# Why do my coeffvalues not produce a sensible result?

조회 수: 1(최근 30일)
Nicholas Turton 28 Aug 2019
댓글: Torsten 28 Aug 2019
I have a script that uses the fit fuction on some data using a poly55 fit type. I then use this to get the coeffvalues for the fittted curve and try to replot the surface using the coeffvalues but the result produced is orders of magnitude different from the original data.
Script attached as well as some example data.
Can anyone explain what is happening or recommend a way forward?

댓글을 달려면 로그인하십시오.

### 채택된 답변

Torsten 28 Aug 2019
If you use the 'Normalize','on' fitting option, your polynomial has powers of (x-meanx)/stdx and (y-meany)/stdy instead of x and y.

#### 댓글 수: 2

Nicholas Turton 28 Aug 2019
Hi Torsten,
Can you elaborate. I am new to matlab and not following fully what you mean
I have used
[Psi_d_xData, Psi_d_yData, Psi_d_zData] = prepareSurfaceData( id_ind, iq_ind, Psi_d);
[Psi_d_fitresult, Psi_d_gof] = fit( [Psi_d_xData, Psi_d_yData], Psi_d_zData, ft, 'Normalize', 'on' );% Fit model to data.
Psi_d_coeffvals = coeffvalues(Psi_d_fitresult);
which when produced numel(Psi_d_coeffvals) = 21
Using the poly55 eqation
f(x,y) = p00 + p10*x + p01*y + p20*x^2 + p11*x*y + p02*y^2 + p30*x^3 + p21*x^2*y
+ p12*x*y^2 + p03*y^3 + p40*x^4 + p31*x^3*y + p22*x^2*y^2
+ p13*x*y^3 + p04*y^4 + p50*x^5 + p41*x^4*y + p32*x^3*y^2
+ p23*x^2*y^3 + p14*x*y^4 + p05*y^5
...I have then called up each of these coeffvals as well as my desired x and y values to try and reproduce the curve but only could manage the following
Are you saying I need to calculate the mean and std values of x and y and use these in the calculation?
Torsten 28 Aug 2019
if you switch the mentioned option off, you can use the polynomial you defined in the calculation.
Otherwise you will have to insert (x-meanx)/stdx for x and (y-meany)/stdy for y in the calculation for your polynomial value:
f(x,y) = p00 + p10*(x-meanx)/stdx + p01*(y-meany)/stdy + p20*((x-meanx)/stdx))^2 + ...

댓글을 달려면 로그인하십시오.

### 추가 답변(1개)

Nicholas Turton 28 Aug 2019
Thanks Torsten, it worked perfectly
function output_fit = fittingcurve(x_data, y_data, coeffvals)
x_mean = mean(x_data(1,:));
x_std = std(x_data(1,:));
y_mean = mean(y_data(:,1));
y_std = std(y_data(:,1));
output_fit = ...
coeffvals(1) ...
+ coeffvals(2).*((x_data-x_mean)./x_std) ...
+ coeffvals(3).*((y_data-y_mean)./y_std) ...
+ coeffvals(4).*((x_data-x_mean)./x_std).^2 ...
+ coeffvals(5).*((x_data-x_mean)./x_std).*((y_data-y_mean)./y_std) ...
+ coeffvals(6).*((y_data-y_mean)./y_std).^2 ...
+ coeffvals(7).*((x_data-x_mean)./x_std).^3 ...
+ coeffvals(8).*((x_data-x_mean)./x_std).^2.*((y_data-y_mean)./y_std) ...
+ coeffvals(9).*((x_data-x_mean)./x_std).*((y_data-y_mean)./y_std).^2 ...
+ coeffvals(10).*((y_data-y_mean)./y_std).^3 ...
+ coeffvals(11).*((x_data-x_mean)./x_std).^4 ...
+ coeffvals(12).*((x_data-x_mean)./x_std).^3.*((y_data-y_mean)./y_std) ...
+ coeffvals(13).*((x_data-x_mean)./x_std).^2.*((y_data-y_mean)./y_std).^2 ...
+ coeffvals(14).*((x_data-x_mean)./x_std).*((y_data-y_mean)./y_std).^3 ...
+ coeffvals(15).*((y_data-y_mean)./y_std).^4 ...
+ coeffvals(16).*((x_data-x_mean)./x_std).^5 ...
+ coeffvals(17).*((x_data-x_mean)./x_std).^4.*((y_data-y_mean)./y_std) ...
+ coeffvals(18).*((x_data-x_mean)./x_std).^3.*((y_data-y_mean)./y_std).^2 ...
+ coeffvals(19).*((x_data-x_mean)./x_std).^2.*((y_data-y_mean)./y_std).^3 ...
+ coeffvals(20).*((x_data-x_mean)./x_std).*((y_data-y_mean)./y_std).^4 ...
+ coeffvals(21).*((y_data-y_mean)./y_std).^5;

댓글을 달려면 로그인하십시오.

### Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by