PointPatternQuest/displaySimuPPQ.m at master · sebherbert/PointPatternQuest · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60


function GrandAll = displaySimuPPQ(Grand, G, figTitle, figSavePath, PARAMS)
% display the figure bearing the Nearest Neighbours histogram and the
% random distribution simulations

xScale = PARAMS.binSize;


GrandAll = {};
GrandAll.all = Grand;
for i=1:size(xScale,2)
    GrandAll.mean(i)=mean(Grand(:,i));
    GrandAll.std(i)=std(Grand(:,i));
    GrandAll.iqr5(i)=prctile(Grand(:,i),5);
    GrandAll.iqr95(i)=prctile(Grand(:,i),95);
    GrandAll.iqr1(i)=prctile(Grand(:,i),1);
    GrandAll.iqr99(i)=prctile(Grand(:,i),99);
end


figure
ylabel('Cumulative cell frequency');
xlabel('distance to nearest neighbor (in cell diameter)');

% Plot the simulation dispersions
hold on
plot(xScale,GrandAll.mean,'-k','linewidth',3);
plot(xScale,GrandAll.iqr5,'-','linewidth',2,'color',[0.6 0.6 0.6]);
plot(xScale,GrandAll.iqr95,'-','linewidth',2,'color',[0.6 0.6 0.6]);
plot(xScale,GrandAll.iqr1,'-','linewidth',1,'color',[0.6 0.6 0.6]);
plot(xScale,GrandAll.iqr99,'-','linewidth',1,'color',[0.6 0.6 0.6]);

% Plot the experimental data
plot(xScale,G,'-r','linewidth',3);
text(0.5,0.95,'95% and 99% intervals')
text(0.5,0.9,[num2str(PARAMS.numPermut),' random perm.'])

% force the axes
if 2*ceil(xScale(min(find(G>0.9))))<14
    axis([0 2*ceil(xScale(min(find(G>0.9)))) 0 1]);
else
    axis([0 14 0 1]);
end

title(figTitle,'FontSize',10)

saveas(gcf,figSavePath);
% saveas(gcf,figSavePath,'tiffn');
saveas(gcf,figSavePath,'png');

% Could use a simple ecdf instead of the manual cdf
% figure test
% [f,x] = ecdf(dn);
% hold on
% plot(x,f,'.-');
% plot(r,G,'.-');
% plot(r,GrandAll.mean);

end