view spdiagsPeriodic.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 bbf303c1f0cf
children
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function A = spdiagsPeriodic(vals,diags)
    % Creates an m x m periodic discretization matrix.
    % vals - m x ndiags matrix of values
    % diags - 1 x ndiags vector of the 'center diagonals' that vals end up on
    % vals that are not on main diagonal are going to spill over to
    % off-diagonal corners.

    default_arg('diags',0);

    [m, ~] = size(vals);

    A = sparse(m,m);

    for i = 1:length(diags)

        d = diags(i);
        a = vals(:,i);

        % Sub-diagonals
        if d < 0
            a_bulk = a(1+abs(d):end);
            a_corner = a(1:1+abs(d)-1);
            corner_diag = m-abs(d);
            A = A + spdiagVariable(a_bulk, d);
            A = A + spdiagVariable(a_corner, corner_diag);

        % Super-diagonals
        elseif d > 0
            a_bulk = a(1:end-d);
            a_corner = a(end-d+1:end);
            corner_diag = -m + d;
            A = A + spdiagVariable(a_bulk, d);
            A = A + spdiagVariable(a_corner, corner_diag);

        % Main diagonal
        else
             A = A + spdiagVariable(a, 0);
        end

    end

end

function A = spdiagVariable(a,i)
    default_arg('i',0);

    if isrow(a)
        a = a';
    end

    n = length(a)+abs(i);

    if i > 0
        a = [sparse(i,1); a];
    elseif i < 0
        a = [a; sparse(abs(i),1)];
    end

    A = spdiags(a,i,n,n);
end