51 lines
1.5 KiB
Matlab
51 lines
1.5 KiB
Matlab
%% Reset everything
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clear all;
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clc;
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close all;
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addpath('helpers');
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%% Configure the benchmark
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% The algorithms we want to test
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algorithms = [ 6; 8; 17 ];
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% The name of the algorithms in the final plots
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names = { '6pt'; 'ge (8pt)'; '17pt'};
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% The main experiment parameters
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min_outlier_fraction = 0.05;%0.05;
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max_outlier_fraction = 0.25;
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outlier_fraction_step = 0.025;
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p = 0.99;
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%% Run the benchmark
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%prepare the overall result arrays
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number_outlier_fraction_levels = round((max_outlier_fraction - min_outlier_fraction) / outlier_fraction_step + 1);
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num_algorithms = size(algorithms,1);
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expected_number_iterations = zeros(num_algorithms,number_outlier_fraction_levels);
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outlier_fraction_levels = zeros(1,number_outlier_fraction_levels);
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%Run the experiment
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for n=1:number_outlier_fraction_levels
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outlier_fraction = (n - 1) * outlier_fraction_step + min_outlier_fraction;
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outlier_fraction_levels(1,n) = outlier_fraction;
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display(['Analyzing outlier fraction level: ' num2str(outlier_fraction)])
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%Now compute the mean and median value of the error for each algorithm
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for a=1:num_algorithms
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expected_number_iterations(a,n) = log(1-p)/log(1-(1-outlier_fraction)^(algorithms(a,1)));
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end
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end
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%% Plot the results
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figure(1)
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plot(outlier_fraction_levels,expected_number_iterations,'LineWidth',2)
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legend(names,'Location','NorthWest')
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xlabel('outlier fraction')
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ylabel('expected number iterations')
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grid on |