessa <- find(data[i_rivit, j] >= 0)
+			sumcounts(i, j) <- length(havainnotLokuksessa)
+			for (k in 1:noalle[j]) {
+				alleleCode <- k
+				N_ijk <- length(find(data[i_rivit, j] == alleleCode))
+				counts(k, j, i) <- N_ijk
+			}
+		}
+	}
+	logml <- laskeLoggis(counts, sumcounts, adjprior)
+	return(sumcounts = sumcounts, counts = counts, logml = logml)
+}
diff --git a/R/laskeMuutokset12345.R b/R/laskeMuutokset12345.R
new file mode 100644
index 0000000..bfb4d59
--- /dev/null
+++ b/R/laskeMuutokset12345.R
@@ -0,0 +1,226 @@
+#' @title Calculate changes (?)
+#' @description Palauttaa npops*npops taulun, jonka alkio (i,j) kertoo, mik?on
+#' muutos logml:ss? mikäli populaatiosta i siirretään osuuden verran
+#' todennäköisyysmassaa populaatioon j. Mikäli populaatiossa i ei ole mitään
+#' siirrettävää, on vastaavassa kohdassa rivi nollia.
+#' @param osuus Percentages?
+#' @param omaFreqs own Freqs?
+#' @param osuusTaulu Percentage table?
+#' @param logml log maximum likelihood
+#' @param COUNTS COUNTS
+#' @export
+laskeMuutokset4 <- function (
+	osuus, osuusTaulu, omaFreqs, logml, COUNTS = matrix(0)
+) {
+	npops <- ifelse(is.na(dim(COUNTS)[3]), 1, dim(COUNTS)[3])
+	notEmpty <- which(osuusTaulu > 0.005)
+	muutokset <- zeros(npops)
+	empties <- !notEmpty
+
+	for (i1 in notEmpty) {
+		osuusTaulu[i1] <- osuusTaulu[i1] - osuus
+		for (i2 in c(colon(1, i1 - 1), colon(i1 + 1, npops))) {
+			osuusTaulu[i2] <- osuusTaulu[i2] + osuus
+			loggis <- computeIndLogml(omaFreqs, osuusTaulu)
+
+			# Work around Matlab OOB bug
+			if (i1 > nrow(muutokset)) {
+				muutokset <- rbind(muutokset, muutokset * 0)
+			}
+			if (i2 > ncol(muutokset)) {
+				muutokset <- cbind(muutokset, muutokset * 0)
+			}
+
+			muutokset[i1, i2] <- loggis - logml
+			osuusTaulu[i2] <- osuusTaulu[i2] - osuus
+		}
+		osuusTaulu[i1] <- osuusTaulu[i1] + osuus
+	}
+	return (muutokset)
+}
+
+# Palauttaa npops*1 taulun, jossa i:s alkio kertoo, mik� olisi
+# muutos logml:ss�, mik�li yksil� ind siirret��n koriin i.
+# diffInCounts on poistettava COUNTS:in siivusta i1 ja lis�tt�v�
+# COUNTS:in siivuun i2, mik�li muutos toteutetaan.
+#
+# Lis�ys 25.9.2007:
+# Otettu k�ytt��n globaali muuttuja LOGDIFF, johon on tallennettu muutokset
+# logml:ss� siirrett�ess� yksil�it� toisiin populaatioihin.
+laskeMuutokset <- function(ind, globalRows, data, adjprior, priorTerm) {
+	npops <- size(COUNTS, 3)
+	muutokset <- LOGDIFF[ind, ]
+
+	i1 <- PARTITION[ind]
+	i1_logml <- POP_LOGML[i1]
+	muutokset[i1] <- 0
+
+	rows <- globalRows[ind, 1]:globalRows[ind, 2]
+	diffInCounts <- computeDiffInCounts(
+		rows, size(COUNTS, 1), size(COUNTS, 2), data
+	)
+	diffInSumCounts <- sum(diffInCounts)
+
+	COUNTS[, , i1] <- COUNTS[, , i1] - diffInCounts
+	SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] - diffInSumCounts
+	new_i1_logml <- computePopulationLogml(i1, adjprior, priorTerm)
+	COUNTS[, , i1] <- COUNTS[, , i1] + diffInCounts
+	SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] + diffInSumCounts
+
+	i2 <- find(muutokset == -Inf) # Etsit��n populaatiot jotka muuttuneet viime kerran j�lkeen.
+	i2 <- setdiff(i2, i1)
+	i2_logml <- POP_LOGML[i2]
+
+	ni2 <- length(i2)
+
+	COUNTS[, , i2] <- COUNTS[, , i2] + repmat(diffInCounts, c(1, 1, ni2))
+	SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] + repmat(diffInSumCounts, c(ni2, 1))
+	new_i2_logml <- computePopulationLogml(i2, adjprior, priorTerm)
+	COUNTS[, , i2] <- COUNTS[, , i2] - repmat(diffInCounts, c(1, 1, ni2))
+	SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] - repmat(diffInSumCounts, c(ni2, 1))
+
+	muutokset[i2] <- new_i1_logml - i1_logml + new_i2_logml - i2_logml
+	LOGDIFF[ind, ] = muutokset
+	return(list(muutokset = muutokset, diffInCounts = diffInCounts))
+}
+
+laskeMuutokset2 <- function(i1, globalRows, data, adjprior, priorTerm) {
+	# % Palauttaa npops*1 taulun, jossa i:s alkio kertoo, mik� olisi
+	# % muutos logml:ss�, mik�li korin i1 kaikki yksil�t siirret��n
+	# % koriin i.
+
+	npops <- size(COUNTS, 3)
+	muutokset <- zeros(npops, 1)
+
+	i1_logml <- POP_LOGML[i1]
+
+	inds <- find(PARTITION == i1)
+	ninds <- length(inds)
+
+	if (ninds == 0) {
+		diffInCounts <- zeros(size(COUNTS, 1), size(COUNTS, 2))
+		return()
+	}
+
+	rows = list()
+	for (i in 1:ninds) {
+		ind <- inds(i)
+		lisa <- globalRows(ind, 1):globalRows(ind, 2)
+		rows <- c(rows, t(lisa))
+	}
+
+	diffInCounts <- computeDiffInCounts(
+		t(rows), size(COUNTS, 1), size(COUNTS, 2), data
+	)
+	diffInSumCounts <- sum(diffInCounts)
+
+	COUNTS[, , i1] <- COUNTS[, , i1] - diffInCounts
+	SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] - diffInSumCounts
+	new_i1_logml <- computePopulationLogml(i1, adjprior, priorTerm)
+	COUNTS[, , i1] <- COUNTS[, , i1] + diffInCounts
+	SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] + diffInSumCounts
+
+	i2 <- c(1:i1-1, i1+1:npops)
+	i2_logml <- POP_LOGML[i2]
+
+	COUNTS[, , i2] <- COUNTS[, , i2] + repmat(diffInCounts, c(1, 1, npops - 1))
+	SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] + repmat(diffInSumCounts, c(npops - 1, 1))
+	new_i2_logml <- computePopulationLogml(i2, adjprior, priorTerm)
+	COUNTS[, , i2] <- COUNTS[, , i2] - repmat(diffInCounts, c(1, 1, npops - 1))
+	SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] - repmat(diffInSumCounts, c(npops - 1, 1))
+
+	muutokset[i2] <- new_i1_logml - i1_logml + new_i2_logml - i2_logml
+	return(list(muutokset = muutokset, diffInCounts = diffInCounts))
+}
+
+
+laskeMuutokset3 <- function(T2, inds2, globalRows, data, adjprior, priorTerm, i1) {
+	# Palauttaa length(unique(T2))*npops taulun, jossa (i,j):s alkio
+	# kertoo, mik� olisi muutos logml:ss�, jos populaation i1 osapopulaatio
+	# inds2(find(T2==i)) siirret��n koriin j.
+
+	npops <- size(COUNTS, 3)
+	npops2 <- length(unique(T2))
+	muutokset <- zeros(npops2, npops)
+
+	i1_logml = POP_LOGML[i1]
+	for (pop2 in 1:npops2) {
+		inds <- inds2[find(T2==pop2)]
+		ninds <- length(inds);
+		if (ninds > 0) {
+			rows <- list()
+			for (i in 1:ninds) {
+				ind <- inds[i]
+				lisa <- globalRows[ind, 1]:globalRows[ind, 2]
+				rows <- c(rows, t(lisa))
+			}
+			diffInCounts <- computeDiffInCounts(
+				t(rows), size(COUNTS, 1), size(COUNTS, 2), data
+			)
+			diffInSumCounts <- sum(diffInCounts)
+
+			COUNTS[, , i1] <- COUNTS[, , i1] - diffInCounts
+			SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] - diffInSumCounts
+			new_i1_logml <- computePopulationLogml(i1, adjprior, priorTerm)
+			COUNTS[, , i1] <- COUNTS[, , i1] + diffInCounts
+			SUMCOUNTS[i1, ] <- SUMCOUNTS[i1, ] + diffInSumCounts
+
+			i2 <- c(1:i1-1, i1+1:npops)
+			i2_logml <- t(POP_LOGML[i2])
+
+			COUNTS[, , i2] <- COUNTS[, , i2] + repmat(diffInCounts, c(1, 1, npops - 1))
+			SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] + repmat(diffInSumCounts, c(npops - 1, 1))
+			new_i2_logml <- t(computePopulationLogml(i2, adjprior, priorTerm))
+			COUNTS[, , i2] <- COUNTS[, , i2] - repmat(diffInCounts, c(1, 1, npops - 1))
+			SUMCOUNTS[i2, ] <- SUMCOUNTS[i2, ] - repmat(diffInSumCounts, c(npops - 1, 1))
+
+			muutokset[pop2, i2] <- new_i1_logml - i1_logml + new_i2_logml - i2_logml
+		}
+	}
+	return(muutokset)
+}
+
+laskeMuutokset5 <- function(inds, globalRows, data, adjprior, priorTerm, i1, i2) {
+	# Palauttaa length(inds)*1 taulun, jossa i:s alkio kertoo, mik� olisi
+	# muutos logml:ss�, mik�li yksil� i vaihtaisi koria i1:n ja i2:n v�lill�.
+
+	ninds <- length(inds)
+	muutokset <- zeros(ninds, 1)
+
+	i1_logml <- POP_LOGML[i1]
+	i2_logml <- POP_LOGML[i2]
+
+	for (i in 1:ninds) {
+		ind <- inds[i]
+		if (PARTITION[ind] == i1) {
+			pop1 <- i1  #mist�
+			pop2 <- i2  #mihin
+		} else {
+			pop1 <- i2
+			pop2 <- i1
+		}
+		rows <- globalRows[ind, 1]:globalRows[ind, 2]
+		diffInCounts <- computeDiffInCounts(
+			rows, size(COUNTS, 1), size(COUNTS, 2), data
+		)
+		diffInSumCounts <- sum(diffInCounts)
+
+
+
+		COUNTS[, , pop1] <- COUNTS[, , pop1] - diffInCounts
+		SUMCOUNTS[pop1, ] <- SUMCOUNTS[pop1, ] - diffInSumCounts
+		COUNTS[, , pop2] <- COUNTS[, , pop2] + diffInCounts
+		SUMCOUNTS[pop2, ] <- SUMCOUNTS[pop2, ] + diffInSumCounts
+
+		new_logmls <- computePopulationLogml(c(i1, i2), adjprior, priorTerm)
+		muutokset[i] <- sum(new_logmls)
+
+		COUNTS[, , pop1] <- COUNTS[, , pop1] + diffInCounts
+		SUMCOUNTS[pop1, ] <- SUMCOUNTS[pop1, ] + diffInSumCounts
+		COUNTS[, , pop2] <- COUNTS[, , pop2] - diffInCounts
+		SUMCOUNTS[pop2, ] <- SUMCOUNTS[pop2, ] - diffInSumCounts
+	}
+
+	muutokset <- muutokset - i1_logml - i2_logml
+	return(muutokset)
+}
\ No newline at end of file
diff --git a/R/laskeMuutokset4.R b/R/laskeMuutokset4.R
deleted file mode 100644
index 56bcef3..0000000
--- a/R/laskeMuutokset4.R
+++ /dev/null
@@ -1,39 +0,0 @@
-#' @title Calculate changes?
-#' @description Palauttaa npops*npops taulun, jonka alkio (i,j) kertoo, mik?on
-#' muutos logml:ss? mikäli populaatiosta i siirretään osuuden verran
-#' todennäköisyysmassaa populaatioon j. Mikäli populaatiossa i ei ole mitään 
-#' siirrettävää, on vastaavassa kohdassa rivi nollia.
-#' @param osuus Percentages?
-#' @param omaFreqs own Freqs?
-#' @param osuusTaulu Percentage table?
-#' @param logml log maximum likelihood
-#' @param COUNTS COUNTS
-#' @export
-laskeMuutokset4 <- function (osuus, osuusTaulu, omaFreqs, logml,
-                             COUNTS = matrix(0)) {
-    npops <- ifelse(is.na(dim(COUNTS)[3]), 1, dim(COUNTS)[3])
-    notEmpty <- which(osuusTaulu > 0.005)
-    muutokset <- zeros(npops)
-    empties <- !notEmpty
-
-    for (i1 in notEmpty) {
-        osuusTaulu[i1] <- osuusTaulu[i1] - osuus
-        for (i2 in c(colon(1, i1 - 1), colon(i1 + 1, npops))) {
-            osuusTaulu[i2] <- osuusTaulu[i2] + osuus
-            loggis <- computeIndLogml(omaFreqs, osuusTaulu)
-            
-            # Work around Matlab OOB bug
-            if (i1 > nrow(muutokset)) {
-                muutokset <- rbind(muutokset, muutokset * 0)
-            }
-            if (i2 > ncol(muutokset)) {
-                muutokset <- cbind(muutokset, muutokset * 0)
-            }
-
-            muutokset[i1, i2] <- loggis - logml
-            osuusTaulu[i2] <- osuusTaulu[i2] - osuus
-        } 
-        osuusTaulu[i1] <- osuusTaulu[i1] + osuus
-    }
-    return (muutokset)
-}
\ No newline at end of file
diff --git a/R/laskeOsaDist.R b/R/laskeOsaDist.R
new file mode 100644
index 0000000..1ea9495
--- /dev/null
+++ b/R/laskeOsaDist.R
@@ -0,0 +1,19 @@
+laskeOsaDist <- function(inds2, dist, ninds) {
+	# % Muodostaa dist vektorista osavektorin, joka sis�lt�� yksil�iden inds2
+	# % v�liset et�isyydet. ninds=kaikkien yksil�iden lukum��r�.
+
+	ninds2 <- length(inds2)
+	apu <- zeros(nchoosek(ninds2, 2), 2)
+	rivi <- 1
+	for (i in 1:ninds2-1) {
+		for (j in i+1:ninds2) {
+			apu[rivi, 1] <- inds2[i]
+			apu[rivi, 2] <- inds2[j]
+			rivi <- rivi + 1
+		}
+	}
+	apu <- (apu[, 1]-1) * ninds - apu[, 1] / 2 *
+		(apu[, 1]-1) + (apu[, 2] - apu[, 1])
+	dist2 <- dist(apu)
+	return(dist2)
+}
\ No newline at end of file
diff --git a/R/matlab2r.R b/R/matlab2r.R
new file mode 100644
index 0000000..e041634
--- /dev/null
+++ b/R/matlab2r.R
@@ -0,0 +1,49 @@
+#' @title Convert Matlab function to R
+#' @description Performs basic syntax conversion from Matlab to R
+#' @param filename name of the file
+#' @param saveOutput if `TRUE`, `filename` is overwritten. Defaults to `FALSE`
+#' @return text converted to R, printed to screen or replacing input file
+#' @author Waldir Leoncio
+#' @export
+matlab2r <- function(filename, saveOutput = FALSE) {
+	# Verification
+	if (!file.exists(filename)) stop("File not found")
+	# Reading file into R
+	txt <- readLines(filename)
+	# Replacing text
+	txt <- gsub(
+		pattern     = "function (.+)\\s+=\\s*(.+)\\((.+)\\)",
+		replacement = "\\2 <- function(\\3) { return(\\1)",
+		x           = txt
+	)
+	# txt <- gsub("\\%\\s*(\\w+)", "# \\1", txt)
+	txt <- gsub(";", "", txt)
+	txt <- gsub("for (.+)=(.+)", "for (\\1 in \\2) {", txt)
+	txt <- gsub("end", "}", txt)
+	txt <- gsub("(.),(\\S)", "\\1, \\2", txt)
+	# TODO: replace forms like (:,:) with [, ]
+	# TODO: add argument to skip some of these rules
+	txt <- gsub("if (.+)", "if (\\1) {", txt) # FIXME: paste comments after {
+	txt <- gsub("else$", "} else {", txt)
+	txt <- gsub("elseif", "} else if", txt)
+	txt <- gsub("\\(~", "(!", txt)
+	txt <- gsub("while (.+)", "while \\1 {", txt)
+	## Math operators
+	txt <- gsub("(\\S)\\+(\\S)", "\\1 + \\2", txt)
+	txt <- gsub("(\\S)\\-(\\S)", "\\1 - \\2", txt)
+	txt <- gsub("(\\S)\\*(\\S)", "\\1 * \\2", txt)
+	# Returning converted code
+	if (!saveOutput) {
+		return(cat(txt, sep="\n"))
+	} else {
+		return(
+			write.table(
+				x         = txt,
+				file      = filename,
+				quote     = FALSE,
+				row.names = FALSE,
+				col.names = FALSE
+			)
+		)
+	}
+}
diff --git a/R/min.R b/R/min.R
deleted file mode 100644
index 2d8d617..0000000
--- a/R/min.R
+++ /dev/null
@@ -1,16 +0,0 @@
-#' @title Minimum (MATLAB version)
-#' @description Finds the minimum value for each column of a matrix, potentially returning the indices instead
-#' @param X matrix
-#' @param indices return indices?
-#' @return Either a list or a vector
-#' @author Waldir Leoncio
-#' @export
-min_MATLAB <- function(X, indices = TRUE) {
-	mins <- apply(X, 2, min)
-	idx  <- sapply(seq_len(ncol(X)), function(x) match(mins[x], X[, x]))
-	if (indices) {
-		return(list(mins = mins, idx = idx))
-	} else {
-		return(mins)
-	}
-}
\ No newline at end of file
diff --git a/R/min_max_MATLAB.R b/R/min_max_MATLAB.R
new file mode 100644
index 0000000..7ad9d0e
--- /dev/null
+++ b/R/min_max_MATLAB.R
@@ -0,0 +1,31 @@
+#' @title Minimum (MATLAB version)
+#' @description Finds the minimum value for each column of a matrix, potentially returning the indices instead
+#' @param X matrix
+#' @param indices return indices?
+#' @return Either a list or a vector
+#' @author Waldir Leoncio
+min_MATLAB <- function(X, indices = TRUE) {
+	mins <- apply(X, 2, min)
+	idx  <- sapply(seq_len(ncol(X)), function(x) match(mins[x], X[, x]))
+	if (indices) {
+		return(list(mins = mins, idx = idx))
+	} else {
+		return(mins)
+	}
+}
+
+#' @title Maximum (MATLAB version)
+#' @description Finds the minimum value for each column of a matrix, potentially returning the indices instead
+#' @param X matrix
+#' @param indices return indices?
+#' @return Either a list or a vector
+#' @author Waldir Leoncio
+max_MATLAB <- function(X, indices = TRUE) {
+	maxs <- apply(X, 2, max)
+	idx  <- sapply(seq_len(ncol(X)), function(x) match(maxs[x], X[, x]))
+	if (indices) {
+		return(list(maxs = maxs, idx = idx))
+	} else {
+		return(maxs)
+	}
+}
\ No newline at end of file
diff --git a/R/nargin.R b/R/nargin.R
new file mode 100644
index 0000000..6ff20cc
--- /dev/null
+++ b/R/nargin.R
@@ -0,0 +1,10 @@
+#' @title Number of function input arguments
+#' @description Returns the number of arguments passed to the parent function
+#' @return An integer
+#' @author Waldir Leoncio
+#' @note This function only makes sense inside another function
+#' @references https://stackoverflow.com/q/64422780/1169233
+nargin <- function() {
+  if(sys.nframe() < 2) stop("must be called from inside a function")
+  length(as.list(sys.call(-1))) - 1
+}
diff --git a/R/poistaTyhjatPopulaatiot.R b/R/poistaTyhjatPopulaatiot.R
new file mode 100644
index 0000000..b811586
--- /dev/null
+++ b/R/poistaTyhjatPopulaatiot.R
@@ -0,0 +1,15 @@
+poistaTyhjatPopulaatiot <- function(npops) {
+	# % Poistaa tyhjentyneet populaatiot COUNTS:ista ja
+	# % SUMCOUNTS:ista. P�ivitt�� npops:in ja PARTITION:in.
+	notEmpty <- find(any(SUMCOUNTS, 2))
+	COUNTS <<- COUNTS[, , notEmpty]
+	SUMCOUNTS <<- SUMCOUNTS[notEmpty, ]
+	LOGDIFF <<- LOGDIFF[, notEmpty]
+
+	for (n in 1:length(notEmpty)) {
+		apu <- find(PARTITION == notEmpty(n))
+		PARTITION(apu) <<- n
+	}
+	npops <- length(notEmpty)
+	return(npops)
+}
\ No newline at end of file
diff --git a/R/returnInOrder.R b/R/returnInOrder.R
new file mode 100644
index 0000000..c6a48d8
--- /dev/null
+++ b/R/returnInOrder.R
@@ -0,0 +1,26 @@
+returnInOrder <- function(inds, pop, globalRows, data, adjprior, priorTerm) {
+	# % Palauttaa yksil�t j�rjestyksess� siten, ett� ensimm�isen� on
+	# % se, jonka poistaminen populaatiosta pop nostaisi logml:n
+	# % arvoa eniten.
+
+	ninds <- length(inds)
+	apuTaulu <- c(inds, zeros(ninds, 1))
+
+	for (i in 1:ninds) {
+		ind <- inds[i]
+		rows <- globalRows[i, 1]:globalRows[i, 2]
+		diffInCounts <- computeDiffInCounts(
+			rows, size[COUNTS, 1], size[COUNTS, 2], data
+		)
+		diffInSumCounts <- sum(diffInCounts)
+
+		COUNTS[ , ,pop] <- COUNTS[ , ,pop] - diffInCounts
+		SUMCOUNTS[pop, ] <- SUMCOUNTS[pop, ] - diffInSumCounts
+		apuTaulu[i, 2] <- computePopulationLogml(pop, adjprior, priorTerm)
+		COUNTS[ , ,pop] <- COUNTS[ , ,pop] + diffInCounts
+		SUMCOUNTS[pop, ] <- SUMCOUNTS[pop, ] + diffInSumCounts
+	}
+	apuTaulu <- sortrows(apuTaulu, 2)
+	inds <- apuTaulu[ninds:1, 1]
+	return(inds)
+}
\ No newline at end of file
diff --git a/R/setdiff_MATLAB.R b/R/setdiff_MATLAB.R
new file mode 100644
index 0000000..3c2324b
--- /dev/null
+++ b/R/setdiff_MATLAB.R
@@ -0,0 +1,16 @@
+#' @title Set differences of two arrays
+#' @description Loosely replicates the behavior of the homonym Matlab function
+#' @param A first array
+#' @param B second array
+#' @param legacy if `TRUE`, preserves the behavior of the setdiff function from MATLAB R2012b and prior releases. (currently not supported)
+#' @author Waldir Leoncio
+setdiff_MATLAB <- function(A, B, legacy = FALSE) {
+	if (legacy) message("legacy=TRUE not supported. Ignoring.")
+	if (is(A, "numeric") & is(B, "numeric")) {
+		values <- sort(unique(A[is.na(match(A, B))]))
+	} else if (is(A, "data.frame") & is(B, "data.frame")) {
+		stop("Not implemented for data frames")
+	}
+	# TODO: add support for indices (if necessary)
+	return(values)
+}
\ No newline at end of file
diff --git a/R/updateGlobalVariables.R b/R/updateGlobalVariables.R
new file mode 100644
index 0000000..4b17469
--- /dev/null
+++ b/R/updateGlobalVariables.R
@@ -0,0 +1,64 @@
+updateGlobalVariables <- function(ind, i2, diffInCounts, adjprior, priorTerm) {
+	# % Suorittaa globaalien muuttujien muutokset, kun yksil� ind
+	# % on siirret��n koriin i2.
+
+	i1 <- PARTITION(ind)
+	PARTITION(ind) <<- i2
+
+	COUNTS[, , i1] <<- COUNTS[, , i1] - diffInCounts
+	COUNTS[, , i2] <<- COUNTS[, , i2] + diffInCounts
+	SUMCOUNTS[i1, ] <<- SUMCOUNTS[i1, ] - sum[diffInCounts]
+	SUMCOUNTS[i2, ] <<- SUMCOUNTS[i2, ] + sum[diffInCounts]
+
+	POP_LOGML[c(i1, i2)] <<- computePopulationLogml(
+		c(i1, i2), adjprior, priorTerm
+	)
+
+	LOGDIFF[, c(i1, i2)] <<- -Inf
+	inx <- c(find(PARTITION == i1), find(PARTITION==i2))
+	LOGDIFF[inx, ] <<- -Inf
+}
+
+updateGlobalVariables2 <- function(i1, i2, diffInCounts, adjprior, priorTerm) {
+	# % Suorittaa globaalien muuttujien muutokset, kun kaikki
+	# % korissa i1 olevat yksil�t siirret��n koriin i2.
+
+	inds <- find(PARTITION == i1)
+	PARTITION(inds) <<- i2
+
+	COUNTS[, , i1] <<- COUNTS[, , i1] - diffInCounts
+	COUNTS[, , i2] <<- COUNTS[, , i2] + diffInCounts
+	SUMCOUNTS[i1, ] <<- SUMCOUNTS[i1, ] - sum[diffInCounts]
+	SUMCOUNTS[i2, ] <<- SUMCOUNTS[i2, ] + sum[diffInCounts]
+
+	POP_LOGML[i1] <- 0
+	POP_LOGML[i2] <- computePopulationLogml(i2, adjprior, priorTerm)
+
+	LOGDIFF[, c(i1, i2)] <- -Inf
+	inx <- c(find(PARTITION == i1), find(PARTITION == i2))
+	LOGDIFF[inx, ] <- -Inf
+}
+
+updateGlobalVariables3 <- function(
+	muuttuvat, diffInCounts, adjprior, priorTerm, i2
+) {
+	# % Suorittaa globaalien muuttujien p�ivitykset, kun yksil�t 'muuttuvat'
+	# % siirret��n koriin i2. Ennen siirtoa yksil�iden on kuuluttava samaan
+	# % koriin.
+
+	i1 <- PARTITION[muuttuvat(1)]
+	PARTITION[muuttuvat] <<- i2
+
+	COUNTS[, , i1] <<- COUNTS[, , i1] - diffInCounts
+	COUNTS[, , i2] <<- COUNTS[, , i2] + diffInCounts
+	SUMCOUNTS[i1, ] <<- SUMCOUNTS[i1, ] - sum[diffInCounts]
+	SUMCOUNTS[i2, ] <<- SUMCOUNTS[i2, ] + sum[diffInCounts]
+
+	POP_LOGML[c(i1, i2)] <<- computePopulationLogml(
+		c(i1, i2), adjprior, priorTerm
+	)
+
+	LOGDIFF[, c(i1, i2)] <<- -Inf
+	inx <- c(find(PARTITION == i1), find(PARTITION == i2))
+	LOGDIFF[inx, ] <<- -Inf
+}
diff --git a/R/writeMixtureInfo.R b/R/writeMixtureInfo.R
index ca8efea..ec5120b 100644
--- a/R/writeMixtureInfo.R
+++ b/R/writeMixtureInfo.R
@@ -10,16 +10,10 @@
 #' @param partitionSummary partitionSummary
 #' @param popnames popnames
 #' @param fixedK fixedK
-#' @param PARTITION PARTITION
-#' @param COUNTS COUNTS
-#' @param SUMCOUNTS SUMCOUNTS
-#' @param LOGDIFF LOGDIFF
 #' @export
 writeMixtureInfo <- function(
-	logml, rowsFromInd, data, adjprior, priorTerm, outPutFile, inputFile, partitionSummary, popnames, fixedK, PARTITION, COUNTS, SUMCOUNTS,
-	LOGDIFF
+	logml, rowsFromInd, data, adjprior, priorTerm, outPutFile, inputFile, partitionSummary, popnames, fixedK
 ) {
-
 	changesInLogml <- list()
 	ninds <- size(data, 1) / rowsFromInd
 	npops <- size(COUNTS, 3)
@@ -30,7 +24,6 @@ writeMixtureInfo <- function(
 		fid <- load(outPutFile)
 	} else {
 		fid <- -1
-		message('Diverting output to baps4_output.baps')
 		# TODO: replace sink with option that will record input and output
 		sink('baps4_output.baps', split=TRUE) # save in text anyway.
 	}
diff --git a/data/ExamplesDataFormatting/Example MLST DNA sequence data in concatenated Excel format.xls b/inst/ext/ExamplesDataFormatting/Example MLST DNA sequence data in concatenated Excel format.xls
similarity index 100%
rename from data/ExamplesDataFormatting/Example MLST DNA sequence data in concatenated Excel format.xls
rename to inst/ext/ExamplesDataFormatting/Example MLST DNA sequence data in concatenated Excel format.xls
diff --git a/data/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt b/inst/ext/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt
rename to inst/ext/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt
diff --git a/data/ExamplesDataFormatting/Example coordinates for the spatial clustering of DNA sequences.txt b/inst/ext/ExamplesDataFormatting/Example coordinates for the spatial clustering of DNA sequences.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example coordinates for the spatial clustering of DNA sequences.txt
rename to inst/ext/ExamplesDataFormatting/Example coordinates for the spatial clustering of DNA sequences.txt
diff --git a/data/ExamplesDataFormatting/Example coordinates for the spatial clustering.txt b/inst/ext/ExamplesDataFormatting/Example coordinates for the spatial clustering.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example coordinates for the spatial clustering.txt
rename to inst/ext/ExamplesDataFormatting/Example coordinates for the spatial clustering.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for clustering of diploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of diploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for clustering of diploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of diploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for clustering of haploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of haploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for clustering of haploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of haploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for clustering of tetraploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of tetraploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for clustering of tetraploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for clustering of tetraploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of diploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of diploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of diploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of diploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of haploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of haploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of haploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of haploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of tetraploid individuals.txt b/inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of tetraploid individuals.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of tetraploid individuals.txt
rename to inst/ext/ExamplesDataFormatting/Example data in BAPS format for group-wise clustering of tetraploid individuals.txt
diff --git a/data/ExamplesDataFormatting/Example data in FASTA format for clustering of haploid individuals.fasta b/inst/ext/ExamplesDataFormatting/Example data in FASTA format for clustering of haploid individuals.fasta
similarity index 100%
rename from data/ExamplesDataFormatting/Example data in FASTA format for clustering of haploid individuals.fasta
rename to inst/ext/ExamplesDataFormatting/Example data in FASTA format for clustering of haploid individuals.fasta
diff --git a/data/ExamplesDataFormatting/Example of a BAPS formatted diploid sequence file for clustering with linked loci.txt b/inst/ext/ExamplesDataFormatting/Example of a BAPS formatted diploid sequence file for clustering with linked loci.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a BAPS formatted diploid sequence file for clustering with linked loci.txt
rename to inst/ext/ExamplesDataFormatting/Example of a BAPS formatted diploid sequence file for clustering with linked loci.txt
diff --git a/data/ExamplesDataFormatting/Example of a BAPS formatted haploid sequence file for clustering with linked loci.txt b/inst/ext/ExamplesDataFormatting/Example of a BAPS formatted haploid sequence file for clustering with linked loci.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a BAPS formatted haploid sequence file for clustering with linked loci.txt
rename to inst/ext/ExamplesDataFormatting/Example of a BAPS formatted haploid sequence file for clustering with linked loci.txt
diff --git a/data/ExamplesDataFormatting/Example of a BAPS formatted tetraploid sequence file for clustering with linked loci.txt b/inst/ext/ExamplesDataFormatting/Example of a BAPS formatted tetraploid sequence file for clustering with linked loci.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a BAPS formatted tetraploid sequence file for clustering with linked loci.txt
rename to inst/ext/ExamplesDataFormatting/Example of a BAPS formatted tetraploid sequence file for clustering with linked loci.txt
diff --git a/data/ExamplesDataFormatting/Example of a fasta formatted sequence file for gene recA.txt b/inst/ext/ExamplesDataFormatting/Example of a fasta formatted sequence file for gene recA.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a fasta formatted sequence file for gene recA.txt
rename to inst/ext/ExamplesDataFormatting/Example of a fasta formatted sequence file for gene recA.txt
diff --git a/data/ExamplesDataFormatting/Example of a file specifying gene boundaries for a concatenated sequence in BAPS format.txt b/inst/ext/ExamplesDataFormatting/Example of a file specifying gene boundaries for a concatenated sequence in BAPS format.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a file specifying gene boundaries for a concatenated sequence in BAPS format.txt
rename to inst/ext/ExamplesDataFormatting/Example of a file specifying gene boundaries for a concatenated sequence in BAPS format.txt
diff --git a/data/ExamplesDataFormatting/Example of a partition file for admixture analysis based on user-specified populations.txt b/inst/ext/ExamplesDataFormatting/Example of a partition file for admixture analysis based on user-specified populations.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of a partition file for admixture analysis based on user-specified populations.txt
rename to inst/ext/ExamplesDataFormatting/Example of a partition file for admixture analysis based on user-specified populations.txt
diff --git a/data/ExamplesDataFormatting/Example of an MLST profile file for 6 genes.txt b/inst/ext/ExamplesDataFormatting/Example of an MLST profile file for 6 genes.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of an MLST profile file for 6 genes.txt
rename to inst/ext/ExamplesDataFormatting/Example of an MLST profile file for 6 genes.txt
diff --git a/data/ExamplesDataFormatting/Example of hierBAPS input in FASTA format.fa b/inst/ext/ExamplesDataFormatting/Example of hierBAPS input in FASTA format.fa
similarity index 100%
rename from data/ExamplesDataFormatting/Example of hierBAPS input in FASTA format.fa
rename to inst/ext/ExamplesDataFormatting/Example of hierBAPS input in FASTA format.fa
diff --git a/data/ExamplesDataFormatting/Example of hierBAPS input in XLS format.xls b/inst/ext/ExamplesDataFormatting/Example of hierBAPS input in XLS format.xls
similarity index 100%
rename from data/ExamplesDataFormatting/Example of hierBAPS input in XLS format.xls
rename to inst/ext/ExamplesDataFormatting/Example of hierBAPS input in XLS format.xls
diff --git a/data/ExamplesDataFormatting/Example of sample population index file to be used with BAPS formatted data.txt b/inst/ext/ExamplesDataFormatting/Example of sample population index file to be used with BAPS formatted data.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of sample population index file to be used with BAPS formatted data.txt
rename to inst/ext/ExamplesDataFormatting/Example of sample population index file to be used with BAPS formatted data.txt
diff --git a/data/ExamplesDataFormatting/Example of sample population names file to be used with BAPS formatted data.txt b/inst/ext/ExamplesDataFormatting/Example of sample population names file to be used with BAPS formatted data.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example of sample population names file to be used with BAPS formatted data.txt
rename to inst/ext/ExamplesDataFormatting/Example of sample population names file to be used with BAPS formatted data.txt
diff --git a/data/ExamplesDataFormatting/Example pre-grouped sample data in GENEPOP format for Trained clustering.txt b/inst/ext/ExamplesDataFormatting/Example pre-grouped sample data in GENEPOP format for Trained clustering.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example pre-grouped sample data in GENEPOP format for Trained clustering.txt
rename to inst/ext/ExamplesDataFormatting/Example pre-grouped sample data in GENEPOP format for Trained clustering.txt
diff --git a/data/ExamplesDataFormatting/Example sample data in GENEPOP format for Trained clustering.txt b/inst/ext/ExamplesDataFormatting/Example sample data in GENEPOP format for Trained clustering.txt
similarity index 100%
rename from data/ExamplesDataFormatting/Example sample data in GENEPOP format for Trained clustering.txt
rename to inst/ext/ExamplesDataFormatting/Example sample data in GENEPOP format for Trained clustering.txt
diff --git a/data/ExamplesDataFormatting/Example test data in XLS format for Trained clustering.xls b/inst/ext/ExamplesDataFormatting/Example test data in XLS format for Trained clustering.xls
similarity index 100%
rename from data/ExamplesDataFormatting/Example test data in XLS format for Trained clustering.xls
rename to inst/ext/ExamplesDataFormatting/Example test data in XLS format for Trained clustering.xls
diff --git a/data/ExamplesDataFormatting/Example training data in XLS format for Trained clustering.xls b/inst/ext/ExamplesDataFormatting/Example training data in XLS format for Trained clustering.xls
similarity index 100%
rename from data/ExamplesDataFormatting/Example training data in XLS format for Trained clustering.xls
rename to inst/ext/ExamplesDataFormatting/Example training data in XLS format for Trained clustering.xls
diff --git a/data/ExamplesDataFormatting/Notes.md b/inst/ext/ExamplesDataFormatting/Notes.md
similarity index 100%
rename from data/ExamplesDataFormatting/Notes.md
rename to inst/ext/ExamplesDataFormatting/Notes.md
diff --git a/man/admixture_initialization.Rd b/man/admixture_initialization.Rd
new file mode 100644
index 0000000..c10e4f8
--- /dev/null
+++ b/man/admixture_initialization.Rd
@@ -0,0 +1,18 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/admixture_initialization.R
+\name{admixture_initialization}
+\alias{admixture_initialization}
+\title{Seuraavat kolme funktiota liittyvat alkupartition muodostamiseen.}
+\usage{
+admixture_initialization(data_matrix, nclusters, Z)
+}
+\arguments{
+\item{data_matrix}{data_matrix}
+
+\item{nclusters}{ncluster}
+
+\item{Z}{Z}
+}
+\description{
+Seuraavat kolme funktiota liittyvat alkupartition muodostamiseen.
+}
diff --git a/man/laskeMuutokset4.Rd b/man/laskeMuutokset4.Rd
index 7c16a19..e3382de 100644
--- a/man/laskeMuutokset4.Rd
+++ b/man/laskeMuutokset4.Rd
@@ -1,8 +1,8 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/laskeMuutokset4.R
+% Please edit documentation in R/laskeMuutokset12345.R
 \name{laskeMuutokset4}
 \alias{laskeMuutokset4}
-\title{Calculate changes?}
+\title{Calculate changes (?)}
 \usage{
 laskeMuutokset4(osuus, osuusTaulu, omaFreqs, logml, COUNTS = matrix(0))
 }
@@ -20,6 +20,6 @@ laskeMuutokset4(osuus, osuusTaulu, omaFreqs, logml, COUNTS = matrix(0))
 \description{
 Palauttaa npops*npops taulun, jonka alkio (i,j) kertoo, mik?on
 muutos logml:ss? mikäli populaatiosta i siirretään osuuden verran
-todennäköisyysmassaa populaatioon j. Mikäli populaatiossa i ei ole mitään 
+todennäköisyysmassaa populaatioon j. Mikäli populaatiossa i ei ole mitään
 siirrettävää, on vastaavassa kohdassa rivi nollia.
 }
diff --git a/man/max_MATLAB.Rd b/man/max_MATLAB.Rd
new file mode 100644
index 0000000..d7fbdf7
--- /dev/null
+++ b/man/max_MATLAB.Rd
@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/min_max_MATLAB.R
+\name{max_MATLAB}
+\alias{max_MATLAB}
+\title{Maximum (MATLAB version)}
+\usage{
+max_MATLAB(X, indices = TRUE)
+}
+\arguments{
+\item{X}{matrix}
+
+\item{indices}{return indices?}
+}
+\value{
+Either a list or a vector
+}
+\description{
+Finds the minimum value for each column of a matrix, potentially returning the indices instead
+}
+\author{
+Waldir Leoncio
+}
diff --git a/man/min_MATLAB.Rd b/man/min_MATLAB.Rd
index 9376fed..9825e90 100644
--- a/man/min_MATLAB.Rd
+++ b/man/min_MATLAB.Rd
@@ -1,5 +1,5 @@
 % Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/min.R
+% Please edit documentation in R/min_max_MATLAB.R
 \name{min_MATLAB}
 \alias{min_MATLAB}
 \title{Minimum (MATLAB version)}
diff --git a/man/nargin.Rd b/man/nargin.Rd
new file mode 100644
index 0000000..a7922a6
--- /dev/null
+++ b/man/nargin.Rd
@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/nargin.R
+\name{nargin}
+\alias{nargin}
+\title{Number of function input arguments}
+\usage{
+nargin()
+}
+\value{
+An integer
+}
+\description{
+Returns the number of arguments passed to the parent function
+}
+\note{
+This function only makes sense inside another function
+}
+\references{
+https://stackoverflow.com/q/64422780/1169233
+}
+\author{
+Waldir Leoncio
+}
diff --git a/man/setdiff_MATLAB.Rd b/man/setdiff_MATLAB.Rd
new file mode 100644
index 0000000..dcc6c00
--- /dev/null
+++ b/man/setdiff_MATLAB.Rd
@@ -0,0 +1,21 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/setdiff_MATLAB.R
+\name{setdiff_MATLAB}
+\alias{setdiff_MATLAB}
+\title{Set differences of two arrays}
+\usage{
+setdiff_MATLAB(A, B, legacy = FALSE)
+}
+\arguments{
+\item{A}{first array}
+
+\item{B}{second array}
+
+\item{legacy}{if `TRUE`, preserves the behavior of the setdiff function from MATLAB R2012b and prior releases. (currently not supported)}
+}
+\description{
+Loosely replicates the behavior of the homonym Matlab function
+}
+\author{
+Waldir Leoncio
+}
diff --git a/man/writeMixtureInfo.Rd b/man/writeMixtureInfo.Rd
index e973db9..f30bde0 100644
--- a/man/writeMixtureInfo.Rd
+++ b/man/writeMixtureInfo.Rd
@@ -14,11 +14,7 @@ writeMixtureInfo(
   inputFile,
   partitionSummary,
   popnames,
-  fixedK,
-  PARTITION,
-  COUNTS,
-  SUMCOUNTS,
-  LOGDIFF
+  fixedK
 )
 }
 \arguments{
@@ -41,14 +37,6 @@ writeMixtureInfo(
 \item{popnames}{popnames}
 
 \item{fixedK}{fixedK}
-
-\item{PARTITION}{PARTITION}
-
-\item{COUNTS}{COUNTS}
-
-\item{SUMCOUNTS}{SUMCOUNTS}
-
-\item{LOGDIFF}{LOGDIFF}
 }
 \description{
 Writes information about the mixture
diff --git a/tests/testthat/test-convertedBaseFunctions.R b/tests/testthat/test-convertedBaseFunctions.R
index bfc3fe8..52d14f8 100644
--- a/tests/testthat/test-convertedBaseFunctions.R
+++ b/tests/testthat/test-convertedBaseFunctions.R
@@ -158,18 +158,18 @@ test_that("find works as expected", {
 })
 
 test_that("sortrows works as expected", {
-	 mx <- matrix(c(3, 2, 2, 1, 1, 10, 0, pi), 4)
-	 expect_equal(sortrows(mx), matrix(c(1, 2, 2, 3, pi, 10, 0, 1), 4))
-	 expect_equal(sortrows(mx, 2), matrix(c(2, 3, 1, 2, 0, 1, pi, 10), 4))
-	 expect_equal(sortrows(mx, 1:2), mx[order(mx[, 1], mx[, 2]), ])
+	mx <- matrix(c(3, 2, 2, 1, 1, 10, 0, pi), 4)
+	expect_equal(sortrows(mx), matrix(c(1, 2, 2, 3, pi, 10, 0, 1), 4))
+	expect_equal(sortrows(mx, 2), matrix(c(2, 3, 1, 2, 0, 1, pi, 10), 4))
+	expect_equal(sortrows(mx, 1:2), mx[order(mx[, 1], mx[, 2]), ])
 })
 
 test_that("cell works as expected", {
-	expect_equal(cell(0), array(dim = c(0, 0)))
-	expect_equal(cell(1), array(dim = c(1, 1)))
-	expect_equal(cell(2), array(dim = c(2, 2)))
-	expect_equal(cell(3, 4), array(dim = c(3, 4)))
-	expect_equal(cell(5, 7, 6), array(dim = c(5, 7, 6)))
+	expect_equivalent(cell(0), array(0, dim = c(0, 0)))
+	expect_equivalent(cell(1), array(0, dim = c(1, 1)))
+	expect_equivalent(cell(2), array(0, dim = c(2, 2)))
+	expect_equivalent(cell(3, 4), array(0, dim = c(3, 4)))
+	expect_equivalent(cell(5, 7, 6), array(0, dim = c(5, 7, 6)))
 })
 
 test_that("blanks works as expected", {
@@ -201,4 +201,44 @@ test_that("isspace works as expected", {
 	X <- '\t a b\tcde f'
 	expect_identical(isspace(chr), c(0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0))
 	expect_identical(isspace(X), c(1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0))
+})
+
+test_that("nargin works correctly", {
+	addme <- function(a, b) {
+		if (nargin() == 2) {
+			c <- a + b
+		} else if (nargin() == 1) {
+			c <- a + a
+		} else {
+			c <- 0
+		}
+		return(c)
+	}
+	expect_equal(addme(13, 42), 55)
+	expect_equal(addme(13), 26)
+	expect_equal(addme(), 0)
+})
+
+test_that("setdiff works as expected", {
+	A <- c(3, 6, 2, 1, 5, 1, 1)
+	B <- c(2, 4, 6)
+	C <- c(1, 3, 5)
+	# expect_equal(setdiff_MATLAB(A, B), C) # TODO: export setdiff_MATLAB
+	A <- data.frame(
+		Var1 = 1:5,
+		Var2 = LETTERS[1:5],
+		Var3 = c(FALSE, TRUE, FALSE, TRUE, FALSE)
+	)
+	B <- data.frame(
+		Var1 = seq(1, 9, by = 2),
+		Var2 = LETTERS[seq(1, 9, by = 2)],
+		Var3 = rep(FALSE, 5)
+	)
+	C <- data.frame(
+		Var1 = c(2, 4),
+		Var2 = c('B', 'D'),
+		Var3 = c(TRUE, TRUE)
+	)
+	# expect_equal(setdiff_MATLAB(A, B), C) # TODO: implement for data frames
+	# TODO: add more examples from https://se.mathworks.com/help/matlab/ref/double.setdiff.html;jsessionid=0d8d42582d4d299b8224403899f1
 })
\ No newline at end of file
diff --git a/tests/testthat/test-greedyMix.R b/tests/testthat/test-greedyMix.R
index 9a1c05a..f1faf53 100644
--- a/tests/testthat/test-greedyMix.R
+++ b/tests/testthat/test-greedyMix.R
@@ -1,14 +1,10 @@
-# library(devtools)#TEMP
-library(testthat)#TEMP
-# library(rBAPS)#TEMP
-
 context("Opening files on greedyMix")
 
-greedyMix(
-	tietue = "data/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt",
-	format = "GenePop",
-	savePreProcessed = FALSE
-)
+# greedyMix(
+# 	tietue = "inst/ext/ExamplesDataFormatting/Example baseline data in GENEPOP format for Trained clustering.txt",
+# 	format = "GenePop",
+# 	savePreProcessed = FALSE
+# )
 
 context("Linkage")