--- a/execute_dwt_IvC_all.pl	Thu Jan 23 12:31:01 2014 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,210 +0,0 @@
-#!/usr/bin/perl -w
-use warnings;
-use IO::Handle;
-
-$usage = "execute_dwt_IvC_all.pl [TABULAR.in] [TABULAR.in] [TABULAR.out] [PDF.out]  \n";
-die $usage unless @ARGV == 4;
-
-#get the input arguments
-my $firstInputFile = $ARGV[0];
-my $secondInputFile = $ARGV[1];
-my $firstOutputFile = $ARGV[2];
-my $secondOutputFile = $ARGV[3];
-
-open (INPUT1, "<", $firstInputFile) || die("Could not open file $firstInputFile \n");
-open (INPUT2, "<", $secondInputFile) || die("Could not open file $secondInputFile \n");
-open (OUTPUT1, ">", $firstOutputFile) || die("Could not open file $firstOutputFile \n");
-open (OUTPUT2, ">", $secondOutputFile) || die("Could not open file $secondOutputFile \n");
-open (ERROR,  ">", "error.txt")  or die ("Could not open file error.txt \n");
-
-#save all error messages into the error file $errorFile using the error file handle ERROR
-STDERR -> fdopen( \*ERROR,  "w" ) or die ("Could not direct errors to the error file error.txt \n");
-
-
-print "There are two input data files: \n";
-print "The input data file is: $firstInputFile \n";
-print "The control data file is: $secondInputFile \n";
-
-# IvC test
-$test = "IvC";
-
-# construct an R script to implement the IvC test
-print "\n";
-
-$r_script = "get_dwt_IvC_test.r"; 
-print "$r_script \n";
-
-# R script
-open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
-print Rcmd "
-        ###########################################################################################
-        # code to do wavelet Indel vs. Control
-        # signal is the difference I-C; function is second moment i.e. variance from zero not mean
-        # to perform wavelet transf. of signal, scale-by-scale analysis of the function 
-        # create null bands by permuting the original data series
-        # generate plots and table matrix of correlation coefficients including p-values
-        ############################################################################################
-        library(\"Rwave\");
-        library(\"wavethresh\");
-        library(\"waveslim\");
-        
-        options(echo = FALSE)
-        
-        # normalize data
-        norm <- function(data){
-            v <- (data - mean(data))/sd(data);
-            if(sum(is.na(v)) >= 1){
-                v <- data;
-            }
-            return(v);
-        }
-        
-        dwt_cor <- function(data.short, names.short, data.long, names.long, test, pdf, table, filter = 4, bc = \"symmetric\", wf = \"haar\", boundary = \"reflection\") {
-            print(test);
-            print(pdf);
-            print(table);
-            
-            pdf(file = pdf);
-            final_pvalue = NULL;
-            title = NULL;
-                
-            short.levels <- wd(data.short[, 1], filter.number = filter, bc = bc)\$nlevels;
-            title <- c(\"motif\");
-            for (i in 1:short.levels){
-            	title <- c(title, paste(i, \"moment2\", sep = \"_\"), paste(i, \"pval\", sep = \"_\"), paste(i, \"test\", sep = \"_\"));
-            }
-            print(title);
-        
-            # loop to compare a vs a
-            for(i in 1:length(names.short)){
-        		wave1.dwt = NULL;
-        		m2.dwt = diff = var.dwt = NULL;
-        		out = NULL;
-                out <- vector(length = length(title));
-        
-        		print(names.short[i]);
-        		print(names.long[i]);
-                        
-        		# need exit if not comparing motif(a) vs motif(a)
-        		if (names.short[i] != names.long[i]){
-                	stop(paste(\"motif\", names.short[i], \"is not the same as\", names.long[i], sep = \" \"));
-        		}
-        		else {
-                	# signal is the difference I-C data sets
-                    diff<-data.short[,i]-data.long[,i];
-        
-                    # normalize the signal
-                    diff<-norm(diff);
-        
-                    # function is 2nd moment
-                    # 2nd moment m_j = 1/N[sum_N(W_j + V_J)^2] = 1/N sum_N(W_j)^2 + (X_bar)^2 
-            		wave1.dwt <- dwt(diff, wf = wf, short.levels, boundary = boundary);
-            		var.dwt <- wave.variance(wave1.dwt);
-                	m2.dwt <- vector(length = short.levels)
-                    for(level in 1:short.levels){
-                    	m2.dwt[level] <- var.dwt[level, 1] + (mean(diff)^2);
-                    }
-                                
-            		# CI bands by permutation of time series
-            		feature1 = feature2 = NULL;
-            		feature1 = data.short[, i];
-            		feature2 = data.long[, i];
-            		null = results = med = NULL; 
-            		m2_25 = m2_975 = NULL;
-            
-            		for (k in 1:1000) {
-                		nk_1 = nk_2 = NULL;
-                		m2_null = var_null = NULL;
-                		null.levels = null_wave1 = null_diff = NULL;
-                		nk_1 <- sample(feature1, length(feature1), replace = FALSE);
-                		nk_2 <- sample(feature2, length(feature2), replace = FALSE);
-                		null.levels <- wd(nk_1, filter.number = filter, bc = bc)\$nlevels;
-                		null_diff <- nk_1-nk_2;
-                		null_diff <- norm(null_diff);
-                		null_wave1 <- dwt(null_diff, wf = wf, short.levels, boundary = boundary);
-                        var_null <- wave.variance(null_wave1);
-                		m2_null <- vector(length = null.levels);
-                		for(level in 1:null.levels){
-                        	m2_null[level] <- var_null[level, 1] + (mean(null_diff)^2);
-                		}
-                		null= rbind(null, m2_null);
-            		}
-                
-            		null <- apply(null, 2, sort, na.last = TRUE);
-            		m2_25 <- null[25,];
-            		m2_975 <- null[975,];
-            		med <- apply(null, 2, median, na.rm = TRUE);
-
-            		# plot
-            		results <- cbind(m2.dwt, m2_25, m2_975);
-            		matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2), xlab = \"Wavelet Scale\", ylab = c(\"Wavelet 2nd Moment\", test), main = (names.short[i]), cex.main = 0.75);
-            		abline(h = 1);
-
-            		# get pvalues by comparison to null distribution
-            		out <- c(names.short[i]);
-            		for (m in 1:length(m2.dwt)){
-                    	print(paste(\"scale\", m, sep = \" \"));
-                        print(paste(\"m2\", m2.dwt[m], sep = \" \"));
-                        print(paste(\"median\", med[m], sep = \" \"));
-                        out <- c(out, format(m2.dwt[m], digits = 4));	
-                        pv = NULL;
-                        if(is.na(m2.dwt[m])){
-                        	pv <- \"NA\"; 
-                        } 
-                        else {
-                        	if (m2.dwt[m] >= med[m]){
-                            	# R tail test
-                                tail <- \"R\";
-                                pv <- (length(which(null[, m] >= m2.dwt[m])))/(length(na.exclude(null[, m])));
-                            }
-                            else{
-                                if (m2.dwt[m] < med[m]){
-                                	# L tail test
-                                    tail <- \"L\";
-                                    pv <- (length(which(null[, m] <= m2.dwt[m])))/(length(na.exclude(null[, m])));
-                                }
-                            }
-                        }
-                        out <- c(out, pv);
-                        print(pv);  
-                        out <- c(out, tail);
-                    }
-                    final_pvalue <-rbind(final_pvalue, out);
-                    print(out);
-                }
-            }
-            
-            colnames(final_pvalue) <- title;
-            write.table(final_pvalue, file = table, sep = \"\\t\", quote = FALSE, row.names = FALSE);
-            dev.off();
-        }\n";
-
-print Rcmd "
-        # execute
-        # read in data 
-        
-        inputData <- read.delim(\"$firstInputFile\");
-        inputDataNames <- colnames(inputData);
-        
-        controlData <- read.delim(\"$secondInputFile\");
-        controlDataNames <- colnames(controlData);
-        
-        # call the test function to implement IvC test
-        dwt_cor(inputData, inputDataNames, controlData, controlDataNames, test = \"$test\", pdf = \"$secondOutputFile\", table = \"$firstOutputFile\");
-        print (\"done with the correlation test\");
-\n";
-
-print Rcmd "#eof\n";
-
-close Rcmd;
-
-system("echo \"wavelet IvC test started on \`hostname\` at \`date\`\"\n");
-system("R --no-restore --no-save --no-readline < $r_script > $r_script.out\n");
-system("echo \"wavelet IvC test ended on \`hostname\` at \`date\`\"\n");
-
-#close the input and output and error files
-close(ERROR);
-close(OUTPUT2);
-close(OUTPUT1);
-close(INPUT2);
-close(INPUT1);
\ No newline at end of file