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Commit 85eb74ee authored by Yves Gouriou's avatar Yves Gouriou
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Amélioration des modules de correction. 

Modification du tracé de la carte pour s'adapter aux limites de la série temporelle visible à l'écran

Desactivation du module PREFERENCE qui bugue
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tsg_util/corTsgLinear.m
+ 48
− 95
View file @ 85eb74ee
function [error] = corTsgLinear(hMainFig, dateMin, dateMax) function [error] = corTsgLinear(hMainFig, dateMin, dateMax)
%
% Correct the TSG salinity time series with the Water sample. % Correct the TSG salinity time series with the Water sample.
% Use the median value of TIME_WINDOWS water sample to compute the % Use a linear fit to the water sample/tsg difference
% correction. see the documentation
% %
% Input % Input
% hMainFig ..... Handle to the main GUI % hMainFig ..... Handle to the main GUI
...@@ -12,119 +10,73 @@ function [error] = corTsgLinear(hMainFig, dateMin, dateMax) ...@@ -12,119 +10,73 @@ function [error] = corTsgLinear(hMainFig, dateMin, dateMax)
% Output % Output
% Error ........ 1 everything OK % Error ........ 1 everything OK
% ........ -1 dateMax <= date Min % ........ -1 dateMax <= date Min
%
% TO DO
% corTsgMethod1.m
% 1) Test if there are NaN values in 'sample':
% We could get some problem with the computation of the median and std
% 2) Initialisation de la structure 'cor'
% 3) Test for anormal sample-tsg difference - Suppress bad points
% 4) Test on the validation code. do we apply the correction whatever the
% is the code ?
% 5) Return an Error code ?
% 6) Test Date_Min < Date_Max
% Get application data % Get application data
% -------------------- % --------------------
tsg = getappdata( hMainFig, 'tsg_data'); tsg = getappdata( hMainFig, 'tsg_data');
sample = getappdata( hMainFig, 'sample'); sample = getappdata( hMainFig, 'sample');
% Shorten the variable name % Get PROBABLY_GOOD, PROBABLY_BAD and VALUE_CHANGED codes
% ------------------------- % -------------------------------------------------------
TIME_WINDOWS = tsg.cst.COR_TIME_WINDOWS;
% Get PROBABLY_GOOD and VALUE_CHANGED code
% ----------------------------------------
PROBABLY_GOOD = get(tsg.qc.hash, 'PROBABLY_GOOD', 'code'); 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'); VALUE_CHANGED = get(tsg.qc.hash, 'VALUE_CHANGED', 'code');
% The correction is computed between dateMin and dateMax
% ------------------------------------------------------
dt = find(sample.DAYD >= dateMin & sample.DAYD <= dateMax);
if dateMax > dateMin if dateMax > dateMin
% 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);
% --------------------
for i = 1 : length(dt)
% Find the sample within TIME_WINDOWS with Good and probably Good QC
% ------------------------------------------------------------------
ind = find( sample.DAYD(dt) >= sample.DAYD(dt(i)) - TIME_WINDOWS/2 &...
sample.DAYD(dt) <= sample.DAYD(dt(i)) + TIME_WINDOWS/2 &...
sample.SSPS_QC(dt) <= PROBABLY_GOOD);
end
% Eliminate the first element if NaN % Find samples within TIME_WINDOWS with Good and probably Good QC
% ---------------------------------- % ---------------------------------------------------------------
if isnan(cor.DAYD(1)) ind = find( sample.DAYD >= dateMin & sample.DAYD <= dateMax &...
cor.DAYD(1) = []; sample.SSPS_QC <= PROBABLY_GOOD);
cor.DIFF(1) = [];
cor.ERROR(1) = []; if ~isempty(ind)
cor.NVALUE(1) = [];
end % detect NaN in sample.SSPS_DIF due to bad QC code for tsg.SSPS
% -------------------------------------------------------------
if ~isempty( cor.DAYD ) ind2 = find(~isnan(sample.SSPS_DIF(ind)));
% The error is maximum if the median is computed with less than 4 samples % Compute linear fit of the TSG/SAMPLE difference
% ----------------------------------------------------------------------- % -----------------------------------------------
cor.ERROR( cor.NVALUE < 4 ) = 1; if ~isempty(sample.SSPS_DIF(ind(ind2)))
% The correction is applied between dateMin and dateMax X = sample.DAYD(ind(ind2));
% We attribute to dateMin the first correction computed Y = sample.SSPS_DIF(ind(ind2));
% and to dateMax the last one
% [p, S, mu] = polyfit( X, Y, 1);
% Find the tsg date in the interval dateMin-dateMax
% ------------------------------------------------- % The correction is applied to the TSG between dateMin and dateMax using
dtTsg = find(tsg.DAYD >= dateMin & tsg.DAYD <= dateMax); % a linear interpolation only on measurements with GOOD and
% PROBABLY_GOOD QC
if cor.DAYD(1) ~= dateMin % ----------------------------------------------------------------------
cor.DAYD = [tsg.DAYD(dtTsg(1)) cor.DAYD]; dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
cor.DIFF = [cor.DIFF(1) cor.DIFF]; tsg.SSPS_QC <= PROBABLY_GOOD);
cor.ERROR = [cor.ERROR(1) cor.ERROR];
cor.NVALUE = [cor.NVALUE(1) cor.NVALUE]; [tsg.SSPS_ADJUSTED(dtTsg), tsg.SSPS_ADJUSTED_ERROR(dtTsg)] =...
end polyval( p, tsg.DAYD(dtTsg), S, mu);
if cor.DAYD(end) ~= dateMax tsg.SSPS_ADJUSTED(dtTsg) = tsg.SSPS(dtTsg) + tsg.SSPS_ADJUSTED(dtTsg);
cor.DAYD = [cor.DAYD tsg.DAYD(dtTsg(end))];
cor.DIFF = [cor.DIFF cor.DIFF(end)]; % VALUE_CHANGED code
cor.ERROR = [cor.ERROR cor.ERROR(end)]; % ------------------
cor.NVALUE = [cor.NVALUE cor.NVALUE(end)]; tsg.SSPS_ADJUSTED_QC(dtTsg) = VALUE_CHANGED;
end end
p = polyfit( x, y, 1);
y = polyval(p,x);
% The correction is applied to the TSG between dateMin and dateMax using
% a linear interpolation
% ----------------------------------------------------------------------
tsg.SSPS_ADJUSTED(dtTsg) = tsg.SSPS(dtTsg) + ...
interp1(cor.DAYD, cor.DIFF, tsg.DAYD(dtTsg));
tsg.SSPS_ADJUSTED_ERROR(dtTsg) = ...
interp1(cor.DAYD, cor.ERROR, tsg.DAYD(dtTsg));
tsg.SSPS_ADJUSTED_QC(dtTsg) = VALUE_CHANGED;
else else
% RAZ if no correction % RAZ if no correction
% -------------------- % --------------------
dt = find(tsg.DAYD >= dateMin & tsg.DAYD <= dateMax); dtTsg = find(tsg.DAYD >= dateMin & tsg.DAYD <= dateMax);
tsg.SSPS_ADJUSTED(dtTsg) = NaN*ones(size(tsg.SSPS(dt)));
tsg.SSPS_ADJUSTED_ERROR(dtTsg) = NaN*ones(size(tsg.SSPS(dt)));
tsg.SSPS_ADJUSTED_QC(dtTsg) = zeros(size(tsg.SSPS(dt)));
tsg.SSPS_ADJUSTED(dt) = NaN*ones(size(tsg.SSPS(dt)));
tsg.SSPS_ADJUSTED_ERROR(dt) = NaN*ones(size(tsg.SSPS(dt)));
tsg.SSPS_ADJUSTED_QC(dt) = zeros(size(tsg.SSPS(dt)));
end end
% Update tsg application data % Update tsg application data
% --------------------------- % ---------------------------
setappdata( hMainFig, 'tsg_data', tsg); setappdata( hMainFig, 'tsg_data', tsg);
setappdata( hMainFig, 'sample', sample);
% everything OK % everything OK
% ------------- % -------------
error = 1; error = 1;
...@@ -134,6 +86,7 @@ else ...@@ -134,6 +86,7 @@ else
% DateMax <= DateMin % DateMax <= DateMin
% ------------------ % ------------------
error = -1; error = -1;
end end
tsg_util/corTsgMedian.m
+ 53
− 27
View file @ 85eb74ee
...@@ -15,16 +15,9 @@ function [error] = corTsgMedian(hMainFig, dateMin, dateMax) ...@@ -15,16 +15,9 @@ function [error] = corTsgMedian(hMainFig, dateMin, dateMax)
% %
% TO DO % TO DO
% corTsgMethod1.m % corTsgMethod1.m
% 1) Test if there are NaN values in 'sample':
% We could get some problem with the computation of the median and std
% 2) Initialisation de la structure 'cor'
% 3) Test for anormal sample-tsg difference - Suppress bad points % 3) Test for anormal sample-tsg difference - Suppress bad points
% 4) Test on the validation code. do we apply the correction whatever the % 4) Test on the validation code. do we apply the correction whatever the
% is the code ? % is the code ?
% 5) Return an Error code ?
% 6) Test Date_Min < Date_Max
% 7) BUG : Le nombre d'elements est faux si il y a des NaN
% Get application data % Get application data
% -------------------- % --------------------
...@@ -35,41 +28,69 @@ sample = getappdata( hMainFig, 'sample'); ...@@ -35,41 +28,69 @@ sample = getappdata( hMainFig, 'sample');
% ------------------------- % -------------------------
TIME_WINDOWS = tsg.cst.COR_TIME_WINDOWS; TIME_WINDOWS = tsg.cst.COR_TIME_WINDOWS;
% Get PROBABLY_GOOD code % Get PROBABLY_GOOD, PROBABLY_BAD and VALUE_CHANGED codes
% ---------------------- % -------------------------------------------------------
PROBABLY_GOOD = get(tsg.qc.hash, 'PROBABLY_GOOD', 'code'); 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'); VALUE_CHANGED = get(tsg.qc.hash, 'VALUE_CHANGED', 'code');
% Create a structure with an NaN % Create a structure with an NaN
% No other solution as I can't add a structure to an empty one % No other solution, as I can't add a structure to an empty one
% ------------------------------------------------------------ % -------------------------------------------------------------
cor = struct('DAYD', NaN, 'DIFF', NaN, 'ERROR', NaN, 'NVALUE', NaN); cor = struct('DAYD', NaN, 'DIFF', NaN, 'ERROR', NaN, 'NVALUE', NaN);
if dateMax > dateMin if dateMax > dateMin
% Find the number of samples within the time limits.
% --------------------------------------------------
indSample = find(sample.DAYD >= dateMin & sample.DAYD <= dateMax); indSample = find(sample.DAYD >= dateMin & sample.DAYD <= dateMax);
indCor = 0; indCor = 0;
for i=1:length(indSample) for i=1:length(indSample)
% Find the sample within TIME_WINDOWS with Good and probably Good QC % Find samples within TIME_WINDOWS with Good and probably Good QC
% ------------------------------------------------------------------ % ---------------------------------------------------------------
ind = find( sample.DAYD >= (sample.DAYD(i) - TIME_WINDOWS/2) &... ind = find( sample.DAYD >= (sample.DAYD(i) - TIME_WINDOWS/2) &...
sample.DAYD <= (sample.DAYD(i) + TIME_WINDOWS/2) &... sample.DAYD <= (sample.DAYD(i) + TIME_WINDOWS/2) &...
sample.SSPS_QC <= PROBABLY_GOOD); sample.SSPS_QC <= PROBABLY_GOOD);
% Compute the median difference and error within TIME_WINDOWS
% -----------------------------------------------------------
if ~isempty(ind) if ~isempty(ind)
indCor = indCor + 1;
cor.DAYD(indCor) = sample.DAYD(i);
cor.DIFF(indCor) = nanmedian(sample.SSPS_DIF(ind));
cor.ERROR(indCor) = nanstd(sample.SSPS_DIF(ind))/sqrt(length(ind));
% BUG : Le nombre d'element est faux si il y a des NaN % detect NaN in sample.SSPS_DIF due to bad QC code in tsg.SSPS
cor.NVALUE(indCor) = length(ind); % ------------------------------------------------------------
ind2 = find(~isnan(sample.SSPS_DIF(ind)));
% Compute the median difference and error within TIME_WINDOWS
% -----------------------------------------------------------
if ~isempty(sample.SSPS_DIF(ind(ind2)))
A = sample.SSPS_DIF(ind(ind2));
meanA = mean(A);
stdA = std(A);
% Standard deviation test: keep these values
% ------------------------------------------
ind3 = find( A >= meanA-3*stdA & A <= meanA+3*stdA);
B = sample.SSPS_DIF(ind(ind2(ind3)));
if ~isempty( B )
indCor = indCor + 1;
cor.DAYD(indCor) = sample.DAYD(i);
cor.DIFF(indCor) = median(B);
cor.ERROR(indCor) = nanstd(B)/sqrt(length(B));
cor.NVALUE(indCor) = length(B);
end
% Standard deviation test: don't keep these values
% QC PROBABLY_BAD
% ------------------------------------------------------
ind4 = find( A < meanA-3*stdA | A > meanA+3*stdA);
if ~isempty( ind4 )
sample.SSPS_QC(ind(ind2(ind4))) = PROBABLY_BAD;
end
end
end end
end end
% Eliminate the first element if NaN % Eliminate the first element if NaN
...@@ -93,7 +114,7 @@ if dateMax > dateMin ...@@ -93,7 +114,7 @@ if dateMax > dateMin
% %
% Find the tsg date in the interval dateMin-dateMax % Find the tsg date in the interval dateMin-dateMax
% ------------------------------------------------- % -------------------------------------------------
dtTsg = find(tsg.DAYD >= dateMin & tsg.DAYD <= dateMax); dtTsg = find(tsg.DAYD >= dateMin & tsg.DAYD <= dateMax);
if cor.DAYD(1) ~= dateMin if cor.DAYD(1) ~= dateMin
cor.DAYD = [tsg.DAYD(dtTsg(1)) cor.DAYD]; cor.DAYD = [tsg.DAYD(dtTsg(1)) cor.DAYD];
...@@ -109,15 +130,19 @@ if dateMax > dateMin ...@@ -109,15 +130,19 @@ if dateMax > dateMin
end end
% The correction is applied to the TSG between dateMin and dateMax using % The correction is applied to the TSG between dateMin and dateMax using
% a linear interpolation % a linear interpolation only on measurements with GOOD and
% PROBABLY_GOOD QC
% ---------------------------------------------------------------------- % ----------------------------------------------------------------------
dtTsg = find( tsg.DAYD >= dateMin & tsg.DAYD <= dateMax &...
tsg.SSPS_QC <= PROBABLY_GOOD);
tsg.SSPS_ADJUSTED(dtTsg) = tsg.SSPS(dtTsg) + ... tsg.SSPS_ADJUSTED(dtTsg) = tsg.SSPS(dtTsg) + ...
interp1(cor.DAYD, cor.DIFF, tsg.DAYD(dtTsg)); interp1(cor.DAYD, cor.DIFF, tsg.DAYD(dtTsg));
tsg.SSPS_ADJUSTED_ERROR(dtTsg) = ... tsg.SSPS_ADJUSTED_ERROR(dtTsg) = ...
interp1(cor.DAYD, cor.ERROR, tsg.DAYD(dtTsg)); interp1(cor.DAYD, cor.ERROR, tsg.DAYD(dtTsg));
% Get PROBABLY_GOOD code % VALUE_CHANGED code
% ---------------------- % ------------------
tsg.SSPS_ADJUSTED_QC(dtTsg) = VALUE_CHANGED; tsg.SSPS_ADJUSTED_QC(dtTsg) = VALUE_CHANGED;
else else
...@@ -135,6 +160,7 @@ if dateMax > dateMin ...@@ -135,6 +160,7 @@ if dateMax > dateMin
% Update tsg application data % Update tsg application data
% --------------------------- % ---------------------------
setappdata( hMainFig, 'tsg_data', tsg); setappdata( hMainFig, 'tsg_data', tsg);
setappdata( hMainFig, 'sample', sample);
% everything OK % everything OK
% ------------- % -------------
......
tsg_util/plot_Sample.m
+ 2
− 4
View file @ 85eb74ee
...@@ -62,7 +62,7 @@ if isempty(MyColor) ...@@ -62,7 +62,7 @@ if isempty(MyColor)
line( sample.DAYD(ind), sample.(Para)(ind), ... line( sample.DAYD(ind), sample.(Para)(ind), ...
'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para '_' key],... 'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para '_' key],...
'LineStyle', 'none',... 'LineStyle', 'none',...
'Marker', 'square', 'MarkerSize', 3,... 'Marker', 'square', 'MarkerSize', 5,...
'MarkerEdgeColor', 'k', 'MarkerFaceColor', color); 'MarkerEdgeColor', 'k', 'MarkerFaceColor', color);
end end
...@@ -73,10 +73,8 @@ else ...@@ -73,10 +73,8 @@ else
line( sample.DAYD, sample.(Para),... line( sample.DAYD, sample.(Para),...
'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para],... 'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para],...
'LineStyle', 'none',... 'LineStyle', 'none', 'Marker', 'square', 'MarkerSize', 5,...
'Marker', 'square', 'MarkerSize', 3,...
'MarkerEdgeColor', MyColor, 'MarkerFaceColor', MyColor); 'MarkerEdgeColor', MyColor, 'MarkerFaceColor', MyColor);
end end
hold off; hold off;
......
tsg_util/plot_Tsg.m
+ 4
− 3
View file @ 85eb74ee
...@@ -80,9 +80,10 @@ if ~isempty( tsg.(Para) ) ...@@ -80,9 +80,10 @@ if ~isempty( tsg.(Para) )
end end
else else
line( tsg.DAYD, tsg.(Para),'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para], ...
'LineStyle', Style, ... line(tsg.DAYD, tsg.(Para),...
'Marker', Mark, 'MarkerSize', 5, 'Color', MyColor); 'Tag', ['TAG_PLOT' num2str(PlotNum) '_LINE_' Para], ...
'LineStyle', Style,'Marker', Mark, 'MarkerSize', 5, 'Color', MyColor);
end end
hold off; hold off;
......
tsg_util/plot_map.m
+ 23
− 7
View file @ 85eb74ee
function plot_map(hTsgGUI, hAxes) function plot_map(hTsgGUI, hPlotAxes)
% Function to plot the earth map and ship trackline % Function to plot the earth map and ship trackline
% %
% Input % Input
...@@ -20,13 +20,28 @@ function plot_map(hTsgGUI, hAxes) ...@@ -20,13 +20,28 @@ function plot_map(hTsgGUI, hAxes)
% ------------------------------- % -------------------------------
tsg = getappdata( hTsgGUI, 'tsg_data'); tsg = getappdata( hTsgGUI, 'tsg_data');
% Get the Geographic limit of the TSG time series
% -----------------------------------------------
dateLim = get(hPlotAxes(1), 'Xlim');
ind = find( tsg.DAYD >= dateLim(1) & tsg.DAYD <= dateLim(2));
latMin = min( tsg.LATX(ind) );
latMax = max( tsg.LATX(ind) );
lonMin = min( tsg.LONX(ind) );
lonMax = max( tsg.LONX(ind) );
% Positionning the right axes % Positionning the right axes
% ---------------------------- % ----------------------------
axes(hAxes(4)); axes(hPlotAxes(4));
%hLines = get( hPlotAxes(4), 'Children' );
%if ~isempty( hLines )
% delete(hLines);
%end
% Use of Mercator projection % Use of Mercator projection
% -------------------------- % --------------------------
m_proj('Mercator','lat',[-70 70],'long',[-180 180]); %m_proj('Mercator','lat',[-70 70],'long',[-180 180]);
m_proj('Mercator','lat',[latMin latMax],'long',[lonMin lonMax]);
% detailed coast lines % detailed coast lines
% m_gshhs_i('patch',[.7 .7 .7]); % m_gshhs_i('patch',[.7 .7 .7]);
...@@ -38,10 +53,11 @@ m_proj('Mercator','lat',[-70 70],'long',[-180 180]); ...@@ -38,10 +53,11 @@ m_proj('Mercator','lat',[-70 70],'long',[-180 180]);
% ---------------------------- % ----------------------------
m_coast('patch',[.7 .7 .7]); m_coast('patch',[.7 .7 .7]);
m_grid('box','fancy','tickdir','in', ... %m_grid('box','fancy','tickdir','in', ...
'ytick', [-70:20:70],... % 'ytick', [-70:20:70],...
'xtick', [-180:40:180],... % 'xtick', [-180:40:180],...
'Fontsize', [10]); % 'Fontsize', [10]);
m_grid('box','fancy','tickdir','in', 'Fontsize', [10]);
% Plot the ship track - Check if LAT-LON in deg-decimal % Plot the ship track - Check if LAT-LON in deg-decimal
% ----------------------------------------------------- % -----------------------------------------------------
......
tsg_util/tsg_preferences.m
+ 2
− 1
View file @ 85eb74ee
...@@ -28,7 +28,8 @@ config_file = [prefdir, filesep, app_name, '.mat']; ...@@ -28,7 +28,8 @@ config_file = [prefdir, filesep, app_name, '.mat'];
% Open config file % Open config file
% ---------------- % ----------------
config = fopen( config_file, 'r' ); %config = fopen( config_file, 'r' );
config = -1;
% test fopen return value % test fopen return value
% ----------------------- % -----------------------
......
tsgqc_GUI.m
+ 80
− 26
View file @ 85eb74ee
...@@ -662,7 +662,7 @@ hrbCorCancel = uicontrol( ... ...@@ -662,7 +662,7 @@ hrbCorCancel = uicontrol( ...
'FontSize',tsg.fontSize-1,... 'FontSize',tsg.fontSize-1,...
'Tag', 'CORRECT_CANCEL_PUSH', ... 'Tag', 'CORRECT_CANCEL_PUSH', ...
'Enable', 'off',... 'Enable', 'off',...
'pos',[.05 .68 .9 .25], ... 'pos',[.05 .08 .9 .25],...
'HandleVisibility','callback', ... 'HandleVisibility','callback', ...
'Callback', @CorCancelCallback); 'Callback', @CorCancelCallback);
hrbCorLinear = uicontrol( ... hrbCorLinear = uicontrol( ...
...@@ -684,7 +684,7 @@ hrbCorMedian = uicontrol( ... ...@@ -684,7 +684,7 @@ hrbCorMedian = uicontrol( ...
'FontSize',tsg.fontSize-1,... 'FontSize',tsg.fontSize-1,...
'Tag', 'CORRECT_MEDIAN_PUSH', ... 'Tag', 'CORRECT_MEDIAN_PUSH', ...
'Enable', 'off',... 'Enable', 'off',...
'pos',[.05 .08 .9 .25],... 'pos',[.05 .68 .9 .25], ...
'HandleVisibility','callback', ... 'HandleVisibility','callback', ...
'Callback', @CorMedianCallback); 'Callback', @CorMedianCallback);
...@@ -893,7 +893,11 @@ end ...@@ -893,7 +893,11 @@ end
% Plot the Map with the ship trackline % Plot the Map with the ship trackline
% ------------------------------------ % ------------------------------------
plot_map( hMainFig, hPlotAxes) % plot_map( hMainFig, hPlotAxes)
% Update QC statistics
% --------------------
display_QC( hMainFig, hPlotAxes)
end end
end end
...@@ -1291,7 +1295,7 @@ end ...@@ -1291,7 +1295,7 @@ end
y = a(2,2); y = a(2,2);
% Code to Activate the PAN function when QC mode is active % Code to Activate the PAN function when QC mode is active
% A PAN zone is defined in the bottom (5%) of PlotAxes(1) % A PAN zone is defined in the bottom (10%) of PlotAxes(1)
% 2 callback are needed : % 2 callback are needed :
% 1 - one to desactivate QC when Pan is set to on. % 1 - one to desactivate QC when Pan is set to on.
% 2 - one to reactivate QC once the pan has been used. % 2 - one to reactivate QC once the pan has been used.
...@@ -1304,9 +1308,9 @@ end ...@@ -1304,9 +1308,9 @@ end
% Suppose that Y axes is increasing from the bottom to the top % Suppose that Y axes is increasing from the bottom to the top
% ------------------------------------------------------------ % ------------------------------------------------------------
limy2 = limy(1) + (limy(2)-limy(1)) * 0.05; limy2 = limy(1) + (limy(2)-limy(1)) * 0.10;
if x > limx(1) && x < limx(2) && y <= limy2 if x > limx(1) && x < limx(2) && y <= limy2 && y >= limy(1)
hPan = pan(hMainFig); hPan = pan(hMainFig);
set(hPan,'ActionPreCallback', @preQcPanCallback); set(hPan,'ActionPreCallback', @preQcPanCallback);
set(hPan,'ActionPostCallback', @postQcPanCallback); set(hPan,'ActionPostCallback', @postQcPanCallback);
...@@ -1381,7 +1385,13 @@ end ...@@ -1381,7 +1385,13 @@ end
% --------------------------------------- % ---------------------------------------
set(hZoomToggletool, 'state', 'off' ); set(hZoomToggletool, 'state', 'off' );
set(hPanToggletool, 'state', 'off' ); set(hPanToggletool, 'state', 'off' );
if ~isempty( get(hMapPanel, 'UserData'))
delete(get(hMapPanel, 'UserData'));
end
plot_map( hMainFig, hPlotAxes)
% Make the earth map visible % Make the earth map visible
% -------------------------- % --------------------------
set(hMapPanel, 'Visible', 'on' ); set(hMapPanel, 'Visible', 'on' );
...@@ -1597,6 +1607,14 @@ end ...@@ -1597,6 +1607,14 @@ end
function CorCancelCallback(hObject, eventdata) function CorCancelCallback(hObject, eventdata)
% Callback function run when ... % Callback function run when ...
% Desactivate somme Toggle button
% -------------------------------
set( hZoomToggletool, 'state', 'off' );
set( hPanToggletool, 'state', 'off' );
set( hQCToggletool, 'state', 'off' );
set( hStartlimitToggletool, 'State', 'off' );
set( hEndlimitToggletool, 'State', 'off' );
tsg = getappdata(hMainFig, 'tsg_data'); tsg = getappdata(hMainFig, 'tsg_data');
tsg.SSPS_ADJUSTED = NaN*ones(size(tsg.SSPS)); tsg.SSPS_ADJUSTED = NaN*ones(size(tsg.SSPS));
...@@ -1616,13 +1634,21 @@ end ...@@ -1616,13 +1634,21 @@ end
%% CorLinearCallback .................................... Correction Module %% CorLinearCallback .................................... Correction Module
function CorLinearCallback(hObject, eventdata) function CorLinearCallback(hObject, eventdata)
% Callback function run when % Callback function run when
% Desactivate somme Toggle button
% -------------------------------
set( hZoomToggletool, 'state', 'off' );
set( hPanToggletool, 'state', 'off' );
set( hQCToggletool, 'state', 'off' );
set( hStartlimitToggletool, 'State', 'off' );
set( hEndlimitToggletool, 'State', 'off' );
% Get the time limits for the correction A TESTER % Get the time limits for the correction A TESTER
% -------------------------------------- % --------------------------------------
dateMin = datenum(get( hetDateMin, 'String'), 'yyyy-mm-dd HH:MM:SS'); dateMin = datenum(get( hetDateMin, 'String'), 'yyyy-mm-dd HH:MM:SS');
dateMax = datenum(get( hetDateMax, 'String'), 'yyyy-mm-dd HH:MM:SS'); dateMax = datenum(get( hetDateMax, 'String'), 'yyyy-mm-dd HH:MM:SS');
% Compute the sample-TSG differences % Compute the sample-TSG differences
% ---------------------------------- % ----------------------------------
diffTsgSample( hMainFig ); diffTsgSample( hMainFig );
...@@ -1630,11 +1656,11 @@ end ...@@ -1630,11 +1656,11 @@ end
% Correction % Correction
% ---------- % ----------
error = corTsgLinear(hMainFig, dateMin, dateMax); error = corTsgLinear(hMainFig, dateMin, dateMax);
switch error switch error
case 1 case 1
% Reinitialise plot 2 and 3 % Reinitialise plot 2 and 3
% ------------------------- % -------------------------
erase_Line( hPlotAxes(2), 2 ) erase_Line( hPlotAxes(2), 2 )
...@@ -1646,19 +1672,28 @@ end ...@@ -1646,19 +1672,28 @@ end
% ---------------------------------------- % ----------------------------------------
plot_Tsg( hMainFig, hPlotAxes(3), 3, 'SSPS_ADJUSTED', 0, 'r' ); plot_Tsg( hMainFig, hPlotAxes(3), 3, 'SSPS_ADJUSTED', 0, 'r' );
tsg = getappdata( hMainFig, 'tsg_data');
% Plot the difference tsg.SSPS_ADJUSTED-tsg.SSPS on axe 2 % Plot the difference tsg.SSPS_ADJUSTED-tsg.SSPS on axe 2
% ------------------------------------------------------- % -------------------------------------------------------
axes( hPlotAxes(2) ); axes( hPlotAxes(2) );
tsg = getappdata( hMainFig, 'tsg_data');
line( tsg.DAYD, tsg.SSPS_ADJUSTED-tsg.SSPS,... line( tsg.DAYD, tsg.SSPS_ADJUSTED-tsg.SSPS,...
'Tag', 'TAG_PLOT2_LINE_TSGDIF', 'Color', 'b'); 'Tag', 'TAG_PLOT2_LINE_TSGDIF', 'Color', 'b');
% Plot TSG + ERROR on axe 3
% -------------------------
errorPlus = tsg.SSPS_ADJUSTED + tsg.SSPS_ADJUSTED_ERROR;
errorMinus = tsg.SSPS_ADJUSTED - tsg.SSPS_ADJUSTED_ERROR;
axes( hPlotAxes(3) );
line( tsg.DAYD, errorPlus,...
'Tag', 'TAG_PLOT3_LINE_TSGERROR_PLUS', 'Color', 'g');
line( tsg.DAYD, errorMinus,...
'Tag', 'TAG_PLOT3_LINE_TSGERROR_MINUS', 'Color', 'g');
case -1 case -1
msgbox( 'Date limits are not correct',... msgbox( 'Date limits are not correct',...
'Correction module', 'warn', 'modal'); 'Correction module', 'warn', 'modal');
end end
msgbox('Method not yet implemented', 'modal' );
end end
...@@ -1666,11 +1701,19 @@ end ...@@ -1666,11 +1701,19 @@ end
function CorMedianCallback(hObject, eventdata) function CorMedianCallback(hObject, eventdata)
% Callback function run when % Callback function run when
% Desactivate somme Toggle button
% -------------------------------
set( hZoomToggletool, 'state', 'off' );
set( hPanToggletool, 'state', 'off' );
set( hQCToggletool, 'state', 'off' );
set( hStartlimitToggletool, 'State', 'off' );
set( hEndlimitToggletool, 'State', 'off' );
% Get the time limits for the correction A TESTER % Get the time limits for the correction A TESTER
% -------------------------------------- % --------------------------------------
dateMin = datenum(get( hetDateMin, 'String'), 'yyyy-mm-dd HH:MM:SS'); dateMin = datenum(get( hetDateMin, 'String'), 'yyyy-mm-dd HH:MM:SS');
dateMax = datenum(get( hetDateMax, 'String'), 'yyyy-mm-dd HH:MM:SS'); dateMax = datenum(get( hetDateMax, 'String'), 'yyyy-mm-dd HH:MM:SS');
% Compute the sample-TSG differences % Compute the sample-TSG differences
% ---------------------------------- % ----------------------------------
diffTsgSample( hMainFig ); diffTsgSample( hMainFig );
...@@ -1678,11 +1721,11 @@ end ...@@ -1678,11 +1721,11 @@ end
% Correction % Correction
% ---------- % ----------
error = corTsgMedian(hMainFig, dateMin, dateMax); error = corTsgMedian(hMainFig, dateMin, dateMax);
switch error switch error
case 1 case 1
% Reinitialise plot 2 and 3 % Reinitialise plot 2 and 3
% ------------------------- % -------------------------
erase_Line( hPlotAxes(2), 2 ) erase_Line( hPlotAxes(2), 2 )
...@@ -1694,18 +1737,29 @@ end ...@@ -1694,18 +1737,29 @@ end
% ---------------------------------------- % ----------------------------------------
plot_Tsg( hMainFig, hPlotAxes(3), 3, 'SSPS_ADJUSTED', 0, 'r' ); plot_Tsg( hMainFig, hPlotAxes(3), 3, 'SSPS_ADJUSTED', 0, 'r' );
tsg = getappdata( hMainFig, 'tsg_data');
% Plot the difference tsg.SSPS_ADJUSTED-tsg.SSPS on axe 2 % Plot the difference tsg.SSPS_ADJUSTED-tsg.SSPS on axe 2
% ------------------------------------------------------- % -------------------------------------------------------
axes( hPlotAxes(2) ); axes( hPlotAxes(2) );
tsg = getappdata( hMainFig, 'tsg_data');
line( tsg.DAYD, tsg.SSPS_ADJUSTED-tsg.SSPS,... line( tsg.DAYD, tsg.SSPS_ADJUSTED-tsg.SSPS,...
'Tag', 'TAG_PLOT2_LINE_TSGDIF', 'Color', 'b'); 'Tag', 'TAG_PLOT2_LINE_TSGDIF', 'Color', 'b');
% Plot TSG + ERROR on axe 3
% -------------------------
errorPlus = tsg.SSPS_ADJUSTED + tsg.SSPS_ADJUSTED_ERROR;
errorMinus = tsg.SSPS_ADJUSTED - tsg.SSPS_ADJUSTED_ERROR;
axes( hPlotAxes(3) );
line( tsg.DAYD, errorPlus,...
'Tag', 'TAG_PLOT3_LINE_TSGERROR_PLUS', 'Color', 'g');
line( tsg.DAYD, errorMinus,...
'Tag', 'TAG_PLOT3_LINE_TSGERROR_MINUS', 'Color', 'g');
case -1 case -1
msgbox( 'Date limits are not correct',... msgbox( 'Date limits are not correct',...
'Correction module', 'warn', 'modal'); 'Correction module', 'warn', 'modal');
end end
end end
%% Clim_OffMenuCallback %% Clim_OffMenuCallback
......
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