annotate tools/discreteWavelet/execute_dwt_var_perFeature.pl @ 2:c2a356708570

Uploaded
author xuebing
date Fri, 09 Mar 2012 19:45:42 -0500
parents 9071e359b9a3
children
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1 #!/usr/bin/perl -w
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2 # Author: Erika Kvikstad
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3
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4 use warnings;
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5 use IO::Handle;
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6 use POSIX qw(floor ceil);
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7
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8 $usage = "execute_dwt_var_perFeature.pl [TABULAR.in] [FEATURE] [ALPHA] [TABULAR.out] [PDF.out] \n";
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9 die $usage unless @ARGV == 5;
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10
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11 #get the input arguments
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parents:
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12 my $inputFile = $ARGV[0];
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13 my @features = split(/,/,$ARGV[1]);
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14 my $features_count = scalar(@features);
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15 my $alpha = $ARGV[2];
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16 my $outFile1 = $ARGV[3];
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17 my $outFile2 = $ARGV[4];
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18
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19 open (INPUT, "<", $inputFile) || die("Could not open file $inputFile \n");
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20 open (OUTPUT2, ">", $outFile1) || die("Could not open file $outFile1 \n");
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21 open (OUTPUT3, ">", $outFile2) || die("Could not open file $outFile2 \n");
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parents:
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22 #open (ERROR, ">", "error.txt") or die ("Could not open file error.txt \n");
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23
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parents:
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24 # choosing meaningful names for the output files
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parents:
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25 $pvalue = $outFile1;
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parents:
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26 $pdf = $outFile2;
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27
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parents:
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28 # write R script
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parents:
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29 $r_script = "get_dwt_varPermut.r";
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30
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31 open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
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32
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33 print Rcmd "
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34 ######################################################################
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parents:
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35 # plot multiscale wavelet variance
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36 # create null bands by permuting the original data series
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37 # generate plots and table of wavelet variance including p-values
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parents:
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38 ######################################################################
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39 options(echo = FALSE)
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parents:
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40 #library(\"Rwave\");
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41 #library(\"wavethresh\");
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42 #library(\"waveslim\");
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43 # turn off diagnostics for de-bugging only, turn back on for functional tests on test
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44 require(\"Rwave\",quietly=TRUE,warn.conflicts = FALSE);
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45 require(\"wavethresh\",quietly=TRUE,warn.conflicts = FALSE);
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46 require(\"waveslim\",quietly=TRUE,warn.conflicts = FALSE);
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47 require(\"bitops\",quietly=TRUE,warn.conflicts = FALSE);
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48
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49 # to determine if data is properly formatted 2^N observations
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50 is.power2<- function(x){x && !(bitAnd(x,x - 1));}
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51
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52 # dwt : discrete wavelet transform using Haar wavelet filter, simplest wavelet function but later can modify to let user-define the wavelet filter function
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53 dwt_var_permut_getMax <- function(data, names, alpha, filter = 1,family=\"DaubExPhase\", bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
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54 max_var = NULL;
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55 matrix = NULL;
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56 title = NULL;
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57 final_pvalue = NULL;
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58 J = NULL;
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59 scale = NULL;
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60 out = NULL;
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61
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62 print(class(data));
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63 print(names);
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64 print(alpha);
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65
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66 par(mar=c(5,4,4,3),oma = c(4, 4, 3, 2), xaxt = \"s\", cex = 1, las = 1);
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67
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68 title<-c(\"Wavelet\",\"Variance\",\"Pvalue\",\"Test\");
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69 print(title);
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70
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71 for(i in 1:length(names)){
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72 temp = NULL;
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73 results = NULL;
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74 wave1.dwt = NULL;
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75
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76 # if data fails formatting check, do something
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77
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78 print(is.numeric(as.matrix(data)[, i]));
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79 if(!is.numeric(as.matrix(data)[, i]))
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80 stop(\"data must be a numeric vector\");
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81
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82 print(length(as.matrix(data)[, i]));
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83 print(is.power2(length(as.matrix(data)[, i])));
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84 if(!is.power2(length(as.matrix(data)[, i])))
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85 stop(\"data length must be a power of two\");
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86
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87
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88 J <- wd(as.matrix(data)[, i], filter.number = filter, family=family, bc = bc)\$nlevels;
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89 print(J);
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90 temp <- vector(length = J);
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91 wave1.dwt <- dwt(as.matrix(data)[, i], wf = wf, J, boundary = boundary);
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parents:
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92 #print(wave1.dwt);
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93
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94 temp <- wave.variance(wave1.dwt)[-(J+1), 1];
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95 print(temp);
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96
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97 #permutations code :
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98 feature1 = NULL;
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99 null = NULL;
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100 var_lower=limit_lower=NULL;
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101 var_upper=limit_upper=NULL;
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102 med = NULL;
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103
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104 limit_lower = alpha/2*1000;
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105 print(limit_lower);
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106 limit_upper = (1-alpha/2)*1000;
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107 print(limit_upper);
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108
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109 feature1 = as.matrix(data)[,i];
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110 for (k in 1:1000) {
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111 nk_1 = NULL;
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112 null.levels = NULL;
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113 var = NULL;
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114 null_wave1 = NULL;
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115
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116 nk_1 = sample(feature1, length(feature1), replace = FALSE);
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117 null.levels <- wd(nk_1, filter.number = filter,family=family ,bc = bc)\$nlevels;
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118 var <- vector(length = length(null.levels));
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119 null_wave1 <- dwt(nk_1, wf = wf, J, boundary = boundary);
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120 var<- wave.variance(null_wave1)[-(null.levels+1), 1];
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121 null= rbind(null, var);
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122 }
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123 null <- apply(null, 2, sort, na.last = TRUE);
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124 var_lower <- null[limit_lower, ];
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125 var_upper <- null[limit_upper, ];
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126 med <- (apply(null, 2, median, na.rm = TRUE));
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127
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parents:
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128 # plot
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129 results <- cbind(temp, var_lower, var_upper);
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130 print(results);
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131 matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2),xaxt='n',xlab=\"Wavelet Scale\",ylab=\"Wavelet variance\" );
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132 mtext(names[i], side = 3, line = 0.5, cex = 1);
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133 axis(1, at = 1:J , labels=c(2^(0:(J-1))), las = 3, cex.axis = 1);
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134
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135 # get pvalues by comparison to null distribution
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parents:
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136 #out <- (names[i]);
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parents:
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137 for (m in 1:length(temp)){
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parents:
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138 print(paste(\"scale\", m, sep = \" \"));
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parents:
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139 print(paste(\"var\", temp[m], sep = \" \"));
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parents:
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140 print(paste(\"med\", med[m], sep = \" \"));
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parents:
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141 pv = tail =scale = NULL;
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142 scale=2^(m-1);
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parents:
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143 #out <- c(out, format(temp[m], digits = 3));
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parents:
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144 if (temp[m] >= med[m]){
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parents:
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145 # R tail test
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parents:
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146 print(\"R\");
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parents:
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147 tail <- \"R\";
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parents:
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148 pv <- (length(which(null[, m] >= temp[m])))/(length(na.exclude(null[, m])));
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parents:
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149
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parents:
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150 } else {
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parents:
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151 if (temp[m] < med[m]){
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parents:
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152 # L tail test
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parents:
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153 print(\"L\");
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parents:
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154 tail <- \"L\";
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155 pv <- (length(which(null[, m] <= temp[m])))/(length(na.exclude(null[, m])));
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parents:
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156 }
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157 }
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158 print(pv);
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159 out<-rbind(out,c(paste(\"Scale\", scale, sep=\"_\"),format(temp[m], digits = 3),pv,tail));
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parents:
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160 }
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161 final_pvalue <-rbind(final_pvalue, out);
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parents:
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162 }
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163 colnames(final_pvalue) <- title;
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parents:
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164 return(final_pvalue);
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parents:
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165 }\n";
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166
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parents:
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167 print Rcmd "
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parents:
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168 # execute
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parents:
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169 # read in data
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parents:
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170 data_test = final = NULL;
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parents:
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171 sub = sub_names = NULL;
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parents:
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172 data_test <- read.delim(\"$inputFile\",header=FALSE);
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173 pdf(file = \"$pdf\", width = 11, height = 8)\n";
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parents:
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174
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parents:
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175 for ($x=0;$x<$features_count;$x++){
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parents:
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176 $feature=$features[$x];
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parents:
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177 print Rcmd "
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parents:
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178 if ($feature > ncol(data_test))
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parents:
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179 stop(\"column $feature doesn't exist\");
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parents:
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180 sub<-data_test[,$feature];
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parents:
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181 #sub_names <- colnames(data_test);
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parents:
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182 sub_names<-colnames(data_test)[$feature];
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parents:
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183 final <- rbind(final,dwt_var_permut_getMax(sub, sub_names,$alpha));\n";
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parents:
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184 }
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parents:
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185
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parents:
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186 print Rcmd "
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parents:
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187
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parents:
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188 dev.off();
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parents:
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189 write.table(final, file = \"$pvalue\", sep = \"\\t\", quote = FALSE, row.names = FALSE);
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parents:
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190
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parents:
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191 #eof\n";
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parents:
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192
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parents:
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193 close Rcmd;
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parents:
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194 system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");
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parents:
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195
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parents:
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196 #close the input and output and error files
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parents:
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197 close(OUTPUT3);
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parents:
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198 close(OUTPUT2);
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parents:
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199 close(INPUT);