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annotate +rv/+time/BdfDerivative.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 4b42999874c0
children 010bb2677230
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4b42999874c0 Add lower level for boot-strapping to RungeKuttaExteriorRV
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1 classdef BdfDerivative < handle
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2 properties
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3 coefficients
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4 end
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5 methods %TBD: Decide if the BDF order should be passed in construction
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6 % and only a row of coefficients stored based on the order.
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7 % There would still be an implicit dependancy on the number
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8 % of vectors in v_prev and elements in coefficients.
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9 % In addition, dt could be stored, but this would be
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10 % inflexible if different step sizes are employed.
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11 function obj = BdfDerivative()
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12 obj.coefficients = obj.getBdfCoefficients();
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13 end
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14 % Add asserts here?
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15 function DvDt = evaluate(obj, v, v_prev, dt)
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16 order = size(v_prev,2);
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17 DvDt = (obj.coefficients(order,1)*v - sum(obj.coefficients(order,2:order+1).*v_prev,2))/dt;
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18 end
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19 end
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20 methods(Static)
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21 function c = getBdfCoefficients()
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22 c = zeros(6,7);
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23 c(1,1) = 1; c(1,2) = 1;
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24 c(2,1) = 3/2; c(2,2) = 4/2; c(2,3) = -1/2;
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25 c(3,1) = 11/6; c(3,2) = 18/6; c(3,3) = -9/6; c(3,4) = 2/6;
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26 c(4,1) = 25/12; c(4,2) = 48/12; c(4,3) = -36/12; c(4,4) = 16/12; c(4,5) = -3/12;
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27 c(5,1) = 137/60; c(5,2) = 300/60; c(5,3) = -300/60; c(5,4) = 200/60; c(5,5) = -75/60; c(5,6) = 12/60;
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28 c(6,1) = 147/60; c(6,2) = 360/60; c(6,3) = -450/60; c(6,4) = 400/60; c(6,5) = -225/60; c(6,6) = 72/60; c(6,7) = -10/60;
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29 end
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30 end
eb441fbdf379 Draft implementation of RungeKutta with exterior RV updates
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31 end