Generate Code from Curve Fitting App

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Hello! so I have multiple sets of data, each of 2 independent (coordinates in space) and 1 dependent (energy flux) variables for which I am trying to find a suitable surface fit. I have used the curve fitting app to generate a polyinomial surface fit for one of the data sets (I did it manually at first and then genrated its function code); however, the code generated gives a total of 25 plots when run, which is unnecessary.
In short, what I am trying to do is generate a surface fitting function (creatFit) and then edit so that it finds the best fit possible (highest R-square value with no center and scale warrning) and then plot the this best fit only. I need this in a code so that I do not have to do it manually in the app for every data set. Furthermore, I want to have a matrix or table that shows the degree of each curve, its R-square, and weather any warning (center and scale) were ditected for that fit. The code segment I currently have is as below, I have deleted the plotting commands:
function [fitresult, gof] = createFits(z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy)
%CREATEFITS(Z_LEFT_BOTTOM,X_LEFT_BOTTOM,EB_LEFT_BOTTOM_STRIP_ARRAY_ENERGY)
% Create fits.
%
% Data for fit:
% X Input : z_Left_Bottom
% Y Input : x_Left_Bottom
% Z Output: Eb_Left_Bottom_strip_array_energy
% Output:
% fitresult : a cell-array of fit objects representing the fits.
% gof : structure array with goodness-of fit info.
%% Initialization.
% Initialize arrays to store fits and goodness-of-fit.
fitresult = cell( 25, 1 );
gof = struct( 'sse', cell( 25, 1 ), ...
'rsquare', [], 'dfe', [], 'adjrsquare', [], 'rmse', [] );
%% Fit: '1x1'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly11' );
% Fit model to data.
[fitresult{1}, gof(1)] = fit( [xData, yData], zData, ft );
%% Fit: '2x1'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly21' );
% Fit model to data.
[fitresult{2}, gof(2)] = fit( [xData, yData], zData, ft );
%% Fit: '3x1'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly31' );
% Fit model to data.
[fitresult{3}, gof(3)] = fit( [xData, yData], zData, ft );
%% Fit: '4x1'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly41' );
% Fit model to data.
[fitresult{4}, gof(4)] = fit( [xData, yData], zData, ft );
%% Fit: '5x1'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly51' );
% Fit model to data.
[fitresult{5}, gof(5)] = fit( [xData, yData], zData, ft );
%% Fit: '1x2'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly12' );
% Fit model to data.
[fitresult{6}, gof(6)] = fit( [xData, yData], zData, ft );
%% Fit: '2x2'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly22' );
% Fit model to data.
[fitresult{7}, gof(7)] = fit( [xData, yData], zData, ft );
%% Fit: '3x2'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly32' );
% Fit model to data.
[fitresult{8}, gof(8)] = fit( [xData, yData], zData, ft );
%% Fit: '4x2'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly42' );
% Fit model to data.
[fitresult{9}, gof(9)] = fit( [xData, yData], zData, ft );
%% Fit: '5x2'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly52' );
% Fit model to data.
[fitresult{10}, gof(10)] = fit( [xData, yData], zData, ft );
%% Fit: '1x3'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly13' );
% Fit model to data.
[fitresult{11}, gof(11)] = fit( [xData, yData], zData, ft );
%% Fit: '2x3'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly23' );
% Fit model to data.
[fitresult{12}, gof(12)] = fit( [xData, yData], zData, ft );
%% Fit: '3x3'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly33' );
% Fit model to data.
[fitresult{13}, gof(13)] = fit( [xData, yData], zData, ft );
%% Fit: '4x3'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly43' );
% Fit model to data.
[fitresult{14}, gof(14)] = fit( [xData, yData], zData, ft );
%% Fit: '5x3'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly53' );
% Fit model to data.
[fitresult{21}, gof(21)] = fit( [xData, yData], zData, ft );
%% Fit: '1x4'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly14' );
% Fit model to data.
[fitresult{22}, gof(22)] = fit( [xData, yData], zData, ft );
%% Fit: '2x4'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly24' );
% Fit model to data.
[fitresult{23}, gof(23)] = fit( [xData, yData], zData, ft );
%% Fit: '3x4'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly34' );
% Fit model to data.
[fitresult{24}, gof(24)] = fit( [xData, yData], zData, ft );
%% Fit: '4x4'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly44' );
% Fit model to data.
[fitresult{25}, gof(25)] = fit( [xData, yData], zData, ft );
%% Fit: '5x4'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly54' );
% Fit model to data.
[fitresult{15}, gof(15)] = fit( [xData, yData], zData, ft );
%% Fit: '1x5'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly15' );
% Fit model to data.
[fitresult{16}, gof(16)] = fit( [xData, yData], zData, ft );
%% Fit: '2x5'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly25' );
% Fit model to data.
[fitresult{17}, gof(17)] = fit( [xData, yData], zData, ft );
%% Fit: '3x5'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly35' );
% Fit model to data.
[fitresult{18}, gof(18)] = fit( [xData, yData], zData, ft );
%% Fit: '4x5'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly45' );
% Fit model to data.
[fitresult{19}, gof(19)] = fit( [xData, yData], zData, ft );
%% Fit: '5x5'.
[xData, yData, zData] = prepareSurfaceData( z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy );
% Set up fittype and options.
ft = fittype( 'poly55' );
% Fit model to data.
[fitresult{20}, gof(20)] = fit( [xData, yData], zData, ft );
  2 个评论
ABDALLA AL KHALEDI
ABDALLA AL KHALEDI 2023-11-10
编辑:ABDALLA AL KHALEDI 2023-11-10
I am getting a bunch of the following warning, I don't want this warning to be shown but I want it to be recorded (at which fit did it happen)
Warning: Equation is badly conditioned. Remove repeated data points or try centering and scaling.
> In curvefit.attention/Warning/throw (line 30)
In fit>iLinearFit (line 680)
In fit>iFit (line 391)
In fit (line 116)
In createFits (line 109)
ABDALLA AL KHALEDI
ABDALLA AL KHALEDI 2023-11-10
I added the following section to the function to obtain a table of the results of intrest
%% % Initialize a table to store the results
resultTable = table('Size', [25, 3], 'VariableTypes', {'double', 'double', 'double'}, 'VariableNames', {'Degree_in_Z', 'Degree_in_X', 'R_Square'});
% Loop through the fits
for i = 1:25
[xData, yData, zData] = prepareSurfaceData(z_Left_Bottom, x_Left_Bottom, Eb_Left_Bottom_strip_array_energy);
% Set up fittype and options
degreeX = floor((i-1)/5) + 1;
degreeY = mod(i-1, 5) + 1;
% Fit model to data
ft = fittype(['poly', num2str(degreeX), num2str(degreeY)]);
[fitresult{i}, gof(i)] = fit([xData, yData], zData, ft);
% Store results in the table
resultTable.Degree_in_Z(i) = degreeX;
resultTable.Degree_in_X(i) = degreeY;
resultTable.R_Square(i) = gof(i).rsquare;
end
% Display the table
disp(resultTable);
and now I am trying to prevent the center and scale warning from showing but I need to know where it happens, I tried the following but with no luck so far.
warning ('off','curvefit:fit:equationBadlyConditioned')
[fitresult, gof] = createFits(z_Right_Bottom, x_Right_Bottom, Eb_Right_Bottom_strip_array_energy);
warning ('on','curvefit:fit:equationBadlyConditioned')
warning('query','curvefit:fit:equationBadlyConditioned')
stack = dbstack;
disp(dbstack)

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采纳的回答

Drew
Drew 2023-11-17
I copy-pasted your last two comments as a query to the MATLAB AI Chatbot https://www.mathworks.com/matlabcentral/playground/new (see announcement at https://blogs.mathworks.com/community/2023/11/07/the-matlab-ai-chat-playground-has-launched/) and the AI gave this answer in image form (see further below for copy-able code), and note that the AI suggests some possible follow-up questions to ask.
Here is the code snippet provided by the AI:
warning('off', 'curvefit:fit:equationBadlyConditioned')
[fitresult, gof] = createFits(z_Right_Bottom, x_Right_Bottom, Eb_Right_Bottom_strip_array_energy);
[~, lastWarning] = lastwarn();
warning('on', 'curvefit:fit:equationBadlyConditioned')
Here is the doc link for the lastwarn function:
If this answer helps you, please remember to accept the answer, and keep in mind to try the MATLAB AI Chat Playground (https://www.mathworks.com/matlabcentral/playground/new) for your MATLAB questions in the future.

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