aug_apr_load

0001 dapr = read_arcSouth('30-Apr-2013:03:16:52  ','     30-Apr-2013:03:36:44')
0002 daug = read_arcSouth('30-Aug-2013:00:50:03 ','     30-Aug-2013:01:22:15 ')
0003 
0004 LL_aug = [daug.antenna0.roach1.LL,daug.antenna0.roach2.LL];
0005 LL_apr = [dapr.antenna0.roach1.LL,dapr.antenna0.roach2.LL];
0006 
0007 LL_load_apr = [dapr.antenna0.roach1.load2,dapr.antenna0.roach2.load2];
0008 LL_load_aug = [daug.antenna0.roach1.load2,daug.antenna0.roach2.load2];
0009 
0010 for freq_chan = 1:128
0011     best_apr = (abs(LL_apr(:,freq_chan)-LL_load_apr(:,freq_chan))<3000); % just find data when difference between them is 3000 (ie. small - units are of order 1e4)
0012     balance_LL_apr(2,freq_chan) = nanmean(dapr.antenna0.thermal.ccTemperatureLoadFast(best_apr));
0013     balance_LL_apr(1,freq_chan)= freq_chan;
0014 end
0015 for freq_chan = 1:128
0016     best_aug = (abs(LL_aug(:,freq_chan)-LL_load_aug(:,freq_chan))<3000); % just find data when difference between them is 3000 (ie. small - units are of order 1e4)
0017     balance_LL_aug(2,freq_chan) = nanmean(daug.antenna0.thermal.ccTemperatureLoadFast(best_aug));
0018     balance_LL_aug(1,freq_chan)= freq_chan;
0019 end
0020 
0021 % Zero data where there was no balance (will be Nan in balance_LL)
0022 
0023 close all
0024 nans=isnan(balance_LL_apr(2,:));
0025 balance_LL_apr(2,nans)=40;
0026 plot(balance_LL_apr(1,:),balance_LL_apr(2,:),'r')
0027 hold all;
0028 nans=isnan(balance_LL_aug(2,:));
0029 balance_LL_aug(2,nans)=40;
0030 plot(balance_LL_aug(1,:),balance_LL_aug(2,:),'b')