= Final Functions =
== Funtion: Reading File ==

Here is the function as whole, below we go through it line by line.

{{{#!highlight r
read.file <- function(file,skip,verbose=T){
    if(verbose) print(paste("read", file))
    tmp <- read.table(file,skip = skip,sep = "\t",
                      header=T,na.strings = c(" +",""),
                      fill=T)
    
    tmp <- tmp[!is.na(tmp$Subject),] 

    if(sum(!str_detect(tmp[,1],"^0[012][0-9]_[1-8]$|^0[012][0-9]_test[12]$")))
        print(paste("id",tmp$Subject[1]))
    
    if(sum(tmp$Stim.Type %in% c("hit","incorrect"))==0) return(NULL)

    tmp <- lapply(tmp,function(x) {
        if( class(x) %in% c("character","factor") ){
            x <- factor(gsub(" ","",as.character(x)))
            return(x)}else{ return(x) }})
    
    tmp <- as.data.frame(tmp)
    
    pause <- which(tmp$Event.Type=="Picture" & tmp$Code=="Pause")
    if(length(pause)>0){
        drei <- which(tmp$Code==3 & !is.na(tmp$Code))
        drei <- drei[drei > pause][1:2]
        if(pause + 1 < drei[1]){
            tmp <- tmp[-(pause:drei[2]),]
        }}

    
    tmp <- tmp[!(tmp$Event.Type %in% c("Pause","Resume")), ]

    first.pic <- min(which(tmp$Event.Type=="Picture" & !is.na(tmp$Event.Type) )) - 1
    tmp <- tmp[-(1:first.pic),]

    last.pic <- min(which(tmp$Event.Type=="Picture" & !is.na(tmp$Event.Type) &
                              tmp$Code=="Fertig!" & !is.na(tmp$Code)))
    tmp <- tmp[-(last.pic:nrow(tmp)),]

    zeilen <- which(tmp$Event.Type %in% c("Response"))
    zeilen <- sort(unique(c(zeilen,zeilen-1)))
    zeilen <- zeilen[zeilen>0]
    tmp <- tmp[zeilen,]
    
    responses <- which(tmp$Code %in% c(1,2))
    events <- responses-1
    tmp$Type <- NA
    tmp$Type[responses] <- as.character(tmp$Event.Type[events])

    if(length(tmp$Type[responses])!=length(tmp$Event.Type[events])) { print(file)}
    tmp$Event.Code <- NA
    tmp$Event.Code[responses] <- as.character(tmp$Code[events])
    tmp$Time1 <- NA
    tmp$Time1[responses] <- tmp$Time[events]
    tmp$Stim.Type[responses] <- as.character(tmp$Stim.Type[events])
    tmp$Duration[responses] <- as.character(tmp$Duration[events])
    tmp$Uncertainty.1[responses] <- as.character(tmp$Uncertainty.1[events])
    tmp$ReqTime[responses] <- as.character(tmp$ReqTime[events])
    tmp$ReqDur[responses] <- as.character(tmp$ReqDur[events])
    tmp$Pair.Index[responses] <- as.character(tmp$Pair.Index[events])
    

    tmp$Stim.Type[responses] <- as.character(tmp$Stim.Type[events])
    tmp <- tmp[tmp$Event.Type=="Response" & !is.na(tmp$Type),]
    tmp <- tmp[tmp$Type=="Picture" & !is.na(tmp$Type),]
    return(tmp)
}
}}}


=== line 1 ===
 * [[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_1|line 1]] gives the function its name including arguments and their default values
 * the file argument will take the file name and is without a default
 * skip takes a number which indicates how many lines will be skipped at the beginning of the file
 * verbose indicates if the file name will be printed out while reading

{{{#!highlight r
 read.file <- function(file,skip=3,verbose=T){
}}}

=== line 2 ===
{{{#!highlight r
 if(verbose) print(paste("read", file))
}}}

 * [[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_2|this line]] just prints out the name of the file while reading it unless verbose is set to wrong

=== Line 3-5 ===
 * [[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_3|here]] we have the command to read in the text file
 * it takes the skip argument from above
 * we are setting sep which indicates the field separator to tab
 * set header to T because the file contains the columns names
 * with setting na.strings to the empty string or any string containing only spaces to we indicate to code this fields as missings
 * [[/ReadingFiles|more on reading files]] 
{{{#!highlight r
 tmp <- read.table(file,skip = skip,sep = "\t",
                          header=T,na.strings = c(" +",""),
                          fill=T)
}}}

=== Line 7 ===
 * [[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_7|here]] we remove all rows with a missing Subject field
 * therefore we need indexing
 * is.na(x) gives back a logical vector, containing TRUE for missings in x and FALSE for any existing value
 * [[/indeXing|read more on indexing/subscripting]]
{{{#!highlight r
    tmp <- tmp[!is.na(tmp$Subject),] 

}}}

=== Line 9-10 ===
 * [[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_9|Line 9 and 10]] print the content of Subject to stdout if the content is not in standard form
 * str_detect() is a R function and part of the stringr package it gives back a logical value dependend on if the pattern is contained in the given string
 * the pattern is a regular expression which is more flexible than to use absolut strings
 * so we check every entry of Subject, take the negation and sum the resulting logical vector - this sum is zero if no deviant Subject coding is found, otherwise the print command is executed
 * [[/StringOperations|some basic information about strings and regular expression can be found here]]

{{{#!highlight r
    if(sum(!str_detect(tmp$Subject,"^0[012][0-9]_[1-8]$|^0[012][0-9]_test[12]$")))
        print(paste("id",tmp$Subject[1]))
}}}





[[#CA-a8692f97d06bd15e4a572260cf8b72ef3c9d984e_18|Line 18]]: 


[[#CA-efbf8a93fbd22f17bfbdcb535a155bbb9c389093_22|Line 22]]: 



== Funtion: Reading All Files from a DIRECTORY ==

{{{#!highlight r
read.files <- function(filesdir,skip=3,...){
    files <- paste(filedir,dir(filedir),sep="/")
    Reduce(rbind,lapply(files,read.file,skip=skip))}
}}}