graph.m

802.11仿真源码 对分析RSSI很有用的

function Graph(x,y,minx,maxx,weight,labelx,labely, heading, colourfit, colourxy, RSSI, PER, yes_fit)
%This function ->
%       Graph: Creates a plot of datasets y vs x and
%           then proceeds to calculate the weigted line of best fit 
%               using a linear polynomial and graphs the resulted fit
%                  if asked with the colour argument as follows:
%       'y' = yellow, 'm' = magenta, 'c' = cyan, 'r' = red, 'g' = green,
%               'b' = blue, 'w' = white or 'k' = black
% Function description is:
%Graph(x data, y data, weights of data, x-axis label,
%   y-axis label,graph heading, the colour for the linear fit, 
%     colour for the data, if RSSI is used, is PER is used 
%       and if a fit is wanted in the created figure)

fh = figure();
iptsetpref('ImshowBorder','tight');
legh_ = []; legt_ = {};   % handles and text for legend
hold on;

% --- Plot data originally in dataset "y vs. x"
if(RSSI == 1)
    xy = plot(x, y, '.'); axis ([minx maxx 161 230]);
    set(xy,'Color',colourxy);
else    
    xy = plot(x, y, '.'); axis ([minx maxx min(y) max(y)]);
    set(xy,'Color',colourxy);
end

% --- Create fit 
fitopt = fitoptions('method','LinearLeastSquares','Weights',weight);
set(fitopt,'Weight',weight);

% Fit this model using new data where poly1 for a linear fit and poly'x' 
% for any (x + 1) order polynomial
x = x(:);
y = y(:);
weight = weight(:);
curvefit = fit(x,y,'poly1',fitopt)
ci = confint(curvefit,0.95)

if(yes_fit == 1)
    % Plot this fit
    wgt_ = plot(curvefit); axis ([minx maxx min(y) max(y)]);       
    set(wgt_(1),'LineWidth',2,'Color',colourfit)

    % Add legend for line of Best fit
    legh_(end+1) = wgt_(1);                     %point used
    legt_{end+1} = 'Weighted Line of Best Fit'; %label
    legend(legh_, legt_);  
end
hold off;

%Labels for x,y and heading
title(heading);xlabel(labelx); ylabel(labely);


f_gcf = getframe(gcf); % get graphic content
imwrite(f_gcf.cdata,[heading '.jpeg']); %save content with heading as prefix