course-idma2016/matlab/idma_box_mean.m

function [boxmean,tim,dep]=idma_box_mean(p,w);
%
% IDMA_BOX_MEAN computes monthly averages (over 1992-2011) of all profiles
%    in p that passed all QCs (i.e. such that weight w>0); both p and
%    w are in MITprof format as obtained using idma_box_subset;
%    boxmean, tim, dep are two dimensional arrays (w. month, depth indices)
%
% Example: box_l=[-180 -140]; box_L=[-10 10]-30; box_D=[0 300];
%          [prof_T,prof_Testim,prof_Tweight]=idma_box_subset(box_l,box_L,box_D);
%          [boxmean,tim,dep]=idma_box_mean(prof_T,prof_Tweight);
%          figureL; pcolor(tim,-dep,boxmean); colorbar;

demoSTATS=1;%set this to one to activate display of results at one level

%%define time and depth arrays
tim=1992+[0.5:239.5]/12;
dep=p.prof_depth;
[dep,tim]=meshgrid(dep,tim);

%%mask out points that did not pass all QCs
p.prof(w.prof==0)=NaN;

%%compute averages
boxnb=NaN*zeros(240,p.nr);
boxmean=NaN*zeros(240,p.nr);
boxmedian=NaN*zeros(240,p.nr);
boxstd=NaN*zeros(240,p.nr);
for yy=1992:2011;
for mm=1:12;
  dd=[datenum(yy,mm,0) datenum(yy,mm+1,0)];
  tt=(yy-1992)*12+mm;
  %
  tmp1=MITprof_subset(p,'date',dd);
  tmp1=tmp1.prof;
  %
  boxnb(tt,:)=sum(~isnan(tmp1),1);
  boxmean(tt,:)=nanmean(tmp1,1);
  boxmedian(tt,:)=nanmedian(tmp1,1);
  boxstd(tt,:)=nanstd(tmp1,1);
  %
end;
end;

%%display results
if demoSTATS;
  figure;
  kk=2;
  subplot(3,1,1); plot(tim(:,kk),boxnb(:,kk));
  legend('sample size','Location','NorthWest');
  subplot(3,1,2); plot(tim(:,kk),boxmean(:,kk)); ylabel('degree C');
  hold on; plot(tim,boxmedian(:,kk),'r'); 
  legend('sample mean','sample median','Location','NorthWest');
  subplot(3,1,3); plot(tim(:,kk),boxstd(:,kk)); ylabel('degree C'); 
  legend('sample std','Location','NorthWest');
end;

1	function [boxmean,tim,dep]=idma_box_mean(p,w);
2	%
3	% IDMA_BOX_MEAN computes monthly averages (over 1992-2011) of all profiles
4	% in p that passed all QCs (i.e. such that weight w>0); both p and
5	% w are in MITprof format as obtained using idma_box_subset;
6	% boxmean, tim, dep are two dimensional arrays (w. month, depth indices)
7	%
8	% Example: box_l=[-180 -140]; box_L=[-10 10]-30; box_D=[0 300];
9	% [prof_T,prof_Testim,prof_Tweight]=idma_box_subset(box_l,box_L,box_D);
10	% [boxmean,tim,dep]=idma_box_mean(prof_T,prof_Tweight);
11	% figureL; pcolor(tim,-dep,boxmean); colorbar;
12
13	demoSTATS=1;%set this to one to activate display of results at one level
14
15	%%define time and depth arrays
16	tim=1992+[0.5:239.5]/12;
17	dep=p.prof_depth;
18	[dep,tim]=meshgrid(dep,tim);
19
20	%%mask out points that did not pass all QCs
21	p.prof(w.prof==0)=NaN;
22
23	%%compute averages
24	boxnb=NaN*zeros(240,p.nr);
25	boxmean=NaN*zeros(240,p.nr);
26	boxmedian=NaN*zeros(240,p.nr);
27	boxstd=NaN*zeros(240,p.nr);
28	for yy=1992:2011;
29	for mm=1:12;
30	dd=[datenum(yy,mm,0) datenum(yy,mm+1,0)];
31	tt=(yy-1992)*12+mm;
32	%
33	tmp1=MITprof_subset(p,'date',dd);
34	tmp1=tmp1.prof;
35	%
36	boxnb(tt,:)=sum(~isnan(tmp1),1);
37	boxmean(tt,:)=nanmean(tmp1,1);
38	boxmedian(tt,:)=nanmedian(tmp1,1);
39	boxstd(tt,:)=nanstd(tmp1,1);
40	%
41	end;
42	end;
43
44	%%display results
45	if demoSTATS;
46	figure;
47	kk=2;
48	subplot(3,1,1); plot(tim(:,kk),boxnb(:,kk));
49	legend('sample size','Location','NorthWest');
50	subplot(3,1,2); plot(tim(:,kk),boxmean(:,kk)); ylabel('degree C');
51	hold on; plot(tim,boxmedian(:,kk),'r');
52	legend('sample mean','sample median','Location','NorthWest');
53	subplot(3,1,3); plot(tim(:,kk),boxstd(:,kk)); ylabel('degree C');
54	legend('sample std','Location','NorthWest');
55	end;
56