Mercurial > repos > public > sbplib
view +time/CdiffNonlin.m @ 1037:2d7ba44340d0 feature/burgers1d
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> |
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date | Fri, 18 Jan 2019 09:02:02 +0100 |
parents | d1f9dd55a2b0 |
children | b5e5b195da1e |
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classdef CdiffNonlin < time.Timestepper properties D E S k t v v_prev n end methods function obj = CdiffNonlin(D, E, S, k, t0,n0, v, v_prev) m = size(D(v),1); default_arg('E',0); default_arg('S',0); if isnumeric(S) S = @(v,t)S; end if isnumeric(E) E = @(v)E; end % m = size(D,1); % default_arg('E',sparse(m,m)); % default_arg('S',sparse(m,1)); obj.D = D; obj.E = E; obj.S = S; obj.k = k; obj.t = t0; obj.n = n0; obj.v = v; obj.v_prev = v_prev; end function [v,t] = getV(obj) v = obj.v; t = obj.t; end function [vt,t] = getVt(obj) vt = (obj.v-obj.v_prev)/obj.k; % Could be improved using u_tt = f(u)) t = obj.t; end function obj = step(obj) D = obj.D(obj.v); E = obj.E(obj.v); S = obj.S(obj.v,obj.t); m = size(D,1); I = speye(m); %% Calculate for which indices we need to solve system of equations [rows,cols] = find(E); j = union(rows,cols); i = setdiff(1:m,j); %% Calculate matrices need for the timestep % Before optimization: A = 1/k^2 * I - 1/(2*k)*E; k = obj.k; Aj = 1/k^2 * I(j,j) - 1/(2*k)*E(j,j); B = 2/k^2 * I + D; C = -1/k^2 * I - 1/(2*k)*E; %% Take the timestep v = obj.v; v_prev = obj.v_prev; % Want to solve the seq A*v_next = b where b = (B*v + C*v_prev + S); % Before optimization: obj.v = A\b; obj.v(i) = k^2*b(i); obj.v(j) = Aj\b(j); obj.v_prev = v; %% Update state of the timestepper obj.t = obj.t + obj.k; obj.n = obj.n + 1; end end end