profilesMatlabProcessing/profiles_stats/MITprof_stats_cost.m

function []=MITprof_stats_cost(dirData,listData,listVar,varargin);
%[]=MITprof_stats_cost(dirData,listData,listVar,varargin);
%object:        computes and displays cost function statistics
%input:         dirData is the data directory name
%               listData is the data file list (e.g. {'argo_in*'} or {'argo_in*','argo_at*'} )
%               listVar is the variable list varCur (e.g. {'T'} or {'T','S'} )
%               year0,year1 (optional) is the first,last year pair
%output:        (none -- figures only)
%
%for example:
% dirData='./';
% listData={'argo_in*'}; listVar={'T','S'};
% MITprof_stats_cost(dirData,listData,listVar);


%load paths and grid:
%--------------------
gcmfaces_path; global mygrid; mygrid=[]; grid_load([gcmfaces_dir '/sample_input/GRIDv4/'],5,'compact');

%time limits:
if nargin>3;
    year0=varargin{1}; year1=varargin{2};
    date0=datenum(year0,1,1); date1=datenum(year1,12,31);
else;
    year0=1992; year1=2008;
    date0=datenum(year0,1,1); date1=datenum(year1,12,31);
end;    

figureL;

for vv=1:length(listVar);
    varCur=listVar{vv};
    
    %get the cost square root:
    [MITprof]=MITprof_stats_load(dirData,listData,varCur);
    
    %mask out values that are not in year range:
    ii=find(MITprof.prof_date<date0|MITprof.prof_date>date1);
    MITprof.prof(ii,:)=NaN;
    
    %mean and median:
    costCur=[nanmean(MITprof.prof(:).^2) nanmedian(MITprof.prof(:).^2)];
    fprintf('mean cost for %s: %0.3g (median: %0.3g) \n',varCur,costCur);
    
    %depth/time mean cost:
    tmp_date=(MITprof.prof_date-date0)/365;
    [x,y,z,n]=MITprof_stats(MITprof.prof_depth,MITprof.prof_depth,...
        tmp_date,[0:1/4:1+(year1-year0)],'mean',MITprof.prof.^2);
    z(n<1e2)=NaN;
    subplot(2,length(listVar),vv); depthStretchPlot('pcolor',{y,x,z}); 
    caxis([0 8]); shading flat; colorbar; ylabel('depth (in m)');
    xlabel(['date (in years since ' num2str(year0) ')']); 
    title(sprintf('mean cost for %s: %0.3g (median: %0.3g)',varCur,costCur));
    
    %latitudinal distribution:
    [x,y,z,n]=MITprof_stats(MITprof.prof_lat,[-90:5:90],MITprof.prof,[-5:0.25:5]);
    tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); 
    z(tmp1==0)=NaN;
    subplot(2,length(listVar),vv+length(listVar)); contourf(x,y,z,[0:0.05:0.5]); grid on;
    caxis([0 0.5]); colorbar; ylabel('normalized misfit'); xlabel('latitude'); title('pdf');
    
end;

1	function []=MITprof_stats_cost(dirData,listData,listVar,varargin);
2	%[]=MITprof_stats_cost(dirData,listData,listVar,varargin);
3	%object: computes and displays cost function statistics
4	%input: dirData is the data directory name
5	% listData is the data file list (e.g. {'argo_in'} or {'argo_in','argo_at*'} )
6	% listVar is the variable list varCur (e.g. {'T'} or {'T','S'} )
7	% year0,year1 (optional) is the first,last year pair
8	%output: (none -- figures only)
9	%
10	%for example:
11	% dirData='./';
12	% listData={'argo_in*'}; listVar={'T','S'};
13	% MITprof_stats_cost(dirData,listData,listVar);
14
15
16	%load paths and grid:
17	%--------------------
18	gcmfaces_path; global mygrid; mygrid=[]; grid_load([gcmfaces_dir '/sample_input/GRIDv4/'],5,'compact');
19
20	%time limits:
21	if nargin>3;
22	year0=varargin{1}; year1=varargin{2};
23	date0=datenum(year0,1,1); date1=datenum(year1,12,31);
24	else;
25	year0=1992; year1=2008;
26	date0=datenum(year0,1,1); date1=datenum(year1,12,31);
27	end;
28
29	figureL;
30
31	for vv=1:length(listVar);
32	varCur=listVar{vv};
33
34	%get the cost square root:
35	[MITprof]=MITprof_stats_load(dirData,listData,varCur);
36
37	%mask out values that are not in year range:
38	ii=find(MITprof.prof_date<date0\|MITprof.prof_date>date1);
39	MITprof.prof(ii,:)=NaN;
40
41	%mean and median:
42	costCur=[nanmean(MITprof.prof(:).^2) nanmedian(MITprof.prof(:).^2)];
43	fprintf('mean cost for %s: %0.3g (median: %0.3g) \n',varCur,costCur);
44
45	%depth/time mean cost:
46	tmp_date=(MITprof.prof_date-date0)/365;
47	[x,y,z,n]=MITprof_stats(MITprof.prof_depth,MITprof.prof_depth,...
48	tmp_date,[0:1/4:1+(year1-year0)],'mean',MITprof.prof.^2);
49	z(n<1e2)=NaN;
50	subplot(2,length(listVar),vv); depthStretchPlot('pcolor',{y,x,z});
51	caxis([0 8]); shading flat; colorbar; ylabel('depth (in m)');
52	xlabel(['date (in years since ' num2str(year0) ')']);
53	title(sprintf('mean cost for %s: %0.3g (median: %0.3g)',varCur,costCur));
54
55	%latitudinal distribution:
56	[x,y,z,n]=MITprof_stats(MITprof.prof_lat,[-90:5:90],MITprof.prof,[-5:0.25:5]);
57	tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2));
58	z(tmp1==0)=NaN;
59	subplot(2,length(listVar),vv+length(listVar)); contourf(x,y,z,[0:0.05:0.5]); grid on;
60	caxis([0 0.5]); colorbar; ylabel('normalized misfit'); xlabel('latitude'); title('pdf');
61
62	end;
63