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annotate +noname/calculateErrors.m @ 1198:2924b3a9b921 feature/d2_compatible

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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>
date Fri, 16 Aug 2019 14:30:28 -0700
parents 1201eb16557e
children
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1 % [discr, trueSolution] = schemeFactory(m)
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2 % where trueSolution should be a timeSnapshot of the true solution a time T
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3 % T is the end time
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4 % m are grid size parameters.
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5 % N are number of timesteps to use for each gird size
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6 % timeOpt are options for the timeStepper
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7 % errorFun is a function_handle taking 2 or 3 arguments, errorFun(trueSolution, approxSolution), errorFun(trueSolution, approxSolution, discr)
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8 function e = calculateErrors(schemeFactory, T, m, N, errorFun, timeOpt)
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9 %TODO: Ability to choose paralell or not
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10 assertType(schemeFactory, 'function_handle');
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11 assertNumberOfArguments(schemeFactory, 1);
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12 assertScalar(T);
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13 assert(length(m) == length(N), 'Vectors m and N must have the same length');
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14 assertType(errorFun, 'function_handle');
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16 if ~ismember(nargin(errorFun), [2,3])
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17 error('sbplib:noname:calculateErrors:wrongNumberOfArguments', '"%s" must have 2 or 3, found %d', toString(errorFun), nargin(errorFun));
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18 end
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20 default_arg('timeOpt', struct());
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23 e = zeros(1,length(m));
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24 parfor i = 1:length(m)
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25 done = timeTask('m = %3d ', m(i));
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27 [discr, trueSolution] = schemeFactory(m(i));
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28
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29 timeOptTemp = timeOpt;
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30 timeOptTemp.k = T/N(i);
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31 ts = discr.getTimestepper(timeOptTemp);
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32 ts.stepTo(N(i), true);
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33 approxSolution = discr.getTimeSnapshot(ts);
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34
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35 switch nargin(errorFun)
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36 case 2
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37 e(i) = errorFun(trueSolution, approxSolution);
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38 case 3
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39 e(i) = errorFun(trueSolution, approxSolution, discr);
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40 end
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42 fprintf('e = %.4e', e(i))
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43 done()
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44 end
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45 fprintf('\n')
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46 end
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49 %% Example error function
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50 % u_true = grid.evalOn(dr.grid, @(x,y)trueSolution(T,x,y));
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51 % err = u_true-u_false;
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52 % e(i) = norm(err)/norm(u_true);
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53 % % e(i) = sqrt(err'*d.H*d.J*err/(u_true'*d.H*d.J*u_true));