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annotate +blockmatrix/zeroTest.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 a5f1b0267dba
children
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1 function tests = zeroTest()
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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 testZero(testCase)
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6 cases = {
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7 {
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8 {[],[]},
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9 {},
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10 },
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11 {
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12 {0,0},
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13 {[]};
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14 },
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15 {
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16 {1,1},
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17 {0};
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18 },
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19 {
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20 {2,1},
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21 {[0; 0]};
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22 },
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23 {
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24 {1,2},
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25 {[0 0]};
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26 },
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27 {
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28 {[1 2],2},
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29 {[0 0];[0 0; 0 0]};
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30 },
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31 {
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32 {[1 2],[2 1]},
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33 {[0 0],[0];[0 0; 0 0],[0; 0]};
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34 },
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35 {
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36 {[3],[0]},
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37 {zeros(3,0)},
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38 },
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39
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40 {
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41 {[0],[3]},
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42 {zeros(0,3)},
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43 },
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44 {
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45 {[0 2],[0 3]},
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46 {
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47 zeros(0,0), zeros(0,3);
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48 zeros(2,0), zeros(2,3);
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49 },
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50 },
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51 };
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52
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53 for i = 1:length(cases)
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54 out = convertToFull(blockmatrix.zero(cases{i}{1}));
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55 expected = cases{i}{2};
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56 testCase.verifyEqual(out,expected);
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57 end
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58 end
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60
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61 function C = convertToFull(C)
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62 [N,M] = size(C);
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63 for i = 1:N
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64 for j = 1:M
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65 C{i,j} = full(C{i,j});
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66 end
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67 end
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68 end