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