Nothing
#' @export
#'
meanEveryN <-
function(x, n=2, lag=round(n/2),showsamples=FALSE) {
# only to be applied to a vector (x) of data
# will first convert vector to a matrix of n rows by length/n columns
# thus allowing for apply to be invoked across a specific column of values
# if each column is n samples in size
# added lag to allow the mean calculation to be centred around
# the sample period appropriately
if(n==1) y<-1; z<-1
if (n>1)
{
t<-seq(0,length(x)-1,1) # create a 'false time index' going from 0 to length of vector
lagx<-x[lag:length(x)] # re-sample vector x, going from sample (N)/2: will alow to centre calculations for slope
len<-length(lagx)
rem<-len/n-trunc(len/n) # check if vector is evenly divisible by # samples
newlen<-len-rem*n
lagt<-t[lag:length(t)] # create corresponding time vector according to the lag
final.x<-rep(NA,newlen) # create new vector (xxx) that is an evenly divisible length filled with NA
final.t<-rep(NA,newlen) # create new vector (ttt) that is an evenly divisible length filled with NA
#lagx<-replace(xx,1:newlen,x) # fill xx with the values from x, leaving final NA values if exist
final.x<-lagx[1:newlen]
final.t<-lagt[1:newlen]
resam<-matrix(matrix(final.x), nrow=n) # convert vector to matrix to allow the BY column calculation
retim<-matrix(matrix(final.t), nrow=n) # convert
y<-apply(retim,2,mean)
z<-apply(resam,2,mean)
}
if(showsamples==FALSE)
{
zz<-z
}
else if(showsamples==TRUE)
{
zz<-cbind(y,z)
colnames(zz)<-c("Sample","Mean")
}
zz<-zz
}
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