Mercurial > repos > public > sbplib
view +parametrization/old/curve_discretise.m @ 774:66eb4a2bbb72 feature/grids
Remove default scaling of the system.
The scaling doens't seem to help actual solutions. One example that fails in the flexural code.
With large timesteps the solutions seems to blow up. One particular example is profilePresentation
on the tdb_presentation_figures branch with k = 0.0005
author | Jonatan Werpers <jonatan@werpers.com> |
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date | Wed, 18 Jul 2018 15:42:52 -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