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function [change_points, ratios, handles, handles_fig_5] = calculate_changepoints( properties, fields, method, closeness, outlier_fraction, varargin )
%CALCULATE_CHANGEPOINTS Summary of this function goes here
% Detailed explanation goes here
if nargin < 2; fields = {'thresholds'}; end
if nargin < 3; method = 'threshold'; end
if nargin < 4; closeness = 10; end
if nargin < 5; outlier_fraction = 0.1; end % The fraction of ourliers, should be the same as the C parameter used for SVDD
% change_points = data_values(change_points, 1);
% ratios = data_values(ratios(:,1), 1);
% change_points = unique(change_points(:,2));
% ratios = unique(ratios(:,2
if strcmp(class(fields), 'char')
fields = {fields};
end
switch method
case 'threshold'
disp('- Using thresholding method');
high = varargin{1};
low = varargin{2};
if length(fields) == 1
disp(['- For a single field ' fields{1}]);
[change_points, ratios, shadow_points] = thresholding_single(properties, fields, high, low, outlier_fraction);
% else
% disp(['- For multiple fields ' cell2mat(fields) ]);
% [change_points, ratios, shadow_points] = thresholding_multiple(properties, fields, high, low, outlier_fraction);
end
otherwise
disp('---')
disp('Error: Unsupported change detection method.');
disp('Supported methods include:');
disp(' - threshold (high, low)');
end
% Merge change points
change_points
change_points_merged = merge_changepoints(change_points, closeness);
% change_points_merged = change_points(:,2);
ratios;
% Plot ratios and changepoint in new figure
sfigure(5); clf;
% Set plot width and height
% screenSize = get(0,'ScreenSize');
% plot_width = screenSize(3);
% plot_height = screenSize(4) / 4;
% set(gcf,'Position',[0 (plot_height * 1.3) plot_width plot_height]);
handle_plot = plot(ratios(:,1), ratios(:,2));
handles_vertical = draw_vertical_lines(change_points_merged, 'r');
% handles_vertical_shadow = draw_vertical_lines(shadow_points(:,2), 'r', 1, '--');
% handles_vertical = horzcat(handles_vertical', handles_vertical_shadow')';
handles_horizontal = draw_horizontal_lines([high low], 'r');
% set(gca, 'XTick', 0:roundn(length(ratios(:,1))/50, 1):ratios(end,1));
set(gca, 'XTick', 0:2:ratios(end,1));
set(gca, 'YTick', 0:0.2:max(ratios(:,2)));
xlim([0 ratios(end,1)]);
% Add empty axis, to create equal spacing with other plots
% addaxis([],[]);
% addaxis([],[]);
% addaxis([],[]);
% Plot change points in original data figure
sfigure(4);
handles = draw_vertical_lines(change_points_merged, 'b');
handles_fig_5 = horzcat(handle_plot, handles_vertical', handles_horizontal');
xlim([0 ratios(end,1)]);
change_points = change_points_merged;
set(gca, 'XTick', 0:2:ratios(end,1));
end
function [change_points, ratios, shadow_points] = thresholding_single(properties, field, high, low, outlier_fraction)
% Use the thresholding method. Sum all the ratios of the data series
% indicated by the fields.
column = 3; % Assume first column is time, second index, third has value
data_values = cell2mat(values(properties, field));
if nargin < 3; high = 3; end
if nargin < 4; low = 0.2; end
% Determine block sizes
block_size = data_values(1,1) - data_values(3,1) + data_values(2,1) - 1;
change_points = [1 1 0]; %zeros(size(data_values),2);
shadow_points = [1 1 0];
ratios = zeros(size(data_values, 1),2);
block_size
outlier_fraction
for i = 2 : length(data_values)
time = data_values(i, 1);
series = data_values(change_points(end,1):i,column);
r = ratio(series);
ratios(i,:) = [time r];
% Skip if last change point was within a certain range
% if (i - change_points(end, 1)) < 10
% continue;
% end
if r > high
disp(['High treshold at i: ' num2str(i) ', time: ' num2str(time) ', value r:' num2str(r) ])
change_points(end+1,:) = [i time 0];
end
% TODO: check block-compenstation for low values
if r < low
disp(['Low treshold at i: ' num2str(i) ', time: ' num2str(time) ', value r:' num2str(r) ])
% disp(['Corrected to time ' num2str(time-block_size+outlier_fraction*block_size) ])
% change_points(end+1,:) = [i time-block_size+outlier_fraction*block_size 1];
change_points(end+1,:) = [i time 1];
shadow_points(end+1,:) = [i time 1];
% NOTE: compensate for block size
% TODO: also, a fraction C of block size need to be added
% again, because those datapoints were first regarded as
% outliers.
end
end
change_points = sortrows(change_points, 2);
[C, ai, ci] = unique(change_points(:,2), 'stable');
change_points = change_points(ai,:);
change_points;
end
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