profilesMatlabProcessing/ecco_v4/insitu_cost.m

function []=insitu_cost(doComp,varargin);
%object:        computes or displays cost function statistics
%input:         doComp states whether to compute & save (1) or load & display (0)
%optional must take the following form {'name',param1,param2,...} Active ones are
%               {'dirData',dirData} is the data subdirectory name ('profiles/output/' by default)
%               {'listData',data1,data2,...} where data1 e.g. is 'argo_indian.nc'
%               {'listVar',var1,var2} where var1 and var2 are 'T' and 'S'
%               {'years',year0,year1} to limit computation to [year0 year1] interval
%               {'dirMat',dirMat} where dirMat is the output subdirectory ('mat/' by default)
%               {'suffMat',suffMat} is the mat file suffix ('all' by default)
%               {'dirTex',dirTex} where dirTex is the tex directory ('tex/' by default)
%               {'nameTex',nameTex} is the tex file name ('myPlots' by default)
%               {'addToTex',addToTex} states whether (1) or not (0 default) to 
%                        augment an ongoing tex file (see write2tex.m, dirTex)
%
%example:         insitu_cost('./',1,{'listData','argo_in*'});

%load paths and grid:
%--------------------
global mygrid; if isempty(mygrid); grid_load('GRID/',5,'compact'); end;

%set more optional paramaters to default values
global myparms; year0=myparms.yearInAve(1); year1=myparms.yearInAve(2);
listData={'argo_*_1992_to_2007*','argo_*_2008_to_2010*',...
          'argo_*_2011_to_2012*','climode_*',...
          'ctd_*','itp_*','seals_*','xbt_*'};
listVar={'T','S'}; 
listBas={'atlExt','pacExt','indExt','arct'};
if sum([90 1170]~=mygrid.ioSize)>0; listBas={}; end;
listBasTxt=''; for bb=1:length(listBas); listBasTxt=[listBasTxt ' ' listBas{bb} '*']; end;
%shorter test case: listData={'argo_in*'}; listVar={'T'};
dirData='/profiles/output/';
dirMat='mat/'; suffMat='_all';
dirTex='tex/'; addToTex=0; nameTex='myPlots';
%set more optional paramaters to user defined values
for ii=1:nargin-1;
   if strcmp(varargin{ii}{1},'listData'); listData={varargin{ii}{2:end}}; 
   elseif strcmp(varargin{ii}{1},'listVar'); listVar={varargin{ii}{2:end}};
   elseif strcmp(varargin{ii}{1},'years'); year0=varargin{ii}{2}; year1=varargin{ii}{3};
   elseif strcmp(varargin{ii}{1},'dirMat'); dirMat=varargin{ii}{2};
   elseif strcmp(varargin{ii}{1},'suffMat'); suffMat=['_' varargin{ii}{2}];
   elseif strcmp(varargin{ii}{1},'dirTex'); dirTex=varargin{ii}{2};
   elseif strcmp(varargin{ii}{1},'addToTex'); addToTex=varargin{ii}{2};
   elseif strcmp(varargin{ii}{1},'nameTex'); nameTex=varargin{ii}{2};
   elseif strcmp(varargin{ii}{1},'dirData'); dirData=varargin{ii}{2};
   else;
       warning('inputCheck:insitu_cost',...
           ['unknown option ''' varargin{ii}{1} ''' was ignored']);
   end;
end;

if doComp;

%time limits:
date0=datenum(year0,1,1); date1=datenum(year1,12,31);

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);
    eval(['costAve' varCur '.mean=costCur(1);']);
    eval(['costAve' varCur '.median=costCur(2);']);
    
    %depth/time mean cost:
    tmp_date=(MITprof.prof_date-date0)/365;
%    [x,y,z,n]=MITprof_stats(MITprof.prof_depth,MITprof.prof_depth,...
    [x,y,z,n]=MITprof_stats(MITprof.prof_depth,[0:200:1000 1500:500:6000],...
        tmp_date,[0:1/4:1+(year1-year0)],'mean',MITprof.prof.^2);
    z(n==0)=NaN; n(n==0)=NaN;
    eval(['depthTimeCost' varCur '.x=x;']); eval(['depthTimeCost' varCur '.y=y;']);
    eval(['depthTimeCost' varCur '.z=z;']); eval(['depthTimeCost' varCur '.n=n;']);
    
    %latitudinal distribution:
    [x,y,z,n]=MITprof_stats(MITprof.prof_lat,[-90:5:90],MITprof.prof,[-5:0.25:5]);
    z(n==0)=NaN; n(n==0)=NaN;
    eval(['misfitDistrib' varCur '.x=x;']); eval(['misfitDistrib' varCur '.y=y;']);
    eval(['misfitDistrib' varCur '.z=z;']); eval(['misfitDistrib' varCur '.n=n;']);

    %upper ocean temporal distribution
    for bb=1:length(listBas); 
    for ll=1:3;
      bbb=listBas{bb};
      if ll==1;     Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur];
      elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur];
      elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur];
      end;
      msk=v4_basin(bbb);
      msk(mygrid.YC<Lmin|mygrid.YC>Lmax)=0;
      %
      msk=convert2array(msk);
      MITprof.prof_msk=msk(MITprof.prof_point);     
      MITprofSub=MITprof_subset(MITprof,'msk',1,'depth',[0 700]);      
      %
      tmp_date=(MITprofSub.prof_date-date0)/365;
      [x,y,z,n]=MITprof_stats(tmp_date,[0:1/4:1+(year1-year0)],MITprofSub.prof,[-5:0.25:5]);
      z(n==0)=NaN; n(n==0)=NaN;
      eval([txt '.x=x;']); eval([txt '.y=y;']);
      eval([txt '.z=z;']); eval([txt '.n=n;']);
    end;
    end;

end;

eval(['save ' dirMat 'insitu_cost' suffMat '.mat costAve* misfitDistrib* depthTimeCost* year* ' ...
      'listData listVar listBas ' listBasTxt ';']);

else;%display result

if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end;

eval(['load ' dirMat 'insitu_cost' suffMat '.mat;']);

figureL;

for vv=1:length(listVar);
    varCur=listVar{vv};

    eval(['costCur=[costAve' varCur '.mean costAve' varCur '.median];']);

    eval(['x=depthTimeCost' varCur '.x;']); eval(['y=depthTimeCost' varCur '.y;']);
    eval(['z=depthTimeCost' varCur '.z;']); eval(['n=depthTimeCost' varCur '.n;']);
    z(n<1e2)=NaN; y=y+year0-1;
    subplot(2,length(listVar),vv); depthStretchPlot('pcolor',{y,x,z},[0:200:1000 1500:500:6000],[0 1000 4000]);
    caxis([0 8]); shading flat; colorbar; ylabel('depth (in m)');
    title(sprintf('mean cost for %s: %0.3g (median: %0.3g)',varCur,costCur));

    %latitudinal distribution:
    eval(['x=misfitDistrib' varCur '.x;']); eval(['y=misfitDistrib' varCur '.y;']);
    eval(['z=misfitDistrib' varCur '.z;']); eval(['n=misfitDistrib' varCur '.n;']);
    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;

myCaption={'Cost function (top) for in situ profiles, as a function of depth and time. ',...
        'Distribution of normalized misfits (bottom) as a function of latitude. For T (left) and S (right).'};
if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end;

if ~isempty(listBas);

ii=0;
ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=3;
ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=3;
ii=ii+1; listPanels(ii).bas='arct'; listPanels(ii).ll=3;
ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=2;
ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=2;
ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=2;
ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=1;
ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=1;
ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=1;

for vv=1:length(listVar);
  varCur=listVar{vv};
  figureL;
  for ii=1:9;
      bbb=listPanels(ii).bas; ll=listPanels(ii).ll;
      if ll==1;     Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur];
      elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur];
      elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur];
      end;

    eval(['x=' txt '.x;']); eval(['y=' txt '.y;']);
    eval(['z=' txt '.z;']); eval(['n=' txt '.n;']);
    x=x+year0-1;
    tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); z(tmp1==0)=NaN;
    subplot(3,3,ii); contourf(x,y,z,[0:0.05:0.5]); grid on;
    caxis([0 0.5]); colorbar; title(txt,'Interpreter','none');
    %title([txt ', normalized misfit pdf'],'Interpreter','none');
    if mod(ii,3)==1; ylabel('normalized misfit'); end;
    %if ii<=6; set(gca,'XTick',[]); end;
  end;

myCaption={'Distribution of normalized misfits per basin (panel) as ',...
        'a function of latitude, for ',varCur};
if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end;

end;

end;

end;


1	gforget	1.5	function []=insitu_cost(doComp,varargin);
2	gforget	1.4	%object: computes or displays cost function statistics
3	gforget	1.5	%input: doComp states whether to compute & save (1) or load & display (0)
4	gforget	1.1	%optional must take the following form {'name',param1,param2,...} Active ones are
5	gforget	1.5	% {'dirData',dirData} is the data subdirectory name ('profiles/output/' by default)
6	gforget	1.1	% {'listData',data1,data2,...} where data1 e.g. is 'argo_indian.nc'
7			% {'listVar',var1,var2} where var1 and var2 are 'T' and 'S'
8			% {'years',year0,year1} to limit computation to [year0 year1] interval
9	gforget	1.5	% {'dirMat',dirMat} where dirMat is the output subdirectory ('mat/' by default)
10	gforget	1.4	% {'suffMat',suffMat} is the mat file suffix ('all' by default)
11	gforget	1.5	% {'dirTex',dirTex} where dirTex is the tex directory ('tex/' by default)
12			% {'nameTex',nameTex} is the tex file name ('myPlots' by default)
13	gforget	1.1	% {'addToTex',addToTex} states whether (1) or not (0 default) to
14	gforget	1.5	% augment an ongoing tex file (see write2tex.m, dirTex)
15	gforget	1.1	%
16	gforget	1.4	%example: insitu_cost('./',1,{'listData','argo_in*'});
17	gforget	1.1
18			%load paths and grid:
19			%--------------------
20			global mygrid; if isempty(mygrid); grid_load('GRID/',5,'compact'); end;
21
22			%set more optional paramaters to default values
23	gforget	1.4	global myparms; year0=myparms.yearInAve(1); year1=myparms.yearInAve(2);
24	gforget	1.6	listData={'argo__1992_to_2007','argo__2008_to_2010',...
25			'argo__2011_to_2012','climode_*',...
26			'ctd_','itp_','seals_','xbt_'};
27	gforget	1.2	listVar={'T','S'};
28	gforget	1.7	listBas={'atlExt','pacExt','indExt','arct'};
29	gforget	1.9	if sum([90 1170]~=mygrid.ioSize)>0; listBas={}; end;
30	gforget	1.7	listBasTxt=''; for bb=1:length(listBas); listBasTxt=[listBasTxt ' ' listBas{bb} '*']; end;
31	gforget	1.2	%shorter test case: listData={'argo_in*'}; listVar={'T'};
32	gforget	1.5	dirData='/profiles/output/';
33			dirMat='mat/'; suffMat='_all';
34			dirTex='tex/'; addToTex=0; nameTex='myPlots';
35	gforget	1.1	%set more optional paramaters to user defined values
36	gforget	1.5	for ii=1:nargin-1;
37	gforget	1.1	if strcmp(varargin{ii}{1},'listData'); listData={varargin{ii}{2:end}};
38			elseif strcmp(varargin{ii}{1},'listVar'); listVar={varargin{ii}{2:end}};
39			elseif strcmp(varargin{ii}{1},'years'); year0=varargin{ii}{2}; year1=varargin{ii}{3};
40	gforget	1.5	elseif strcmp(varargin{ii}{1},'dirMat'); dirMat=varargin{ii}{2};
41	gforget	1.1	elseif strcmp(varargin{ii}{1},'suffMat'); suffMat=['_' varargin{ii}{2}];
42	gforget	1.5	elseif strcmp(varargin{ii}{1},'dirTex'); dirTex=varargin{ii}{2};
43	gforget	1.1	elseif strcmp(varargin{ii}{1},'addToTex'); addToTex=varargin{ii}{2};
44	gforget	1.5	elseif strcmp(varargin{ii}{1},'nameTex'); nameTex=varargin{ii}{2};
45			elseif strcmp(varargin{ii}{1},'dirData'); dirData=varargin{ii}{2};
46	gforget	1.1	else;
47			warning('inputCheck:insitu_cost',...
48			['unknown option ''' varargin{ii}{1} ''' was ignored']);
49			end;
50			end;
51
52			if doComp;
53
54			%time limits:
55			date0=datenum(year0,1,1); date1=datenum(year1,12,31);
56
57			for vv=1:length(listVar);
58			varCur=listVar{vv};
59
60			%get the cost square root:
61	gforget	1.5	[MITprof]=MITprof_stats_load([dirData],listData,varCur);
62	gforget	1.1
63			%mask out values that are not in year range:
64			ii=find(MITprof.prof_date<date0\|MITprof.prof_date>date1);
65			MITprof.prof(ii,:)=NaN;
66
67			%mean and median:
68			costCur=[nanmean(MITprof.prof(:).^2) nanmedian(MITprof.prof(:).^2)];
69			fprintf('mean cost for %s: %0.3g (median: %0.3g) \n',varCur,costCur);
70			eval(['costAve' varCur '.mean=costCur(1);']);
71			eval(['costAve' varCur '.median=costCur(2);']);
72
73			%depth/time mean cost:
74			tmp_date=(MITprof.prof_date-date0)/365;
75			% [x,y,z,n]=MITprof_stats(MITprof.prof_depth,MITprof.prof_depth,...
76			[x,y,z,n]=MITprof_stats(MITprof.prof_depth,[0:200:1000 1500:500:6000],...
77			tmp_date,[0:1/4:1+(year1-year0)],'mean',MITprof.prof.^2);
78			z(n==0)=NaN; n(n==0)=NaN;
79			eval(['depthTimeCost' varCur '.x=x;']); eval(['depthTimeCost' varCur '.y=y;']);
80			eval(['depthTimeCost' varCur '.z=z;']); eval(['depthTimeCost' varCur '.n=n;']);
81
82			%latitudinal distribution:
83			[x,y,z,n]=MITprof_stats(MITprof.prof_lat,[-90:5:90],MITprof.prof,[-5:0.25:5]);
84			z(n==0)=NaN; n(n==0)=NaN;
85			eval(['misfitDistrib' varCur '.x=x;']); eval(['misfitDistrib' varCur '.y=y;']);
86			eval(['misfitDistrib' varCur '.z=z;']); eval(['misfitDistrib' varCur '.n=n;']);
87
88	gforget	1.7	%upper ocean temporal distribution
89			for bb=1:length(listBas);
90			for ll=1:3;
91			bbb=listBas{bb};
92			if ll==1; Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur];
93			elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur];
94			elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur];
95			end;
96			msk=v4_basin(bbb);
97			msk(mygrid.YC<Lmin\|mygrid.YC>Lmax)=0;
98			%
99			msk=convert2array(msk);
100			MITprof.prof_msk=msk(MITprof.prof_point);
101			MITprofSub=MITprof_subset(MITprof,'msk',1,'depth',[0 700]);
102			%
103			tmp_date=(MITprofSub.prof_date-date0)/365;
104			[x,y,z,n]=MITprof_stats(tmp_date,[0:1/4:1+(year1-year0)],MITprofSub.prof,[-5:0.25:5]);
105			z(n==0)=NaN; n(n==0)=NaN;
106			eval([txt '.x=x;']); eval([txt '.y=y;']);
107			eval([txt '.z=z;']); eval([txt '.n=n;']);
108			end;
109			end;
110
111	gforget	1.1	end;
112
113	gforget	1.7	eval(['save ' dirMat 'insitu_cost' suffMat '.mat costAve* misfitDistrib* depthTimeCost* year* ' ...
114			'listData listVar listBas ' listBasTxt ';']);
115	gforget	1.1
116			else;%display result
117
118	gforget	1.9	if isdir([dirMat 'cost/']); dirMat=[dirMat 'cost/']; end;
119
120	gforget	1.5	eval(['load ' dirMat 'insitu_cost' suffMat '.mat;']);
121	gforget	1.1
122			figureL;
123
124			for vv=1:length(listVar);
125			varCur=listVar{vv};
126
127			eval(['costCur=[costAve' varCur '.mean costAve' varCur '.median];']);
128
129			eval(['x=depthTimeCost' varCur '.x;']); eval(['y=depthTimeCost' varCur '.y;']);
130			eval(['z=depthTimeCost' varCur '.z;']); eval(['n=depthTimeCost' varCur '.n;']);
131	gforget	1.7	z(n<1e2)=NaN; y=y+year0-1;
132	gforget	1.1	subplot(2,length(listVar),vv); depthStretchPlot('pcolor',{y,x,z},[0:200:1000 1500:500:6000],[0 1000 4000]);
133			caxis([0 8]); shading flat; colorbar; ylabel('depth (in m)');
134			title(sprintf('mean cost for %s: %0.3g (median: %0.3g)',varCur,costCur));
135
136			%latitudinal distribution:
137			eval(['x=misfitDistrib' varCur '.x;']); eval(['y=misfitDistrib' varCur '.y;']);
138			eval(['z=misfitDistrib' varCur '.z;']); eval(['n=misfitDistrib' varCur '.n;']);
139			tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); z(tmp1==0)=NaN;
140			subplot(2,length(listVar),vv+length(listVar)); contourf(x,y,z,[0:0.05:0.5]); grid on;
141			caxis([0 0.5]); colorbar; ylabel('normalized misfit'); xlabel('latitude'); title('pdf');
142
143			end;
144
145	gforget	1.3	myCaption={'Cost function (top) for in situ profiles, as a function of depth and time. ',...
146	gforget	1.4	'Distribution of normalized misfits (bottom) as a function of latitude. For T (left) and S (right).'};
147	gforget	1.5	if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end;
148	gforget	1.1
149	gforget	1.8	if ~isempty(listBas);
150
151	gforget	1.7	ii=0;
152			ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=3;
153			ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=3;
154			ii=ii+1; listPanels(ii).bas='arct'; listPanels(ii).ll=3;
155			ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=2;
156			ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=2;
157			ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=2;
158			ii=ii+1; listPanels(ii).bas='atlExt'; listPanels(ii).ll=1;
159			ii=ii+1; listPanels(ii).bas='pacExt'; listPanels(ii).ll=1;
160			ii=ii+1; listPanels(ii).bas='indExt'; listPanels(ii).ll=1;
161
162			for vv=1:length(listVar);
163			varCur=listVar{vv};
164			figureL;
165			for ii=1:9;
166			bbb=listPanels(ii).bas; ll=listPanels(ii).ll;
167			if ll==1; Lmin=-90; Lmax=-25; txt=[bbb '_90S25S_misDis' varCur];
168			elseif ll==2; Lmin=-25; Lmax=25; txt=[bbb '_25S25N_misDis' varCur];
169			elseif ll==3; Lmin=25; Lmax=90; txt=[bbb '_25N90N_misDis' varCur];
170			end;
171
172			eval(['x=' txt '.x;']); eval(['y=' txt '.y;']);
173			eval(['z=' txt '.z;']); eval(['n=' txt '.n;']);
174			x=x+year0-1;
175			tmp1=(nansum(n,2)>1e4)*ones(1,size(n,2)); z(tmp1==0)=NaN;
176			subplot(3,3,ii); contourf(x,y,z,[0:0.05:0.5]); grid on;
177			caxis([0 0.5]); colorbar; title(txt,'Interpreter','none');
178			%title([txt ', normalized misfit pdf'],'Interpreter','none');
179			if mod(ii,3)==1; ylabel('normalized misfit'); end;
180			%if ii<=6; set(gca,'XTick',[]); end;
181			end;
182
183			myCaption={'Distribution of normalized misfits per basin (panel) as ',...
184			'a function of latitude, for ',varCur};
185			if addToTex; write2tex([dirTex '/' nameTex '.tex'],2,myCaption,gcf); end;
186
187			end;
188
189	gforget	1.1	end;
190
191	gforget	1.8	end;
192
193	gforget	1.1