diff --git a/tsg_data/Touc0702.nc b/tsg_data/Touc0702.nc
index 400530823f0fcc462d4ea5b787472a7385d27890..5def61e2ec195795ad2bddadc3f225053387fbd8 100644
Binary files a/tsg_data/Touc0702.nc and b/tsg_data/Touc0702.nc differ
diff --git a/tsg_util/corTsgLinear.m b/tsg_util/corTsgLinear.m
index bfe88cde6cf5bee806b4af129341d2e286e5de55..99bbb9021693d96224babe491fdea5a01eb9bb5e 100644
--- a/tsg_util/corTsgLinear.m
+++ b/tsg_util/corTsgLinear.m
@@ -22,20 +22,24 @@ PROBABLY_GOOD = get(tsg.qc.hash, 'PROBABLY_GOOD', 'code');
PROBABLY_BAD = get(tsg.qc.hash, 'PROBABLY_BAD', 'code');
VALUE_CHANGED = get(tsg.qc.hash, 'VALUE_CHANGED', 'code');
+% intialisation
+% -------------
+if isempty( tsg.([PARA '_ADJUSTED']) )
+ tsg.([PARA '_ADJUSTED']) = tsg.(PARA);
+ tsg.([PARA '_ADJUSTED_QC']) = tsg.([PARA '_QC']);
+end
+% If only calibration have been applied ERROR is empty
+% ---------------------------------------------------
+if isempty( tsg.([PARA '_ADJUSTED_ERROR']) )
+ tsg.([PARA '_ADJUSTED_ERROR']) = NaN* ones(size(tsg.(PARA)));
+end
+
if dateMax > dateMin
-
- % intialisation
- % -------------
- if isempty( tsg.([PARA '_ADJUSTED']) )
- msgbox( ['Variable ' PARA '_ADJUSTED should be initialise in updateTsgStruct'],...
- 'Function ''corTsgLinear''',...
- 'warn', 'modal');
- end
- % Find samples within TIME_WINDOWS with Good and probably Good QC
+ % Find samples within TIME_WINDOWS with Good, probably Good, , probably bad QC
% ---------------------------------------------------------------
ind = find( tsg.DAYD_SPL >= dateMin & tsg.DAYD_SPL <= dateMax &...
- tsg.([PARA '_SPL_QC']) <= PROBABLY_GOOD);
+ tsg.([PARA '_SPL_QC']) <= PROBABLY_BAD);
if ~isempty(ind)
@@ -56,20 +60,21 @@ if dateMax > dateMin
[p, S, mu] = polyfit( X, Y, 1);
% The correction is applied to the TSG between dateMin and dateMax using
- % a linear interpolation only on measurements with GOOD and
- % PROBABLY_GOOD QC
+ % a linear interpolation only on measurements better than
+ % PROBABLY_BAD QC
% ----------------------------------------------------------------------
dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
- tsg.([PARA '_QC']) <= PROBABLY_GOOD);
+ tsg.([PARA '_QC']) <= PROBABLY_BAD);
[tsg.([PARA '_ADJUSTED'])(dtTsg), tsg.([PARA '_ADJUSTED_ERROR'])(dtTsg)] =...
polyval( p, tsg.DAYD(dtTsg), S, mu);
tsg.([PARA '_ADJUSTED'])(dtTsg) = ...
tsg.(PARA)(dtTsg) + tsg.([PARA '_ADJUSTED'])(dtTsg);
- % VALUE_CHANGED code
- % ------------------
- tsg.([PARA '_ADJUSTED_QC'])(dtTsg) = VALUE_CHANGED;
+ % Line commented - We do not used anymore the VALUE_CHANGED code for
+ % the ADJUSTED variable
+ % ------------------------------------------------------------------
+ % tsg.([PARA '_ADJUSTED_QC'])(dtTsg) = VALUE_CHANGED;
end
end
end
diff --git a/tsg_util/corTsgMedian.m b/tsg_util/corTsgMedian.m
index 42e6c0d3c31e5f15245020acfa8154815b9fd3a6..7d3038bc700d8619cad36e7603a97567e08078fa 100644
--- a/tsg_util/corTsgMedian.m
+++ b/tsg_util/corTsgMedian.m
@@ -35,23 +35,28 @@ TIME_WINDOWS = tsg.cst.COR_TIME_WINDOWS;
% Get PROBABLY_GOOD, PROBABLY_BAD and VALUE_CHANGED codes
% -------------------------------------------------------
PROBABLY_GOOD = get(tsg.qc.hash, 'PROBABLY_GOOD', 'code');
-PROBABLY_BAD = get(tsg.qc.hash, 'PROBABLY_BAD', 'code');
+PROBABLY_BAD = get(tsg.qc.hash, 'PROBABLY_BAD', 'code');
+BAD = get(tsg.qc.hash, 'BAD', 'code');
VALUE_CHANGED = get(tsg.qc.hash, 'VALUE_CHANGED', 'code');
-
+
+% intialisation
+% -------------
+if isempty( tsg.([PARA '_ADJUSTED']) )
+ tsg.([PARA '_ADJUSTED']) = tsg.(PARA);
+ tsg.([PARA '_ADJUSTED_QC']) = tsg.([PARA '_QC']);
+end
+% If only calibration have been applied ERROR is empty
+% ---------------------------------------------------
+if isempty( tsg.([PARA '_ADJUSTED_ERROR']) )
+ tsg.([PARA '_ADJUSTED_ERROR']) = NaN* ones(size(tsg.(PARA)));
+end
+
% Create a structure with an NaN
% No other solution, as I can't add a structure to an empty one
% -------------------------------------------------------------
cor = struct('DAYD', NaN, 'DIFF', NaN, 'ERROR', NaN, 'NVALUE', NaN);
if dateMax > dateMin
-
- % intialisation
- % -------------
- if isempty( tsg.([PARA '_ADJUSTED']) )
- msgbox( ['Variable ' PARA '_ADJUSTED should be initialise in updateTsgStruct'],...
- 'Function ''corTsgMedian''',...
- 'warn', 'modal');
- end
% Find the indices of samples within the time limits.
% --------------------------------------------------
@@ -61,11 +66,11 @@ if dateMax > dateMin
for i = 1:length(indSample)
- % Find samples within TIME_WINDOWS with Good and probably Good QC
+ % Find samples within TIME_WINDOWS with Good, probably Good, probably Bad QC
% ---------------------------------------------------------------
ind = find( tsg.DAYD_SPL >= (tsg.DAYD_SPL(indSample(i)) - TIME_WINDOWS/2) &...
tsg.DAYD_SPL <= (tsg.DAYD_SPL(indSample(i)) + TIME_WINDOWS/2) &...
- tsg.([PARA '_SPL_QC']) <= PROBABLY_GOOD);
+ tsg.([PARA '_SPL_QC']) <= PROBABLY_BAD);
if ~isempty(ind)
@@ -100,7 +105,7 @@ if dateMax > dateMin
% ------------------------------------------------------
ind4 = find( A < meanA-3*stdA | A > meanA+3*stdA);
if ~isempty( ind4 )
- tsg.([PARA '_SPL_QC'])(ind(ind2(ind4))) = PROBABLY_BAD;
+ tsg.([PARA '_SPL_QC'])(ind(ind2(ind4))) = BAD;
end
end
end
@@ -148,16 +153,17 @@ if dateMax > dateMin
% PROBABLY_GOOD QC
% ----------------------------------------------------------------------
dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
- tsg.([PARA '_QC']) <= PROBABLY_GOOD);
+ tsg.([PARA '_QC']) <= PROBABLY_BAD);
tsg.([PARA '_ADJUSTED'])(dtTsg) = tsg.(PARA)(dtTsg) + ...
interp1(cor.DAYD, cor.DIFF, tsg.DAYD(dtTsg));
tsg.([PARA '_ADJUSTED_ERROR'])(dtTsg) = ...
interp1(cor.DAYD, cor.ERROR, tsg.DAYD(dtTsg));
- % VALUE_CHANGED code
- % ------------------
- tsg.([PARA '_ADJUSTED_QC'])(dtTsg) = VALUE_CHANGED;
+ % Line commented - We do not used anymore the VALUE_CHANGED code for
+ % the ADJUSTED variable
+ % ------------------------------------------------------------------
+ % tsg.([PARA '_ADJUSTED_QC'])(dtTsg) = VALUE_CHANGED;
end
diff --git a/tsg_util/plot_Correction.m b/tsg_util/plot_Correction.m
index 084c6dcc8dfcfc04a03c365478ec3b6df7344ecd..dca6682154a2be697aa3dfe4eb4673b56557902a 100644
--- a/tsg_util/plot_Correction.m
+++ b/tsg_util/plot_Correction.m
@@ -39,18 +39,10 @@ if ~isempty( tsg.([PARA '_SPL']) )
end
end
-% Select the record with VALUE_CHANGED code
-% -----------------------------------------
-iVC = find( tsg.([PARA '_ADJUSTED_QC']) == VALUE_CHANGED );
-
-% Select only records corrected but not calibrated.
-% Records corrected and calibrated have the same QC code.
+% Select the records CORRECTED
% Records corrected have an error value
-% ------------------------------------------------------
-iERR = [];
-if iVC ~= 0
- iERR = find( isnan( tsg.([PARA '_ADJUSTED_ERROR'])(iVC) ) == 0 );
-end
+% -------------------------------------------
+iERR = find( isnan(tsg.([PARA '_ADJUSTED_ERROR'])) == 0);
% Plot the difference tsg.SSPS_ADJUSTED-tsg.SSPS on axe 1
% but only for records that were corrected using Water Sample
@@ -58,8 +50,8 @@ end
% -----------------------------------------------------------
if iERR ~= 0
plot_Tsg( hMainFig, hPlotAxes, 1,...
- tsg.DAYD(iVC(iERR)),...
- tsg.([PARA '_ADJUSTED'])(iVC(iERR))-tsg.(PARA)(iVC(iERR)),...
+ tsg.DAYD(iERR),...
+ tsg.([PARA '_ADJUSTED'])(iERR)-tsg.(PARA)(iERR),...
[], [PARA '_ADJUSTED'],'b','none','.',1);
end
@@ -98,11 +90,11 @@ plot_Tsg( hMainFig, hPlotAxes, 3, tsg.DAYD, tsg.(PARA),...
% Plot TSG_ADJUSTED + ERROR on axe 3
% -----------------------------------
if iERR ~= 0
- plot_Tsg( hMainFig, hPlotAxes, 3, tsg.DAYD(iVC(iERR)),...
- tsg.([PARA '_ADJUSTED'])(iVC(iERR)) + tsg.([PARA '_ADJUSTED_ERROR'])(iVC(iERR)),...
+ plot_Tsg( hMainFig, hPlotAxes, 3, tsg.DAYD(iERR),...
+ tsg.([PARA '_ADJUSTED'])(iERR) + tsg.([PARA '_ADJUSTED_ERROR'])(iERR),...
[], [PARA '_ADJUSTED'],'g','none','*',2);
- plot_Tsg( hMainFig, hPlotAxes, 3, tsg.DAYD(iVC(iERR)),...
- tsg.([PARA '_ADJUSTED'])(iVC(iERR)) - tsg.([PARA '_ADJUSTED_ERROR'])(iVC(iERR)),...
+ plot_Tsg( hMainFig, hPlotAxes, 3, tsg.DAYD(iERR),...
+ tsg.([PARA '_ADJUSTED'])(iERR) - tsg.([PARA '_ADJUSTED_ERROR'])(iERR),...
[], [PARA '_ADJUSTED'],'g','none','*',2);
end
diff --git a/tsg_util/updateAdjustedVariable.m b/tsg_util/updateAdjustedVariable.m
index 14bf2bb103308535380db28dd65d671dd9cf382a..94c8310fbb6015d925c0cd72d135512ad0bb2978 100644
--- a/tsg_util/updateAdjustedVariable.m
+++ b/tsg_util/updateAdjustedVariable.m
@@ -1,7 +1,7 @@
function updateAdjustedVariable( hMainFig )
%
-% Update adjusted SSPS, SSJT, and SSTP arrays once calibration has been
-% applied to these variable.
+% Update adjusted SSPS, SSJT, and SSTP arrays with calibrated
+% variables if they exist
%
% The TRICK :
% The programe test the variable ADJUSTED_ERROR as only records corrected
@@ -33,37 +33,56 @@ for i = 1 :3
% -----------------------
if ~isempty( tsg.(para5) )
- % in case of the ADJUSTED_ERROR is not initialised
- % ------------------------------------------------
- if isempty( tsg.(para4) )
- tsg.(para4) = NaN * ones(size(tsg.DAYD));
- end
-
- % Get Adjusted records that were not corrected using Water samples
- % Only records corrected get error values
- % ----------------------------------------------------------------
- ind = find( isnan(tsg.(para4) ) == 1);
-
- if ~isempty(tsg.(para1))
-
- tsg.(para2)(ind) = tsg.(para1)(ind);
+ % If no correction have been made and CAL parameter exists, the
+ % ADJUSTED variable is set to CAL
+ % -------------------------------------------------------------
+ if isempty( tsg.(para4) ) && ~isempty( tsg.(para1) )
- % I do not want that calibration get a VALUE_CHANGED code
- %tsg.(para3)(ind) = VALUE_CHANGED;
+ tsg.(para2) = tsg.(para1);
+ tsg.(para3) = tsg.(para6);
+
+ elseif isempty( tsg.(para4) ) && isempty( tsg.(para1) )
- else
+ % No Correction and no Calibrated records : ADJUSTED variable is
+ % empty
+ % --------------------------------------------------------------
+ tsg.(para2) = [];
+ tsg.(para3) = [];
+
+ elseif ~isempty( tsg.(para4) ) % If ERROR not empty
- % If the calibration has been canceled the ADJUSTED value is set to
- % the raw value
- % -----------------------------------------------------------------
- tsg.(para2)(ind) = tsg.(para5)(ind);
- tsg.(para3)(ind) = tsg.(para6)(ind);
+ % The QC code are set to the QC code of the raw variable
+ % ------------------------------------------------------
+ tsg.(para3) = tsg.(para6);
+ % Get Adjusted records that were not corrected using Water samples
+ % Only records corrected get error values
+ % ----------------------------------------------------------------
+ ind = find( isnan(tsg.(para4) ) == 1);
+
+ % If the parameter has been calibrated
+ % ------------------------------------
+ if ~isempty( tsg.(para1) )
+
+ % Adjusted records not corrected are set to the calibrated value
+ % --------------------------------------------------------------
+ if ~isempty( ind )
+ tsg.(para2)(ind) = tsg.(para1)(ind);
+ end
+
+ else
+
+ % Adjusted records not corrected are set to the raw value
+ % -------------------------------------------------------
+ if ~isempty( ind )
+ tsg.(para2)(ind) = tsg.(para5)(ind);
+ end
+ end
+
end
end
-end
-% Save tsg application data
+ % Save tsg application data
% --------------------------
setappdata( hMainFig, 'tsg_data', tsg );
diff --git a/tsg_util/updateTsgStruct.m b/tsg_util/updateTsgStruct.m
index bfd7c1f297423e901aea703df4a94514ff2f23ae..88340ef0e62266945a10962ce151d270a27efc5b 100644
--- a/tsg_util/updateTsgStruct.m
+++ b/tsg_util/updateTsgStruct.m
@@ -43,28 +43,32 @@ if isempty(tsg.SPDC)
tsg.SPDC = [tsg.SPDC';0];
end
-% Initialise ADJUSTED variables if empty
-% --------------------------------------
+% Varaibles must exists
+% ---------------------
for i = 1: nPARA
para1 = PARA(i,:);
- para2 = [PARA(i,:) '_QC'];
- para3 = [PARA(i,:) '_ADJUSTED'];
- para4 = [PARA(i,:) '_ADJUSTED_QC'];
- para5 = [PARA(i,:) '_ADJUSTED_ERROR'];
-
- if isempty( tsg.(para3) ) && ~isempty( tsg.(para1) )
- tsg.(para3) = tsg.(para1);
- tsg.(para4) = tsg.(para2);
- tsg.(para5) = NaN * ones( size( tsg.(para1) ));
-
- elseif isempty( tsg.(para1) )
-
+ if isempty( tsg.(para1) )
msgbox(['You must initialise the tsg.' PARA(i) ' variable'],...
- 'function ''updateTsgStruct''', ....
- 'warn', 'modal');
+ 'function ''updateTsgStruct''', ....
+ 'warn', 'modal');
+ end
+end
+
+% Empty variables filled with NaN
+% -------------------------------
+names = fieldnames( tsg );
+for i = 1: length(names)
+ para = char( names(i) );
+ if ~isstruct( tsg.(para) ) && ~isempty( tsg.(para) )
+ A = tsg.(para);
+ ind = find( isnan( A ) == 0 );
+ if isempty( ind )
+ tsg.(para) = [];
+ end
end
end
+
% Initialise 'variables_LINCOEF'
% -------------------------------
diff --git a/tsgqc_GUI.m b/tsgqc_GUI.m
index e6926aaaae8c85acd69069fb00710d9376e36855..9a93f30d4f8f803152448df20b480eef01978c54 100644
--- a/tsgqc_GUI.m
+++ b/tsgqc_GUI.m
@@ -1425,10 +1425,6 @@ errTsg = readTsgDataTsg( hMainFig, fullFileName);
% Get tsg application data
% ------------------------
tsg = getappdata( hMainFig, 'tsg_data' );
-
- % pour test
-% tsg.SSTP = [];
-% setappdata( hMainFig, 'tsg_data', tsg );
% Draw the 3 plots of the validation figure
% -----------------------------------------
@@ -1545,6 +1541,9 @@ errTsg = readTsgDataTsg( hMainFig, fullFileName);
% ------------------------
tsg = getappdata( hMainFig, 'tsg_data' );
+ % Emptied the CAL variables
+ % -------------------------
+ tsg.CNDC_CAL = [];
tsg.SSPS_CAL = [];
tsg.SSJT_CAL = [];
tsg.SSTP_CAL = [];
@@ -1553,8 +1552,8 @@ errTsg = readTsgDataTsg( hMainFig, fullFileName);
% --------------------------
setappdata( hMainFig, 'tsg_data', tsg );
- % Update the Adjusted variables (SSPS - SSJT) with calibrated records
- % -------------------------------------------------------------------
+ % Update the Adjusted variables
+ % -----------------------------
updateAdjustedVariable( hMainFig );
% Refresh plot #1
@@ -2343,11 +2342,10 @@ errTsg = readTsgDataTsg( hMainFig, fullFileName);
% --------------------------------------------------
PARA = tsg.preference.parameter;
- % To cancel the correction set the ERROR to NaN then
+ % To cancel the correction set the ERROR to [] then
% call updateAdjustedVariable.
% --------------------------------------------------
- tsg.([PARA '_ADJUSTED_ERROR']) = ...
- NaN * ones( size(tsg.([PARA '_ADJUSTED_ERROR'])));
+ tsg.([PARA '_ADJUSTED_ERROR']) = [];
% Save tsg data
% -------------