how to do curve fiting of polynom?

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elina sk
elina sk 2019-1-3
编辑： Star Strider 2019-1-3
q_vec=-0.0141600000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.00943999999999996 -0.00944000000000003 -0.00944000000000003 -0.00707999999999998 -0.00707999999999998 -0.00472000000000001
s_veq=0.700000000000000 0.909545454545454 1.11909090909091 1.32863636363636 1.53818181818182 1.74772727272727 1.95727272727273 2.16681818181818 2.37636363636364 2.58590909090909 2.79545454545455 3.00500000000000
plot(s_veq,q_vec)
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Luna
Luna 2019-1-3
Hi Elina,
Please first explain your question clearly and what do you want to do.
Also please correct your syntax error on that code part you have shared.

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回答（2 个）

Star Strider
Star Strider 2019-1-3
编辑：Star Strider 2019-1-3
Try this:
q_vec = [-0.0141600000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.00943999999999996 -0.00944000000000003 -0.00944000000000003 -0.00707999999999998 -0.00707999999999998 -0.00472000000000001];
s_veq = [0.700000000000000 0.909545454545454 1.11909090909091 1.32863636363636 1.53818181818182 1.74772727272727 1.95727272727273 2.16681818181818 2.37636363636364 2.58590909090909 2.79545454545455 3.00500000000000];
plot(s_veq,q_vec)
How are ‘S’ and ‘Q’ related to ‘s_veq’ and ‘q_vec’?
EDIT —
With respect to fitting them, it depends on what you want to do.
Two examples:
q_vec = [-0.0141600000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.00943999999999996 -0.00944000000000003 -0.00944000000000003 -0.00707999999999998 -0.00707999999999998 -0.00472000000000001];
s_veq = [0.700000000000000 0.909545454545454 1.11909090909091 1.32863636363636 1.53818181818182 1.74772727272727 1.95727272727273 2.16681818181818 2.37636363636364 2.58590909090909 2.79545454545455 3.00500000000000];
p1 = polyfit(s_veq,q_vec,1);
v1 = polyval(p1, s_veq);
p5 = polyfit(s_veq,q_vec,5);
v5 = polyval(p5, s_veq);
figure
plot(s_veq,q_vec, 'pg', 'MarkerFaceColor','g')
hold on
plot(s_veq, v1, '-b')
plot(s_veq, v5, '-r')
hold off
grid
legend('Data', '1^{st}-Order Polynomial', '5^{th}-Order Polynomial', 'Location', 'NW')
Luna
Luna 2019-1-3
As far as I understand from your question I have fixed your array definition as follows:
Please read my comments below. And check this link for more info: Polynomial Curve Fitting
q_vec= [-0.0141600000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.0118000000000000 -0.00943999999999996 -0.00944000000000003 -0.00944000000000003 -0.00707999999999998 -0.00707999999999998 -0.00472000000000001];
s_veq=[0.700000000000000 0.909545454545454 1.11909090909091 1.32863636363636 1.53818181818182 1.74772727272727 1.95727272727273 2.16681818181818 2.37636363636364 2.58590909090909 2.79545454545455 3.00500000000000];
%% Fitting part
p = polyfit(s_veq,q_vec,2); % gets the coeffs of fitted polynomial, I used 2nd degree you can change it by yourself as you wish.
f = polyval(p,s_veq); % creates the new y axis values from that polynomial.
plot(s_veq,q_vec,'*r',s_veq,f,'-b'); % plots red stars the existing data and blue line for fitted data.
% your polynomial coefficients are in the array p with P(X) = P(1)*X^N + P(2)*X^(N-1) +...+ P(N)*X + P(N+1) descending order.
% your polynomial results are in the array f which gives Y = P(X).

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