When the raw data obtained from an experiment is too noisy and you need to smooth-en it to better represent the trend, you need to calculate the
moving average . Moving average is nothing but average of
n previous numbers, with a specific step size. Let me give an example: if there are 100 numbers, then moving average is calculated by averaging 1-15, 2-16, 3-17 and so on. Here, the n is 15 and step size is 1.
The R script to do this:
datain <- read.table("input.txt", header=1) field2 = datain[,2] coef15 = 1/15 mvavg15 = filter(field2, rep(coef15, 15), sides=1) jpeg('input.jpg') plot(mvavg15, type="l", main="Plot Title", xlab="X label", ylab="Y label") dev.off()
Here, the data is assumed to be 2 column, first with serial number and second with value.