How to turn a curve fit into a function

I have been fitting some data generated in the lab. The best fit is by piecewise polynomial

I would now need to turn this into a function that I can then plug in a model (where I repeat this function with different time delays and then sum them up). What is the best way to do this? If I generate a fit wth the FIT function, I am then unable to use that object as a normal function. Any advice?

[Mathieu NOE]

hi

see : Matlab function: pchip – Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) – iTecTec

[Steven Lord]

As Matt J and Walter Roberson stated, you can evaluate the fit by treating it like it was a function. This documentation page shows this technique and also some of the other operations you can perform on the object representing the fitted curve.

Answer 1

[Matt J]

If I generate a fit wth the FIT function, I am then unable to use that object as a normal function.

Sure you can.

x=1:5;
y=x.^2;

f=fit(x(:),y(:),'poly2')

f = 
     Linear model Poly2:
     f(x) = p1*x^2 + p2*x + p3
     Coefficients (with 95% confidence bounds):
       p1 =           1  (1, 1)
       p2 =  -1.619e-14  (-1.234e-13, 9.105e-14)
       p3 =   2.667e-14  (-1.141e-13, 1.674e-13)

f(2)

ans = 4.0000

Answer 2

[Walter Roberson]

If you generate a fit with the fit function, then the result is usable as a function.

fitobj = fit(X(:), Y(:), 'pchip');

xq = linspace(min(X), max(X));
ypred = fitobj(xq);   %notice fitobj has been used as if it is a function
plot(X, Y, '*', xq, ypred, '-')