PT:average absoulte residuals
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scripts/createFit.m
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40
scripts/createFit.m
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function [fitresult, gof] = createFit(SA, FY)
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%CREATEFIT(SA,FY)
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% Create a fit.
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%
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% Data for 'untitled fit 1' fit:
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% X Input: SA
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% Y Output: FY
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% Output:
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% fitresult : a fit object representing the fit.
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% gof : structure with goodness-of fit info.
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%
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% See also FIT, CFIT, SFIT.
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% Auto-generated by MATLAB on 04-Jan-2024 14:49:41
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%% Fit: 'untitled fit 1'.
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[xData, yData] = prepareCurveData( SA, FY );
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% Set up fittype and options.
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ft = fittype( 'fourier8' );
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opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
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opts.Display = 'Off';
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opts.MaxFunEvals = 100000;
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opts.MaxIter = 50000;
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opts.StartPoint = [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7.29927003160889];
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% Fit model to data.
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[fitresult, gof] = fit( xData, yData, ft, opts );
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% % Plot fit with data.
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% figure( 'Name', 'untitled fit 1' );
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% h = plot( fitresult, xData, yData );
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% legend( h, 'FY vs. SA', 'untitled fit 1', 'Location', 'NorthEast', 'Interpreter', 'none' );
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% % Label axes
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% xlabel( 'SA', 'Interpreter', 'none' );
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% ylabel( 'FY', 'Interpreter', 'none' );
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% grid on
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@ -1,6 +1,7 @@
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%% please open Magic Formular APP first
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clear
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n = 20; % <=60
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n = 20
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mkdir('similarityData');
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%%
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directoryPath = "..\sorted_data";
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subdirectories = getSubdirectories(directoryPath);
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@ -13,7 +14,7 @@ subdirectories_list = contents([contents.isdir] & ~ismember({contents.name}, {'.
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% Extract and display the names of the subdirectories
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subdirectoryNames = {subdirectories_list.name};
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%%
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%%
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figure()
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for i=1:length(subdirectories)
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@ -23,6 +24,7 @@ for i=1:length(subdirectories)
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measurement = measurements(n);
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[SX,SA,FZ,IP,IA,VX,FX,FY,MZ,MY,MX,W,T] = unpack(measurement);
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FY = smoothdata(FY, "gaussian",100);
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if i < length(subdirectories)/3
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plot(SA, FY, 'LineWidth', 1)
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elseif i <= length(subdirectories)/3*2
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@ -30,9 +32,27 @@ for i=1:length(subdirectories)
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else
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plot(SA, FY, '-.','LineWidth', 1)
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end
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SAA{i} = SA;
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FYY{i} = FY;
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hold on
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end
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legend(subdirectoryNames{:})
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title("Similarities, n=",n)
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xlabel("Slip Angle")
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ylabel("FY")
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ylabel("FY")
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%% without plot
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for n=1:60
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for i=1:length(subdirectories)
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fileMeasurement = fullfile("..\sorted_data", subdirectories{i}, "\cornering.mat");
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parser = tydex.parsers.FSAETTC_SI_ISO_Mat();
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measurements = parser.run(fileMeasurement);
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measurement = measurements(n);
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[SX,SA,FZ,IP,IA,VX,FX,FY,MZ,MY,MX,W,T] = unpack(measurement);
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FY = smoothdata(FY, "gaussian",100);
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SAA{i} = SA;
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FYY{i} = FY;
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end
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file_name = ['similarityData\nEqu' num2str(n) '.mat'];
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save(file_name, 'SAA', 'FYY');
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end
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58
scripts/similarities2.m
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scripts/similarities2.m
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clear;
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clc;
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% Use the dir function to get information about files and directories
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directoryPath = ".\similarityData";
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% Get a list of all files in the directory
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files = dir(fullfile(directoryPath, '*.mat')); % You can adjust the file extension as needed
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% Extract file names
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fileNames = {files.name};
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for n=1:length(fileNames)
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% fit the curve of 43075 , 8 inch
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filePath = fullfile(directoryPath, fileNames(n));
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load(filePath)
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[fitresult, gof] = createFit(SAA{8},FYY{8});
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residual = [];
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% Evaluate the fitted curves
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for i=1:length(SAA)
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y_fit = fitresult(SAA{i});
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% Calculate residuals
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residual = [residual, mean(abs(FYY{i} - y_fit))];
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end
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residuals{n} = residual;
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end
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for i=1:length(residual)
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residuals_sum{i} = 0;
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num = length(fileNames);
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for j=1:length(fileNames)
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if isnan(residuals{j}(i))
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num = num - 1;
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residuals{j}(i) = 0;
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end
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residuals_sum{i} = residuals{j}(i) + residuals_sum{i};
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end
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residuals_mean{i} = residuals_sum{i}/num;
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end
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% figure()
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% idx = linspace(1,length(SAA),length(SAA));
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% for i=1:length(fileNames)
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% plot(idx, residuals{i}, "-*")
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% hold on;
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% end
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% title("Residuials")
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% legend(fileNames)
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% xlabel("order of the tires(8 is our traget tire)")
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figure()
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idx = linspace(1,length(SAA),length(SAA));
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y = cell2mat(residuals_mean)
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plot(idx, y, "-*")
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title("Average Absolute Residuials")
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legend(fileNames)
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xlabel("order of the tires(8 is our traget tire)")
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xticks(idx)
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grid on
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