v01

thirdparty/opengv/matlab/plot_expected_iterations.m

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