view plotConvergenceFit.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 0ef8965dd745
children
line wrap: on
line source

% Draws a line in a loglog plot with slope `slope` fitted to the data in `x`
% and `y`. `xlength` scales how much of the interval [x(1) x(end)] is coverd
% by the line. `offset` is a multiplicative offset to where the line is drawn
% relative to the data.
function hand = plotConvergenceFit(slope, x, y, xlength, offset)
    default_arg('xlength', 0.8)
    default_arg('offset', 1);

    % Optimise for log(y) = p*log(x) + q

    p = slope;

    logx = log(x);
    logy = log(y);

    N = length(logx);

    q = 1/N*sum(logy-p*logx);

    logxlength = xlength * abs(logx(end)-logx(1));
    logxends = (logx(1)+logx(end))/2 + [-logxlength/2, logxlength/2];

    xends = exp(logxends);
    yends = exp(q)*xends.^p;

    hand = line(xends, yends);
    hand.Color = Color.black;
    hand.LineStyle = '--';
    hand.LineWidth = 2;
end



% function hand = plotConvergenceFit(slope, pos, width)
%     x0 = pos(1);
%     y0 = pos(2);

%     x = [x0*10^-(width/2) x0*10^(width/2)];
%     y = x.^slope * x0^-slope * y0;

%     hand = line(x,y);
%     hand.Color = Color.black;
%     hand.LineStyle = '--';
%     hand.LineWidth = 2;
% end