Mercurial > repos > devteam > dwt_var_perfeature

comparison execute_dwt_var_perFeature.pl @ 0:d56c5d2e1a29 draft

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Imported from capsule None
author devteam
date Mon, 27 Jan 2014 09:26:33 -0500
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-1:000000000000 0:d56c5d2e1a29
1 #!/usr/bin/perl -w
2 # Author: Erika Kvikstad
3
4 use warnings;
5 use IO::Handle;
6 use POSIX qw(floor ceil);
7
8 $usage = "execute_dwt_var_perFeature.pl [TABULAR.in] [FEATURE] [ALPHA] [TABULAR.out] [PDF.out] \n";
9 die $usage unless @ARGV == 5;
10
11 #get the input arguments
12 my $inputFile = $ARGV[0];
13 my @features = split(/,/,$ARGV[1]);
14 my $features_count = scalar(@features);
15 my $alpha = $ARGV[2];
16 my $outFile1 = $ARGV[3];
17 my $outFile2 = $ARGV[4];
18
19 open (INPUT, "<", $inputFile) || die("Could not open file $inputFile \n");
20 open (OUTPUT2, ">", $outFile1) || die("Could not open file $outFile1 \n");
21 open (OUTPUT3, ">", $outFile2) || die("Could not open file $outFile2 \n");
22 #open (ERROR, ">", "error.txt") or die ("Could not open file error.txt \n");
23
24 # choosing meaningful names for the output files
25 $pvalue = $outFile1;
26 $pdf = $outFile2;
27
28 # write R script
29 $r_script = "get_dwt_varPermut.r";
30
31 open(Rcmd, ">", "$r_script") or die "Cannot open $r_script \n\n";
32
33 print Rcmd "
34 ######################################################################
35 # plot multiscale wavelet variance
36 # create null bands by permuting the original data series
37 # generate plots and table of wavelet variance including p-values
38 ######################################################################
39 options(echo = FALSE)
40 #library(\"Rwave\");
41 #library(\"wavethresh\");
42 #library(\"waveslim\");
43 # turn off diagnostics for de-bugging only, turn back on for functional tests on test
44 suppressMessages(require(\"Rwave\",quietly=TRUE,warn.conflicts = FALSE));
45 suppressMessages(require(\"wavethresh\",quietly=TRUE,warn.conflicts = FALSE));
46 suppressMessages(require(\"waveslim\",quietly=TRUE,warn.conflicts = FALSE));
47 suppressMessages(require(\"bitops\",quietly=TRUE,warn.conflicts = FALSE));
48
49 # to determine if data is properly formatted 2^N observations
50 is.power2<- function(x){x && !(bitAnd(x,x - 1));}
51
52 # dwt : discrete wavelet transform using Haar wavelet filter, simplest wavelet function but later can modify to let user-define the wavelet filter function
53 dwt_var_permut_getMax <- function(data, names, alpha, filter = 1,family=\"DaubExPhase\", bc = \"symmetric\", method = \"kendall\", wf = \"haar\", boundary = \"reflection\") {
54 max_var = NULL;
55 matrix = NULL;
56 title = NULL;
57 final_pvalue = NULL;
58 J = NULL;
59 scale = NULL;
60 out = NULL;
61
62 print(class(data));
63 print(names);
64 print(alpha);
65
66 par(mar=c(5,4,4,3),oma = c(4, 4, 3, 2), xaxt = \"s\", cex = 1, las = 1);
67
68 title<-c(\"Wavelet\",\"Variance\",\"Pvalue\",\"Test\");
69 print(title);
70
71 for(i in 1:length(names)){
72 temp = NULL;
73 results = NULL;
74 wave1.dwt = NULL;
75
76 # if data fails formatting check, do something
77
78 print(is.numeric(as.matrix(data)[, i]));
79 if(!is.numeric(as.matrix(data)[, i]))
80 stop(\"data must be a numeric vector\");
81
82 print(length(as.matrix(data)[, i]));
83 print(is.power2(length(as.matrix(data)[, i])));
84 if(!is.power2(length(as.matrix(data)[, i])))
85 stop(\"data length must be a power of two\");
86
87
88 J <- wd(as.matrix(data)[, i], filter.number = filter, family=family, bc = bc)\$nlevels;
89 print(J);
90 temp <- vector(length = J);
91 wave1.dwt <- dwt(as.matrix(data)[, i], wf = wf, J, boundary = boundary);
92 #print(wave1.dwt);
93
94 temp <- wave.variance(wave1.dwt)[-(J+1), 1];
95 print(temp);
96
97 #permutations code :
98 feature1 = NULL;
99 null = NULL;
100 var_lower=limit_lower=NULL;
101 var_upper=limit_upper=NULL;
102 med = NULL;
103
104 limit_lower = alpha/2*1000;
105 print(limit_lower);
106 limit_upper = (1-alpha/2)*1000;
107 print(limit_upper);
108
109 feature1 = as.matrix(data)[,i];
110 for (k in 1:1000) {
111 nk_1 = NULL;
112 null.levels = NULL;
113 var = NULL;
114 null_wave1 = NULL;
115
116 nk_1 = sample(feature1, length(feature1), replace = FALSE);
117 null.levels <- wd(nk_1, filter.number = filter,family=family ,bc = bc)\$nlevels;
118 var <- vector(length = length(null.levels));
119 null_wave1 <- dwt(nk_1, wf = wf, J, boundary = boundary);
120 var<- wave.variance(null_wave1)[-(null.levels+1), 1];
121 null= rbind(null, var);
122 }
123 null <- apply(null, 2, sort, na.last = TRUE);
124 var_lower <- null[limit_lower, ];
125 var_upper <- null[limit_upper, ];
126 med <- (apply(null, 2, median, na.rm = TRUE));
127
128 # plot
129 results <- cbind(temp, var_lower, var_upper);
130 print(results);
131 matplot(results, type = \"b\", pch = \"*\", lty = 1, col = c(1, 2, 2),xaxt='n',xlab=\"Wavelet Scale\",ylab=\"Wavelet variance\" );
132 mtext(names[i], side = 3, line = 0.5, cex = 1);
133 axis(1, at = 1:J , labels=c(2^(0:(J-1))), las = 3, cex.axis = 1);
134
135 # get pvalues by comparison to null distribution
136 #out <- (names[i]);
137 for (m in 1:length(temp)){
138 print(paste(\"scale\", m, sep = \" \"));
139 print(paste(\"var\", temp[m], sep = \" \"));
140 print(paste(\"med\", med[m], sep = \" \"));
141 pv = tail =scale = NULL;
142 scale=2^(m-1);
143 #out <- c(out, format(temp[m], digits = 3));
144 if (temp[m] >= med[m]){
145 # R tail test
146 print(\"R\");
147 tail <- \"R\";
148 pv <- (length(which(null[, m] >= temp[m])))/(length(na.exclude(null[, m])));
149
150 } else {
151 if (temp[m] < med[m]){
152 # L tail test
153 print(\"L\");
154 tail <- \"L\";
155 pv <- (length(which(null[, m] <= temp[m])))/(length(na.exclude(null[, m])));
156 }
157 }
158 print(pv);
159 out<-rbind(out,c(paste(\"Scale\", scale, sep=\"_\"),format(temp[m], digits = 3),pv,tail));
160 }
161 final_pvalue <-rbind(final_pvalue, out);
162 }
163 colnames(final_pvalue) <- title;
164 return(final_pvalue);
165 }\n";
166
167 print Rcmd "
168 # execute
169 # read in data
170 data_test = final = NULL;
171 sub = sub_names = NULL;
172 data_test <- read.delim(\"$inputFile\",header=FALSE);
173 pdf(file = \"$pdf\", width = 11, height = 8)\n";
174
175 for ($x=0;$x<$features_count;$x++){
176 $feature=$features[$x];
177 print Rcmd "
178 if ($feature > ncol(data_test))
179 stop(\"column $feature doesn't exist\");
180 sub<-data_test[,$feature];
181 #sub_names <- colnames(data_test);
182 sub_names<-colnames(data_test)[$feature];
183 final <- rbind(final,dwt_var_permut_getMax(sub, sub_names,$alpha));\n";
184 }
185
186 print Rcmd "
187
188 dev.off();
189 write.table(final, file = \"$pvalue\", sep = \"\\t\", quote = FALSE, row.names = FALSE);
190
191 #eof\n";
192
193 close Rcmd;
194 system("R --no-restore --no-save --no-readline < $r_script > $r_script.out");
195
196 #close the input and output and error files
197 close(OUTPUT3);
198 close(OUTPUT2);
199 close(INPUT);