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calc_ica_pred_noDP.m
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%% sea ice cover anomaly experiments
% clear all
close all
% region = 'scratch'
% region = 'Arctic';
% region = 'ChukchiBeaufort';
% region = 'Beaufort';
% region = 'Chukchi';
% region = 'EastSibLaptev';
% region = 'EastSib';
% region = 'Laptev';
% region = 'BarentsKara';
% region = 'Barents';
% region = 'Kara';
% region = 'Greenland';
% region = 'Baffin';
% region = 'Labrador';
% region = 'Hudson';
% region = 'Bering';
% region = 'Okhotsk';
% embedWin = 12;
% varsUsed = 'SIC';
% varsUsed = 'SIC_SST';
% varsUsed = 'SIC_SST_SIT';
% varsUsed = 'SIC_SST_SIT_SLP';
% predOn = 1;
% fullDataOn = 1;
%% define experiment
switch region
case 'scratch'
lonLim = [165 200];
latLim = [55 65];
case 'Arctic'
lonLim = [0 360];
latLim = [45 90];
case 'ChukchiBeaufort'
lonLim = [175 235];
latLim = [65 75];
case 'Chukchi'
lonLim = [175 205];
latLim = [65 75];
case 'Beaufort'
lonLim = [205 235];
latLim = [65 75];
case 'EastSibLaptev'
lonLim = [105 175];
latLim = [65 75];
case 'EastSib'
lonLim = [140 175];
latLim = [65 75];
case 'Laptev'
lonLim = [105 140];
latLim = [70 80];
case 'BarentsKara'
lonLim = [30 95];
latLim = [65 80];
case 'Barents'
lonLim = [30 60];
latLim = [65 80];
case 'Kara'
lonLim = [60 95];
latLim = [65 80];
case 'Greenland'
lonLim = [325 360];
latLim = [65 80];
case 'Baffin'
lonLim = [280 310];
latLim = [70 80];
case 'Labrador'
lonLim = [290 310];
latLim = [50 70];
case 'Hudson'
lonLim = [265 285];
latLim = [55 65];
case 'Bering'
lonLim = [165 200];
latLim = [55 65];
case 'Okhotsk'
lonLim = [135 165];
latLim = [45 65];
end
switch varsUsed
case 'SIC'
varsFlag = 1;
case 'SIC_SST'
varsFlag = 2;
case 'SIC_SST_SIT'
varsFlag = 3;
case 'SIC_SST_SIT_SLP'
varsFlag = 4;
case 'SIC_SIT'
varsFlag = 5;
case 'SIC_SLP'
varsFlag = 6;
end
saveTag = strcat(region,'_',varsUsed,'_q',num2str(embedWin),'_train_',num2str(trainLim(1)),'_',num2str(trainLim(2)));
saveDir = fullfile('output/',saveTag,'/');
arcticTag = strcat('Arctic_',varsUsed,'_q',num2str(embedWin),'_train_',num2str(trainLim(1)),'_',num2str(trainLim(2)));
arcticDir = fullfile('output/',arcticTag,'/');
if exist(saveDir) == 0
mkdir(saveDir)
end
trainTag = sprintf( 'x%i-%i_y%i-%i_yr%i-%i', lonLim( 1 ), ...
lonLim( 2 ), ...
latLim( 1 ), ...
latLim( 2 ), ...
trainLim( 1 ), ...
trainLim( 2 ) );
testTag = sprintf( 'x%i-%i_y%i-%i_yr%i-%i', lonLim( 1 ), ...
lonLim( 2 ), ...
latLim( 1 ), ...
latLim( 2 ), ...
testLim( 1 ), ...
testLim( 2 ) );
%% get raw data
checkDir = fullfile('data/raw/CCSM4_Data/b40.1850/SIC/',trainTag,'/data/');
if exist(checkDir) == 0
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),trainLim(1),trainLim(2),'SIC')
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),testLim(1),testLim(2),'SIC')
end
checkDir = fullfile('data/raw/CCSM4_Data/b40.1850/SST/',trainTag,'/data/');
if exist(checkDir) == 0
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),trainLim(1),trainLim(2),'SST')
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),testLim(1),testLim(2),'SST')
end
checkDir = fullfile('data/raw/CCSM4_Data/b40.1850/SIT/',trainTag,'/data/');
if exist(checkDir) == 0
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),trainLim(1),trainLim(2),'SIT')
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),testLim(1),testLim(2),'SIT')
end
%% calculate anomalies
checkFile = fullfile(strcat(saveDir,'ICA.mat'));
if exist(checkFile) == 0
dataTrainPath = fullfile('data/raw/CCSM4_Data/b40.1850/SIA/',trainTag,'/data/');
dataTestPath = fullfile('data/raw/CCSM4_Data/b40.1850/SIA/',testTag,'/data/');
if exist(dataTrainPath) == 0
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),trainLim(1),trainLim(2),'SIA')
ccsm4DataRaw(lonLim(1),lonLim(2),latLim(1),latLim(2),testLim(1),testLim(2),'SIA')
end
load ( fullfile( dataTrainPath, 'dataX.mat' ) )
ice_raw = x; % dimensions space x time
% domain climatology
ice_clim = zeros(12,1);
ice_anom_train = zeros(nT,1);
for i = 1:12
month = 0;
j = 1;
while i + (j-1)*12 <=nT
month(j) = sum(ice_raw(:,i+(j-1)*12));
j = j+1;
end
ice_clim(i) = mean(month);
end
for i = 1:nT
if mod(i,12) ~= 0
ice_anom_train(i) = sum(ice_raw(:,i)) - ice_clim(mod(i,12));
elseif mod(i,12) == 0
ice_anom_train(i) = sum(ice_raw(:,i)) - ice_clim(12);
end
end
load ( fullfile( dataTestPath, 'dataX.mat' ) )
ice_raw = x; % dimensions space x time
ice_anom_test = zeros(nT,1);
for i = 1:nT
if mod(i,12) ~= 0
ice_anom_test(i) = sum(ice_raw(:,i)) - ice_clim(mod(i,12));
elseif mod(i,12) == 0
ice_anom_test(i) = sum(ice_raw(:,i)) - ice_clim(12);
end
end
ice_anom_train = ice_anom_train*10^(-6);
ice_anom_test = ice_anom_test*10^(-6);
ice_clim = ice_clim*10^(-6);
S = fullfile(strcat(saveDir,'ICA.mat'));
save(S,'ice_anom_train','ice_anom_test','ice_clim')
end
%% evaluate kernel distances, either based on region only or pan-Arctic data
if fullDataOn == 0
checkFile = fullfile(strcat(saveDir,'pMatrix.mat'));
end
if fullDataOn == 1
checkFile = fullfile(strcat(arcticDir, 'pMatrix.mat'))
end
if exist(checkFile) == 0
if fullDataOn == 0
model = nlsa_ose_ica( lonLim, latLim, trainLim, testLim, embedWin, varsFlag );
end
if fullDataOn == 1
model = nlsa_ose_ica( [0 360], [45 90], trainLim, testLim, embedWin, varsFlag );
end
disp( 'Embedding' ); makeEmbedding( model )
disp( 'Phase space velocity' ); computePhaseSpaceVelocity( model, 'ifWriteXi', true )
fprintf( 'Pairwise distances, %i/%i\n', 1, 1 ); computePairwiseDistances( model, 1, 1 )
disp( 'OSE embedding' ); makeOSEEmbedding( model );
disp( 'OSE phase space velocity' ); computeOSEPhaseSpaceVelocity( model, 'ifWriteXi', true )
fprintf( 'OSE pairwise distances, %i/%i\n', 1, 1 ); computeOSEPairwiseDistances( model, 1, 1 )
distPath = model.pDistance.path;
distPath = fullfile( distPath, model.pDistance.pathY );
% dcnote find cleaner way
if embedWin == 6
load ( fullfile( distPath, 'dataY_1_1-4791.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
elseif embedWin == 12
load ( fullfile( distPath, 'dataY_1_1-4785.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
elseif embedWin == 24
load ( fullfile( distPath, 'dataY_1_1-4773.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
end
dist_ord = zeros(size(p1));
[disti, distj] = size(p1);
for i = 1:disti
for j = 1:distj
dist_ord(i,y1(i,j)) = p1(i,j);
end
end
clear p1 y1
oseDistPath = model.osePDistance.path;
oseDistPath = fullfile( oseDistPath, model.osePDistance.pathY );
if embedWin == 6
load ( fullfile( oseDistPath, 'dataY_1_1-4791.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
elseif embedWin == 12
load ( fullfile( oseDistPath, 'dataY_1_1-4785.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
elseif embedWin == 24
load ( fullfile( oseDistPath, 'dataY_1_1-4773.mat' ) );
p1 = yVal;
y1 = yInd;
clear yVal yInd;
end
% form kernel matrix
oseDist_ord = zeros(size(p1));
[disti, distj] = size(p1);
for i = 1:disti
for j = 1:distj
oseDist_ord(i,y1(i,j)) = p1(i,j);
end
end
clear p1 y1
if fullDataOn == 0
S = fullfile(strcat(saveDir,'pMatrix.mat'));
end
if fullDataOn == 1
S = fullfile(strcat(arcticDir,'pMatrix.mat'));
end
save(S,'dist_ord','oseDist_ord')
rmdir('ica_scratch/*','s')
end
%% form predictions
checkFile = fullfile(strcat(saveDir,'pred_ica.mat'));
if exist(checkFile) == 0 | predOn == 1
S = fullfile(strcat(saveDir,'ICA.mat'));
load(S)
% note shift by embedding window, as well as adjustment for phase space
% velocity calculation (In.fdOrder = 4 in nlsa_ose_ica.m)
data_train = ice_anom_train(embedWin + 2: end - 2);
data_test = ice_anom_test(embedWin + 2: end - 2);
S = fullfile(strcat(saveDir,'pMatrix.mat'));
load(S)
% Laplacian pyramid extention inputs
tLag = 13;
d_ref = dist_ord(1:end-tLag,1:end-tLag);
d_ose = oseDist_ord(:,1:end-tLag);
f_ref = data_train;
A=d_ref;
A(d_ref==0)=NaN;
eps_0 = nanmedian(nanmedian(A));
% eps_0 = .1*eps_0;
decomp = LP_precomp(d_ref, f_ref, tLag, eps_0);
V_pred = LP_forecast(d_ose, eps_0, decomp);
f_ext = V_pred(:,1);
% check for NaNs in predictions - make loop over loosening tol_cons
S = fullfile(strcat(saveDir,'nan_sum.mat'));
if exist(S) > 0
delete(S)
end
if sum(sum(isnan(V_pred))) > 0
nan_sum = sum(sum(isnan(V_pred)))
save(S,'nan_sum')
end
% errors for all
pred_traj = V_pred(1:end-tLag+1,:);
% format truth
[nIter, tmp] = size(pred_traj);
truth = zeros(nIter,tLag);
for j = 1:nIter
for i = 1:tLag
truth(j,i) = data_test(j+i-1);
end
end
[ pred_rms, pred_pc, pred_rmsP, pred_pcP ] = calc_errors_v2( pred_traj, truth );
% condition trajectories on initial month
pred_rmsIM = zeros(12,tLag);
pred_pcIM = zeros(12,tLag);
pred_rmsIMP = zeros(12,tLag);
pred_pcIMP = zeros(12,tLag);
pred_rmsTM = zeros(12,tLag);
pred_pcTM = zeros(12,tLag);
pred_rmsTMP = zeros(12,tLag);
pred_pcTMP = zeros(12,tLag);
mIter = floor(nIter/12);
for m = 1:12
initM = m;
% initial month - predictions start in month initM
pred_trajM = zeros(mIter,tLag);
truthM = zeros(mIter,tLag);
for j = 1:mIter-1
pred_trajM(j,:) = pred_traj(initM + (j-1)*12, :);
truthM(j,:) = truth(initM + (j-1)*12, :);
end
[ pred_rms_tmp, pred_pc_tmp, pred_rmsP_tmp, pred_pcP_tmp ] = calc_errors_v2( pred_trajM, truthM );
pred_rmsIM(initM,:) = pred_rms_tmp;
pred_pcIM(initM,:) = pred_pc_tmp;
pred_rmsIMP(initM,:) = pred_rmsP_tmp;
pred_pcIMP(initM,:) = pred_pcP_tmp;
% target month - predictions end in month initM
pred_trajM = zeros(mIter,tLag);
truthM = zeros(mIter,tLag);
for j = 1:mIter-1
for i = 1:tLag
pred_trajM(j,i) = pred_traj(initM + (i-1) + (j-1)*12, i);
truthM (j,i) = truth (initM + (i-1) + (j-1)*12, i);
end
end
[ pred_rms_tmp, pred_pc_tmp, pred_rmsP_tmp, pred_pcP_tmp ] = calc_errors_v2( pred_trajM, truthM );
pred_rmsTM(initM,:) = pred_rms_tmp;
pred_pcTM(initM,:) = pred_pc_tmp;
pred_rmsTMP(initM,:) = pred_rmsP_tmp;
pred_pcTMP(initM,:) = pred_pcP_tmp;
end
S = fullfile(strcat(saveDir,'pred_ica.mat'));
save(S,'pred_traj','pred_rms','pred_pc','pred_rmsIM','pred_pcIM','pred_rmsTM','pred_pcTM', ...
'pred_rmsP','pred_pcP','pred_rmsIMP','pred_pcIMP','pred_rmsTMP','pred_pcTMP', ...
'f_ext','truth','d_ref','d_ose','tLag','data_train','data_test','eps_0')
end