[Dart-dev] [4251] DART/trunk: read_obs_netcdf no longer has a 'maxQC' argument, nor will it
nancy at ucar.edu
nancy at ucar.edu
Wed Feb 3 13:50:30 MST 2010
Revision: 4251
Author: thoar
Date: 2010-02-03 13:50:30 -0700 (Wed, 03 Feb 2010)
Log Message:
-----------
read_obs_netcdf no longer has a 'maxQC' argument, nor will it
return observations subsetted based on maxQC. The routine is more
useful if it returns all the observations and you can query based
on any/all QC value(s).
The plotting routines now have a 'twoup' flag so you can plot the
observations above and the QC values below.
The linked_observations() function now plots a scatterplot of
the observation value vs. prior ensemble mean (for example).
GetNCindices is one step closer to recognizing WRF coordinate variables.
Modified Paths:
--------------
DART/trunk/diagnostics/matlab/linked_observations.m
DART/trunk/diagnostics/matlab/plot_evolution.m
DART/trunk/diagnostics/matlab/plot_obs_netcdf.m
DART/trunk/diagnostics/matlab/plot_obs_netcdf_diffs.m
DART/trunk/diagnostics/matlab/read_obs_netcdf.m
DART/trunk/matlab/DART.m
DART/trunk/matlab/GetNCindices.m
DART/trunk/matlab/get_qc_index.m
-------------- next part --------------
Modified: DART/trunk/diagnostics/matlab/linked_observations.m
===================================================================
--- DART/trunk/diagnostics/matlab/linked_observations.m 2010-02-03 18:02:11 UTC (rev 4250)
+++ DART/trunk/diagnostics/matlab/linked_observations.m 2010-02-03 20:50:30 UTC (rev 4251)
@@ -1,13 +1,6 @@
-function linked_observations(obsmat,obs)
-% linked_observations(obs)
-%
-% obs is a structure with the following required components
-%
-% obs.lons longitudes of the observations
-% obs.lats latitudes of the observations
-% obs.z vertical level (depth) of the observations
-% obs.obs observation values
-% obs.qc observation DART QC code
+function linked_observations(obs)
+% linked_observations(obs) is a helper function for link_obs.m
+% linked_observations is never meant to be called directly.
%% DART software - Copyright \xA9 2004 - 2010 UCAR. This open source software is
% provided by UCAR, "as is", without charge, subject to all terms of use at
@@ -19,14 +12,46 @@
% $Revision$
% $Date$
+% obs has components (for example):
+% fname: '/ptmp/thoar/POP/CAM/POP8/obs_sequence_001.nc'
+% ObsTypeString: 'RADIOSONDE_TEMPERATURE'
+% ObsCopyString: 'NCEP BUFR observation'
+% CopyString: 'prior ensemble mean'
+% QCString: 'DART quality control'
+% region: [0 360 -90 90 -Inf Inf]
+% verbose: 1
+% timestring: [2x20 char]
+% lons: [794x1 double]
+% lats: [794x1 double]
+% z: [794x1 double]
+% obs: [794x1 double]
+% Ztyp: [794x1 int32]
+% keys: [794x1 int32]
+% time: [794x1 double]
+% qc: [794x1 int32]
+% colnames: {1x9 cell}
+% lonindex: 1
+% latindex: 2
+% zindex: 3
+% obsindex: 4
+% copyindex: 5
+% qcindex: 6
+% keyindex: 7
+% timeindex: 8
+% indindex: 9
+
+global obsmat
+
% Create figure
%figure1 = figure('XVisual',...
% '0x24 (TrueColor, depth 24, RGB mask 0xff0000 0xff00 0x00ff)',...
% 'Renderer','OpenGL');
-figure1 = figure(1); clf(figure1);;
+figure1 = figure(1); clf(figure1);
-%% Create axes for 3D plot
-axes0 = axes('Parent',figure1,'OuterPosition',[0 0 1 0.90],'FontSize',12);
+%% Create axes for 3D scatterplot
+% should figure out how to query the vertical coordinate to determine
+% direction of the Z axis ...
+axes0 = axes('Parent',figure1,'OuterPosition',[0 0 1 0.90],'FontSize',18);
view(axes0,[-37.5 30]);
grid(axes0,'on');
hold(axes0,'all');
@@ -35,16 +60,18 @@
ystring = sprintf('obsmat(:,%d)',obs.latindex);
zstring = sprintf('obsmat(:,%d)',obs.zindex );
-h0 = scatter3(obsmat(:,obs.lonindex), obsmat(:,obs.latindex), obsmat(:,obs.zindex), ...
+scatter3(obsmat(:,obs.lonindex), obsmat(:,obs.latindex), obsmat(:,obs.zindex), ...
'Parent',axes0,'DisplayName','observation locations', ...
'XDataSource',xstring, ...
'YDataSource',ystring, ...
'ZDataSource',zstring);
worldmap('light');
-xlabel('longitude');
-ylabel('latitude');
-zlabel('depth');
+
+xlabel(obs.colnames{obs.lonindex});
+ylabel(obs.colnames{obs.latindex});
+zlabel(obs.colnames{obs.zindex});
+
h = title({obs.ObsTypeString, ...
sprintf('%s ---> %s',obs.timestring(1,:),obs.timestring(2,:)) });
set(h,'Interpreter','none')
@@ -55,28 +82,29 @@
figure2 = figure(2); clf(figure2); orient tall; wysiwyg
%% Create axes for time VS. QC
-axes4 = axes('Parent',figure2,'OuterPosition',[0 0.80 1 0.175]);
+axes4 = axes('Parent',figure2,'OuterPosition',[0 0.80 1 0.175],'FontSize',14);
set(axes4,'XAxisLocation','top')
box(axes4,'on');
hold(axes4,'all');
xstring = sprintf('obsmat(:,%d)',obs.timeindex);
ystring = sprintf('obsmat(:,%d)',obs.qcindex);
-h4 = scatter(obsmat(:,obs.timeindex),obsmat(:,obs.qcindex),'Parent',axes4, ...
+scatter(obsmat(:,obs.timeindex),obsmat(:,obs.qcindex),'Parent',axes4, ...
'DisplayName','time vs qc', ...
'XDataSource',xstring, ...
'YDataSource',ystring);
datetick(axes4,'x',6);
-ylabel(obs.QCString);
+ylabel(obs.colnames{obs.qcindex});
%% Create axes for observation index VS. time
-axes3 = axes('Parent',figure2,'OuterPosition',[0 0.575 1 0.175]);
+%axes3 = axes('Parent',figure2,'OuterPosition',[0 0.575 1 0.175]);
+axes3 = axes('Parent',figure2,'OuterPosition',[0 0.600 1 0.2],'FontSize',14);
box(axes3,'on');
hold(axes3,'all');
xstring = sprintf('obsmat(:,%d)',obs.timeindex);
ystring = sprintf('obsmat(:,%d)',obs.indindex);
-h3 = scatter(obsmat(:,obs.timeindex),obsmat(:,obs.indindex),'Parent',axes3, ...
+scatter(obsmat(:,obs.timeindex),obsmat(:,obs.indindex),'Parent',axes3, ...
'DisplayName','time vs key', ...
'XDataSource',xstring, ...
'YDataSource',ystring);
@@ -84,37 +112,70 @@
datetick(axes3,'x',6);
%% Create axes for observation index VS. linked list key
-axes2 = axes('Parent',figure2,'OuterPosition',[0.0 0.400 1 0.15]);
+%axes2 = axes('Parent',figure2,'OuterPosition',[0.0 0.375 1 0.2]);
+axes2 = axes('Parent',figure2,'OuterPosition',[0.0 0.35 1 0.25],'FontSize',14);
box(axes2,'on');
hold(axes2,'all');
xstring = sprintf('obsmat(:,%d)',obs.indindex);
ystring = sprintf('obsmat(:,%d)',obs.keyindex);
-h2 = scatter(obsmat(:,obs.indindex),obsmat(:,obs.keyindex),'Parent',axes2, ...
+scatter(obsmat(:,obs.indindex),obsmat(:,obs.keyindex),'Parent',axes2, ...
'DisplayName','count vs key', ...
'XDataSource',xstring, ...
'YDataSource',ystring);
xlabel('obs count');
ylabel('key');
-%% Create axes for QC vs. ObsVal scatterplot
-axes1 = axes('Parent',figure2,'Position',[0.05 0.05 0.6 0.25]);
+%% Create axes for ObsVal vs. QC scatterplot
+axes1 = axes('Parent',figure2,'Position',[0.05 0.05 0.6 0.25],'FontSize',14);
box(axes1,'on');
hold(axes1,'all');
xstring = sprintf('obsmat(:,%d)',obs.obsindex);
ystring = sprintf('obsmat(:,%d)',obs.qcindex);
-h1 = scatter(obsmat(:,obs.obsindex),obsmat(:,obs.qcindex),'Parent',axes1, ...
+scatter(obsmat(:,obs.obsindex),obsmat(:,obs.qcindex),'Parent',axes1, ...
'DisplayName','obs vs qc', ...
'XDataSource',xstring, ...
'YDataSource',ystring);
-xlabel(obs.CopyString);
-title(obs.QCString);
+xlabel( obs.colnames{obs.obsindex});
+h = title( obs.ObsTypeString);
+set(h,'Interpreter','none');
+LabelQC(obs.colnames{obs.qcindex}, obs.qc)
+refreshdata
+linkdata on
-LabelQC(obs.QCString, obs.qc)
+%% Create axes for observation vs ensemble
+% This figure is most useful when all the 'bad' obs have been
+% replaced by Matlab's NAN so as not to blow the scale.
+% The idea is - if both copies 'match', they line up on the diagonal.
+figure3 = figure(3); clf(figure3);
+axes5 = axes('Parent',figure3,'OuterPosition',[0 0 1 0.95],'FontSize',18);
+grid(axes5,'on');
+hold(axes5,'all');
+
+xstring = sprintf('obsmat(:,%d)',obs.obsindex);
+ystring = sprintf('obsmat(:,%d)',obs.copyindex);
+
+scatter(obsmat(:,obs.obsindex), obsmat(:,obs.copyindex), ...
+ 'Parent',axes5,'DisplayName','copy1 v copy2', ...
+ 'XDataSource',xstring, ...
+ 'YDataSource',ystring);
+
+xlabel(obs.colnames{obs.obsindex});
+ylabel(obs.colnames{obs.copyindex});
+h = title({obs.ObsTypeString, ...
+ sprintf('%s ---> %s',obs.timestring(1,:),obs.timestring(2,:)) });
+set(h,'Interpreter','none');
+
+axlims = [min(axis) max(axis) min(axis) max(axis)];
+axis(axlims)
+plot(axes5,[min(axis) max(axis)],[min(axis) max(axis)],'k-')
+
+%% thats it folks
+
refreshdata
linkdata on
@@ -148,13 +209,14 @@
qcvals = unique(qcarray);
qccount = zeros(size(qcvals));
+ s = cell(length(qcvals),1);
for i = 1:length(qcvals)
qccount(i) = sum(qcarray == qcvals(i));
s{i} = sprintf('%d - %s %d obs',qcvals(i), dartqc_strings{qcvals(i)+1}, qccount(i));
end
set(gca,'YTick',qcvals,'YAxisLocation','right')
- set(gca,'YTickLabel',char(s))
+ set(gca,'YTickLabel',char(s{:}),'FontSize',12)
otherwise,
str = sprintf('no way to interpret values of %s',strtrim(QCString));
Modified: DART/trunk/diagnostics/matlab/plot_evolution.m
===================================================================
--- DART/trunk/diagnostics/matlab/plot_evolution.m 2010-02-03 18:02:11 UTC (rev 4250)
+++ DART/trunk/diagnostics/matlab/plot_evolution.m 2010-02-03 20:50:30 UTC (rev 4251)
@@ -217,7 +217,7 @@
mean_post = NaN;
end
- string_guess = sprintf('guess: mean=%.5g', mean_prior);
+ string_guess = sprintf('forecast: mean=%.5g', mean_prior);
string_analy = sprintf('analysis: mean=%.5g', mean_post);
% Plot the requested quantity on the left axis.
Modified: DART/trunk/diagnostics/matlab/plot_obs_netcdf.m
===================================================================
--- DART/trunk/diagnostics/matlab/plot_obs_netcdf.m 2010-02-03 18:02:11 UTC (rev 4250)
+++ DART/trunk/diagnostics/matlab/plot_obs_netcdf.m 2010-02-03 20:50:30 UTC (rev 4251)
@@ -1,5 +1,5 @@
function obsstruct = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, ...
- QCString, maxQC, verbose)
+ QCString, maxQC, verbose, twoup)
%% plot_obs_netcdf will plot the locations and values of the observations in a DART netcdf file.
% any observations with a QC value greater than 'maxgoodQC' will get
% plotted on a separate figure ... color-coded to its QC value, not the
@@ -15,11 +15,10 @@
% QCString = 'DART quality control';
% maxgoodQC = 2;
% verbose = 1; % anything > 0 == 'true'
+% twoup = 1; % anything > 0 == 'true'
%
-% bob = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, maxgoodQC, verbose);
+% bob = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, maxgoodQC, verbose, twoup);
%
-% view(0,90); % for a traditional '2D' plot
-%
%--------------------------------------------------
% EXAMPLE 2: plotting all the observation types
%--------------------------------------------------
@@ -30,8 +29,9 @@
% QCString = 'WOD QC';
% maxgoodQC = 0;
% verbose = 1; % anything > 0 == 'true'
+% twoup = 1; % anything > 0 == 'true'
%
-% bob = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, maxgoodQC, verbose);
+% bob = plot_obs_netcdf(fname, ObsTypeString, region, CopyString, QCString, maxgoodQC, verbose, twoup);
%% DART software - Copyright \xA9 2004 - 2010 UCAR. This open source software is
% provided by UCAR, "as is", without charge, subject to all terms of use at
@@ -47,11 +47,54 @@
error('%s does not exist.',fname)
end
+if ( twoup > 0 )
+ clf; orient tall
+ positions = [0.1, 0.55, 0.8, 0.35 ; ...
+ 0.1, 0.10, 0.8, 0.35 ; ...
+ 0.1, 0.02, 0.8, 0.08];
+else
+ clf; orient landscape
+ positions = [0.1, 0.20, 0.8, 0.65 ; ...
+ 0.1, 0.20, 0.8, 0.65 ; ...
+ 0.1, 0.05, 0.8, 0.10];
+end
+
%% Read the observation sequence
obsstruct = read_obs_netcdf(fname, ObsTypeString, region, ...
- CopyString, QCString, maxQC, verbose);
+ CopyString, QCString, verbose);
+% subset based on qc value
+
+if ( (~ isempty(obsstruct.qc)) && (~ isempty(maxQC)) )
+
+ inds = find(obsstruct.qc > maxQC);
+
+ obsstruct.numflagged = length(inds);
+
+ if (~isempty(inds))
+ flaggedobs.lons = obsstruct.lons(inds);
+ flaggedobs.lats = obsstruct.lats(inds);
+ flaggedobs.Ztyp = obsstruct.Ztyp(inds);
+ flaggedobs.z = obsstruct.z( inds);
+ flaggedobs.obs = obsstruct.obs( inds);
+ flaggedobs.qc = obsstruct.qc( inds);
+ end
+
+ fprintf('Removing %d obs with a %s value greater than %f\n', ...
+ length(inds), QCString, maxQC)
+
+ inds = find(obsstruct.qc <= maxQC);
+
+ bob = obsstruct.lons(inds); obsstruct.lons = bob;
+ bob = obsstruct.lats(inds); obsstruct.lats = bob;
+ bob = obsstruct.Ztyp(inds); obsstruct.Ztyp = bob;
+ bob = obsstruct.z( inds); obsstruct.z = bob;
+ bob = obsstruct.obs( inds); obsstruct.obs = bob;
+ bob = obsstruct.qc( inds); obsstruct.qc = bob;
+
+end
+
%% Create graphic with area-weighted symbols for the good observations.
% It has happened that there have been zero good observations in a file.
@@ -70,14 +113,14 @@
fprintf('There are no ''good'' observations to plot\n')
else
- figure(gcf+1); clf
+ subplot('position',positions(1,:))
% choose a symbol size based on the number of obs to plot.
- if (length(obsstruct.obs) < 1000)
+ if (length(obsstruct.obs) > 1000)
pstruct.scalearray = scaleme(obsstruct.obs, 36);
else
- pstruct.scalearray = 50.0 * ones(size(obsstruct.obs));
+ pstruct.scalearray = 128.0 * ones(size(obsstruct.obs));
end
pstruct.clim = [min(obsstruct.obs) max(obsstruct.obs)];
pstruct.str2 = sprintf('%s (%d locations)',obsstruct.CopyString,length(obsstruct.obs));
@@ -89,19 +132,19 @@
pstruct.axis = [xmin xmax ymin ymax zmin zmax];
pstruct.str1 = sprintf('%s level (%.2f - %.2f)',obsstruct.ObsTypeString,zmin,zmax);
- plot_3D(obsstruct, pstruct)
+ plot_3D(obsstruct, pstruct);
else
pstruct.axis = [xmin xmax ymin ymax];
pstruct.str1 = sprintf('%s',obsstruct.ObsTypeString);
- plot_2D(obsstruct, pstruct)
+ plot_2D(obsstruct, pstruct);
end
end
-%% Create graphic of spatial distribution of 'bad' observations & their QC value.
+%% Create graphic of spatial distribution of 'flagged' observations & their QC value.
%
% 0 observation assimilated
% 1 observation evaluated only
@@ -124,39 +167,42 @@
'''outlier rejected''',...
'''reserved for future use'''};
-if (obsstruct.numbadqc > 0 ) % if there are bad observation to plot ... carry on.
+if (obsstruct.numflagged > 0 ) % if there are flagged observation to plot ... carry on.
- figure(gcf+1); clf
+ if (twoup <= 0)
+ figure(gcf+1); clf
+ end
- subplot('position',[0.1 0.20 0.8 0.65])
+ subplot('position',positions(2,:))
- zmin = min(obsstruct.badobs.z);
- zmax = max(obsstruct.badobs.z);
+ zmin = min(flaggedobs.z);
+ zmax = max(flaggedobs.z);
- pstruct.scalearray = 128 * ones(size(obsstruct.badobs.obs));
+ prej = 100.0 * length(flaggedobs.obs) / ...
+ (length(flaggedobs.obs) + length(obsstruct.obs));
+ pstruct.scalearray = 128 * ones(size(flaggedobs.obs));
pstruct.colorbarstring = QCString;
- pstruct.clim = [min(obsstruct.badobs.qc) max(obsstruct.badobs.qc)];
+ pstruct.clim = [min(flaggedobs.qc) max(flaggedobs.qc)];
pstruct.str1 = sprintf('%s level (%.2f - %.2f)',obsstruct.ObsTypeString,zmin,zmax);
- pstruct.str2 = sprintf('%s (%d bad observations)', ...
- obsstruct.CopyString, ...
- length(obsstruct.badobs.obs));
+ pstruct.str2 = sprintf('%s (%d ''good'', %d ''flagged'' -- %.2f %%)', obsstruct.CopyString, ...
+ length(obsstruct.obs), length(flaggedobs.obs), prej);
- obsstruct.badobs.obs = obsstruct.badobs.qc; % plot QC values, not obs values
+ flaggedobs.obs = flaggedobs.qc; % plot QC values, not obs values
if ( zmin ~= zmax )
pstruct.axis = [xmin xmax ymin ymax zmin zmax];
- plot_3D(obsstruct.badobs, pstruct)
+ plot_3D(flaggedobs, pstruct);
else
pstruct.axis = [xmin xmax ymin ymax];
- plot_2D(obsstruct.badobs, pstruct)
+ plot_2D(flaggedobs, pstruct);
end
- subplot('position',[0.1 0.05 0.8 0.10])
+ subplot('position',positions(3,:))
axis off
%% If the QC is a DART QC, we know how to interpret them.
@@ -164,15 +210,16 @@
switch lower(strtrim(QCString))
case 'dart quality control',
- qcvals = unique(obsstruct.badobs.qc);
+ qcvals = unique(flaggedobs.qc);
qccount = zeros(size(qcvals));
+ s = cell(length(qcvals));
for i = 1:length(qcvals)
- qccount(i) = sum(obsstruct.badobs.qc == qcvals(i));
+ qccount(i) = sum(flaggedobs.qc == qcvals(i));
s{i} = sprintf('%d obs with qc == %d %s',qccount(i),qcvals(i), ...
dartqc_strings{qcvals(i)});
end
- dy = 1.0/length(s);
+ dy = 0.8*1.0/length(s);
for i = 1:length(s)
text(0.0, (i-1)*dy ,s{i})
end
@@ -213,10 +260,10 @@
% We need to determine the geographic subset of the elevation matrix.
%---------------------------------------------------------------------------
-lon_ind1 = min(find(ax(1) <= lons));
-lon_ind2 = min(find(ax(2) <= lons));
-lat_ind1 = min(find(ax(3) <= lats));
-lat_ind2 = min(find(ax(4) <= lats));
+lon_ind1 = find(ax(1) <= lons, 1);
+lon_ind2 = find(ax(2) <= lons, 1);
+lat_ind1 = find(ax(3) <= lats, 1);
+lat_ind2 = find(ax(4) <= lats, 1);
if (isempty(lon_ind1)), lon_ind1 = 1; end;
if (isempty(lon_ind2)), lon_ind2 = nlon; end;
@@ -273,7 +320,7 @@
-function plot_3D(obsstruct, pstruct)
+function h1 = plot_3D(obsstruct, pstruct)
if (pstruct.clim(1) == pstruct.clim(2))
% If all the observations have the same value, setting the
@@ -282,7 +329,7 @@
% colormap and setting the colorbar to have some more
% colors 'on top' - that are never used.
cmap = colormap;
- h = plot3(obsstruct.lons, obsstruct.lats, obsstruct.z, 'bo');
+ h = plot3(obsstruct.lons, obsstruct.lats, obsstruct.z, 'bd');
set(h,'MarkerFaceColor',cmap(1,:),'MarkerEdgeColor',cmap(1,:))
set(gca,'Clim',[pstruct.clim(1) pstruct.clim(2)+1])
set(gca,'XGrid','on','YGrid','on','ZGrid','on')
@@ -291,12 +338,12 @@
scatter3(obsstruct.lons, obsstruct.lats, obsstruct.z, ...
pstruct.scalearray, obsstruct.obs, 'd', 'filled');
end
+h1 = gca;
+clim = get(h1,'CLim');
-clim = get(gca,'CLim');
-
axis(pstruct.axis)
-title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',16);
+title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',14);
xlabel('longitude')
ylabel('latitude')
@@ -315,19 +362,19 @@
myworldmap;
set(gca,'CLim',clim)
-h = colorbar;
-set(get(h,'YLabel'),'String',pstruct.colorbarstring,'Interpreter','none')
+hb = colorbar;
+set(get(hb,'YLabel'),'String',pstruct.colorbarstring,'Interpreter','none')
-function plot_2D(obsstruct, pstruct)
+function h1 = plot_2D(obsstruct, pstruct)
axis(pstruct.axis); hold on; worldmap('light');
if (pstruct.clim(1) == pstruct.clim(2))
cmap = colormap;
- h = plot(obsstruct.lons, obsstruct.lats, 'bo');
+ h = plot(obsstruct.lons, obsstruct.lats, 'bd');
set(h,'MarkerFaceColor',cmap(1,:),'MarkerEdgeColor',cmap(1,:))
set(gca,'Clim',[pstruct.clim(1) pstruct.clim(2)+1])
set(gca,'XGrid','on','YGrid','on')
@@ -338,9 +385,10 @@
pstruct.scalearray, obsstruct.obs, 'd', 'filled');
end
-clim = get(gca,'CLim');
+h1 = gca;
+clim = get(h1,'CLim');
-title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',16);
+title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',14);
xlabel('longitude')
ylabel('latitude')
Modified: DART/trunk/diagnostics/matlab/plot_obs_netcdf_diffs.m
===================================================================
--- DART/trunk/diagnostics/matlab/plot_obs_netcdf_diffs.m 2010-02-03 18:02:11 UTC (rev 4250)
+++ DART/trunk/diagnostics/matlab/plot_obs_netcdf_diffs.m 2010-02-03 20:50:30 UTC (rev 4251)
@@ -1,17 +1,55 @@
function obsstruct = plot_obs_netcdf_diffs(fname, ObsTypeString, region, ...
- CopyString1, CopyString2, QCString, maxQC, verbose)
+ CopyString1, CopyString2, QCString, maxQC, verbose, twoup)
+% plot_obs_netcdf_diffs will plot the difference between any two 'copies' of an observation-style netcdf file.
%
+% bob = plot_obs_netcdf_diffs(fname, ObsTypeString, region, CopyString1, CopyString2, ...
+% QCString, maxQC, verbose, twoup);
+%
+% fname the name of the netCDF file (from obs_seq_to_netcdf)
+%
+% ObsTypeString the variable of interest (from ObsTypesMetaData variable)
+%
+% region region of interest [lonmin lonmax latmin latmax zmin zmax]
+%
+% CopyString1 the difference is taken 'CopyString2 - CopyString1'
+% CopyString2
+%
+% QCString There are multiple QC copies
+% maxQC The highest QC value of interest. Anything more than this
+% will not be differenced. The locations will be plotted on
+% a separate axis.
+% verbose logical flag ... if 'true', a table listing the possible
+% observation types and observation counts is displayed.
+%
+% twoup logical flag indicating that both the plot of the rejected
+% observations and the plot of the differences is
+% created on the same figure window.
+%
+% The 'copies' are recorded in the netCDF 'CopyMetaData' variable -
+% the observation types are recorded in the 'ObsTypesMetaData' variable,
+% and the QC strings of interest are recorded in QCMetaData - so
+% ncdump -v CopyMetaData,ObsTypesMetaData,QCMetaData obs_sequence_001.nc
+% is a useful endeavor.
+%
+% $Id$
+%
+%--------------------------------------------------
+% EXAMPLE : plot the difference between the ensemble mean of the prior
+% and the actual observation value - while rejecting any obs that had
+% a DART QC greater than 3 ( prior forward operator failed ... or worse)
+%--------------------------------------------------
% fname = 'obs_sequence_001.nc';
% ObsTypeString = 'RADIOSONDE_U_WIND_COMPONENT';
% region = [0 360 -90 90 -Inf Inf];
% CopyString1 = 'NCEP BUFR observation';
% CopyString2 = 'prior ensemble mean';
% QCString = 'DART quality control';
-% maxQC = 1;
+% maxQC = 1; % max QC to consider when taking differences.
% verbose = 1; % anything > 0 == 'true'
+% twoup = 1; % anything > 0 == 'true'
%
% bob = plot_obs_netcdf_diffs(fname, ObsTypeString, region, CopyString1, CopyString2, ...
-% QCString, maxQC, verbose);
+% QCString, maxQC, verbose, twoup);
% record the user input
@@ -21,127 +59,57 @@
%
% <next few lines under version control, do not edit>
% $URL$
-% $Id$
% $Revision$
% $Date$
-obsstruct.fname = fname;
-obsstruct.ObsTypeString = ObsTypeString;
-obsstruct.region = region;
-obsstruct.CopyString1 = CopyString1;
-obsstruct.CopyString2 = CopyString2;
-obsstruct.QCString = QCString;
-obsstruct.maxQC = maxQC;
-obsstruct.verbose = verbose;
-
-% get going
-
-ObsTypes = nc_varget(fname,'ObsTypes');
-ObsTypeStrings = nc_varget(fname,'ObsTypesMetaData');
-CopyStrings = nc_varget(fname,'CopyMetaData');
-QCStrings = nc_varget(fname,'QCMetaData');
-
-t = nc_varget(fname,'time');
-obs_type = nc_varget(fname,'obs_type');
-z_type = nc_varget(fname,'which_vert');
-
-loc = nc_varget(fname,'location');
-obs = nc_varget(fname,'observations');
-qc = nc_varget(fname,'qc');
-
-my_types = unique(obs_type); % only ones in the file, actually.
-timeunits = nc_attget(fname,'time','units');
-timerange = nc_attget(fname,'time','valid_range');
-calendar = nc_attget(fname,'time','calendar');
-timebase = sscanf(timeunits,'%*s%*s%d%*c%d%*c%d'); % YYYY MM DD
-timeorigin = datenum(timebase(1),timebase(2),timebase(3));
-timestring = datestr(timerange + timeorigin);
-
-% Echo summary if requested
-
-if ( verbose > 0 )
- for i = 1:length(my_types)
- obtype = my_types(i);
- inds = find(obs_type == obtype);
- myz = loc(inds,3);
-
- disp(sprintf('N = %6d %s obs (type %3d) between levels %.2f and %.2f', ...
- length(inds), ObsTypeStrings(obtype,:), obtype, ...
- unique(min(myz)), unique(max(myz))))
- end
-
-% uniquelevels = unique(loc(:,3));
-
-% for i = 1:length(uniquelevels)
-% mylevel = uniquelevels(i);
-% inds = find(loc(:,3) == mylevel);
-% disp(sprintf('level %2d %f has %d observations',i,mylevel,length(inds)))
-% end
-
+if (exist(fname,'file') ~= 2)
+ error('%s does not exist.',fname)
end
-% Find observations of the correct types.
-
-myind = strmatch(ObsTypeString,ObsTypeStrings);
-
-if ( isempty(myind) )
- error('no %s observations ... stopping',obsstruct.ObsTypeString)
-end
-
-mytype1 = get_copy_index(fname, CopyString1);
-mytype2 = get_copy_index(fname, CopyString2);
-inds = find(obs_type == myind);
-mylocs = loc(inds,:);
-myobs1 = obs(inds,mytype1);
-myobs2 = obs(inds,mytype2);
-myobs = myobs2 - myobs1;
-
-if ~ isempty(QCString)
- myQCind = get_qc_index(fname, QCString);
- myqc = qc(inds,myQCind);
+if ( twoup > 0 )
+ clf; orient tall
+ positions = [0.1, 0.55, 0.8, 0.35 ; ...
+ 0.1, 0.10, 0.8, 0.35 ; ...
+ 0.1, 0.02, 0.8, 0.08];
else
- myqc = [];
+ clf; orient landscape
+ positions = [0.1, 0.20, 0.8, 0.65 ; ...
+ 0.1, 0.20, 0.8, 0.65 ; ...
+ 0.1, 0.05, 0.8, 0.10];
end
-clear myobs1 myobs2 obs loc qc
+%% Read the observation sequence
-% geographic subset if needed
+obsstruct = read_obs_netcdf(fname, ObsTypeString, region, ...
+ CopyString1, QCString, verbose);
-inds = locations_in_region(mylocs,region);
+obsstruct2 = read_obs_netcdf(fname, ObsTypeString, region, ...
+ CopyString2, QCString, verbose);
-obsstruct.lons = mylocs(inds,1);
-obsstruct.lats = mylocs(inds,2);
-obsstruct.z = mylocs(inds,3);
-obsstruct.obs = myobs(inds);
-obsstruct.Ztyp = z_type(inds);
-obsstruct.numbadqc = 0;
+xdat = obsstruct2.obs - obsstruct.obs;
+obsstruct.obs = xdat;
+clear obsstruct2 xdat
-if (isempty(myqc))
- obsstruct.qc = [];
-else
- obsstruct.qc = myqc(inds);
-end
-
% subset based on qc value
-if ( (~ isempty(myqc)) & (~ isempty(maxQC)) )
+if ( (~ isempty(obsstruct.qc)) && (~ isempty(maxQC)) )
inds = find(obsstruct.qc > maxQC);
- obsstruct.numbadqc = length(inds);
-
+ obsstruct.numflagged = length(inds);
+
if (~isempty(inds))
- badobs.lons = obsstruct.lons(inds);
- badobs.lats = obsstruct.lats(inds);
- badobs.Ztyp = obsstruct.Ztyp(inds);
- badobs.z = obsstruct.z( inds);
- badobs.obs = obsstruct.obs(inds);
- badobs.qc = obsstruct.qc(inds);
+ flaggedobs.lons = obsstruct.lons(inds);
+ flaggedobs.lats = obsstruct.lats(inds);
+ flaggedobs.Ztyp = obsstruct.Ztyp(inds);
+ flaggedobs.z = obsstruct.z( inds);
+ flaggedobs.obs = obsstruct.obs( inds);
+ flaggedobs.qc = obsstruct.qc( inds);
end
-
- disp(sprintf('Removing %d obs with a %s value greater than %f', ...
- length(inds),QCString,maxQC))
+ fprintf('Removing %d obs with a %s value greater than %f\n', ...
+ length(inds),QCString,maxQC)
+
inds = find(obsstruct.qc <= maxQC);
bob = obsstruct.lons(inds); obsstruct.lons = bob;
@@ -153,12 +121,9 @@
end
-%-------------------------------------------------------------------------------
-% Create graphic with area-weighted symbols for the good observations.
-%-------------------------------------------------------------------------------
+%% Create graphic with area-weighted symbols for the good observations.
+% It has happened that there have been zero good observations in a file.
-figure(1); clf
-
xmin = min(region(1:2));
xmax = max(region(1:2));
ymin = min(region(3:4));
@@ -166,110 +131,145 @@
zmin = min(obsstruct.z);
zmax = max(obsstruct.z);
-scalearray = scaleme(obsstruct.obs,36);
-scalearray = 128 * ones(size(obsstruct.obs));
+pstruct.colorbarstring = sprintf('%s - %s',CopyString2,CopyString1);
+pstruct.region = region;
+pstruct.str3 = sprintf('%s - %s',obsstruct.timestring(1,:),obsstruct.timestring(2,:));
-scatter3(obsstruct.lons, obsstruct.lats, obsstruct.z, ...
- scalearray, obsstruct.obs,'d','filled');
+if ( length(obsstruct.obs) < 1 )
+ fprintf('There are no ''good'' observations to plot\n')
+else
-axis([xmin xmax ymin ymax zmin zmax])
+ subplot('position',positions(1,:))
-str1 = sprintf('%s level (%.2f - %.2f)',ObsTypeString,zmin,zmax);
-str2 = sprintf('%s - %s (%d locations)',CopyString2,CopyString1,length(obsstruct.obs));
-str3 = sprintf('%s - %s',timestring(1,:),timestring(2,:));
+ % choose a symbol size based on the number of obs to plot.
-title( {str1, str3, str2}, 'Interpreter','none','FontSize',16);
-xlabel('longitude')
-ylabel('latitude')
+ if (length(obsstruct.obs) > 1000)
+ pstruct.scalearray = scaleme(obsstruct.obs, 36);
+ else
+ pstruct.scalearray = 128.0 * ones(size(obsstruct.obs));
+ end
+ pstruct.clim = [min(obsstruct.obs) max(obsstruct.obs)];
+ pstruct.str2 = sprintf('%s (%d locations)',obsstruct.CopyString,length(obsstruct.obs));
-if (obsstruct.Ztyp(1) == -2) % VERTISUNDEF = -2
- zlabel('curious ... undefined')
-elseif (obsstruct.Ztyp(1) == -1) % VERTISSURFACE = -1
- zlabel('surface')
-elseif (obsstruct.Ztyp(1) == 1) % VERTISLEVEL = 1
- zlabel('level')
-elseif (obsstruct.Ztyp(1) == 2) % VERTISPRESSURE = 2
- set(gca,'ZDir','reverse')
- zlabel('pressure')
-elseif (obsstruct.Ztyp(1) == 3) % VERTISHEIGHT = 3
- zlabel('height')
+ % If all the observations live on the same level ... make a 2D plot.
+
+ if ( zmin ~= zmax )
+
+ pstruct.axis = [xmin xmax ymin ymax zmin zmax];
+ pstruct.str1 = sprintf('%s level (%.2f - %.2f)',obsstruct.ObsTypeString,zmin,zmax);
+
+ plot_3D(obsstruct, pstruct);
+
+ else
+
+ pstruct.axis = [xmin xmax ymin ymax];
+ pstruct.str1 = sprintf('%s',obsstruct.ObsTypeString);
+
+ plot_2D(obsstruct, pstruct);
+
+ end
end
-myworldmap;
-set(gca,'CLim',[min(obsstruct.obs) max(obsstruct.obs)])
-h = colorbar;
-set(get(h,'YLabel'),'String',ObsTypeString,'Interpreter','none')
+%% Create graphic of spatial distribution of 'flagged' observations & their QC value.
+%
+% 0 observation assimilated
+% 1 observation evaluated only
+% --- everything above this means the prior and posterior are OK
+% 2 assimilated, but the posterior forward operator failed
+% 3 Evaluated only, but the posterior forward operator failed
+% --- everything above this means only the prior is OK
+% 4 prior forward operator failed
+% 5 not used
+% 6 prior QC rejected
+% 7 outlier rejected
-%-------------------------------------------------------------------------------
-% Create graphic of spatial distribution of 'bad' observations & their QC value.
-%-------------------------------------------------------------------------------
+dartqc_strings = { ...
+ '''observation evaluated only''', ...
+ '''assimilated, but the posterior forward operator failed''', ...
+ '''evaluated only, but the posterior forward operator failed''',...
+ '''prior forward operator failed''',...
+ '''not used''',...
+ '''prior QC rejected''',...
+ '''outlier rejected''',...
+ '''reserved for future use'''};
-if (obsstruct.numbadqc > 0 )
+if (obsstruct.numflagged > 0 ) % if there are flagged observation to plot ... carry on.
- figure(2); clf
+ if (twoup <= 0)
+ figure(gcf+1); clf
+ end
- subplot('position',[0.1 0.20 0.8 0.65])
- scalearray = 128 * ones(size(badobs.obs));
+ subplot('position',positions(2,:))
- zmin = min(badobs.z);
- zmax = max(badobs.z);
-
- scatter3(badobs.lons, badobs.lats, badobs.z, scalearray, badobs.qc,'filled')
-
- title( {str1, str3, 'Bad Observations'}, 'Interpreter','none','FontSize',16);
- xlabel('longitude')
- ylabel('latitude')
-
- if (badobs.Ztyp(1) == -2) % VERTISUNDEF = -2
- zlabel('curious ... undefined')
- elseif (badobs.Ztyp(1) == -1) % VERTISSURFACE = -1
- zlabel('surface')
- elseif (badobs.Ztyp(1) == 1) % VERTISLEVEL = 1
- zlabel('level')
- elseif (badobs.Ztyp(1) == 2) % VERTISPRESSURE = 2
- set(gca,'ZDir','reverse')
- zlabel('pressure')
- elseif (badobs.Ztyp(1) == 3) % VERTISHEIGHT = 3
- zlabel('height')
+ zmin = min(flaggedobs.z);
+ zmax = max(flaggedobs.z);
+
+ prej = 100.0 * length(flaggedobs.obs) / ...
+ (length(flaggedobs.obs) + length(obsstruct.obs));
+ pstruct.scalearray = 128 * ones(size(flaggedobs.obs));
+ pstruct.colorbarstring = QCString;
+ pstruct.clim = [min(flaggedobs.qc) max(flaggedobs.qc)];
+ pstruct.str1 = sprintf('%s level (%.2f - %.2f)',obsstruct.ObsTypeString,zmin,zmax);
+ pstruct.str2 = sprintf('%s (%d ''good'', %d ''flagged'' -- %.2f %%)', obsstruct.CopyString, ...
+ length(obsstruct.obs), length(flaggedobs.obs), prej);
+
+ flaggedobs.obs = flaggedobs.qc; % plot QC values, not obs values
+ if ( zmin ~= zmax )
+
+ pstruct.axis = [xmin xmax ymin ymax zmin zmax];
+
+ plot_3D(flaggedobs, pstruct);
+
+ else
+
+ pstruct.axis = [xmin xmax ymin ymax];
+
+ plot_2D(flaggedobs, pstruct);
+
end
- axis([region(1) region(2) ymin ymax zmin zmax])
-
- myworldmap;
- set(gca,'CLim',[min(badobs.qc) max(badobs.qc)])
- h = colorbar;
- set(get(h,'YLabel'),'String',QCString,'Interpreter','none')
-
- subplot('position',[0.1 0.05 0.8 0.10])
+ subplot('position',positions(3,:))
axis off
+
+ %% If the QC is a DART QC, we know how to interpret them.
+
+ switch lower(strtrim(QCString))
+ case 'dart quality control',
+
+ qcvals = unique(flaggedobs.qc);
+ qccount = zeros(size(qcvals));
+ for i = 1:length(qcvals)
+ qccount(i) = sum(flaggedobs.qc == qcvals(i));
+ s{i} = sprintf('%d obs with qc == %d %s',qccount(i),qcvals(i), ...
+ dartqc_strings{qcvals(i)});
+ end
- qcvals = unique(badobs.qc);
- qccount = zeros(size(qcvals));
- for i = 1:length(qcvals)
- qccount(i) = sum(badobs.qc == qcvals(i));
- s{i} = sprintf('%d obs with qc == %d',qccount(i),qcvals(i));
+ dy = 0.8*1.0/length(s);
+ for i = 1:length(s)
+ text(0.0, (i-1)*dy ,s{i})
+ end
+
+ otherwise,
+ str = sprintf('no way to interpret values of %s',strtrim(QCString));
+ text(0.0, 0.0, str)
end
-
- dy = 1.0/length(s);
- for i = 1:length(s)
- text(0.0, (i-1)*dy ,s{i})
- end
-
end
+
+
function h = myworldmap
-%---------------------------------------------------------------------------
+%%--------------------------------------------------------------------------
% GET THE ELEVATION DATA AND SET UP THE ASSOCIATED COORDINATE DATA
%---------------------------------------------------------------------------
-load topo; % GET Matlab-native [180x360] ELEVATION DATASET
-lats = [-89.5:89.5]; % CREATE LAT ARRAY FOR TOPO MATRIX
-lons = [0.5:359.5]; % CREATE LON ARRAY FOR TOPO MATRIX
+load topo; % GET Matlab-native [180x360] ELEVATION DATASET
+lats = -89.5:89.5; % CREATE LAT ARRAY FOR TOPO MATRIX
+lons = 0.5:359.5; % CREATE LON ARRAY FOR TOPO MATRIX
nlon = length(lons);
nlat = length(lats);
-%---------------------------------------------------------------------------
+%%--------------------------------------------------------------------------
% IF WE NEED TO SWAP HEMISPHERES, DO SO NOW.
% If we didn't explicitly tell it, make a guess.
%---------------------------------------------------------------------------
@@ -281,28 +281,28 @@
topo = [ topo(:,nlon/2+1:nlon) topo(:,1:nlon/2) ];
end
-%---------------------------------------------------------------------------
+%%--------------------------------------------------------------------------
% We need to determine the geographic subset of the elevation matrix.
%---------------------------------------------------------------------------
-lon_ind1 = min(find(ax(1) <= lons));
-lon_ind2 = min(find(ax(2) <= lons));
-lat_ind1 = min(find(ax(3) <= lats));
-lat_ind2 = min(find(ax(4) <= lats));
+lon_ind1 = find(ax(1) <= lons, 1);
+lon_ind2 = find(ax(2) <= lons, 1);
+lat_ind1 = find(ax(3) <= lats, 1);
+lat_ind2 = find(ax(4) <= lats, 1);
-if (isempty(lon_ind1)) lon_ind1 = 1; end;
-if (isempty(lon_ind2)) lon_ind2 = nlon; end;
-if (isempty(lat_ind1)) lat_ind1 = 1; end;
-if (isempty(lat_ind2)) lat_ind2 = nlat; end;
+if (isempty(lon_ind1)), lon_ind1 = 1; end;
+if (isempty(lon_ind2)), lon_ind2 = nlon; end;
+if (isempty(lat_ind1)), lat_ind1 = 1; end;
+if (isempty(lat_ind2)), lat_ind2 = nlat; end;
elev = topo(lat_ind1:lat_ind2,lon_ind1:lon_ind2);
x = lons(lon_ind1:lon_ind2);
y = lats(lat_ind1:lat_ind2);
-%---------------------------------------------------------------------------
+%%--------------------------------------------------------------------------
% Contour the "subset"
% There are differences between 6.5 and 7.0 that make changing the colors
-% of the filled contours a real pain. Providing both solutions.
+% of the filled contours a real pain.
%---------------------------------------------------------------------------
orgholdstate = ishold;
@@ -319,19 +319,19 @@
[c,h] = contourf(x,y,elev,[0.0 0.0],'k-');
-new_level = 1000;
+h_patch = get(h, 'Children');
-h_patch = get(h, 'Children');
-
for i = 1:numel(h_patch)
y = get(h_patch(i), 'YData');
s = size(y);
set(h_patch(i), 'ZData', zlevel*ones(s),'FaceColor',fcolor);
end
-if (orgholdstate == 0) hold off; end;
+if (orgholdstate == 0), hold off; end;
+
+
function s = scaleme(x,minsize)
% scaleme returns a uniformly scaled array the same size as the input
% array where the maximum is 10 times the minimum
@@ -343,3 +343,81 @@
s = x*slope + b;
+
+
+function h1 = plot_3D(obsstruct, pstruct)
+
+if (pstruct.clim(1) == pstruct.clim(2))
+ % If all the observations have the same value, setting the
+ % colorbar limits is a real pain. Fundamentally, I am
+ % forcing the plot symbols to be the lowest color of the
+ % colormap and setting the colorbar to have some more
+ % colors 'on top' - that are never used.
+ cmap = colormap;
+ h = plot3(obsstruct.lons, obsstruct.lats, obsstruct.z, 'bd');
+ set(h,'MarkerFaceColor',cmap(1,:),'MarkerEdgeColor',cmap(1,:))
+ set(gca,'Clim',[pstruct.clim(1) pstruct.clim(2)+1])
+ set(gca,'XGrid','on','YGrid','on','ZGrid','on')
+
+else
+ scatter3(obsstruct.lons, obsstruct.lats, obsstruct.z, ...
+ pstruct.scalearray, obsstruct.obs, 'd', 'filled');
+end
+h1 = gca;
+clim = get(h1,'CLim');
+
+axis(pstruct.axis)
+
+title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',14);
+xlabel('longitude')
+ylabel('latitude')
+
+if (obsstruct.Ztyp(1) == -2) % VERTISUNDEF = -2
+ zlabel('unspecified')
+elseif (obsstruct.Ztyp(1) == -1) % VERTISSURFACE = -1
+ zlabel('surface')
+elseif (obsstruct.Ztyp(1) == 1) % VERTISLEVEL = 1
+ zlabel('level')
+elseif (obsstruct.Ztyp(1) == 2) % VERTISPRESSURE = 2
+ set(gca,'ZDir','reverse')
+ zlabel('pressure')
+elseif (obsstruct.Ztyp(1) == 3) % VERTISHEIGHT = 3
+ zlabel('height')
+end
+
+myworldmap;
+set(gca,'CLim',clim)
+hb = colorbar;
+set(get(hb,'YLabel'),'String',pstruct.colorbarstring,'Interpreter','none')
+
+
+
+
+function h1 = plot_2D(obsstruct, pstruct)
+
+axis(pstruct.axis); hold on; worldmap('light');
+
+if (pstruct.clim(1) == pstruct.clim(2))
+ cmap = colormap;
+ h = plot(obsstruct.lons, obsstruct.lats, 'bd');
+ set(h,'MarkerFaceColor',cmap(1,:),'MarkerEdgeColor',cmap(1,:))
+ set(gca,'Clim',[pstruct.clim(1) pstruct.clim(2)+1])
+ set(gca,'XGrid','on','YGrid','on')
+
+else
+
+ scatter(obsstruct.lons, obsstruct.lats, ...
+ pstruct.scalearray, obsstruct.obs, 'd', 'filled');
+end
+
+h1 = gca;
+clim = get(h1,'CLim');
+
+title( {pstruct.str1, pstruct.str3, pstruct.str2}, 'Interpreter','none','FontSize',14);
+xlabel('longitude')
+ylabel('latitude')
+
+set(gca,'CLim',clim)
+h = colorbar;
+set(get(h,'YLabel'),'String',pstruct.colorbarstring,'Interpreter','none')
+hold off
Modified: DART/trunk/diagnostics/matlab/read_obs_netcdf.m
===================================================================
--- DART/trunk/diagnostics/matlab/read_obs_netcdf.m 2010-02-03 18:02:11 UTC (rev 4250)
+++ DART/trunk/diagnostics/matlab/read_obs_netcdf.m 2010-02-03 20:50:30 UTC (rev 4251)
@@ -1,5 +1,5 @@
function obsstruct = read_obs_netcdf(fname, ObsTypeString, region, CopyString, ...
- QCString, maxQC, verbose)
+ QCString, verbose)
%% read_obs_netcdf reads in the netcdf flavor observation sequence file
% and returns a subsetted structure.
%
@@ -8,10 +8,9 @@
% region = [0 360 -90 90 -Inf Inf];
% CopyString = 'NCEP BUFR observation';
% QCString = 'DART quality control';
-% maxQC = 2;
@@ Diff output truncated at 40000 characters. @@
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