root/OptimizingMATLABCode/testFitEx/testFitRedo3.m @ 10
| 10 | anderm8 | function testFitRedo3(desiredTest,splineSample)
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%% Example 2
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% Input values desiredTest = 60, splineSample = 200;
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%
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% Load in output of a desired model, fit, filter and evaluate a spline
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% Output written into an excel data file
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% Copyright 2015 The MathWorks, Inc.
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%% Defaults
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if ~nargin
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desiredTest = 60;
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splineSample = 200;
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end
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%% Finding Names of all Text Files in the ModelResults Directory
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xlsfile = 'FinalResults.xls';
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datadir = fullfile(pwd, 'ModelResults');
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modelFiles = dir(fullfile(datadir, '*.txt'));
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if isempty(modelFiles)
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error('No data files.\nRun "FileGenerator.m" in the ModelResults folder')
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else
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numModels = length(modelFiles);
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end
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% Preallocate empty table
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datatable = table;
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disp('Processing test results...')
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%% Reading, Averaging, and Fitting all Text Files
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for ii = 1:numModels
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%% Read in the Relevant Model Data
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fileName = fullfile(datadir, modelFiles(ii).name);
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fid = fopen(fileName);
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% Getting the number of timesteps from the header of the txt file
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nTimes = textscan(fid, '%*s %d \n', 1);
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nTimes = nTimes{1};
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% Read through models we don't want data from and keep resaving model
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% info into modelData until it gets to desiredModel
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textscan(fid, '%*s \n', (nTimes+1) * (desiredTest-1)); % get model output data
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fgets(fid); % read test header line
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modelData = textscan(fid, '%f %f \n', nTimes); % get model output data
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modelData = cell2mat(modelData);
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fclose(fid);
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%% Filter, Fit and Evaluate Spline on Model Data
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nPoints = 10; % setting number of points to average over
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b = (1 / nPoints) * ones(1, nPoints); % moving average over nPoints
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filterData = filter(b, 1, modelData); % create moving average
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splineData = spline(filterData(:, 1), filterData(:, 2)); % create spline
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splineTime = linspace(0, filterData(end, 1), splineSample);
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finalData = ppval(splineData, splineTime); % evaluate spline
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coltitle = {sprintf('time%03d', ii), sprintf('data%03d', ii)};
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datatable.(coltitle{1}) = splineTime';
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datatable.(coltitle{2}) = finalData';
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%% Plot the Results
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subplot(2, 1, 1)
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plot(modelData(:, 1), modelData(:, 2))
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line(filterData(:, 1), filterData(:, 2), 'Color', 'r');
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title('Original and Moving Average')
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subplot(2, 1, 2)
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plot(filterData(:, 1), filterData(:, 2))
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line(splineTime, finalData, 'Color', 'r', 'Marker', '+');
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title('Moving Average and Spline')
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% Force graphics update
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drawnow
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% Save figure
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% saveas(gcf, fullfile('PlotFigs', [modelName, '.fig']));
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end
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close all % close all figures
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%% Output Spline Results to an Excel File
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writetable(datatable, xlsfile);
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