| 1 |
function [myFld,myFld1]=profiles_subgrid_stats_assemble(VV,KK,choiceFld,COORD); |
| 2 |
%KK level choice |
| 3 |
%VV variable choice |
| 4 |
%choiceFld stat choice |
| 5 |
%COORD is the coordinate type |
| 6 |
|
| 7 |
doSave=1; |
| 8 |
dirData='./'; |
| 9 |
|
| 10 |
%========= PART 1 : load grid & atlases ======== |
| 11 |
|
| 12 |
gcmfaces_global; |
| 13 |
|
| 14 |
listSGN=[0 45 30 18 15 10 9 6 5 3 2 1] |
| 15 |
|
| 16 |
global atlas; |
| 17 |
test0=isempty(atlas);%no previously loaded atlas? |
| 18 |
if ~test0; test0=~strcmp(atlas.coord,COORD); end;%same coordinate as before? |
| 19 |
if test0; |
| 20 |
atlas=[]; |
| 21 |
atlas.coord=COORD; |
| 22 |
% |
| 23 |
dirAtlases=[myenv.gcmfaces_dir 'sample_input/OCCAetcONv4GRID/']; |
| 24 |
if ~strcmp(atlas.coord,'depth'); |
| 25 |
eval(['load ' myenv.gcmfaces_dir 'gcmfaces_devel/RCsig0.mat RCsig0;']); |
| 26 |
atlas.RC=RCsig0; |
| 27 |
txt=['_' atlas.coord]; |
| 28 |
else; |
| 29 |
atlas.RC=-mygrid.RC; |
| 30 |
txt=''; |
| 31 |
end; |
| 32 |
nr=length(atlas.RC); |
| 33 |
% |
| 34 |
if ~strcmp(atlas.coord,'depth'); |
| 35 |
tmp1=read2memory([dirAtlases 'D_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); |
| 36 |
tmp1(tmp1==0)=NaN; |
| 37 |
atlas.D=convert2gcmfaces(tmp1); |
| 38 |
% |
| 39 |
tmp1=1*(sum(~isnan(atlas.D),4)>2); |
| 40 |
tmp1(tmp1==0)=NaN; |
| 41 |
% |
| 42 |
tmp2=nanmean(atlas.D,4); |
| 43 |
tmp2=1*(tmp2<2000); |
| 44 |
tmp2(tmp2==0)=NaN; |
| 45 |
% |
| 46 |
atlas.mskC=tmp1.*tmp2; |
| 47 |
else; |
| 48 |
atlas.mskC=mygrid.mskC; |
| 49 |
end; |
| 50 |
% |
| 51 |
if 0;%only needed for slanted diffusion |
| 52 |
tmp1=read2memory([dirAtlases 'T_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); |
| 53 |
tmp1(tmp1==0)=NaN; |
| 54 |
atlas.T=convert2gcmfaces(tmp1); |
| 55 |
% |
| 56 |
tmp1=read2memory([dirAtlases 'S_OWPv1_M_eccollc_90x50' txt '.bin'],[90 1170 nr 12]); |
| 57 |
tmp1(tmp1==0)=NaN; |
| 58 |
atlas.S=convert2gcmfaces(tmp1); |
| 59 |
end; |
| 60 |
end; |
| 61 |
|
| 62 |
%========= PART 2 : load and average estimates of std ======== |
| 63 |
|
| 64 |
%if result was not completed, then skip: |
| 65 |
test0=dir([dirData 'stats/' VV '_k' num2str(KK) '_' num2str(1) '.mat']); |
| 66 |
if isempty(test0); myFld=NaN*mygrid.RAC; myFld1=myFld; return; end; |
| 67 |
|
| 68 |
listStats={'prc10','mea','med','prc90','std','iqr','mad'}; |
| 69 |
|
| 70 |
myWeightPower=4 |
| 71 |
|
| 72 |
for sgn=listSGN; |
| 73 |
eval(['load ' dirData 'stats/' VV '_k' num2str(KK) '_' num2str(sgn) '.mat myStat;']); |
| 74 |
%"bootstrap" |
| 75 |
kk=find(listSGN==sgn); |
| 76 |
if kk==1; |
| 77 |
myFld=myStat; |
| 78 |
w=myStat.nb/(sqrt(90*1170)^myWeightPower); |
| 79 |
myFld.nb=w; |
| 80 |
for ff=1:length(listStats); |
| 81 |
eval(['myFld.' listStats{ff} '=myStat.' listStats{ff} '.*w;']); |
| 82 |
end; |
| 83 |
else; |
| 84 |
w=myStat.nb/(sgn^myWeightPower); |
| 85 |
myFld.nb=myFld.nb+w; |
| 86 |
for ff=1:length(listStats); |
| 87 |
eval(['myFld.' listStats{ff} '=myFld.' listStats{ff} '+myStat.' listStats{ff} '.*w;']); |
| 88 |
end; |
| 89 |
end; |
| 90 |
end; |
| 91 |
|
| 92 |
%THIS WAS A BUG : myFld.nb=myFld.nb+w; |
| 93 |
for ff=1:length(listStats); |
| 94 |
eval(['myFld.' listStats{ff} '=(myFld.' listStats{ff} './myFld.nb);']); |
| 95 |
end; |
| 96 |
myFld.msk=atlas.mskC(:,:,KK); |
| 97 |
|
| 98 |
%original value & "local" value forcing: |
| 99 |
suff=listStats{choiceFld}; |
| 100 |
eval(['myFld1=myFld.msk.*myFld.' suff ';']); |
| 101 |
|
| 102 |
%========= PART 3 : smoothing setup ======== |
| 103 |
|
| 104 |
if 0;%simple smoothing, which does not account for no. of obs |
| 105 |
eval(['myFld.mean=myFld.msk.*atlas.' VV '(:,:,KK);']); |
| 106 |
myFld.sm0=diffsmooth2D(myFld1,mygrid.DXC*3,mygrid.DYC*3); |
| 107 |
dxy=3*sqrt(mygrid.RAC); |
| 108 |
myFld.sm1=diffsmooth2D(myFld1,dxy,dxy); |
| 109 |
myFld.sm2=diffsmooth2Drotated(myFld1,dxy,dxy/10,myFld.mean); |
| 110 |
end; |
| 111 |
|
| 112 |
|
| 113 |
%scale the diffusive operator: |
| 114 |
dxLarge=3*sqrt(mygrid.RAC); |
| 115 |
dxSmall=0.1*dxLarge; |
| 116 |
|
| 117 |
%time scale: |
| 118 |
tmp0=dxLarge./mygrid.DXC; tmp0(isnan(myFld1))=NaN; tmp00=nanmax(tmp0); |
| 119 |
tmp0=dxLarge./mygrid.DYC; tmp0(isnan(myFld1))=NaN; tmp00=max([tmp00 nanmax(tmp0)]); |
| 120 |
nbt=tmp00; |
| 121 |
nbt=ceil(1.1*2*nbt^2); |
| 122 |
|
| 123 |
dt=1; |
| 124 |
T=nbt*dt; |
| 125 |
|
| 126 |
%build diffusion operator: |
| 127 |
kLarge=dxLarge.*dxLarge/T/2; |
| 128 |
kSmall=dxSmall.*dxSmall/T/2; |
| 129 |
|
| 130 |
if 1;%isotropic diffusion, rather than slanted diffusion |
| 131 |
Kux=dxLarge.*dxLarge/T/2; |
| 132 |
Kvy=dxLarge.*dxLarge/T/2; |
| 133 |
Kuy=[]; Kvx=[]; |
| 134 |
else;%slanted diffusion |
| 135 |
eval(['myFld.mean=myFld.msk.*atlas.' VV '(:,:,KK);']); |
| 136 |
[Kux,Kuy,Kvx,Kvy]=diffrotated(kLarge,kSmall,myFld.mean); |
| 137 |
end; |
| 138 |
|
| 139 |
%finalize diffusion/smoothing problem set-up: |
| 140 |
myOp.dt=1; |
| 141 |
% myOp.nbt=nbt; |
| 142 |
myOp.eps=1e-3; |
| 143 |
myOp.Kux=Kux; |
| 144 |
myOp.Kuy=Kuy; |
| 145 |
myOp.Kvx=Kvx; |
| 146 |
myOp.Kvy=Kvy; |
| 147 |
|
| 148 |
%========= PART 4 : relaxation term setup ======== |
| 149 |
|
| 150 |
%1) set relaxation strength: (local <-> smoother) |
| 151 |
%--------------------------- |
| 152 |
|
| 153 |
%use the myFld.nb index, modified as follows |
| 154 |
w=myFld.nb; |
| 155 |
%I do a linear transiton in log10 |
| 156 |
w=log10(w); |
| 157 |
%by mapping [-2 2] to [2 -1] |
| 158 |
w=(-1-3*(w-2)/(2+2)); |
| 159 |
%go back to original units (~nb obs) and scale by nbt (nbt = 1 smoother) |
| 160 |
w=nbt*exp( w*log(10) ); |
| 161 |
%ensure stability |
| 162 |
w(w<1)=1; |
| 163 |
%enforce minimum forcing |
| 164 |
w(w>1e3*nbt)=1e3*nbt; |
| 165 |
if 0; |
| 166 |
%figureL; m_map_gcmfaces(log10(myFld.nb),0,{'myCaxis',[-4 3]}); |
| 167 |
figureL; m_map_gcmfaces(log10(w/nbt),0,{'myCaxis',[-2 2]}); return; |
| 168 |
end; |
| 169 |
myOp.tau=w*myOp.dt; |
| 170 |
|
| 171 |
% myOp.tau=0.5*myOp.dt; |
| 172 |
% myOp.tau=nbt*myOp.dt; |
| 173 |
% myOp.tau=nbt; |
| 174 |
|
| 175 |
%2) set relaxation field: ("local" value) |
| 176 |
%------------------------ |
| 177 |
|
| 178 |
fldRelax=myFld1; |
| 179 |
|
| 180 |
|
| 181 |
%========= PART 5 : resolve smoothing/relaxation problem ======== |
| 182 |
% |
| 183 |
% here we integrate to a balance between |
| 184 |
% "local" value (relaxation term) |
| 185 |
% vs smoothing (diffusion) |
| 186 |
|
| 187 |
myFld=gcmfaces_timestep(myOp,myFld1,fldRelax); |
| 188 |
|
| 189 |
%plot / save result: |
| 190 |
%=================== |
| 191 |
|
| 192 |
if 0; |
| 193 |
figureL; m_map_gcmfaces(log10(myFld),0,{'myCaxis',[-1.5 0.5]}); |
| 194 |
end; |
| 195 |
|
| 196 |
if doSave; |
| 197 |
eval(['save ' dirData 'stats/' VV '_k' num2str(KK) '_' suff '.mat myFld myFld1;']); |
| 198 |
end; |
| 199 |
|
Parent Directory
| 
Revision Log
| 
Revision Graph