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annotate +parametrization/TiTest.m @ 1037:2d7ba44340d0 feature/burgers1d

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Pass scheme specific parameters as cell array. This will enabale constructDiffOps to be more general. In addition, allow for schemes returning function handles as diffOps, which is currently how non-linear schemes such as Burgers1d are implemented.
author Vidar Stiernström <vidar.stiernstrom@it.uu.se>
date Fri, 18 Jan 2019 09:02:02 +0100
parents 77ad5de4432e
children
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1 function tests = TiTest()
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2 tests = functiontests(localfunctions);
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3 end
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4
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5 function testScalarInput(testCase)
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6 ti = getMinimumTi();
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7
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8 cases = {
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9 % {u, v, out},
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10 {0, 0, [1; 2]},
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11 {0, 1, [1; 4]},
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12 {1, 0, [3; 2]},
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13 {1, 1, [3; 4]},
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14 {0.5, 0.5, [2; 3]},
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15 };
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16
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17 for i = 1:length(cases)
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18 u = cases{i}{1};
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19 v = cases{i}{2};
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20 expected = cases{i}{3};
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21
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22 testCase.verifyEqual(ti.S(u,v), expected, sprintf('Case: %d',i));
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23 end
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24 end
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25
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26 function testRowVectorInput(testCase)
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27 ti = getMinimumTi();
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28
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29 u = [0, 0.5, 1];
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30 v = [0, 0, 0.5];
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31 expected = [
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32 1, 2, 3;
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33 2, 2, 3;
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34 ];
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35
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36 testCase.verifyEqual(ti.S(u,v), expected);
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37 end
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38
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39 function testColumnvectorInput(testCase)
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40 ti = getMinimumTi();
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41
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42 u = [0; 0.5; 1];
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43 v = [0; 0; 0.5];
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44 expected = [1; 2; 3; 2; 2; 3];
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45
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46 testCase.verifyEqual(ti.S(u,v), expected);
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47 end
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49
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50 function ti = getMinimumTi()
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51 ti = parametrization.Ti.rectangle([1; 2], [3; 4]);
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52 end