[Swift-commit] r3045 - in SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis: . Rturning
noreply at svn.ci.uchicago.edu
noreply at svn.ci.uchicago.edu
Wed Aug 5 16:05:28 CDT 2009
Author: andric
Date: 2009-08-05 16:05:28 -0500 (Wed, 05 Aug 2009)
New Revision: 3045
Added:
SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/
SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/for3dDecon.PK2_4condSHORTcat_all.1D
SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/turnchi.R
Log:
this dir holds the R script and design matrix
Added: SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/for3dDecon.PK2_4condSHORTcat_all.1D
===================================================================
--- SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/for3dDecon.PK2_4condSHORTcat_all.1D (rev 0)
+++ SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/for3dDecon.PK2_4condSHORTcat_all.1D 2009-08-05 21:05:28 UTC (rev 3045)
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Added: SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/turnchi.R
===================================================================
--- SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/turnchi.R (rev 0)
+++ SwiftApps/SIDGrid/swift/projects/andric/peakfit_pilots/PK2/turnpointAnalysis/Rturning/turnchi.R 2009-08-05 21:05:28 UTC (rev 3045)
@@ -0,0 +1,174 @@
+### TURNPOINTS
+library(akima)
+library(pastecs)
+
+allargs <- Sys.getenv("R_SWIFT_ARGS")
+print(allargs)
+
+outprefix <- noquote(strsplit(allargs," ")[[1]][2])
+print(outprefix)
+output_file_prefix <- paste(outprefix)
+vertnum <- noquote(strsplit(allargs," ")[[1]][3])
+vertnum <- as.numeric(vertnum)
+print(vertnum)
+hemi <- noquote(strsplit(allargs," ")[[1]][4])
+h <- paste(hemi)
+print(h)
+tar_name <- noquote(strsplit(allargs," ")[[1]][5])
+tar_name <- paste(tar_name)
+print(tar_name)
+
+inputfilename <- Sys.getenv("R_INPUT")
+
+inputTS <- as.matrix(read.table(inputfilename))
+inputTS <- data.frame(inputTS[1,])[,1]
+print(length(inputTS))
+
+
+#### Now do peak and valley analysis based on turnpoints
+
+ts_turnpoints <- turnpoints(inputTS)
+ts_peaks <- (1:length(inputTS))[extract(ts_turnpoints, no.tp = FALSE, peak = TRUE, pit = FALSE)]
+ts_valleys <- (1:length(inputTS))[extract(ts_turnpoints, no.tp = FALSE, peak = FALSE, pit = TRUE)]
+lower = 1
+
+ts_peaks_and_valleys <- NULL
+# this if loop is for when we start with a valley
+if (ts_peaks[1] > ts_valleys[1]) {
+ # this section fills from time 1 to the pitt with "v"
+ upper <- ts_valleys[lower]
+ for (i in seq(lower,upper)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "v")
+ }
+ # this section alternates between the base of a peak to the peak back down to the pitt, etc
+ for (lower in c(1:min(length(ts_peaks),length(ts_valleys)))) {
+ valley_index <- ts_valleys[lower]
+ peak_index <- ts_peaks[lower]
+ for (i in seq(valley_index,peak_index-1)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "p")
+ }
+ if (lower < max(length(ts_peaks),length(ts_valleys))) {
+ valley_index <- ts_valleys[lower+1]
+ for (i in seq(peak_index,valley_index-1)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "v")
+ }
+ }
+ }
+ # if you started with valley end with peak
+ valley_index <- max(ts_valleys,ts_peaks)+1
+ peak_index <- length(inputTS)
+ for (i in seq(valley_index,peak_index)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "p")
+ }
+ #PCs_peaks_and_valleys[,column] <- ts_peaks_and_valleys
+ #column <- column +1
+} else if (ts_peaks[1] < ts_valleys[1]) { # this if loop is for when we start with a peak
+ # this section fills from time 1 to the peak with "p"
+ upper <- ts_peaks[lower]
+ for (i in seq(lower,upper)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "p")
+ }
+ # this section alternates between the base of a peak to the peak back down to the pitt, etc
+ for (lower in c(1:(min(length(ts_peaks),length(ts_valleys))))) {
+ valley_index <- ts_peaks[lower]
+ peak_index <- ts_valleys[lower]
+ for (i in seq(valley_index,peak_index-1)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "v")
+ }
+ if (lower < max(length(ts_peaks),length(ts_valleys))) {
+ valley_index <- ts_peaks[lower+1]
+ for (i in seq(peak_index,valley_index-1)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "p")
+ }
+ }
+ }
+ # if you started with peak end with valley
+ valley_index <- max(ts_valleys,ts_peaks)+1
+ peak_index <- length(inputTS)
+ for (i in seq(valley_index,peak_index)) {
+ ts_peaks_and_valleys <- c(ts_peaks_and_valleys, "v")
+ }
+ #PCs_peaks_and_valleys[,column] <- ts_peaks_and_valleys
+ #column <- column +1
+}
+
+### would've written out here, but trying tpchisqtest instead
+
+write.table(ts_peaks_and_valleys,"ts_peak_valley.tmp",row.name = F,col.name = F,append=FALSE)
+ts_peaks_and_valleys <- read.table("ts_peak_valley.tmp")
+
+coded <- read.table("Rturning/for3dDecon.PK2_4condSHORTcat_all.1D")
+annotation_recode <- ""
+annotation_recode[coded[,1]==1] <- "still"
+annotation_recode[coded[,2]==1] <- "move"
+annotation_recode[coded[,3]==1] <- "still"
+annotation_recode[coded[,4]==1] <- "move"
+annotation_recode[which(is.na(annotation_recode))] <- "blank"
+
+# set the resulting recoded attributes of interest as variables
+# the primary attribute should go first
+dimension_1 <- "move"
+dimension_2 <- "still"
+
+
+#### source call was here !!!!!!!
+
+## don't need to read in this var, never wrote it out..........ts_peaks_and_valleys <- read.table(inputfilename)
+## annotation shift:
+## by TR (ts & coding not resampled here)
+#matrix_to_add_to_ts_peaks_and_valleys <- matrix(ncol=1,nrow=10,data=0)
+#ts_peaks_and_valleys <- rbind(ts_peaks_and_valleys,matrix_to_add_to_ts_peaks_and_valleys)
+
+# set lags
+#lags <- as.factor(c(0,.5,1,1.5,2,2.5,3,3.5,4,4.5,5,5.5,6,6.5,7,7.5,8,8.5,9,9.5,10))
+lags <- as.factor(c(0,1,2,3,4,5,6))
+
+for (lag in as.numeric(levels(lags))) {
+
+ # Now we need to pad the "annotation_recode" file in an appropriate manner
+ if (lag == 0) {
+ annotation_recode_short <- as.matrix(annotation_recode)
+ #add_to_end_of_annotation_recode_short <- matrix(ncol=1,nrow=0,data=0)
+ #annotation_recode_long <- as.character(rbind(annotation_recode_short,add_to_end_of_annotation_recode_short))
+ annotation_recode_long <- annotation_recode_short
+ }
+
+ if (lag > 0 && lag < 6) {
+ annotation_recode_short <- as.matrix(annotation_recode)
+ beginning_number_of_rows <- lag*1
+ end_number_of_rows <- 6-lag*1
+ add_to_beginning_of_annotation_recode_short <- matrix(ncol=1,nrow=beginning_number_of_rows,data=0)
+ add_to_end_of_annotation_recode_short <- matrix(ncol=1,nrow=end_number_of_rows,data=0)
+ annotation_recode_long <- as.character(rbind(add_to_beginning_of_annotation_recode_short,annotation_recode_short,add_to_end_of_annotation_recode_short))
+ }
+
+ if (lag == 6) {
+ annotation_recode_short <- as.matrix(annotation_recode)
+ add_to_beginning_of_annotation_recode_short <- matrix(ncol=1,nrow=6,data=0)
+ annotation_recode_long <- as.character(rbind(add_to_beginning_of_annotation_recode_short,annotation_recode_short))
+ }
+
+ contingency_table <- matrix(ncol=2,nrow=2)
+ one_way_contingency_table_results <- matrix(nrow = 1, ncol= 5)
+ #colnames(one_way_contingency_table_results) <- c("attribute_at_peak", "attribute_at_valley", "x_square", "p_value")
+ two_way_contingency_table_results <- matrix(nrow = 1, ncol= 7)
+ #colnames(two_way_contingency_table_results) <- c("attribute_at_peak", "no_attribute_at_peak", "attribute_at_valley", "no_attribute_at_valley", "x_square", "p_value")
+
+ ts_PVdata <- ts_peaks_and_valleys[,1]
+ contingency_table <- matrix(ncol=2,nrow=2,dimnames = list(c(dimension_1, dimension_2),c("Peak", "Pit")))
+ # This converts the amount of time to TR. Do we like this?
+ contingency_table[1,1] <- length(which(ts_PVdata[annotation_recode_long==dimension_1]=="p"))
+ contingency_table[1,2] <- length(which(ts_PVdata[annotation_recode_long==dimension_1]=="v"))
+ contingency_table[2,1] <- length(which(ts_PVdata[annotation_recode_long==dimension_2]=="p"))
+ contingency_table[2,2] <- length(which(ts_PVdata[annotation_recode_long==dimension_2]=="v"))
+ one_way_chisq_contingency_table <- chisq.test(as.table(contingency_table[1,]))
+ two_way_chisq_contingency_table <- chisq.test(as.table(contingency_table))
+
+ one_way_contingency_table_results[1,] <- c(vertnum,as.vector(c(as.vector(contingency_table[1,]),one_way_chisq_contingency_table$statistic, one_way_chisq_contingency_table$p.value)))
+ two_way_contingency_table_results[1,] <- c(vertnum,as.vector(contingency_table),two_way_chisq_contingency_table$statistic, two_way_chisq_contingency_table$p.value)
+
+ write.table(round(one_way_contingency_table_results,4),paste(output_file_prefix,".lag",lag,".oneway.chisqresult",sep=""),row.name = FALSE,col.name = FALSE,append=FALSE)
+
+ write.table(round(two_way_contingency_table_results,4),paste(output_file_prefix,".lag",lag,".twoway.chisqresult",sep=""),row.name = FALSE,col.name = FALSE,append=FALSE)
+}
+system(paste("tar cfz ",tar_name," *.chisqresult",sep=""));
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