root/OptimizingMATLABCode/testFitEx/testFitRedo1.m @ 10
| 10 | anderm8 | function testFitRedo1(desiredTest,splineSample)
|
|
%% Example 2
|
|||
% Input values desiredTest = 60, splineSample = 200;
|
|||
%
|
|||
% Load in output of a desired model, fit, filter and evaluate a spline
|
|||
% Output written into an excel data file
|
|||
% Copyright 2015 The MathWorks, Inc.
|
|||
%% Defaults
|
|||
if ~nargin
|
|||
desiredTest = 60;
|
|||
splineSample = 200;
|
|||
end
|
|||
%% Finding Names of all Text Files in the ModelResults Directory
|
|||
xlsfile = 'FinalResults.xls';
|
|||
datadir = fullfile(pwd, 'ModelResults');
|
|||
modelFiles = dir(fullfile(datadir, '*.txt'));
|
|||
if isempty(modelFiles)
|
|||
error('No data files.\nRun "FileGenerator.m" in the ModelResults folder')
|
|||
else
|
|||
numModels = length(modelFiles);
|
|||
end
|
|||
% Preallocate empty table
|
|||
datatable = table;
|
|||
disp('Processing test results...')
|
|||
%% Reading, Averaging, and Fitting all Text Files
|
|||
for ii = 1:numModels
|
|||
%% Read in the Relevant Model Data
|
|||
fileName = fullfile(datadir, modelFiles(ii).name);
|
|||
fid = fopen(fileName);
|
|||
% Getting the number of timesteps from the header of the txt file
|
|||
nTimes = textscan(fid, '%*s %d \n', 1);
|
|||
nTimes = nTimes{1};
|
|||
% Read through models we don't want data from and keep resaving model
|
|||
% info into modelData until it gets to desiredModel
|
|||
for jj = 1:desiredTest-1
|
|||
fgets(fid); % read test header line
|
|||
textscan(fid, '%*f %*f \n', nTimes); % get model output data
|
|||
end
|
|||
fgets(fid); % read test header line
|
|||
modelData = textscan(fid, '%f %f \n', nTimes); % get model output data
|
|||
modelData = cell2mat(modelData);
|
|||
fclose(fid);
|
|||
%% Filter, Fit and Evaluate Spline on Model Data
|
|||
nPoints = 10; % setting number of points to average over
|
|||
b = (1 / nPoints) * ones(1, nPoints); % moving average over nPoints
|
|||
filterData = filter(b, 1, modelData); % create moving average
|
|||
splineData = spline(filterData(:, 1), filterData(:, 2)); % create spline
|
|||
splineTime = linspace(0, filterData(end, 1), splineSample);
|
|||
finalData = ppval(splineData, splineTime); % evaluate spline
|
|||
coltitle = {sprintf('time%03d', ii), sprintf('data%03d', ii)};
|
|||
datatable.(coltitle{1}) = splineTime';
|
|||
datatable.(coltitle{2}) = finalData';
|
|||
%% Plot the Results
|
|||
figure
|
|||
subplot(2, 1, 1)
|
|||
plot(modelData(:, 1), modelData(:, 2))
|
|||
line(filterData(:, 1), filterData(:, 2), 'Color', 'r');
|
|||
title('Original and Moving Average')
|
|||
subplot(2, 1, 2)
|
|||
plot(filterData(:, 1), filterData(:, 2))
|
|||
line(splineTime, finalData, 'Color', 'r', 'Marker', '+');
|
|||
title('Moving Average and Spline')
|
|||
% Force graphics update
|
|||
drawnow
|
|||
% Save figure
|
|||
% saveas(gcf, fullfile('PlotFigs', [modelName, '.fig']));
|
|||
end
|
|||
close all % close all figures
|
|||
%% Output Spline Results to an Excel File
|
|||
writetable(datatable, xlsfile);
|