Reduction started at: 20050120-105456 Reading data from rxh3-20050119-221027.fits Reduction ID: default Read keywords into global array holo_keys Read binary table data into global array holo_data Finished reading data Converted positions to arcsec, times to elapsed seconds, and reversed x-axis Pattern extent: min = 2402.7 max = 2431.2 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.500 mm ----------------- Data Summary --------------------- Number of samples: 370025 This is a 80 GHz map Number of frequencies: 16 Frequencies (GHz): 80.338000 80.340000 80.342000 80.344000 80.346000 80.348000 80.350000 80.352000 80.354000 80.356000 80.358000 80.360000 80.362000 80.364000 80.366000 80.368000 item min max mean loreal -3.26904 3.25439 -0.03071 loimag -3.35693 3.33008 0.01305 hireal -5.00000 4.99756 -0.54134 hiimag -5.00000 4.99756 -0.17071 xpos -2431.18323 2411.94273 -12.92628 ypos -2402.91200 2402.70268 -0.00526 plock160 0.95703 2.36084 1.71901 lorefpwr 0.21484 1.67725 1.22268 losigpwr -4.59961 -0.03418 -4.41974 hirefpwr 0.29297 1.71387 1.28050 hisigpwr -4.50928 4.99756 -0.71162 encltemp 31.68945 32.91016 32.19357 flags 0.00000 256.00000 2.76738 phi-lock -1.22559 0.14404 -0.56877 sindex 0.00000 128.00000 63.61104 time 0.00000 2947.99697 1473.10141 zeropt -0.00732 -0.00244 -0.00490 !!!Warning!!! philock max less than 0.2 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 129 rows There are 121 data rows and 8 calibrator rows Calibrator rows: 0 21 42 63 84 105 126 128 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 40.00618 arcsec Mean row spacing = 40.00622 arcsec (alternate estimator) Mean tracking incline = 0.08882 arcsec Mean pointing range = 0.61203 arcsec Mean pointing rms = 0.10310 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (0, 0 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Doing geometric phase correction Status bits counts: bit: 0 1 2 3 4 5 6 7 8 set: 0 0 0 0 0 0 0 0 4000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22681 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22681 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 40.0 arcseconds Using a grid of 128 points Grid has even number of points Maximum data offset = 2431.18 arcsec Grid extent = 2540 arcsec lambda_min = 0.00373025 scale = 0.00129968 Diffraction scale lambda/D = 51.3137 arcsec Gridding function extent = 307.882 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 153.941 arcsec Airy first null at 62.5858 arcsec Gridding frequency index 0 lambda = 0.00373164 metres, scale = 0.0012992 radians per metre Gridding real part of frequency 0... Gridding imag part of frequency 0... Pattern is holo(res.pattern0) Weights in holo(obs.real,wt0) and holo(obs.imag,wt0) Maximum amplitude = 3.18337 at (0.0, -40.01493689163285) arcsec Real: mean = 0.000633593 sum of squares = 1069.93 Imag: mean = -0.00155684 sum of squares = 935.003 Gridding frequency index 1 lambda = 0.00373155 metres, scale = 0.00129923 radians per metre Gridding real part of frequency 1... Gridding imag part of frequency 1... Pattern is holo(res.pattern1) Weights in holo(obs.real,wt1) and holo(obs.imag,wt1) Maximum amplitude = 3.19286 at (0.0, -40.013940751804832) arcsec Real: mean = 0.00052944 sum of squares = 986.438 Imag: mean = -0.00207918 sum of squares = 1017.19 Gridding frequency index 2 lambda = 0.00373145 metres, scale = 0.00129926 radians per metre Gridding real part of frequency 2... Gridding imag part of frequency 2... Pattern is holo(res.pattern2) Weights in holo(obs.real,wt2) and holo(obs.imag,wt2) Maximum amplitude = 3.18953 at (0.0, -40.01294466157178) arcsec Real: mean = 0.000717594 sum of squares = 914.176 Imag: mean = -0.00258969 sum of squares = 1089.11 Gridding frequency index 3 lambda = 0.00373136 metres, scale = 0.00129929 radians per metre Gridding real part of frequency 3... Gridding imag part of frequency 3... Pattern is holo(res.pattern3) Weights in holo(obs.real,wt3) and holo(obs.imag,wt3) Maximum amplitude = 3.19152 at (0.0, -40.011948620929999) arcsec Real: mean = 0.0011388 sum of squares = 901.468 Imag: mean = -0.0029664 sum of squares = 1101.06 Gridding frequency index 4 lambda = 0.00373127 metres, scale = 0.00129933 radians per metre Gridding real part of frequency 4... Gridding imag part of frequency 4... Pattern is holo(res.pattern4) Weights in holo(obs.real,wt4) and holo(obs.imag,wt4) Maximum amplitude = 3.19843 at (0.0, -40.010952629875788) arcsec Real: mean = 0.0016878 sum of squares = 959.998 Imag: mean = -0.00307338 sum of squares = 1043.23 Gridding frequency index 5 lambda = 0.00373118 metres, scale = 0.00129936 radians per metre Gridding real part of frequency 5... Gridding imag part of frequency 5... Pattern is holo(res.pattern5) Weights in holo(obs.real,wt5) and holo(obs.imag,wt5) Maximum amplitude = 3.22085 at (0.0, -40.009956688405431) arcsec Real: mean = 0.00220591 sum of squares = 1051.52 Imag: mean = -0.00291274 sum of squares = 954.718 Gridding frequency index 6 lambda = 0.00373108 metres, scale = 0.00129939 radians per metre Gridding real part of frequency 6... Gridding imag part of frequency 6... Pattern is holo(res.pattern6) Weights in holo(obs.real,wt6) and holo(obs.imag,wt6) Maximum amplitude = 3.24668 at (0.0, 0.0) arcsec Real: mean = 0.00262021 sum of squares = 1110.52 Imag: mean = -0.00261807 sum of squares = 900.861 Gridding frequency index 7 lambda = 0.00373099 metres, scale = 0.00129942 radians per metre Gridding real part of frequency 7... Gridding imag part of frequency 7... Pattern is holo(res.pattern7) Weights in holo(obs.real,wt7) and holo(obs.imag,wt7) Maximum amplitude = 3.25926 at (0.0, -40.007964954201512) arcsec Real: mean = 0.00291486 sum of squares = 1092.42 Imag: mean = -0.00221747 sum of squares = 924.136 Gridding frequency index 8 lambda = 0.0037309 metres, scale = 0.00129946 radians per metre Gridding real part of frequency 8... Gridding imag part of frequency 8... Pattern is holo(res.pattern8) Weights in holo(obs.real,wt8) and holo(obs.imag,wt8) Maximum amplitude = 3.26571 at (0.0, -40.006969161460532) arcsec Real: mean = 0.00303528 sum of squares = 1010.44 Imag: mean = -0.00170025 sum of squares = 1012.33 Gridding frequency index 9 lambda = 0.0037308 metres, scale = 0.00129949 radians per metre Gridding real part of frequency 9... Gridding imag part of frequency 9... Pattern is holo(res.pattern9) Weights in holo(obs.real,wt9) and holo(obs.imag,wt9) Maximum amplitude = 3.26647 at (0.0, -40.005973418288612) arcsec Real: mean = 0.00280846 sum of squares = 930.064 Imag: mean = -0.00112066 sum of squares = 1097.96 Gridding frequency index 10 lambda = 0.00373071 metres, scale = 0.00129952 radians per metre Gridding real part of frequency 10... Gridding imag part of frequency 10... Pattern is holo(res.pattern10) Weights in holo(obs.real,wt10) and holo(obs.imag,wt10) Maximum amplitude = 3.25841 at (0.0, -40.004977724682043) arcsec Real: mean = 0.00226932 sum of squares = 912.786 Imag: mean = -0.000780122 sum of squares = 1118.1 Gridding frequency index 11 lambda = 0.00373062 metres, scale = 0.00129955 radians per metre Gridding real part of frequency 11... Gridding imag part of frequency 11... Pattern is holo(res.pattern11) Weights in holo(obs.real,wt11) and holo(obs.imag,wt11) Maximum amplitude = 3.24306 at (0.0, -40.00398208063713) arcsec Real: mean = 0.00178155 sum of squares = 970.791 Imag: mean = -0.000829538 sum of squares = 1061.37 Gridding frequency index 12 lambda = 0.00373053 metres, scale = 0.00129959 radians per metre Gridding real part of frequency 12... Gridding imag part of frequency 12... Pattern is holo(res.pattern12) Weights in holo(obs.real,wt12) and holo(obs.imag,wt12) Maximum amplitude = 3.23473 at (0.0, -40.002986486150171) arcsec Real: mean = 0.0015002 sum of squares = 1060.6 Imag: mean = -0.00101289 sum of squares = 972.513 Gridding frequency index 13 lambda = 0.00373043 metres, scale = 0.00129962 radians per metre Gridding real part of frequency 13... Gridding imag part of frequency 13... Pattern is holo(res.pattern13) Weights in holo(obs.real,wt13) and holo(obs.imag,wt13) Maximum amplitude = 3.22873 at (0.0, -40.001990941217464) arcsec Real: mean = 0.00129924 sum of squares = 1118.48 Imag: mean = -0.0012074 sum of squares = 917.395 Gridding frequency index 14 lambda = 0.00373034 metres, scale = 0.00129965 radians per metre Gridding real part of frequency 14... Gridding imag part of frequency 14... Pattern is holo(res.pattern14) Weights in holo(obs.real,wt14) and holo(obs.imag,wt14) Maximum amplitude = 3.23047 at (0.0, -40.000995445835301) arcsec Real: mean = 0.00101009 sum of squares = 1107.49 Imag: mean = -0.00140391 sum of squares = 932.288 Gridding frequency index 15 lambda = 0.00373025 metres, scale = 0.00129968 radians per metre Gridding real part of frequency 15... Gridding imag part of frequency 15... Pattern is holo(res.pattern15) Weights in holo(obs.real,wt15) and holo(obs.imag,wt15) Maximum amplitude = 3.22607 at (0.0, -40.0) arcsec Real: mean = 0.000804064 sum of squares = 1037.88 Imag: mean = -0.00191205 sum of squares = 1005.81 Masking frequency index 0 Mask scale size = 3.05915 Masking frequency index 1 Mask scale size = 3.05923 Masking frequency index 2 Mask scale size = 3.05931 Masking frequency index 3 Mask scale size = 3.05938 Masking frequency index 4 Mask scale size = 3.05946 Masking frequency index 5 Mask scale size = 3.05953 Masking frequency index 6 Mask scale size = 3.05961 Masking frequency index 7 Mask scale size = 3.05969 Masking frequency index 8 Mask scale size = 3.05976 Masking frequency index 9 Mask scale size = 3.05984 Masking frequency index 10 Mask scale size = 3.05992 Masking frequency index 11 Mask scale size = 3.05999 Masking frequency index 12 Mask scale size = 3.06007 Masking frequency index 13 Mask scale size = 3.06014 Masking frequency index 14 Mask scale size = 3.06022 Masking frequency index 15 Mask scale size = 3.0603 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.175781 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.178223 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.0170898 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 0.16593 107.62 Freq 1: Shift, scale = -0.26759 106.41 Freq 2: Shift, scale = -0.7059 105.05 Freq 3: Shift, scale = -1.1437 103.25 Freq 4: Shift, scale = -1.5823 102.05 Freq 5: Shift, scale = -2.0211 101.01 Freq 6: Shift, scale = -2.4623 101.23 Freq 7: Shift, scale = -2.9093 102.12 Freq 8: Shift, scale = 2.925 103.65 Freq 9: Shift, scale = 2.4781 105.3 Freq 10: Shift, scale = 2.0362 106.84 Freq 11: Shift, scale = 1.6001 107.92 Freq 12: Shift, scale = 1.1686 108.89 Freq 13: Shift, scale = 0.73735 108.97 Freq 14: Shift, scale = 0.3066 108.55 Freq 15: Shift, scale = -0.12276 107.48 Calculating phase corrections for index 0 Calculating phase corrections for index 1 Calculating phase corrections for index 2 Calculating phase corrections for index 3 Calculating phase corrections for index 4 Calculating phase corrections for index 5 Calculating phase corrections for index 6 Calculating phase corrections for index 7 Calculating phase corrections for index 8 Calculating phase corrections for index 9 Calculating phase corrections for index 10 Calculating phase corrections for index 11 Calculating phase corrections for index 12 Calculating phase corrections for index 13 Calculating phase corrections for index 14 Calculating phase corrections for index 15 Apply near field corrections for frequency 0 Apply secondary diffraction correction for frequency 0 Apply near field corrections for frequency 1 Apply secondary diffraction correction for frequency 1 Apply near field corrections for frequency 2 Apply secondary diffraction correction for frequency 2 Apply near field corrections for frequency 3 Apply secondary diffraction correction for frequency 3 Apply near field corrections for frequency 4 Apply secondary diffraction correction for frequency 4 Apply near field corrections for frequency 5 Apply secondary diffraction correction for frequency 5 Apply near field corrections for frequency 6 Apply secondary diffraction correction for frequency 6 Apply near field corrections for frequency 7 Apply secondary diffraction correction for frequency 7 Apply near field corrections for frequency 8 Apply secondary diffraction correction for frequency 8 Apply near field corrections for frequency 9 Apply secondary diffraction correction for frequency 9 Apply near field corrections for frequency 10 Apply secondary diffraction correction for frequency 10 Apply near field corrections for frequency 11 Apply secondary diffraction correction for frequency 11 Apply near field corrections for frequency 12 Apply secondary diffraction correction for frequency 12 Apply near field corrections for frequency 13 Apply secondary diffraction correction for frequency 13 Apply near field corrections for frequency 14 Apply secondary diffraction correction for frequency 14 Apply near field corrections for frequency 15 Apply secondary diffraction correction for frequency 15 Fitting piston, pointing and defocus terms Fitting frequency 0 Minimiser fit code = 3 piston: -0.313 radians x offset: 0.37 arcsec y offset: 13.5 arcsec defocus: 0.248 mm Estimated x pointing error is 0.3705 arcsec (used 0 arcsec) Estimated y pointing error is 13.49 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.748 mm (used 2.5 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.31 radians x offset: 0.379 arcsec y offset: 13.5 arcsec defocus: 0.245 mm Estimated x pointing error is 0.3793 arcsec (used 0 arcsec) Estimated y pointing error is 13.51 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.745 mm (used 2.5 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.299 radians x offset: 0.112 arcsec y offset: 13.5 arcsec defocus: 0.253 mm Estimated x pointing error is 0.1121 arcsec (used 0 arcsec) Estimated y pointing error is 13.49 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.753 mm (used 2.5 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.301 radians x offset: 0.126 arcsec y offset: 13.5 arcsec defocus: 0.252 mm Estimated x pointing error is 0.1257 arcsec (used 0 arcsec) Estimated y pointing error is 13.49 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.752 mm (used 2.5 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.302 radians x offset: 0.132 arcsec y offset: 13.5 arcsec defocus: 0.252 mm Estimated x pointing error is 0.1325 arcsec (used 0 arcsec) Estimated y pointing error is 13.49 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.752 mm (used 2.5 mm) Fitting frequency 5 Minimiser fit code = 3 piston: -0.306 radians x offset: 0.129 arcsec y offset: 13.5 arcsec defocus: 0.249 mm Estimated x pointing error is 0.1291 arcsec (used 0 arcsec) Estimated y pointing error is 13.49 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.749 mm (used 2.5 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.311 radians x offset: 0.123 arcsec y offset: 13.5 arcsec defocus: 0.249 mm Estimated x pointing error is 0.1226 arcsec (used 0 arcsec) Estimated y pointing error is 13.5 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.749 mm (used 2.5 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.32 radians x offset: 0.146 arcsec y offset: 13.5 arcsec defocus: 0.25 mm Estimated x pointing error is 0.1459 arcsec (used 0 arcsec) Estimated y pointing error is 13.5 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.75 mm (used 2.5 mm) Fitting frequency 8 Minimiser fit code = 3 piston: -0.331 radians x offset: 0.189 arcsec y offset: 13.5 arcsec defocus: 0.252 mm Estimated x pointing error is 0.1889 arcsec (used 0 arcsec) Estimated y pointing error is 13.51 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.752 mm (used 2.5 mm) Fitting frequency 9 Minimiser fit code = 3 piston: -0.341 radians x offset: 0.253 arcsec y offset: 13.5 arcsec defocus: 0.251 mm Estimated x pointing error is 0.2527 arcsec (used 0 arcsec) Estimated y pointing error is 13.48 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.751 mm (used 2.5 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.346 radians x offset: 0.32 arcsec y offset: 13.4 arcsec defocus: 0.25 mm Estimated x pointing error is 0.3204 arcsec (used 0 arcsec) Estimated y pointing error is 13.45 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.75 mm (used 2.5 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.345 radians x offset: 0.37 arcsec y offset: 13.4 arcsec defocus: 0.247 mm Estimated x pointing error is 0.3698 arcsec (used 0 arcsec) Estimated y pointing error is 13.43 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.747 mm (used 2.5 mm) Fitting frequency 12 Minimiser fit code = 3 piston: -0.34 radians x offset: 0.401 arcsec y offset: 13.4 arcsec defocus: 0.244 mm Estimated x pointing error is 0.4006 arcsec (used 0 arcsec) Estimated y pointing error is 13.42 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.744 mm (used 2.5 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.334 radians x offset: 0.421 arcsec y offset: 13.4 arcsec defocus: 0.24 mm Estimated x pointing error is 0.4211 arcsec (used 0 arcsec) Estimated y pointing error is 13.41 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.74 mm (used 2.5 mm) Fitting frequency 14 Minimiser fit code = 3 piston: -0.329 radians x offset: 0.441 arcsec y offset: 13.4 arcsec defocus: 0.237 mm Estimated x pointing error is 0.4414 arcsec (used 0 arcsec) Estimated y pointing error is 13.42 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.737 mm (used 2.5 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.32 radians x offset: 0.458 arcsec y offset: 13.4 arcsec defocus: 0.236 mm Estimated x pointing error is 0.4577 arcsec (used 0 arcsec) Estimated y pointing error is 13.42 arcsec (used 0 arcsec) !!!Warning!!! Pointing error in elevation > 5.0 arcsec Estimated defocus error is 2.736 mm (used 2.5 mm) Making masked surfaces in microns, and cubes Fitting Zernikes Fitting many Zernikes for frequency 0 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00016 piston 1 1 -0.00164 tilt_x 1 -1 0.01922 tilt_y 2 2 0.04355 astigmatism_0 2 0 0.00376 curvature 2 -2 0.06779 astigmatism45 3 3 -0.02113 trefoil_0 3 1 -0.02574 coma_x 3 -1 0.03736 coma_y 3 -3 -0.08017 trefoil_30 Fitting many Zernikes for frequency 1 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00006 piston 1 1 -0.00094 tilt_x 1 -1 0.01910 tilt_y 2 2 0.04144 astigmatism_0 2 0 0.00423 curvature 2 -2 0.06744 astigmatism45 3 3 -0.02227 trefoil_0 3 1 -0.02266 coma_x 3 -1 0.03728 coma_y 3 -3 -0.07961 trefoil_30 Fitting many Zernikes for frequency 2 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00060 piston 1 1 -0.00831 tilt_x 1 -1 0.02085 tilt_y 2 2 0.05549 astigmatism_0 2 0 0.00148 curvature 2 -2 0.06612 astigmatism45 3 3 -0.00934 trefoil_0 3 1 -0.04815 coma_x 3 -1 0.04180 coma_y 3 -3 -0.08003 trefoil_30 Fitting many Zernikes for frequency 3 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00056 piston 1 1 -0.00687 tilt_x 1 -1 0.02150 tilt_y 2 2 0.05386 astigmatism_0 2 0 0.00198 curvature 2 -2 0.06603 astigmatism45 3 3 -0.01064 trefoil_0 3 1 -0.04282 coma_x 3 -1 0.04371 coma_y 3 -3 -0.07863 trefoil_30 Fitting many Zernikes for frequency 4 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00059 piston 1 1 -0.00579 tilt_x 1 -1 0.02225 tilt_y 2 2 0.05347 astigmatism_0 2 0 0.00214 curvature 2 -2 0.06670 astigmatism45 3 3 -0.01220 trefoil_0 3 1 -0.03917 coma_x 3 -1 0.04554 coma_y 3 -3 -0.07769 trefoil_30 Fitting many Zernikes for frequency 5 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00065 piston 1 1 -0.00449 tilt_x 1 -1 0.02249 tilt_y 2 2 0.05411 astigmatism_0 2 0 0.00210 curvature 2 -2 0.06752 astigmatism45 3 3 -0.01424 trefoil_0 3 1 -0.03538 coma_x 3 -1 0.04597 coma_y 3 -3 -0.07811 trefoil_30 Fitting many Zernikes for frequency 6 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00066 piston 1 1 -0.00389 tilt_x 1 -1 0.02269 tilt_y 2 2 0.05514 astigmatism_0 2 0 0.00200 curvature 2 -2 0.06847 astigmatism45 3 3 -0.01583 trefoil_0 3 1 -0.03408 coma_x 3 -1 0.04626 coma_y 3 -3 -0.07886 trefoil_30 Fitting many Zernikes for frequency 7 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00060 piston 1 1 -0.00336 tilt_x 1 -1 0.02213 tilt_y 2 2 0.05447 astigmatism_0 2 0 0.00202 curvature 2 -2 0.06867 astigmatism45 3 3 -0.01781 trefoil_0 3 1 -0.03275 coma_x 3 -1 0.04478 coma_y 3 -3 -0.07828 trefoil_30 Fitting many Zernikes for frequency 8 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00051 piston 1 1 -0.00265 tilt_x 1 -1 0.02073 tilt_y 2 2 0.05363 astigmatism_0 2 0 0.00224 curvature 2 -2 0.06804 astigmatism45 3 3 -0.01916 trefoil_0 3 1 -0.03101 coma_x 3 -1 0.04103 coma_y 3 -3 -0.07790 trefoil_30 Fitting many Zernikes for frequency 9 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00040 piston 1 1 -0.00221 tilt_x 1 -1 0.02004 tilt_y 2 2 0.05084 astigmatism_0 2 0 0.00253 curvature 2 -2 0.06672 astigmatism45 3 3 -0.02013 trefoil_0 3 1 -0.02940 coma_x 3 -1 0.03943 coma_y 3 -3 -0.07781 trefoil_30 Fitting many Zernikes for frequency 10 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00033 piston 1 1 -0.00150 tilt_x 1 -1 0.01959 tilt_y 2 2 0.04895 astigmatism_0 2 0 0.00289 curvature 2 -2 0.06608 astigmatism45 3 3 -0.02162 trefoil_0 3 1 -0.02702 coma_x 3 -1 0.03861 coma_y 3 -3 -0.07660 trefoil_30 Fitting many Zernikes for frequency 11 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00031 piston 1 1 -0.00120 tilt_x 1 -1 0.01994 tilt_y 2 2 0.04750 astigmatism_0 2 0 0.00310 curvature 2 -2 0.06631 astigmatism45 3 3 -0.02306 trefoil_0 3 1 -0.02582 coma_x 3 -1 0.03978 coma_y 3 -3 -0.07646 trefoil_30 Fitting many Zernikes for frequency 12 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00027 piston 1 1 -0.00111 tilt_x 1 -1 0.02005 tilt_y 2 2 0.04619 astigmatism_0 2 0 0.00338 curvature 2 -2 0.06698 astigmatism45 3 3 -0.02413 trefoil_0 3 1 -0.02504 coma_x 3 -1 0.04026 coma_y 3 -3 -0.07469 trefoil_30 Fitting many Zernikes for frequency 13 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00023 piston 1 1 -0.00113 tilt_x 1 -1 0.02037 tilt_y 2 2 0.04575 astigmatism_0 2 0 0.00360 curvature 2 -2 0.06618 astigmatism45 3 3 -0.02584 trefoil_0 3 1 -0.02467 coma_x 3 -1 0.04159 coma_y 3 -3 -0.07525 trefoil_30 Fitting many Zernikes for frequency 14 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00017 piston 1 1 -0.00072 tilt_x 1 -1 0.02083 tilt_y 2 2 0.04504 astigmatism_0 2 0 0.00401 curvature 2 -2 0.06591 astigmatism45 3 3 -0.02611 trefoil_0 3 1 -0.02297 coma_x 3 -1 0.04322 coma_y 3 -3 -0.07571 trefoil_30 Fitting many Zernikes for frequency 15 Using terms up to Zernike order 3 Fitting 10 Zernike terms: 0 1 2 3 4 5 6 7 8 9 Minimiser fit code = 1 n l coeff name 0 0 -0.00008 piston 1 1 -0.00006 tilt_x 1 -1 0.02100 tilt_y 2 2 0.04412 astigmatism_0 2 0 0.00446 curvature 2 -2 0.06541 astigmatism45 3 3 -0.02784 trefoil_0 3 1 -0.02044 coma_x 3 -1 0.04408 coma_y 3 -3 -0.07599 trefoil_30 Averaged 16 maps to make holo(res.mean_surface) Computing differences from mean surface (phase) Unweighted rms analysis, frequency 0 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 22.5 19.5 32.9 25.6 32.9 45.6 35.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 24 19.4 31.7 24 28.1 38.3 31.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.61 5.05 6.91 8.57 10.8 14.9 21.9 14.2 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 22.5 19.6 35.1 25.8 33.2 45.7 36 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.6 24 19.6 34.1 24.3 28.3 38.5 32.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.51 4.87 6.69 8.37 10.7 14.8 21.6 14 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 22 19.2 36.5 25.4 33.4 46.2 36.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27 23.6 19.8 35.2 24.3 28.6 39 33.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.66 6.95 9.07 10.4 11.8 15.5 23.2 15.3 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.1 21.8 19 33.6 25.3 33.7 46.6 36.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 23.5 19.4 32.3 24.3 28.9 39.4 33 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.51 6.68 8.76 10.1 11.5 15.2 22.8 15 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 21.6 18.6 31.4 25.3 33.7 47.1 36 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.3 23.4 18.8 30.3 24.2 29.1 39.8 32.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.45 6.56 8.63 9.98 11.5 15.2 22.7 15 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.6 21.6 19.2 30.2 25.5 34.2 47.8 36 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.6 23.5 19.2 29.1 24.3 29.5 40.3 32.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.33 6.36 8.41 9.84 11.5 15.4 22.8 15 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.2 21.8 20.2 29.3 25.9 34.2 48.6 36.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 30.2 23.7 20.1 28.3 24.6 29.6 40.8 32.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.3 6.31 8.38 9.86 11.7 15.6 23.1 15.2 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.7 22.2 21 28.8 26.1 34.3 48.8 36 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.6 23.9 20.9 27.7 24.8 29.7 41.1 32.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.19 6.11 8.15 9.68 11.6 15.5 22.9 15.1 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.7 22.5 21.1 29.2 25.9 34 48.7 35.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.5 24.1 21.1 28 24.6 29.3 41.1 32.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.96 5.69 7.67 9.28 11.4 15.4 22.6 14.8 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.9 22.5 21 29.4 25.5 33.7 48 35.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.6 24 21.1 27.9 24.3 29.1 40.5 31.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.83 5.45 7.37 8.97 11.1 15.1 22.2 14.5 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.7 22.4 19.8 27.9 25.2 33.2 47.3 34.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.4 24 19.9 26.2 24 28.6 39.7 31.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.71 5.23 7.11 8.72 10.9 14.9 21.8 14.2 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29 22.3 17.7 28.8 25 33.3 46.6 34.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.7 23.9 17.7 27.1 23.9 28.6 39 30.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.73 5.26 7.14 8.73 10.8 14.8 21.7 14.2 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.1 22.6 19 29.3 24.9 33.3 46.1 34.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.9 24.2 18.8 27.7 23.9 28.5 38.5 31 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.73 5.26 7.13 8.7 10.8 14.7 21.5 14.1 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 22.6 19.6 30.2 25 33.6 45.7 34.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.7 24.3 19.4 28.7 23.9 28.7 38.1 31.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.78 5.35 7.22 8.76 10.8 14.7 21.6 14.1 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.6 22.6 19.9 31.6 24.9 33.9 45.8 35.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.4 24.4 19.7 30.2 23.9 28.9 38.1 31.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.81 5.4 7.28 8.79 10.8 14.7 21.6 14.1 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 22.3 19.9 33.9 25.1 34 45.8 36 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 24.1 19.8 32.5 24 28.9 38.3 32.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.79 5.36 7.23 8.74 10.7 14.6 21.6 14.1 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 24.7 20.8 16.8 22.2 23.4 31.9 45.8 33.2 Mean deviation is 1.3339360421825679 microns Taper = 10 dB, Ruze illumination-weighted rms = 31.7 micron Estimating beam: f = 650GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 650 GHz Ruze rms = 28.0 micron Centre pixel: 64.0 64.0 Value = 2771.19 (estimate), 3708.89 (perfect) Strehl = 0.55827 Strehl ratio estimate = 0.5583 Estimating beam: f = 900GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 900 GHz Ruze rms = 27.2 micron Centre pixel: 64.0 64.0 Value = 2192.47 (estimate), 3708.89 (perfect) Strehl = 0.349446 Strehl ratio estimate = 0.3494 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.15028 metres panel scale = 3.00000 metres mean frequency = 80.35300 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 14.7 7.6 6.0 17.6 2 1 2 20.3 12.0 31.8 39.6 3 1 3 42.3 30.7 0.9 52.3 4 1 4 58.9 14.6 12.9 62.0 5 1 5 51.1 35.5 70.9 94.4 6 1 6 52.8 50.2 52.0 89.5 7 1 7 37.4 54.8 56.6 87.2 8 1 8 32.3 50.7 62.6 86.7 9 1 9 -25.3 26.0 22.6 42.7 10 1 10 25.7 27.4 30.1 48.1 11 1 11 49.1 28.1 25.2 61.9 12 1 12 34.7 8.6 9.4 37.0 13 2 1 15.6 -30.9 -28.1 44.6 14 2 2 10.3 -2.8 -10.0 14.6 15 2 3 31.2 -20.5 -20.6 42.6 16 2 4 25.9 -14.4 -5.4 30.1 17 2 5 36.9 -1.2 20.7 42.4 18 2 6 28.8 34.9 38.1 59.2 19 2 7 16.3 9.0 15.4 24.2 20 2 8 41.5 14.0 -6.0 44.2 21 2 9 44.2 -0.6 14.8 46.6 22 2 10 44.0 13.3 23.3 51.5 23 2 11 46.8 10.4 4.9 48.2 24 2 12 43.1 3.4 0.4 43.3 25 2 13 50.5 0.2 -7.7 51.1 26 2 14 41.7 -7.5 4.8 42.6 27 2 15 57.1 3.6 -0.6 57.2 28 2 16 47.7 17.4 6.2 51.2 29 2 17 24.7 5.0 -8.6 26.6 30 2 18 25.1 -3.5 -5.3 25.9 31 2 19 17.6 -16.3 -13.9 27.7 32 2 20 26.4 -19.0 -12.2 34.7 33 2 21 27.8 -7.4 -16.2 33.0 34 2 22 20.0 -18.1 -23.7 35.9 35 2 23 35.5 -11.9 -6.6 38.0 36 2 24 10.4 -18.3 -23.0 31.1 37 3 1 -14.8 -5.4 -3.6 16.1 38 3 2 -12.1 -4.8 -0.7 13.1 39 3 3 -22.9 -6.5 -5.0 24.3 40 3 4 -13.4 -8.4 15.7 22.3 41 3 5 -25.5 2.0 11.4 28.0 42 3 6 -20.7 -1.8 -0.7 20.8 43 3 7 -11.1 -3.2 -16.4 20.0 44 3 8 1.9 2.0 -4.0 4.9 45 3 9 27.2 0.8 0.5 27.2 46 3 10 6.1 13.2 6.6 15.9 47 3 11 25.3 14.5 3.3 29.4 48 3 12 13.7 34.4 4.3 37.3 49 3 13 -11.0 21.7 -9.7 26.2 50 3 14 3.0 -6.6 -5.9 9.3 51 3 15 -8.0 -5.8 3.8 10.6 52 3 16 7.5 7.0 4.8 11.4 53 3 17 24.8 14.5 1.7 28.8 54 3 18 27.4 7.3 -2.4 28.5 55 3 19 24.2 5.9 -35.5 43.4 56 3 20 1.8 -5.3 -19.0 19.8 57 3 21 4.5 -11.6 -10.2 16.1 58 3 22 -10.3 -7.4 -11.7 17.3 59 3 23 5.6 -8.2 -17.8 20.4 60 3 24 -17.4 -15.7 -33.9 41.2 61 3 25 -7.8 -18.7 -22.6 30.4 62 3 26 -12.2 -9.6 -14.4 21.2 63 3 27 -15.4 -6.6 -11.9 20.6 64 3 28 10.8 -14.3 -18.0 25.4 65 3 29 7.1 -11.6 -16.7 21.6 66 3 30 6.1 -17.6 -38.7 42.9 67 3 31 11.7 -2.4 -20.3 23.6 68 3 32 13.9 6.6 -14.7 21.2 69 3 33 14.9 6.0 7.4 17.7 70 3 34 9.0 -10.9 5.8 15.3 71 3 35 26.3 -6.4 -27.1 38.3 72 3 36 8.8 -7.8 -21.8 24.7 73 3 37 3.0 -10.0 -29.4 31.2 74 3 38 13.2 8.0 -14.8 21.4 75 3 39 6.6 4.6 -10.0 12.9 76 3 40 18.9 -0.3 -8.7 20.8 77 3 41 17.7 6.6 -6.6 20.0 78 3 42 0.4 8.5 -6.4 10.6 79 3 43 -4.1 8.2 -3.6 9.9 80 3 44 8.1 2.8 6.6 10.8 81 3 45 14.8 -4.9 -1.7 15.7 82 3 46 -7.5 0.1 -3.7 8.4 83 3 47 -8.1 -1.7 -3.4 8.9 84 3 48 -16.9 -5.0 -18.0 25.2 85 4 1 -24.1 -31.0 -11.6 41.0 86 4 2 2.9 -29.0 -54.5 61.8 87 4 3 -4.9 -23.8 -42.1 48.7 88 4 4 5.2 -9.1 -51.8 52.8 89 4 5 19.3 -2.5 -21.3 28.9 90 4 6 19.8 4.5 -9.5 22.4 91 4 7 21.2 3.7 8.1 23.0 92 4 8 -8.1 9.0 -0.2 12.1 93 4 9 5.2 2.2 -6.2 8.4 94 4 10 8.8 7.7 -12.6 17.2 95 4 11 -6.7 -0.5 -40.7 41.2 96 4 12 -44.7 -36.8 24.5 62.9 97 4 13 -5.2 -1.3 12.2 13.3 98 4 14 8.9 -10.2 -33.6 36.2 99 4 15 -8.2 -8.9 -1.2 12.2 100 4 16 -10.8 4.2 2.2 11.8 101 4 17 -12.5 3.9 -23.5 26.9 102 4 18 4.0 -19.4 -7.9 21.3 103 4 19 -15.8 -20.0 -36.7 44.7 104 4 20 -22.1 -17.5 -38.2 47.5 105 4 21 -21.3 -26.2 -28.9 44.4 106 4 22 -47.6 -19.8 -3.7 51.7 107 4 23 -38.2 -27.2 -37.3 59.9 108 4 24 -38.3 -24.9 -0.7 45.7 109 4 25 -47.1 -20.9 27.5 58.4 110 4 26 -29.1 -37.0 -41.6 62.8 111 4 27 -30.3 -27.9 -14.6 43.7 112 4 28 -27.6 -30.8 -22.0 46.8 113 4 29 -41.4 -18.1 -70.0 83.4 114 4 30 -39.0 -29.5 -20.5 53.0 115 4 31 -32.1 -30.2 -15.1 46.6 116 4 32 -35.6 -11.4 -28.1 46.7 117 4 33 -24.9 -4.6 -5.5 25.9 118 4 34 4.7 -9.2 -18.8 21.5 119 4 35 -21.3 -24.5 -51.6 61.0 120 4 36 -47.6 -18.6 -37.8 63.6 121 4 37 -6.1 -10.1 -11.4 16.4 122 4 38 -11.2 -2.3 -41.9 43.4 123 4 39 1.7 3.5 -3.7 5.4 124 4 40 -6.5 0.7 -4.3 7.9 125 4 41 -3.7 11.3 9.3 15.1 126 4 42 12.7 0.9 3.7 13.3 127 4 43 16.9 0.3 7.8 18.6 128 4 44 7.9 14.6 7.1 18.0 129 4 45 5.3 8.0 -1.5 9.8 130 4 46 6.0 -11.3 -18.9 22.8 131 4 47 -4.6 -12.3 -37.1 39.4 132 4 48 -8.7 -25.6 -9.4 28.6 133 5 1 -16.9 -2.8 -10.2 20.0 134 5 2 -25.9 -13.3 -8.5 30.4 135 5 3 -16.3 -16.0 -30.0 37.7 136 5 4 -9.6 -13.3 5.1 17.2 137 5 5 -17.2 -5.6 -25.1 30.9 138 5 6 5.6 1.8 -30.8 31.3 139 5 7 17.2 11.1 5.3 21.1 140 5 8 13.4 27.0 -9.3 31.5 141 5 9 6.5 20.8 12.6 25.2 142 5 10 -10.2 -8.9 -36.4 38.8 143 5 11 -4.7 -6.1 2.8 8.2 144 5 12 -12.7 14.0 10.5 21.7 145 5 13 -13.2 8.2 1.0 15.6 146 5 14 -12.5 4.8 0.4 13.4 147 5 15 -0.4 -13.4 -26.5 29.7 148 5 16 0.9 -4.8 3.3 5.9 149 5 17 -16.9 -4.6 3.5 17.9 150 5 18 -10.2 -23.8 177.1 179.0 151 5 19 -31.3 -20.5 -12.5 39.5 152 5 20 -24.6 1.2 -7.2 25.7 153 5 21 -10.5 0.8 0.1 10.6 154 5 22 -14.4 -16.1 -24.4 32.6 155 5 23 -24.5 -4.2 1.0 24.9 156 5 24 -3.9 -2.3 -5.6 7.2 157 5 25 -7.4 -5.2 -15.6 18.0 158 5 26 -17.0 -15.4 -10.5 25.2 159 5 27 -12.8 -27.5 -56.3 63.9 160 5 28 -3.4 -17.8 -36.4 40.6 161 5 29 -21.4 -13.4 -28.2 37.9 162 5 30 -24.2 -25.5 -20.5 40.7 163 5 31 -12.4 -21.9 -27.9 37.6 164 5 32 -26.0 -28.1 -13.4 40.6 165 5 33 14.2 -31.2 -9.2 35.5 166 5 34 -23.5 -45.6 -45.7 68.7 167 5 35 -16.9 -39.2 21.5 47.8 168 5 36 -12.2 -3.1 -6.3 14.1 169 5 37 3.8 -1.3 1.7 4.3 170 5 38 -1.7 -2.8 -5.8 6.6 171 5 39 -2.9 -5.8 -40.6 41.1 172 5 40 5.4 10.4 -11.1 16.2 173 5 41 17.5 16.2 24.7 34.4 174 5 42 4.1 10.3 2.7 11.4 175 5 43 15.1 14.5 -12.3 24.3 176 5 44 18.8 14.2 -17.1 29.1 177 5 45 18.7 9.5 -20.6 29.4 178 5 46 15.2 -18.6 -30.4 38.7 179 5 47 -8.1 -18.7 -18.1 27.3 180 5 48 -7.3 -3.7 -15.9 17.9 181 6 1 -13.5 -39.4 -60.9 73.8 182 6 2 -10.3 -36.1 -76.4 85.1 183 6 3 -23.4 -26.5 -60.6 70.1 184 6 4 -20.3 -6.1 -113.2 115.2 185 6 5 -7.8 -14.1 -23.3 28.4 186 6 6 -5.0 -8.1 -25.6 27.3 187 6 7 -1.1 -10.9 -18.6 21.6 188 6 8 -11.1 16.6 -26.4 33.1 189 6 9 3.1 12.2 -38.7 40.7 190 6 10 -36.0 25.0 -2.8 43.9 191 6 11 -1.8 12.1 -10.2 15.9 192 6 12 -0.7 18.1 -3.7 18.5 193 6 13 1.1 18.1 1.4 18.1 194 6 14 -8.9 3.8 2.4 10.0 195 6 15 -20.8 5.8 -2.6 21.7 196 6 16 -15.2 8.8 -49.7 52.7 197 6 17 -25.0 -6.5 -10.1 27.7 198 6 18 -27.2 2.6 13.3 30.4 199 6 19 -7.6 -4.8 34.4 35.5 200 6 20 -3.0 30.7 41.1 51.4 201 6 21 -31.1 21.0 -24.0 44.5 202 6 22 -32.4 27.0 34.6 54.5 203 6 23 2.4 25.5 55.4 61.1 204 6 24 -9.6 12.2 41.3 44.1 205 6 25 -18.1 11.4 -3.4 21.7 206 6 26 0.6 -4.9 4.1 6.4 207 6 27 -61.5 1.7 -14.2 63.1 208 6 28 -77.2 -25.7 -56.9 99.3 209 6 29 -73.9 -13.5 -16.0 76.8 210 6 30 -41.7 -32.4 22.3 57.3 211 6 31 -24.6 -29.3 -14.2 40.8 212 6 32 -44.4 -19.7 -18.0 51.8 213 6 33 -74.7 1.8 -95.5 121.3 214 6 34 -117.1 24.2 -12.8 120.3 215 6 35 -2.2 4.9 40.7 41.1 216 6 36 -10.5 44.0 62.6 77.2 217 6 37 0.1 29.5 55.1 62.5 218 6 38 15.5 17.1 34.1 41.2 219 6 39 -29.4 31.7 44.1 61.8 220 6 40 -38.7 42.6 -15.3 59.6 221 6 41 4.1 46.2 15.5 48.9 222 6 42 20.4 17.7 41.1 49.2 223 6 43 2.8 17.2 26.3 31.6 224 6 44 2.8 9.1 12.2 15.5 225 6 45 -25.1 19.7 -93.2 98.5 226 6 46 -69.0 -5.3 -30.7 75.7 227 6 47 -16.4 -25.5 -42.9 52.5 228 6 48 -20.3 -38.8 -47.5 64.6 229 7 1 -85.0 -26.5 -80.9 120.3 230 7 2 -68.1 -65.1 -105.6 141.6 231 7 3 -22.8 -63.1 -77.2 102.3 232 7 4 -21.1 -96.6 -12.3 99.7 233 7 5 0.5 -38.4 -13.8 40.8 234 7 6 -11.7 18.4 -20.9 30.2 235 7 7 -12.0 12.3 15.7 23.3 236 7 8 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69 2 10 1 24 10 2 6 10 3 25 10 4 -4 10 5 13 10 6 -11 10 7 14 10 8 23 10 9 21 10 10 13 10 11 9 10 12 -9 10 13 8 10 14 16 10 15 16 10 16 10 10 17 5 10 18 4 10 19 19 10 20 22 10 21 14 10 22 16 10 23 9 10 24 0 10 25 -3 10 26 3 10 27 1 10 28 -1 10 29 0 10 30 -2 10 31 -12 10 32 -1 10 33 0 10 34 -1 10 35 1 10 36 0 10 37 -1 10 38 0 10 39 0 10 40 -12 10 41 0 10 42 -3 10 43 0 10 44 0 10 45 1 10 46 -3 10 47 -3 10 48 -1 10 49 -3 10 50 1 10 51 2 10 52 -3 10 53 -5 10 54 8 10 55 -4 10 56 2 10 57 4 10 58 8 10 59 7 10 60 9 10 61 -9 10 62 -3 10 63 0 10 64 -2 10 65 5 10 66 -4 10 67 -2 10 68 0 10 69 5 11 1 5 11 2 5 11 3 11 11 4 3 11 5 2 11 6 0 11 7 -3 11 8 13 11 9 -7 11 10 8 11 11 5 11 12 0 11 13 15 11 14 10 11 15 17 11 16 12 11 17 5 11 18 6 11 19 19 11 20 17 11 21 24 11 22 4 11 23 14 11 24 1 11 25 -5 11 26 4 11 27 5 11 28 2 11 29 4 11 30 2 11 31 -3 11 32 4 11 33 4 11 34 2 11 35 0 11 36 5 11 37 0 11 38 3 11 39 1 11 40 1 11 41 0 11 42 3 11 43 7 11 44 4 11 45 5 11 46 2 11 47 3 11 48 -1 11 49 -1 11 50 2 11 51 -1 11 52 -7 11 53 -5 11 54 6 11 55 -1 11 56 2 11 57 0 11 58 8 11 59 15 11 60 7 11 61 -2 11 62 2 11 63 5 11 64 -3 11 65 8 11 66 -4 11 67 2 11 68 0 11 69 2 12 1 -3 12 2 36 12 3 -13 12 4 -14 12 5 -11 12 6 -6 12 7 -20 12 8 1 12 9 -5 12 10 -13 12 11 -7 12 12 -5 12 13 4 12 14 0 12 15 2 12 16 -9 12 17 -1 12 18 -21 12 19 6 12 20 -14 12 21 2 12 22 -28 12 23 6 12 24 -7 12 25 -4 12 26 -1 12 27 -2 12 28 -2 12 29 -7 12 30 -2 12 31 -5 12 32 -5 12 33 -2 12 34 -11 12 35 -3 12 36 -1 12 37 -9 12 38 -5 12 39 4 12 40 -5 12 41 -3 12 42 1 12 43 -6 12 44 2 12 45 5 12 46 0 12 47 2 12 48 1 12 49 -1 12 50 0 12 51 -2 12 52 -7 12 53 -5 12 54 3 12 55 -1 12 56 0 12 57 -2 12 58 2 12 59 10 12 60 2 12 61 0 12 62 -1 12 63 4 12 64 -9 12 65 10 12 66 -2 12 67 -5 12 68 -1 12 69 -5 Adjuster movements: rms = 32.6 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050120-110250 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1 !!!Warning!!! 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