This function computes the derivative of data (e.g., angular position) using either a smooth spline fit or numerical gradient.
Usage
compute_derivative(x, y, method = c("spline", "gradient"), deriv = 1)Arguments
- x
A numeric vector representing the independent variable (e.g., time).
- y
A numeric vector representing the dependent variable (e.g., angular position).
- method
A character string specifying the method to compute the derivative. Options are "spline" for smooth spline fitting or "gradient" for numerical gradient using
pracma::gradient. Default is "spline".- deriv
An integer specifying the order of the derivative. Default is 1 for the first derivative. Higher values (e.g., 2) will return higher derivatives (second derivative, etc.).