How do I get a symbolic differentiation of cfit/sfit functions?

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Hi everyone,
I am trying to get the symbolic partial derivative of a sfit function. Best case would be having the differentition as an sfit function, too.
Thanks in advance!
EDIT:
Here's an example:
%data
x = [0.5850;0.0734;0.8223;0.7229;0.9259;0.4926];
y = [0.6549;0.8901;0.5385;0.2822;0.9760;0.0364];
z = [0.3262;0.9730;0.3650;0.3091;0.1209;0.9158];
%surface fit
sf = fit([x, y],z,'poly22')
plot(sf)
% Linear model Poly22:
% sf(x,y) = p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2
% Coefficients:
% p00 = 5.048
% p10 = -11.04
% p01 = -1.326
% p20 = 5.179
% p11 = 5.682
% p02 = -3.135
Now I could use the differentiate method to get the derivative at specific points but I would like to have the derived function, like this (witthout having to derive it manually):
% sf_x(x,y) = p10 + 2*p20*x + p11*y

采纳的回答

Walter Roberson
Walter Roberson 2019-12-16
When sf is the fit object,
f = subs(str2sym(formula(sf)),coeffnames(sf),num2cell(coeffvalues(sf).'));
vars = sym(indepnames(sf));
diff(f, vars(1))
  5 个评论
Walter Roberson
Walter Roberson 2019-12-20
The upper and lower bounds are in the fit options, which I have it add in via 'options', fitoptions(sf)

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