I have generated some real data of the motion of a damping pendulum:
I took its derivative in R by taking the difference of consecutive points and dividing by difference in time. There are 1202 data points in this picture.
That gave this graph:
I took the derivative of this graph again:
However, this graph is very erratic and unusable for analysis. I was wondering if there is a function in R which allows for accurate numerical differentiation? I know of Fourier Transforms although I'm not sure how to directly apply them on a damping pendulum.
This is a function I'm using in R to compute the derivative:
derivative <- function(x,y,deriv0){
# deriv0 = value of the derivative at time zero
deriv <- diff(y[2:length(x)]) / diff(x[2:length(y)])
w = length(x)-2
deriv <- c(deriv0,deriv[1:w])
time <- x[1:length(x)-1]
return(data.frame(time,deriv))
}
The original dataset is here:
Thanks
I ended up finding a simple and elegant solution.
library(pspline)
t <- time vector
x <- data vector
For the first derivative:
deriv1st <- predict(sm.spline(t, x), t, 1)
plot(t,deriv1st)
For the second derivative:
deriv2nd <- predict(sm.spline(t, x), t, 2)
plot(t,deriv2nd)
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