matthiasm@8: % PLOTCOV2 - Plots a covariance ellipse with major and minor axes matthiasm@8: % for a bivariate Gaussian distribution. matthiasm@8: % matthiasm@8: % Usage: matthiasm@8: % h = plotcov2(mu, Sigma[, OPTIONS]); matthiasm@8: % matthiasm@8: % Inputs: matthiasm@8: % mu - a 2 x 1 vector giving the mean of the distribution. matthiasm@8: % Sigma - a 2 x 2 symmetric positive semi-definite matrix giving matthiasm@8: % the covariance of the distribution (or the zero matrix). matthiasm@8: % matthiasm@8: % Options: matthiasm@8: % 'conf' - a scalar between 0 and 1 giving the confidence matthiasm@8: % interval (i.e., the fraction of probability mass to matthiasm@8: % be enclosed by the ellipse); default is 0.9. matthiasm@8: % 'num-pts' - the number of points to be used to plot the matthiasm@8: % ellipse; default is 100. matthiasm@8: % matthiasm@8: % This function also accepts options for PLOT. matthiasm@8: % matthiasm@8: % Outputs: matthiasm@8: % h - a vector of figure handles to the ellipse boundary and matthiasm@8: % its major and minor axes matthiasm@8: % matthiasm@8: % See also: PLOTCOV3 matthiasm@8: matthiasm@8: % Copyright (C) 2002 Mark A. Paskin matthiasm@8: % matthiasm@8: % This program is free software; you can redistribute it and/or modify matthiasm@8: % it under the terms of the GNU General Public License as published by matthiasm@8: % the Free Software Foundation; either version 2 of the License, or matthiasm@8: % (at your option) any later version. matthiasm@8: % matthiasm@8: % This program is distributed in the hope that it will be useful, but matthiasm@8: % WITHOUT ANY WARRANTY; without even the implied warranty of matthiasm@8: % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU matthiasm@8: % General Public License for more details. matthiasm@8: % matthiasm@8: % You should have received a copy of the GNU General Public License matthiasm@8: % along with this program; if not, write to the Free Software matthiasm@8: % Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 matthiasm@8: % USA. matthiasm@8: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% matthiasm@8: matthiasm@8: function h = plotcov2(mu, Sigma, varargin) matthiasm@8: matthiasm@8: if size(Sigma) ~= [2 2], error('Sigma must be a 2 by 2 matrix'); end matthiasm@8: if length(mu) ~= 2, error('mu must be a 2 by 1 vector'); end matthiasm@8: matthiasm@8: [p, ... matthiasm@8: n, ... matthiasm@8: plot_opts] = process_options(varargin, 'conf', 0.9, ... matthiasm@8: 'num-pts', 100); matthiasm@8: h = []; matthiasm@8: holding = ishold; matthiasm@8: if (Sigma == zeros(2, 2)) matthiasm@8: z = mu; matthiasm@8: else matthiasm@8: % Compute the Mahalanobis radius of the ellipsoid that encloses matthiasm@8: % the desired probability mass. matthiasm@8: k = conf2mahal(p, 2); matthiasm@8: % The major and minor axes of the covariance ellipse are given by matthiasm@8: % the eigenvectors of the covariance matrix. Their lengths (for matthiasm@8: % the ellipse with unit Mahalanobis radius) are given by the matthiasm@8: % square roots of the corresponding eigenvalues. matthiasm@8: if (issparse(Sigma)) matthiasm@8: [V, D] = eigs(Sigma); matthiasm@8: else matthiasm@8: [V, D] = eig(Sigma); matthiasm@8: end matthiasm@8: % Compute the points on the surface of the ellipse. matthiasm@8: t = linspace(0, 2*pi, n); matthiasm@8: u = [cos(t); sin(t)]; matthiasm@8: w = (k * V * sqrt(D)) * u; matthiasm@8: z = repmat(mu, [1 n]) + w; matthiasm@8: % Plot the major and minor axes. matthiasm@8: L = k * sqrt(diag(D)); matthiasm@8: h = plot([mu(1); mu(1) + L(1) * V(1, 1)], ... matthiasm@8: [mu(2); mu(2) + L(1) * V(2, 1)], plot_opts{:}); matthiasm@8: hold on; matthiasm@8: h = [h; plot([mu(1); mu(1) + L(2) * V(1, 2)], ... matthiasm@8: [mu(2); mu(2) + L(2) * V(2, 2)], plot_opts{:})]; matthiasm@8: end matthiasm@8: matthiasm@8: h = [h; plot(z(1, :), z(2, :), plot_opts{:})]; matthiasm@8: if (~holding) hold off; end