Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/KPMtools/plotcov3.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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% PLOTCOV3 - Plots a covariance ellipsoid with axes for a trivariate % Gaussian distribution. % % Usage: % [h, s] = plotcov3(mu, Sigma[, OPTIONS]); % % Inputs: % mu - a 3 x 1 vector giving the mean of the distribution. % Sigma - a 3 x 3 symmetric positive semi-definite matrix giving % the covariance of the distribution (or the zero matrix). % % Options: % 'conf' - a scalar between 0 and 1 giving the confidence % interval (i.e., the fraction of probability mass to % be enclosed by the ellipse); default is 0.9. % 'num-pts' - if the value supplied is n, then (n + 1)^2 points % to be used to plot the ellipse; default is 20. % 'plot-opts' - a cell vector of arguments to be handed to PLOT3 % to contol the appearance of the axes, e.g., % {'Color', 'g', 'LineWidth', 1}; the default is {} % 'surf-opts' - a cell vector of arguments to be handed to SURF % to contol the appearance of the ellipsoid % surface; a nice possibility that yields % transparency is: {'EdgeAlpha', 0, 'FaceAlpha', % 0.1, 'FaceColor', 'g'}; the default is {} % % Outputs: % h - a vector of handles on the axis lines % s - a handle on the ellipsoid surface object % % See also: PLOTCOV2 % Copyright (C) 2002 Mark A. Paskin % % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation; either version 2 of the License, or % (at your option) any later version. % % This program is distributed in the hope that it will be useful, but % WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU % General Public License for more details. % % You should have received a copy of the GNU General Public License % along with this program; if not, write to the Free Software % Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 % USA. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [h, s] = plotcov3(mu, Sigma, varargin) if size(Sigma) ~= [3 3], error('Sigma must be a 3 by 3 matrix'); end if length(mu) ~= 3, error('mu must be a 3 by 1 vector'); end [p, ... n, ... plot_opts, ... surf_opts] = process_options(varargin, 'conf', 0.9, ... 'num-pts', 20, ... 'plot-opts', {}, ... 'surf-opts', {}); h = []; holding = ishold; if (Sigma == zeros(3, 3)) z = mu; else % Compute the Mahalanobis radius of the ellipsoid that encloses % the desired probability mass. k = conf2mahal(p, 3); % The axes of the covariance ellipse are given by the eigenvectors of % the covariance matrix. Their lengths (for the ellipse with unit % Mahalanobis radius) are given by the square roots of the % corresponding eigenvalues. if (issparse(Sigma)) [V, D] = eigs(Sigma); else [V, D] = eig(Sigma); end if (any(diag(D) < 0)) error('Invalid covariance matrix: not positive semi-definite.'); end % Compute the points on the surface of the ellipsoid. t = linspace(0, 2*pi, n); [X, Y, Z] = sphere(n); u = [X(:)'; Y(:)'; Z(:)']; w = (k * V * sqrt(D)) * u; z = repmat(mu(:), [1 (n + 1)^2]) + w; % Plot the axes. L = k * sqrt(diag(D)); h = plot3([mu(1); mu(1) + L(1) * V(1, 1)], ... [mu(2); mu(2) + L(1) * V(2, 1)], ... [mu(3); mu(3) + L(1) * V(3, 1)], plot_opts{:}); hold on; h = [h; plot3([mu(1); mu(1) + L(2) * V(1, 2)], ... [mu(2); mu(2) + L(2) * V(2, 2)], ... [mu(3); mu(3) + L(2) * V(3, 2)], plot_opts{:})]; h = [h; plot3([mu(1); mu(1) + L(3) * V(1, 3)], ... [mu(2); mu(2) + L(3) * V(2, 3)], ... [mu(3); mu(3) + L(3) * V(3, 3)], plot_opts{:})]; end s = surf(reshape(z(1, :), [(n + 1) (n + 1)]), ... reshape(z(2, :), [(n + 1) (n + 1)]), ... reshape(z(3, :), [(n + 1) (n + 1)]), ... surf_opts{:}); if (~holding) hold off; end