Mercurial > repos > public > sbplib
view +parametrization/old/curve_discretise.m @ 1198:2924b3a9b921 feature/d2_compatible
Add OpSet for fully compatible D2Variable, created from regular D2Variable by replacing d1 by first row of D1. Formal reduction by one order of accuracy at the boundary point.
author | Martin Almquist <malmquist@stanford.edu> |
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date | Fri, 16 Aug 2019 14:30:28 -0700 |
parents | 81e0ead29431 |
children |
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% Discretises the curve g with the smallest number of points such that all segments % are shorter than h. If do_plot is true the points of the discretisation and % the normals of the curve in those points are plotted. % % [t,p,d] = curve_discretise(g,h,do_plot) % % t is a vector of input values to g. % p is a cector of points. % d are the length of the segments. function [t,p,d] = curve_discretise(g,h,do_plot) default_arg('do_plot',false) n = 10; [t,p,d] = curve_discretise_n(g,n); % ni = 0; while any(d>h) [t,p,d] = curve_discretise_n(g,n); n = ceil(n*d(1)/h); % ni = ni+1; end % nj = 0; while all(d<h) [t,p,d] = curve_discretise_n(g,n); n = n-1; % nj = nj+1; end [t,p,d] = curve_discretise_n(g,n+1); % fprintf('ni = %d, nj = %d\n',ni,nj); if do_plot fprintf('n:%d max: %f min: %f\n', n, max(d),min(d)); p = parametrization.map_curve(g,t); figure show(g,t,h); end end function [t,p,d] = curve_discretise_n(g,n) t = linspace(0,1,n); t = equalize_d(g,t); d = D(g,t); p = parametrization.map_curve(g,t); end function d = D(g,t) p = parametrization.map_curve(g,t); d = zeros(1,length(t)-1); for i = 1:length(d) d(i) = norm(p(:,i) - p(:,i+1)); end end function t = equalize_d(g,t) d = D(g,t); v = d-mean(d); while any(abs(v)>0.01*mean(d)) dt = t(2:end)-t(1:end-1); t(2:end) = t(2:end) - cumsum(dt.*v./d); t = t/t(end); d = D(g,t); v = d-mean(d); end end function show(g,t,hh) p = parametrization.map_curve(g,t); h = parametrization.plot_curve(g); h.LineWidth = 2; axis equal hold on h = plot(p(1,:),p(2,:),'.'); h.Color = [0.8500 0.3250 0.0980]; h.MarkerSize = 24; hold off n = parametrization.curve_normals(g,t); hold on for i = 1:length(t) p0 = p(:,i); p1 = p0 + hh*n(:,i); l = [p0, p1]; h = plot(l(1,:),l(2,:)); h.Color = [0.8500 0.3250 0.0980]; end end