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annotate +parametrization/old/min_h.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 3a3cf386bb7e
children
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Jonatan Werpers <jonatan@werpers.com>
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1 function [d_min, i1_min, j1_min, i2_min, j2_min] = min_h(X,Y)
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2 ni = size(X,1);
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3 nj = size(X,2);
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4 d_min = norm([X(1,1);Y(1,1)] - [X(ni,nj);Y(ni,nj)]);
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5
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6 i1_min = 0;
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7 j1_min = 0;
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8 i2_min = 0;
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9 j2_min = 0;
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10
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11 D = {[-1,-1],[0,-1],[1,-1],[1,0],[1,1],[0,1],[-1,1],[-1,0]};
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12 % D = {[0,-1],[1,0],[0,1],[-1,0]};
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13
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14 for i = 1:ni
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15 for j = 1:nj
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16 p1 = [X(i,j); Y(i,j)];
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17 for k = 1:length(D)
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18 i2 = i+D{k}(1);
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19 j2 = j+D{k}(2);
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20 if i2 >= 1 && i2 <= ni && j2 >= 1 && j2 <= nj
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21 p2 = [X(i2,j2); Y(i2,j2)];
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22 d = norm(p2-p1);
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23 if d < d_min;
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24 d_min = d;
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25 i1_min = i;
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26 j1_min = j;
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27 i2_min = i2;
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28 j2_min = j2;
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29 end
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