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Commit faac0d9f authored by gael.alory_legos.obs-mip.fr's avatar gael.alory_legos.obs-mip.fr
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Ajout de valeurs suggérées par défaut lors de la demande de bias et erreur à... 

Ajout de valeurs suggérées par défaut lors de la demande de bias et erreur à attribuer à la série TSG:
- moyenne des différences échantillons-TSG pour le biais
- écart-type des différences pour l'erreur associée
(écart-type négatif s'il n'y a que 2 échantillons ou égal à -1 s'il n'y en a qu'un)
parent caa1a583
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tsg_util/corTsgBias.m
+ 132
− 82
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......@@ -40,15 +40,15 @@ keptCode = [];
nKeptCode = 0;
for key = qc_list
% get handle of checkbox
% ----------------------
hCb = findobj(hMainFig, 'tag', ['TAG_CHECK_CORRECTION_' char(key)]);
if get( hCb, 'value' )
nKeptCode = nKeptCode + 1;
keptCode(nKeptCode) = tsg.qc.hash.(key).code;
end
% get handle of checkbox
% ----------------------
hCb = findobj(hMainFig, 'tag', ['TAG_CHECK_CORRECTION_' char(key)]);
if get( hCb, 'value' )
nKeptCode = nKeptCode + 1;
keptCode(nKeptCode) = tsg.qc.hash.(key).code;
end
end
% Get PROBABLY_GOOD, PROBABLY_BAD and VALUE_CHANGED codes
......@@ -62,85 +62,135 @@ VALUE_CHANGED = tsg.qc.hash.VALUE_CHANGED.code;
% BE CAREFUL:
% netcdf toolbox failed with assertion when we write NaN to ncbyte variable
% -------------------------------------------------------------------------
if isempty( tsg.([PARA{1} '_ADJUSTED_ERROR']) )
tsg.([PARA{1} '_ADJUSTED']) = NaN*ones(size(tsg.(PARA{1})));
tsg.([PARA{1} '_ADJUSTED_QC']) = zeros(size(tsg.([PARA{1} '_QC'])));
tsg.([PARA{1} '_ADJUSTED_ERROR']) = NaN*ones(size(tsg.(PARA{1})));
if isempty( tsg.([PARA{1} '_ADJUSTED_ERROR']) )
tsg.([PARA{1} '_ADJUSTED']) = NaN*ones(size(tsg.(PARA{1})));
tsg.([PARA{1} '_ADJUSTED_QC']) = zeros(size(tsg.([PARA{1} '_QC'])));
tsg.([PARA{1} '_ADJUSTED_ERROR']) = NaN*ones(size(tsg.(PARA{1})));
end
% Enter the bias that will be applied to PARA{1}
% ----------------------------------------------
defaultValue = {'0'};
prompt = ['Constant value to be applied to the ' PARA{1} ' time series'];
a = inputdlg(prompt,'Bias Correction',1,defaultValue);
prompt = ['Error value to be applied to the ' PARA{1} ' time series'];
b = inputdlg(prompt,'Bias Error',1,defaultValue);
% everything OK
% -------------
error = 1;
if ~isempty( a )
% If necessary replace a comma by a point
% ---------------------------------------
bias = regexprep(a, ',', '.');
biasError = regexprep(b, ',', '.');
% If bias not a numeric, str2doublereturn a NaN
% ------------------------------------
bias = str2double( bias );
biasError = str2double( biasError );
if isnumeric( bias ) && ~isnan( bias)
if dateMax > dateMin
% if bias ~= 0
% The correction is applied to the TSG between dateMin and dateMax
% only to measurements with keptCode Quality Codes
% ------------------------------------------------------------------------
dtTsgQCkept=[];
for icode = 1 : length( keptCode )
dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
tsg.([PARA{1} '_QC']) == keptCode( icode ));
if ~isempty( dtTsg )
dtTsgQCkept=[dtTsgQCkept; dtTsg];
% Compute the corrected value : orignal value + correction
% --------------------------------------------------------
tsg.([PARA{1} '_ADJUSTED'])(dtTsg) = tsg.(PARA{2})(dtTsg) + bias;
% Attribute an error
% ------------------
tsg.([PARA{1} '_ADJUSTED_ERROR'])(dtTsg) = biasError;
% Transfer the QC
% ---------------
tsg.([PARA{1} '_ADJUSTED_QC'])(dtTsg) = tsg.([PARA{1} '_QC'])(dtTsg);
end
if dateMax > dateMin
% Find samples within TIME_WINDOWS with Good, probably Good, QC
% -------------------------------------------------------------
ind = find( tsg.DAYD_EXT >= dateMin & tsg.DAYD_EXT <= dateMax &...
tsg.([SAMPLE '_EXT_QC']) <= PROBABLY_GOOD);
if ~isempty(ind)
% detect NaN in sample.SSPS_DIF due to bad QC code for tsg.SSPS
% -------------------------------------------------------------
ind2 = find(~isnan(tsg.EXT_DIF(ind)));
% Compute mean and standard deviation of the TSG/SAMPLE difference
% that are suggested as default value for bias and error
% ----------------------------------------------------------------
if ~isempty(ind2) && length(ind2) > 2
meanDif = mean(tsg.EXT_DIF(ind(ind2)));
stdDif = std(tsg.EXT_DIF(ind(ind2)));
% Case with 2 samples only: the suggested bias is the
% mean TSG/SAMPLE difference and the suggested error is the standard
% deviation of the TSG/SAMPLE difference, the latter negative to warn that
% the correction is not done with a significant number of samples
% --------------------------------------------------------------------------
elseif ~isempty(ind2) && length(ind2) == 2
meanDif = mean( tsg.EXT_DIF(ind(ind2)) );
stdDif = -std( tsg.EXT_DIF(ind(ind2)) );
% Case with 1 sample only: the suggested bias is the
% TSG/SAMPLE difference and the suggested error is -1
% --------------------------------------------------------------------------
elseif ~isempty(ind2) && length(ind2) == 1
meanDif = tsg.EXT_DIF(ind(ind2));
stdDif = -1;
end
% end
% Update tsg application data
% ---------------------------
setappdata( hMainFig, 'tsg_data', tsg);
% everything OK
% -------------
error = 1;
defaultValueBias = {num2str(meanDif)};
defaultValueError = {num2str(stdDif)};
else
% DateMax <= DateMin
% ------------------
error = -1;
defaultValueBias = {'0'};
defaultValueError = {'0'};
end
end
% Enter the bias that will be applied to PARA{1}
% ----------------------------------------------
prompt = ['Constant value to be applied to the ' PARA{1} ' time series'];
a = inputdlg(prompt,'Bias Correction',1,defaultValueBias);
prompt = ['Error value to be applied to the ' PARA{1} ' time series'];
b = inputdlg(prompt,'Bias Error',1,defaultValueError);
% everything OK
% -------------
error = 1;
if ~isempty( a )
% If necessary replace a comma by a point
% ---------------------------------------
bias = regexprep(a, ',', '.');
biasError = regexprep(b, ',', '.');
% If bias not a numeric, str2doublereturn a NaN
% ------------------------------------
bias = str2double( bias );
biasError = str2double( biasError );
if isnumeric( bias ) && ~isnan( bias)
% if bias ~= 0
% The correction is applied to the TSG between dateMin and dateMax
% only to measurements with keptCode Quality Codes
% ------------------------------------------------------------------------
dtTsgQCkept=[];
for icode = 1 : length( keptCode )
dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
tsg.([PARA{1} '_QC']) == keptCode( icode ));
if ~isempty( dtTsg )
dtTsgQCkept=[dtTsgQCkept; dtTsg];
% Compute the corrected value : orignal value + correction
% --------------------------------------------------------
tsg.([PARA{1} '_ADJUSTED'])(dtTsg) = tsg.(PARA{2})(dtTsg) + bias;
% Attribute an error
% ------------------
tsg.([PARA{1} '_ADJUSTED_ERROR'])(dtTsg) = biasError;
% Transfer the QC
% ---------------
tsg.([PARA{1} '_ADJUSTED_QC'])(dtTsg) = tsg.([PARA{1} '_QC'])(dtTsg);
end
end
% Update tsg application data
% ---------------------------
setappdata( hMainFig, 'tsg_data', tsg);
% everything OK
% -------------
error = 1;
end
end
else
% DateMax <= DateMin
% ------------------
error = -1;
end
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