view +sbp/+implementations/d1_gauss_4.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>
date Fri, 18 Jan 2019 09:02:02 +0100
parents 0bc37a25ed88
children
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function [D1,H,x,h,e_l,e_r] = d1_gauss_4(L)

% L: Domain length
default_arg('L',1);

N = 4;

% Quadrature nodes on interval [-1, 1]
x = [ -0.8611363115940526; -0.3399810435848563; 0.3399810435848563; 0.8611363115940526];

% Shift nodes to [0,L]
x = (x+1)/2*L;

% Boundary extrapolation operators
e_l = [1.5267881254572668; -0.8136324494869273; 0.4007615203116504; -0.1139171962819899];
e_r = flipud(e_l);
e_l = sparse(e_l);
e_r = sparse(e_r);

%%%% Compute approximate h %%%%%%%%%%
h = L/(N-1);
%%%%%%%%%%%%%%%%%%%%%%%%%

%%%% Norm matrix on [-1,1] %%%%%%%%
P = sparse(N,N);
P(1,1) =  0.3478548451374539;
P(2,2) =  0.6521451548625461;
P(3,3) =  0.6521451548625461;
P(4,4) =  0.3478548451374539;
%%%%%%%%%%%%%%%%%%%%%%%%%

%%%% Norm matrix on [0,L] %%%%%%%%
H = P*L/2;
%%%%%%%%%%%%%%%%%%%%%%%%%

%%%% D1 on [-1,1] %%%%%%%%
D1 = sparse(N,N);
D1(1,1) = -3.3320002363522817;
D1(1,2) = 4.8601544156851962;
D1(1,3) = -2.1087823484951789;
D1(1,4) = 0.5806281691622644;

D1(2,1) = -0.7575576147992339;
D1(2,2) = -0.3844143922232086;
D1(2,3) = 1.4706702312807167;
D1(2,4) = -0.3286982242582743;

D1(3,1) = 0.3286982242582743;
D1(3,2) = -1.4706702312807167;
D1(3,3) = 0.3844143922232086;
D1(3,4) = 0.7575576147992339;

D1(4,1) = -0.5806281691622644;
D1(4,2) = 2.1087823484951789;
D1(4,3) = -4.8601544156851962;
D1(4,4) = 3.3320002363522817;
%%%%%%%%%%%%%%%%%%%%%%%%%

% D1 on [0,L]
D1 = D1*2/L;