Mercurial > repos > public > sbplib
view +noname/testCfl.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 | 7f6f04bfc007 |
children |
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% noname.testCfl(discr, timestepper_method, T, alpha0, tol,threshold, silentFlag) % Example: % noname.testCfl(Discr(100,4), 'rk4', 1, [0, 1]) function testCfl(discr, timestepper_method, T, alpha0, tol,threshold, silentFlag) default_arg('tol',0.00005); default_arg('threshold',1e2); default_arg('silentFlag', false); % TODO: % Set threshold from the initial conditions of the pde? % Take a set number of steps instead of evolving to a certain time? % Stop evolving when it has blown up? testAlpha = getAlphaTester(discr, T, threshold, silentFlag, timestepper_method); % Make sure that the upper bound is not working ok = testAlpha(alpha0(2)); if ok % Upper bound too large! error('The upper bound on alpha is stable!') end % Make sure that the lower bound is ok if alpha0(1) ~= 0 ok = testAlpha(alpha0(1)); if ~ok error('The lower bound on alpha is unstable!'); end end if silentFlag rsInterval = util.ReplaceableString(''); end % Use bisection to find sharp estimate while( (alpha0(2)-alpha0(1))/alpha0(1) > tol) alpha = mean(alpha0); if ~silentFlag fprintf('[%.3e,%.3e]: ', alpha0(1), alpha0(2)); else rsInterval.update('[%.3e,%.3e]: ', alpha0(1), alpha0(2)); end [ok, n_step, maxVal] = testAlpha(alpha); if ok alpha0(1) = alpha; stability = 'STABLE'; else alpha0(2) = alpha; stability = 'UNSTABLE'; end if ~silentFlag fprintf('a = %.3e, n_step=%d %8s max = %.2e\n', alpha, n_step, stability, maxVal); end end if silentFlag rsInterval = util.ReplaceableString(''); end fprintf('T = %-3d dof = %-4d order = %d: clf = %.4e\n',T, discr.size(), discr.order, alpha0(1)); end function f = getAlphaTester(discr, T, threshold, silentFlag, timestepper_method) % Returns true if cfl was ok function [ok, n_step, maxVal] = testAlpha(alpha) ts = discr.getTimestepper(struct('method', timestepper_method, 'cfl', alpha)); warning('off','all') ts.evolve(T,true); warning('on','all') [v,t] = ts.getV(); maxVal = max(v); if isnan(maxVal) || maxVal == Inf || abs(maxVal) > threshold ok = false; else ok = true; end n_step = ts.n; end f = @testAlpha; end