@@ -1128,8 +1128,6 @@ genotype.Illumina <- function(sampleSheet=NULL,

 			      cdfName,

 			      copynumber=TRUE,

 			      batch,

-			      ##                          outdir=".",

-			      ##                          fns,

 			      saveDate=TRUE,

 			      stripNorm=TRUE,

 			      useTarget=TRUE,

@@ -1148,124 +1146,64 @@ genotype.Illumina <- function(sampleSheet=NULL,

 			      returnParams=TRUE,

 			      badSNP=0.7) {

 	is.lds = ifelse(isPackageLoaded("ff"), TRUE, FALSE)

+	stopifnot(is.lds)

 	if(missing(cdfName)) stop("must specify cdfName")

 	if(!isValidCdfName(cdfName)) stop("cdfName not valid.  see validCdfNames")

         pkgname = getCrlmmAnnotationName(cdfName)

-##        if(missing(outdir))

-##		stop("Must specify a directory to store large data objects")

-	##callSet <- .GlobalEnv[["callSet"]]

-	##if(is.null(callSet)){

-		callSet <- construct.Illumina(sampleSheet=sampleSheet, arrayNames=arrayNames,

-					      ids=ids, path=path, arrayInfoColNames=arrayInfoColNames,

-					      highDensity=highDensity, sep=sep, fileExt=fileExt,

-					      cdfName=cdfName, copynumber=copynumber, verbose=verbose, batch=batch, # fns=fns,

-					      saveDate=saveDate) #, outdir=outdir)

-		sampleNames(callSet) <- basename(sampleNames(callSet))

-	##save(callSet, file=file.path(ldPath(), "callSet.rda"))

-	##} else message("Using callSet loaded from GlobalEnv")

+	callSet <- construct.Illumina(sampleSheet=sampleSheet, arrayNames=arrayNames,

+				      ids=ids, path=path, arrayInfoColNames=arrayInfoColNames,

+				      highDensity=highDensity, sep=sep, fileExt=fileExt,

+				      cdfName=cdfName, copynumber=copynumber, verbose=verbose, batch=batch, # fns=fns,

+				      saveDate=saveDate) #, outdir=outdir)

+	sampleNames(callSet) <- basename(sampleNames(callSet))

 	if(missing(sns)) sns = basename(sampleNames(callSet))

-	if(is.lds) {

-		open(A(callSet))

-		open(B(callSet))

-		## open(callSet)

-	}

+	open(A(callSet))

+	open(B(callSet))

  	is.snp = isSnp(callSet)

 	snp.index = which(is.snp)

 	narrays = ncol(callSet)

-	if(is.lds) {

-##		index <- .GlobalEnv[["index"]]

-##		if(is.null(index)){

-##			sampleBatches = splitIndicesByLength(seq(along=sampleNames(callSet)), ocSamples())

-##		} else sampleBatches <- splitIndicesByLength(seq(length=ncol(callSet)), ocSamples())

-		sampleBatches <- splitIndicesByLength(seq(length=ncol(callSet)), ocSamples())

-		mixtureParams = initializeBigMatrix("crlmmMixt-", 4, narrays, "double")

-		SNR = initializeBigVector("crlmmSNR-", narrays, "double")

-		SKW = initializeBigVector("crlmmSKW-", narrays, "double")

-		ocLapply(stratum=seq_along(sampleBatches), processIDAT, sampleBatches=sampleBatches,

-			 sampleSheet=sampleSheet, arrayNames=arrayNames,

-			 ids=ids, path=path, arrayInfoColNames=arrayInfoColNames, highDensity=highDensity,

-			 sep=sep, fileExt=fileExt, saveDate=saveDate, verbose=verbose, mixtureSampleSize=mixtureSampleSize,

-			 fitMixture=fitMixture, eps=eps, seed=seed, cdfName=cdfName, sns=sns, stripNorm=stripNorm,

-			 useTarget=useTarget, A=A(callSet), B=B(callSet), SKW=SKW, SNR=SNR,

-			 mixtureParams=mixtureParams, is.snp=is.snp, neededPkgs=c("crlmm", pkgname)) # outdir=outdir,

-		open(SKW)

-		open(SNR)

-		pData(callSet)$SKW = SKW

-		pData(callSet)$SNR = SNR

-		save(callSet, file=file.path(ldPath(), "callSet.rda"))

-		close(SNR)

-		close(SKW)

-	} else {

-		mixtureParams = matrix(NA, 4, nrow(callSet))

-		RG <- readIdatFiles(sampleSheet=sampleSheet, arrayNames=arrayNames,

-				    ids=ids, path=path, arrayInfoColNames=arrayInfoColNames,

-				    highDensity=highDensity, sep=sep, fileExt=fileExt, saveDate=saveDate)

-		XY = RGtoXY(RG, chipType=cdfName)

-		rm(RG); gc()

-

-		res <- preprocessInfinium2(XY, mixtureSampleSize=mixtureSampleSize, fitMixture=TRUE, verbose=verbose,

-					   seed=seed, eps=eps, cdfName=cdfName, sns=sns, stripNorm=stripNorm, useTarget=useTarget) # , outdir=outdir)

-		rm(XY); gc()

-		if(verbose) message("Finished preprocessing.")

-		np.index = which(!is.snp)

-		A(callSet)[snp.index, ] = res[["A"]]

-		B(callSet)[snp.index, ] = res[["B"]]

-		if(length(np.index)>0) {

-			A(callSet)[np.index, ] = res[["cnAB"]]$A

-			B(callSet)[np.index, ] = res[["cnAB"]]$B

-		}

-		SKW = pData(callSet)$SKW = res[["SKW"]]

-		SNR = pData(callSet)$SNR = res[["SNR"]]

-		mixtureParams = res[["mixtureParams"]]

-		rm(res)

-	}

+	sampleBatches <- splitIndicesByLength(seq(length=ncol(callSet)), ocSamples())

+	mixtureParams = initializeBigMatrix("crlmmMixt-", 4, narrays, "double")

+	SNR = initializeBigVector("crlmmSNR-", narrays, "double")

+	SKW = initializeBigVector("crlmmSKW-", narrays, "double")

+	ocLapply(seq_along(sampleBatches), processIDAT, sampleBatches=sampleBatches,

+		 sampleSheet=sampleSheet, arrayNames=arrayNames,

+		 ids=ids, path=path, arrayInfoColNames=arrayInfoColNames, highDensity=highDensity,

+		 sep=sep, fileExt=fileExt, saveDate=saveDate, verbose=verbose, mixtureSampleSize=mixtureSampleSize,

+		 fitMixture=fitMixture, eps=eps, seed=seed, cdfName=cdfName, sns=sns, stripNorm=stripNorm,

+		 useTarget=useTarget, A=A(callSet), B=B(callSet), SKW=SKW, SNR=SNR,

+		 mixtureParams=mixtureParams, is.snp=is.snp, neededPkgs=c("crlmm", pkgname)) # outdir=outdir,

+	open(SKW)

+	open(SNR)

+	pData(callSet)$SKW = SKW

+	pData(callSet)$SNR = SNR

+	save(callSet, file=file.path(ldPath(), "callSet.rda"))

+	close(SNR)

+	close(SKW)

 	FUN = ifelse(is.lds, "crlmmGT2", "crlmmGT")

-	## genotyping

 	crlmmGTfxn = function(FUN,...){

 		switch(FUN,

 		       crlmmGT2=crlmmGT2(...),

 		       crlmmGT=crlmmGT(...))

 	}

-	if(is.lds) {

-		open(A(callSet))

-		open(B(callSet))

-		tmpA = initializeBigMatrix(name="tmpA", length(snp.index), narrays)

-		tmpB = initializeBigMatrix(name="tmpB", length(snp.index), narrays)

-		##ffcolapply(tmpA[,i1:i2] <- A(callSet)[snp.index,i1:i2], X=A(callSet))

-		##ffcolapply(tmpB[,i1:i2] <- B(callSet)[snp.index,i1:i2], X=B(callSet))

-		for(j in seq(length=ncol(callSet))){

-			tmpA[, j] <- as.integer(A(callSet)[snp.index, j])

-			tmpB[, j] <- as.integer(B(callSet)[snp.index, j])

-		}

-		close(A(callSet))

-		close(B(callSet))

-		close(tmpA)

-		close(tmpB)

-	} else {

-		tmpA = A(callSet)[snp.index,]

-		tmpB = B(callSet)[snp.index,]

+	open(A(callSet))

+	open(B(callSet))

+	tmpA = initializeBigMatrix(name="tmpA", length(snp.index), narrays)

+	tmpB = initializeBigMatrix(name="tmpB", length(snp.index), narrays)

+	for(j in seq(length=ncol(callSet))){

+		tmpA[, j] <- as.integer(A(callSet)[snp.index, j])

+		tmpB[, j] <- as.integer(B(callSet)[snp.index, j])

 	}

-##	return(list(tmpA,

-##		    tmpB,

-##		    SNR,

-##		    mixtureParams,

-##		    cdfName,

-##		    sampleNames(callSet),

-##		    probs,

-##		    DF,

-##		    SNRMin,

-##		    recallMin,

-##		    recallRegMin,

-##		    gender,

-##		    verbose,

-##		    returnParams,

-##		    badSNP))

+	close(A(callSet))

+	close(B(callSet))

+	close(tmpA)

+	close(tmpB)

 	save(tmpA, file=file.path(ldPath(), "tmpA.rda"))

 	save(tmpB, file=file.path(ldPath(), "tmpB.rda"))

 	save(SNR, file=file.path(ldPath(), "SNR.rda"))

 	save(SKW, file=file.path(ldPath(), "SKW.rda"))

 	save(mixtureParams, file=file.path(ldPath(), "mixtureParams.rda"))

-##	return(NULL)

+	message("Begin genotyping")

 	tmp <- crlmmGTfxn(FUN,

 			  A=tmpA,

 			  B=tmpB,

@@ -1283,29 +1221,16 @@ genotype.Illumina <- function(sampleSheet=NULL,

 			  verbose=verbose,

 			  returnParams=returnParams,

 			  badSNP=badSNP)

+	save(tmp, file=file.path(ldPath(), "tmp.rda"))

 	if(verbose) message("Genotyping finished.  Updating container with genotype calls and confidence scores.")

-	if(is.lds){

-		##       bb = getOption("ffbatchbytes") # ocProbesets()*ncol(callSet)*8

-		open(tmp[["calls"]])

-		open(tmp[["confs"]])

-		open(calls(callSet))

-		open(snpCallProbability(callSet))

-		ffcolapply(snpCall(callSet)[snp.index,i1:i2] <- tmp[["calls"]][,i1:i2], X=tmp[["calls"]]) #, BATCHBYTES=bb)

-		ffcolapply(snpCallProbability(callSet)[snp.index,i1:i2] <- tmp[["confs"]][,i1:i2], X=tmp[["confs"]]) #, BATCHBYTES=bb)

-		close(tmp[["calls"]])

-		close(tmp[["confs"]])

-		close(tmpA); close(tmpB)

-		delete(tmpA); delete(tmpB);

-		## This line is not needed as tmp[["calls"]]

-		## is stored in tmpA and tmp[["confs"]] is stored in tmpB

-		## So deleting tmpA and tmpB in the above command removes

-		## the ff objects on disk

-		##delete(tmp[["calls"]]); delete(tmp[["confs"]])

-	} else {

-		calls(callSet)[snp.index, ] = tmp[["calls"]]

-		snpCallProbability(callSet)[snp.index, ] = tmp[["confs"]]

-		rm(tmpA, tmpB)

+	open(tmpA)

+	open(tmpB)

+	for(j in 1:ncol(callSet)){

+		snpCall(callSet)[snp.index, j] <- as.integer(tmpA[, j])

+		snpCallProbability(callSet)[snp.index, j] <- as.integer(tmpB[, j])

 	}

+	close(tmpA); close(tmpB)

+	delete(tmpA); delete(tmpB);

 	callSet$gender = tmp$gender

 	rm(tmp)

 	close(callSet)