--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/execute_dwt_var_perFeature.pl	Mon Jan 27 09:26:33 2014 -0500
@@ -0,0 +1,199 @@
+#!/usr/bin/perl -w
+# Author: Erika Kvikstad
+
+use warnings;
+use IO::Handle;
+use POSIX qw(floor ceil);
+
+$usage = "execute_dwt_var_perFeature.pl [TABULAR.in] [FEATURE] [ALPHA] [TABULAR.out] [PDF.out] \n";
+die $usage unless @ARGV == 5;
+
+#get the input arguments
+my $inputFile = $ARGV[0];
+my @features = split(/,/,$ARGV[1]);
+my $features_count = scalar(@features);
+my $alpha = $ARGV[2];
+my $outFile1 = $ARGV[3];
+my $outFile2 = $ARGV[4];
+
+open (INPUT, "<", $inputFile) || die("Could not open file $inputFile \n");
+open (OUTPUT2, ">", $outFile1) || die("Could not open file $outFile1 \n");
+open (OUTPUT3, ">", $outFile2) || die("Could not open file $outFile2 \n");
+#open (ERROR,  ">", "error.txt")  or die ("Could not open file error.txt \n");
+
+# choosing meaningful names for the output files
+$pvalue = $outFile1; 
+$pdf = $outFile2; 
+
+# write R script
+$r_script = "get_dwt_varPermut.r"; 
+
+open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
+
+print Rcmd "
+	######################################################################
+	# plot multiscale wavelet variance 
+	# create null bands by permuting the original data series
+	# generate plots and table of wavelet variance including p-values
+	######################################################################
+	options(echo = FALSE)
+	#library(\"Rwave\");
+	#library(\"wavethresh\");
+	#library(\"waveslim\");
+	# turn off diagnostics for de-bugging only, turn back on for functional tests on test
+	suppressMessages(require(\"Rwave\",quietly=TRUE,warn.conflicts = FALSE));
+	suppressMessages(require(\"wavethresh\",quietly=TRUE,warn.conflicts = FALSE));
+	suppressMessages(require(\"waveslim\",quietly=TRUE,warn.conflicts = FALSE));
+	suppressMessages(require(\"bitops\",quietly=TRUE,warn.conflicts = FALSE));
+
+	# to determine if data is properly formatted 2^N observations
+	is.power2<- function(x){x && !(bitAnd(x,x - 1));}
+
+	# dwt : discrete wavelet transform using Haar wavelet filter, simplest wavelet function but later can modify to let user-define the wavelet filter function
+	dwt_var_permut_getMax <- function(data, names, alpha, filter = 1,family=\"DaubExPhase\", bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
+		max_var = NULL;
+    		matrix = NULL;
+		title = NULL;
+    		final_pvalue = NULL;
+		J = NULL;
+		scale = NULL;
+		out = NULL;
+	
+	print(class(data));	
+    	print(names);
+	print(alpha);
+    	
+	par(mar=c(5,4,4,3),oma = c(4, 4, 3, 2), xaxt = \"s\", cex = 1, las = 1);
+   
+	title<-c(\"Wavelet\",\"Variance\",\"Pvalue\",\"Test\");
+	print(title);
+
+    	for(i in 1:length(names)){
+		temp = NULL;
+		results = NULL;
+		wave1.dwt = NULL;
+	
+		# if data fails formatting check, do something
+				
+		print(is.numeric(as.matrix(data)[, i]));
+		if(!is.numeric(as.matrix(data)[, i]))
+			stop(\"data must be a numeric vector\");
+		
+		print(length(as.matrix(data)[, i]));
+		print(is.power2(length(as.matrix(data)[, i])));
+		if(!is.power2(length(as.matrix(data)[, i])))	
+			stop(\"data length must be a power of two\");
+
+
+    		J <- wd(as.matrix(data)[, i], filter.number = filter, family=family, bc = bc)\$nlevels;
+		print(J);
+            	temp <- vector(length = J);
+               	wave1.dwt <- dwt(as.matrix(data)[, i], wf = wf, J, boundary = boundary); 
+		#print(wave1.dwt);
+                		
+                temp <- wave.variance(wave1.dwt)[-(J+1), 1];
+		print(temp);
+
+                #permutations code :
+                feature1 = NULL;
+		null = NULL;
+		var_lower=limit_lower=NULL;
+		var_upper=limit_upper=NULL;
+		med = NULL;
+
+		limit_lower = alpha/2*1000;
+		print(limit_lower);
+		limit_upper = (1-alpha/2)*1000;
+		print(limit_upper);
+		
+		feature1 = as.matrix(data)[,i];
+                for (k in 1:1000) {
+			nk_1 = NULL;
+			null.levels = NULL;
+			var = NULL;
+			null_wave1 = NULL;
+
+                       	nk_1 = sample(feature1, length(feature1), replace = FALSE);
+                       	null.levels <- wd(nk_1, filter.number = filter,family=family ,bc = bc)\$nlevels;
+                       	var <- vector(length = length(null.levels));
+                       	null_wave1 <- dwt(nk_1, wf = wf, J, boundary = boundary);
+                       	var<- wave.variance(null_wave1)[-(null.levels+1), 1];
+                       	null= rbind(null, var);
+               }
+               null <- apply(null, 2, sort, na.last = TRUE);
+               var_lower <- null[limit_lower, ];
+               var_upper <- null[limit_upper, ];
+               med <- (apply(null, 2, median, na.rm = TRUE));
+
+               # plot
+               results <- cbind(temp, var_lower, var_upper);
+		print(results);
+                matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2),xaxt='n',xlab=\"Wavelet Scale\",ylab=\"Wavelet variance\" );
+		mtext(names[i], side = 3, line = 0.5, cex = 1);
+		axis(1, at = 1:J , labels=c(2^(0:(J-1))), las = 3, cex.axis = 1);
+
+                # get pvalues by comparison to null distribution
+		#out <- (names[i]);
+                for (m in 1:length(temp)){
+                    	print(paste(\"scale\", m, sep = \" \"));
+                       	print(paste(\"var\", temp[m], sep = \" \"));
+                       	print(paste(\"med\", med[m], sep = \" \"));
+                       	pv = tail =scale = NULL;
+			scale=2^(m-1);
+			#out <- c(out, format(temp[m], digits = 3));	
+                       	if (temp[m] >= med[m]){
+                       		# R tail test
+                           	print(\"R\");
+	                       	tail <- \"R\";
+                            	pv <- (length(which(null[, m] >= temp[m])))/(length(na.exclude(null[, m])));
+
+                       	} else {
+                       		if (temp[m] < med[m]){
+                               		# L tail test
+                               		print(\"L\");
+	                            	tail <- \"L\";
+                                	pv <- (length(which(null[, m] <= temp[m])))/(length(na.exclude(null[, m])));
+                        	}
+			}
+			print(pv);
+			out<-rbind(out,c(paste(\"Scale\", scale, sep=\"_\"),format(temp[m], digits = 3),pv,tail));
+                }
+		final_pvalue <-rbind(final_pvalue, out);
+  	}
+	colnames(final_pvalue) <- title;
+    	return(final_pvalue);
+}\n";
+
+print Rcmd "
+# execute
+# read in data 
+data_test = final = NULL;
+sub = sub_names = NULL;
+data_test <- read.delim(\"$inputFile\",header=FALSE);
+pdf(file = \"$pdf\", width = 11, height = 8)\n";
+
+for ($x=0;$x<$features_count;$x++){	
+	$feature=$features[$x];
+print Rcmd "
+	if ($feature > ncol(data_test))
+		stop(\"column $feature doesn't exist\");	
+	sub<-data_test[,$feature];
+	#sub_names <- colnames(data_test);
+	sub_names<-colnames(data_test)[$feature];
+	final <- rbind(final,dwt_var_permut_getMax(sub, sub_names,$alpha));\n";
+}
+
+print Rcmd "
+
+	dev.off();
+	write.table(final, file = \"$pvalue\", sep = \"\\t\", quote = FALSE, row.names = FALSE);
+
+#eof\n";
+
+close Rcmd;
+system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");
+
+#close the input and output and error files
+close(OUTPUT3);
+close(OUTPUT2);
+close(INPUT);