Given data values of some real-time physical process (e.g. network traffic) it is to find a name of the function which “at best” matches with the data.
I have a set of functions of type y=f(t) where y and t are real:
funcs = set([cos, tan, exp, log])
and a list of data values:
vals = [59874.141, 192754.791, 342413.392, 1102604.284, 3299017.372]
What is the simplest possible method to find a function from given set which will generate the very similar values?
PS: t is increasing starting from some positive value by almost-equal intervals
Scipy has functions for fitting data, but they use polynomes or splines. You can use one of Gauß’ many discoveries, the method of least squares to fit other functions.