Index: sm/trunk/src/m/classes/public/qmu/qmu_correlation.m
===================================================================
--- /issm/trunk/src/m/classes/public/qmu/qmu_correlation.m	(revision 4785)
+++ 	(revision )
@@ -1,50 +1,0 @@
-function factors=qmu_correlation(md,variablename,responsename)
-%QMU_CORRELATION - compute correlation between qmu output and a certain input variable.
-%
-%   Usage:
-%      factors=qmu_correlation(md,variablename,responsename)
-%
-%
-%   Example: mass_flux_drag_correlation=qmu_correlation(md,'drag','mass_flux');
-%
-
-if ~isfield(md.dakotaresults,'dresp_dat'),
-	error('qmu_correlation error message: could not find dresp_dat field in dakota results. you need to run montecarlo before computing correlations');
-end
-	
-data=md.dakotaresults.dresp_dat;
-
-%go through all the rows and figure which one we are interested in.
-found=0;
-for i=1:numel(data),
-	if strcmpi(data(i).descriptor,responsename),
-		found=i;
-		break;
-	end
-end
-if found==0,
-	error(['qmu_correlation error message: could not find data descriptor for response ' responsename]);
-end
-
-%get the response samples.
-response_samples=data(found).sample;
-
-%now go through variables, and compute correlation coefficient each time: 
-variablenamelength=length(variablename);
-index=[];
-for i=1:numel(data),
-	if strncmpi(variablename,data(i).descriptor,variablenamelength),
-		%this observation is one we are looking for.
-		index=[index;i];
-	end
-end
-
-if isempty(index),
-	error(['qmu_correlation error message: could not find correlation descriptor for variable ' variablename]);
-end
-
-factors=zeros(numel(index),1);
-for i=1:numel(index),
-	matrix=corrcoef(data(index(i)).sample,response_samples);
-	factors(i)=matrix(2,1);
-end
Index: /issm/trunk/src/m/qmu/qmu_correlation.m
===================================================================
--- /issm/trunk/src/m/qmu/qmu_correlation.m	(revision 4786)
+++ /issm/trunk/src/m/qmu/qmu_correlation.m	(revision 4786)
@@ -0,0 +1,50 @@
+function factors=qmu_correlation(md,variablename,responsename)
+%QMU_CORRELATION - compute correlation between qmu output and a certain input variable.
+%
+%   Usage:
+%      factors=qmu_correlation(md,variablename,responsename)
+%
+%
+%   Example: mass_flux_drag_correlation=qmu_correlation(md,'drag','mass_flux');
+%
+
+if ~isfield(md.dakotaresults,'dresp_dat'),
+	error('qmu_correlation error message: could not find dresp_dat field in dakota results. you need to run montecarlo before computing correlations');
+end
+	
+data=md.dakotaresults.dresp_dat;
+
+%go through all the rows and figure which one we are interested in.
+found=0;
+for i=1:numel(data),
+	if strcmpi(data(i).descriptor,responsename),
+		found=i;
+		break;
+	end
+end
+if found==0,
+	error(['qmu_correlation error message: could not find data descriptor for response ' responsename]);
+end
+
+%get the response samples.
+response_samples=data(found).sample;
+
+%now go through variables, and compute correlation coefficient each time: 
+variablenamelength=length(variablename);
+index=[];
+for i=1:numel(data),
+	if strncmpi(variablename,data(i).descriptor,variablenamelength),
+		%this observation is one we are looking for.
+		index=[index;i];
+	end
+end
+
+if isempty(index),
+	error(['qmu_correlation error message: could not find correlation descriptor for variable ' variablename]);
+end
+
+factors=zeros(numel(index),1);
+for i=1:numel(index),
+	matrix=corrcoef(data(index(i)).sample,response_samples);
+	factors(i)=matrix(2,1);
+end