Differences

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--- code:fit [2011/05/14 15:22] – neater code laurenceb
+++ code:fit [2011/05/14 15:24] (current) – neater code laurenceb
@@ Line 3: / Line 3: @@
 bias_gain needs to be initialized to a reasonably sensible value for this to be well behaved.
 <code matlab>
-function bias_gain=nr_fit(data,initial)			#data is in x,y,z format with samples along columns
+function bias_gain=nr_fit(data,initial)			%data is in x,y,z format with samples along columns
 	datalenght=size(data)(2)
-	#bias_gain=[0.0015;0.0015;0.0015;0;0;0]; - e.g. for lsm303dlh magno (this has to be close to ~order of magnitude)
+	%bias_gain=[0.0015;0.0015;0.0015;0;0;0]; - e.g. for lsm303dlh magno (this has to be close to ~order of magnitude)
 	bias_gain=initial;
 	convergence=0.5;iterations=0;
 	while(convergence<0.99 || convergence>1)
 		measured=[bias_gain(1),0,0;0,bias_gain(2),0;0,0,bias_gain(3)]*(data(1:3,:)-repmat(bias_gain(4:6),1,datalenght));
-		errors=1.-sum(measured.*measured);		#try to normalise the vectors
+		errors=1.-sum(measured.*measured);		%try to normalise the vectors
 		corrections=[2*bias_gain(1)*(data(1,:)-bias_gain(4)).^2;2*bias_gain(2)*(data(2,:)-bias_gain(5)).^2;...
 *bias_gain(3)*(data(3,:)-bias_gain(6)).^2;-2*(bias_gain(1)^2)*(data(1,:)-bias_gain(4));...
 		-2*(bias_gain(2)^2)*(data(2,:)-bias_gain(5));-2*(bias_gain(3)^2)*(data(3,:)-bias_gain(6))];
-		bias_gain+=pinv(corrections')*errors'./2;	#not the factor of 1/2 - this increases stability
+		bias_gain+=pinv(corrections')*errors'./2;	%note the factor of 1/2 - this increases stability
 		err_mean=sqrt(mean(abs(errors))+1)-1;
 		if(iterations==1)
-			convergence=(err_mean/old_err_mean);	#we iterate until we stop converging
+			convergence=(err_mean/old_err_mean);	%we iterate until we stop converging
 		elseif(iterations>1)
 			convergence=0.66*convergence+0.34*(err_mean/old_err_mean);