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function [myStat]=profiles_subgrid_stats(KK,VV,TYPE,SUB,COORD); |
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%KK level choice |
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%VV variable choice |
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%TYPE 'obs' 'estim' or 'anom' |
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%SUB is the subsampling rate (box width=SUB) |
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%COORD is the coordinate type |
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|
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%global variables: |
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gcmfaces_global; |
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global lon lat obs point; |
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global COORDOld; if isempty(COORDOld); COORDOld='x'; end; |
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global VVOld; if isempty(VVOld); VVOld='x'; end; |
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global TYPEOld; if isempty(TYPEOld); TYPEOld='x'; end; |
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global KKOld; if isempty(KKOld); KKOld=0; end; |
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|
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%choice of time/depth ranges |
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if strcmp(COORD,'depth'); |
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%KK is ecco v4 level index; kk is corresponding MITprof level indices |
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RC=squeeze(rdmds([myenv.gcmfaces_dir '/sample_input/GRIDv4/RC'])); |
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RF=squeeze(rdmds([myenv.gcmfaces_dir '/sample_input/GRIDv4/RF'])); |
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depth0=-RF(1:end-1); depth0(2:end-1)=depth0(1:end-2); |
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depth1=-RF(2:end); depth1(2:end-1)=depth1(3:end); |
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if KK>=1; |
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depth0=depth0(KK); depth1=depth1(KK);%choice of depth range |
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else; |
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error('not implemented'); |
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end; |
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end; |
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% |
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date0=datenum(1950,1,1); date1=datenum(2049,12,31);%choice of time range |
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|
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%get the grid: |
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grid_load([myenv.gcmfaces_dir '/sample_input/GRIDv4/'],5,'compact'); |
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gcmfaces_bindata; |
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|
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%get the data: |
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dirData='./'; |
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listData=dir([dirData 'argo_2may13_set*.nc']); |
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listData={listData(:).name}; |
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suffOut='argo'; |
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|
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% |
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test1=~strcmp(VV,VVOld)|~strcmp(TYPE,TYPEOld)|KK~=KKOld|~strcmp(COORD,COORDOld); |
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if test1; |
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if strcmp(TYPE,'anom'); |
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[MITprof]=MITprof_stats_load(dirData,listData,VV,1); |
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elseif strcmp(TYPE,'estim'); |
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[MITprof]=MITprof_stats_load(dirData,listData,VV,['prof_' VV 'estim']); |
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else; |
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[MITprof]=MITprof_stats_load(dirData,listData,VV,['prof_' VV]); |
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end; |
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%in DRHODR case, switch to log10 : |
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if strcmp(VV,'DRHODR'); MITprof.prof=log10(MITprof.prof); end; |
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%mask out values that are not in year range: |
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ii=find(MITprof.prof_date<date0|MITprof.prof_date>date1); |
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MITprof.prof(ii,:)=NaN; |
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%restrict to depth range of interest: |
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if strcmp(COORD,'depth'); |
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%KK is ecco v4 level index; kk is corresponding MITprof level indices |
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kk=find(MITprof.prof_depth>=depth0&MITprof.prof_depth<=depth1); |
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else; |
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%kk is simply KK; assumes same density grid throughout |
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kk=KK; |
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end; |
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lon=MITprof.prof_lon; lat=MITprof.prof_lat; obs=MITprof.prof(:,kk); |
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end; |
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% |
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KKOld=KK; |
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VVOld=VV; |
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TYPEOld=TYPE; |
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COORDOld=COORD; |
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|
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%get indices in full grid: (not necessarily the ecco_v4 one) |
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point=gcmfaces_bindata(lon,lat); |
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|
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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|
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%check nearest neighbor mapping: |
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% [tmp1,tmp2]=gcmfaces_bindata(lon,lat,lon); |
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% figureL; qwckplot(log10(tmp2)); |
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% figureL; qwckplot(tmp1./tmp2); |
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|
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%map of full grid indices: (consistent with prof_point2) |
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indGrid=convert2array(mygrid.XC); |
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indGrid(:)=[1:length(indGrid(:))]; |
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indGrid=convert2array(indGrid); |
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|
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%reduce grid and map reduced grid indices: |
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indBox=mygrid.XC; |
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if SUB==0; |
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%global computation |
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indBox(:)=1; |
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else; |
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%regional computation |
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boxMax=0; |
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for iFace=1:mygrid.nFaces; |
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tmp1=indBox{iFace}; |
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tmp3=ceil([1:size(tmp1,1)]'/SUB); |
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tmp4=(ceil([1:size(tmp1,2)]/SUB)-1)*max(tmp3); |
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tmp5=tmp3*ones(1,size(tmp1,2))+ones(size(tmp1,1),1)*tmp4; |
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indBox{iFace}=tmp5+boxMax; |
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boxMax=boxMax+max(tmp5(:)); |
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end; |
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end; |
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|
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
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|
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%main computational loop: stats for each region in indBox |
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% |
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indBox=convert2array(indBox); |
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box=repmat(indBox(point),[1 size(obs,2)]); |
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box(isnan(obs))=NaN; |
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boxList=unique(indBox(:)); |
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boxList=boxList(find(~isnan(boxList))); |
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% |
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tmp1=convert2array(0*mygrid.XC); |
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myStat.mea=tmp1; myStat.prc90=tmp1; myStat.med=tmp1; myStat.prc10=tmp1; myStat.nb=tmp1; |
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myStat.std=tmp1; myStat.iqr=tmp1; myStat.mad=tmp1; |
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% |
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for ii=boxList'; |
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if mod(ii,1000)==0; |
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[KK ii length(boxList)] |
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end; |
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jj=find(box==ii); |
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if length(jj)>=10; |
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tmpStat=myStats(obs(jj));%need reduced params |
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jj=find(indBox==ii); |
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tmpList=fieldnames(tmpStat); |
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for pp=1:length(tmpList); |
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eval(['myStat.' tmpList{pp} '(jj)=tmpStat.' tmpList{pp} ';']); |
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end; |
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end; |
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end; |
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% |
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tmpList=fieldnames(myStat); |
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for pp=1:length(tmpList); |
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eval(['myStat.' tmpList{pp} '=convert2array(myStat.' tmpList{pp} ');']); |
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end; |
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|
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eval(['save ' dirData 'stats/' VV '_k' num2str(KK) '_' num2str(SUB) '.mat myStat;']); |
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|
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function [myStat]=myStats(obs); |
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|
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myStat.nb=sum(~isnan( obs )); |
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|
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myStat.mea=mean(obs);%sample mean |
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myStat.prc10=prctile(obs,10); |
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myStat.med=median(obs); |
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myStat.prc90=prctile(obs,90); |
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|
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myStat.std=std(obs);%sample standard deviation |
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myStat.iqr=0.7413*iqr(obs);%intequartile range estimate of std |
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myStat.mad=1.4826*mad(obs,1);%median absolute difference estimate of std |
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