Reduction started at: 20040809-143826 Reading data from rxh3-20040808-224129.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 = 2402.2 max = 2432.6 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.870 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 -3.01514 2.92236 -0.02580 loimag -3.17627 3.06885 0.00101 hireal -5.00000 4.99756 -0.31165 hiimag -5.00000 4.99756 -0.20395 xpos -2432.61352 2416.96798 -10.03238 ypos -2402.80673 2402.18132 -0.00404 plock160 0.73486 2.24854 1.55545 lorefpwr 0.30029 1.65283 1.24242 losigpwr -4.57031 -0.28809 -4.38280 hirefpwr 0.37598 1.70410 1.29395 hisigpwr -4.47754 4.99756 -0.77316 encltemp 31.56738 32.76367 32.08485 flags 0.00000 256.00000 2.76738 phi-lock -1.31836 0.08545 -0.63963 sindex 0.00000 128.00000 63.61104 time 0.00000 2948.99435 1473.94078 zeropt -0.00732 -0.00244 -0.00423 !!!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 = 40.00622 arcsec Mean row spacing = 40.00625 arcsec (alternate estimator) Mean tracking incline = 0.03536 arcsec Mean pointing range = 0.57510 arcsec Mean pointing rms = 0.10440 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (-4.7, 10.9 ) 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: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22680 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22680 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 = 2432.61 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 = 2.81673 at (0.0, -40.01493689163285) arcsec Real: mean = 0.00128122 sum of squares = 1063.31 Imag: mean = -0.0014898 sum of squares = 933.985 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 = 2.82197 at (0.0, 0.0) arcsec Real: mean = 0.000990112 sum of squares = 986.417 Imag: mean = -0.0018786 sum of squares = 1011.56 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 = 2.83164 at (0.0, 0.0) arcsec Real: mean = 0.00105121 sum of squares = 917.771 Imag: mean = -0.00252031 sum of squares = 1080.02 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 = 2.86423 at (0.0, 0.0) arcsec Real: mean = 0.0015456 sum of squares = 905.281 Imag: mean = -0.00310245 sum of squares = 1092.76 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 = 2.90627 at (0.0, 0.0) arcsec Real: mean = 0.00229039 sum of squares = 959.808 Imag: mean = -0.0032155 sum of squares = 1040.17 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 = 2.97055 at (0.0, 0.0) arcsec Real: mean = 0.00281715 sum of squares = 1047.64 Imag: mean = -0.00285059 sum of squares = 957.714 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 = 3.02396 at (0.0, 0.0) arcsec Real: mean = 0.00304091 sum of squares = 1106.65 Imag: mean = -0.00245079 sum of squares = 906.175 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 = 3.05423 at (0.0, 0.0) arcsec Real: mean = 0.00314656 sum of squares = 1090.37 Imag: mean = -0.00220528 sum of squares = 928.688 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 = 3.04714 at (0.0, 0.0) arcsec Real: mean = 0.00332062 sum of squares = 1013.35 Imag: mean = -0.00189807 sum of squares = 1011.75 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 = 3.02288 at (0.0, 0.0) arcsec Real: mean = 0.00335326 sum of squares = 936.683 Imag: mean = -0.00139608 sum of squares = 1091.31 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 = 2.98062 at (0.0, 0.0) arcsec Real: mean = 0.0029797 sum of squares = 919.528 Imag: mean = -0.000896129 sum of squares = 1111.98 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 = 2.94801 at (0.0, 0.0) arcsec Real: mean = 0.00246035 sum of squares = 972.292 Imag: mean = -0.000762808 sum of squares = 1061.91 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 = 2.90727 at (0.0, 0.0) arcsec Real: mean = 0.00203513 sum of squares = 1058.96 Imag: mean = -0.000888334 sum of squares = 979.738 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 = 2.89093 at (0.0, 0.0) arcsec Real: mean = 0.00173048 sum of squares = 1117.63 Imag: mean = -0.00107586 sum of squares = 926.51 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 = 2.87365 at (0.0, 0.0) arcsec Real: mean = 0.00140699 sum of squares = 1108.03 Imag: mean = -0.00134255 sum of squares = 940.823 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 = 2.89403 at (0.0, 0.0) arcsec Real: mean = 0.00123842 sum of squares = 1040.71 Imag: mean = -0.00186016 sum of squares = 1012.24 Masking frequency index 0 Mask scale size = 3.05849 Masking frequency index 1 Mask scale size = 3.05857 Masking frequency index 2 Mask scale size = 3.05864 Masking frequency index 3 Mask scale size = 3.05872 Masking frequency index 4 Mask scale size = 3.05879 Masking frequency index 5 Mask scale size = 3.05887 Masking frequency index 6 Mask scale size = 3.05895 Masking frequency index 7 Mask scale size = 3.05902 Masking frequency index 8 Mask scale size = 3.0591 Masking frequency index 9 Mask scale size = 3.05918 Masking frequency index 10 Mask scale size = 3.05925 Masking frequency index 11 Mask scale size = 3.05933 Masking frequency index 12 Mask scale size = 3.0594 Masking frequency index 13 Mask scale size = 3.05948 Masking frequency index 14 Mask scale size = 3.05956 Masking frequency index 15 Mask scale size = 3.05963 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.178223 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.175781 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.175781 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.17334 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.166016 Median point-to-point PLL voltage change: 0.0146484 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0146484 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 0.234 110.43 Freq 1: Shift, scale = -0.19967 109.21 Freq 2: Shift, scale = -0.63455 107.51 Freq 3: Shift, scale = -1.0684 105.56 Freq 4: Shift, scale = -1.5021 103.98 Freq 5: Shift, scale = -1.9406 103.05 Freq 6: Shift, scale = -2.3821 103.29 Freq 7: Shift, scale = -2.8298 104.28 Freq 8: Shift, scale = 3.003 105.68 Freq 9: Shift, scale = 2.5543 107.2 Freq 10: Shift, scale = 2.1099 108.59 Freq 11: Shift, scale = 1.6726 109.93 Freq 12: Shift, scale = 1.2407 110.71 Freq 13: Shift, scale = 0.812 111.3 Freq 14: Shift, scale = 0.38293 111.06 Freq 15: Shift, scale = -0.045207 110.16 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 = 1 piston: -0.134 radians x offset: -0.0426 arcsec y offset: 0.032 arcsec defocus: 0.00209 mm Estimated x pointing error is -4.743 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.93 arcsec (used 10.9 arcsec) Estimated defocus error is 2.872 mm (used 2.87 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.131 radians x offset: -0.0585 arcsec y offset: 0.0531 arcsec defocus: 0.00192 mm Estimated x pointing error is -4.758 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.95 arcsec (used 10.9 arcsec) Estimated defocus error is 2.872 mm (used 2.87 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.127 radians x offset: -0.0537 arcsec y offset: 0.0781 arcsec defocus: 0.00208 mm Estimated x pointing error is -4.754 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.98 arcsec (used 10.9 arcsec) Estimated defocus error is 2.872 mm (used 2.87 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.117 radians x offset: -0.214 arcsec y offset: 0.0863 arcsec defocus: 0.00617 mm Estimated x pointing error is -4.914 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.99 arcsec (used 10.9 arcsec) Estimated defocus error is 2.876 mm (used 2.87 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.115 radians x offset: -0.22 arcsec y offset: 0.0789 arcsec defocus: 0.00266 mm Estimated x pointing error is -4.92 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.98 arcsec (used 10.9 arcsec) Estimated defocus error is 2.873 mm (used 2.87 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.118 radians x offset: -0.239 arcsec y offset: 0.0802 arcsec defocus: 0.00107 mm Estimated x pointing error is -4.939 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.98 arcsec (used 10.9 arcsec) Estimated defocus error is 2.871 mm (used 2.87 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.121 radians x offset: -0.249 arcsec y offset: 0.0726 arcsec defocus: 0.00107 mm Estimated x pointing error is -4.949 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.97 arcsec (used 10.9 arcsec) Estimated defocus error is 2.871 mm (used 2.87 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.131 radians x offset: -0.245 arcsec y offset: 0.0524 arcsec defocus: 0.00202 mm Estimated x pointing error is -4.945 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.95 arcsec (used 10.9 arcsec) Estimated defocus error is 2.872 mm (used 2.87 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.142 radians x offset: -0.212 arcsec y offset: 0.0283 arcsec defocus: 0.00448 mm Estimated x pointing error is -4.912 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.93 arcsec (used 10.9 arcsec) Estimated defocus error is 2.874 mm (used 2.87 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.154 radians x offset: -0.154 arcsec y offset: 0.00725 arcsec defocus: 0.00316 mm Estimated x pointing error is -4.854 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.91 arcsec (used 10.9 arcsec) Estimated defocus error is 2.873 mm (used 2.87 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.161 radians x offset: -0.101 arcsec y offset: -0.0185 arcsec defocus: 0.00345 mm Estimated x pointing error is -4.801 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.88 arcsec (used 10.9 arcsec) Estimated defocus error is 2.873 mm (used 2.87 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.162 radians x offset: -0.0377 arcsec y offset: -0.0287 arcsec defocus: 0.00121 mm Estimated x pointing error is -4.738 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.87 arcsec (used 10.9 arcsec) Estimated defocus error is 2.871 mm (used 2.87 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.157 radians x offset: -0.00083 arcsec y offset: -0.021 arcsec defocus: -0.00145 mm Estimated x pointing error is -4.701 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.88 arcsec (used 10.9 arcsec) Estimated defocus error is 2.869 mm (used 2.87 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.149 radians x offset: 0.032 arcsec y offset: -0.0112 arcsec defocus: -0.0038 mm Estimated x pointing error is -4.668 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.89 arcsec (used 10.9 arcsec) Estimated defocus error is 2.866 mm (used 2.87 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.139 radians x offset: 0.0357 arcsec y offset: -0.00305 arcsec defocus: -0.00482 mm Estimated x pointing error is -4.664 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.9 arcsec (used 10.9 arcsec) Estimated defocus error is 2.865 mm (used 2.87 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.129 radians x offset: 0.0399 arcsec y offset: -0.00452 arcsec defocus: -0.00608 mm Estimated x pointing error is -4.66 arcsec (used -4.7 arcsec) Estimated y pointing error is 10.9 arcsec (used 10.9 arcsec) Estimated defocus error is 2.864 mm (used 2.87 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 -0.00078 piston 1 1 0.00304 tilt_x 1 -1 0.00041 tilt_y 2 2 0.05757 astigmatism_0 2 0 -0.00168 curvature 2 -2 0.01865 astigmatism45 3 3 -0.00691 trefoil_0 3 1 -0.00540 coma_x 3 -1 -0.00296 coma_y 3 -3 -0.00076 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 -0.00074 piston 1 1 0.00274 tilt_x 1 -1 0.00088 tilt_y 2 2 0.05869 astigmatism_0 2 0 -0.00149 curvature 2 -2 0.01793 astigmatism45 3 3 -0.00736 trefoil_0 3 1 -0.00665 coma_x 3 -1 -0.00146 coma_y 3 -3 -0.00190 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 -0.00069 piston 1 1 0.00349 tilt_x 1 -1 0.00168 tilt_y 2 2 0.05868 astigmatism_0 2 0 -0.00114 curvature 2 -2 0.01687 astigmatism45 3 3 -0.00772 trefoil_0 3 1 -0.00416 coma_x 3 -1 0.00137 coma_y 3 -3 -0.00260 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 -0.00106 piston 1 1 -0.00022 tilt_x 1 -1 0.00290 tilt_y 2 2 0.06943 astigmatism_0 2 0 -0.00297 curvature 2 -2 0.01531 astigmatism45 3 3 -0.00124 trefoil_0 3 1 -0.01789 coma_x 3 -1 0.00496 coma_y 3 -3 -0.00323 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 -0.00106 piston 1 1 0.00030 tilt_x 1 -1 0.00397 tilt_y 2 2 0.06837 astigmatism_0 2 0 -0.00288 curvature 2 -2 0.01425 astigmatism45 3 3 -0.00222 trefoil_0 3 1 -0.01574 coma_x 3 -1 0.00871 coma_y 3 -3 -0.00234 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 -0.00109 piston 1 1 0.00111 tilt_x 1 -1 0.00446 tilt_y 2 2 0.06789 astigmatism_0 2 0 -0.00284 curvature 2 -2 0.01550 astigmatism45 3 3 -0.00246 trefoil_0 3 1 -0.01295 coma_x 3 -1 0.01005 coma_y 3 -3 -0.00090 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 -0.00117 piston 1 1 0.00130 tilt_x 1 -1 0.00455 tilt_y 2 2 0.06823 astigmatism_0 2 0 -0.00313 curvature 2 -2 0.01667 astigmatism45 3 3 -0.00180 trefoil_0 3 1 -0.01257 coma_x 3 -1 0.01010 coma_y 3 -3 -0.00075 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 -0.00121 piston 1 1 0.00175 tilt_x 1 -1 0.00419 tilt_y 2 2 0.06784 astigmatism_0 2 0 -0.00324 curvature 2 -2 0.01864 astigmatism45 3 3 -0.00121 trefoil_0 3 1 -0.01138 coma_x 3 -1 0.00865 coma_y 3 -3 -0.00020 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 -0.00120 piston 1 1 0.00226 tilt_x 1 -1 0.00343 tilt_y 2 2 0.06804 astigmatism_0 2 0 -0.00319 curvature 2 -2 0.01915 astigmatism45 3 3 -0.00219 trefoil_0 3 1 -0.01015 coma_x 3 -1 0.00644 coma_y 3 -3 0.00081 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 -0.00113 piston 1 1 0.00254 tilt_x 1 -1 0.00241 tilt_y 2 2 0.06600 astigmatism_0 2 0 -0.00305 curvature 2 -2 0.01806 astigmatism45 3 3 -0.00346 trefoil_0 3 1 -0.00912 coma_x 3 -1 0.00382 coma_y 3 -3 0.00175 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 -0.00104 piston 1 1 0.00345 tilt_x 1 -1 0.00183 tilt_y 2 2 0.06576 astigmatism_0 2 0 -0.00269 curvature 2 -2 0.01650 astigmatism45 3 3 -0.00492 trefoil_0 3 1 -0.00635 coma_x 3 -1 0.00252 coma_y 3 -3 0.00190 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 -0.00095 piston 1 1 0.00366 tilt_x 1 -1 0.00163 tilt_y 2 2 0.06305 astigmatism_0 2 0 -0.00234 curvature 2 -2 0.01510 astigmatism45 3 3 -0.00753 trefoil_0 3 1 -0.00516 coma_x 3 -1 0.00214 coma_y 3 -3 0.00104 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 -0.00087 piston 1 1 0.00421 tilt_x 1 -1 0.00183 tilt_y 2 2 0.06216 astigmatism_0 2 0 -0.00197 curvature 2 -2 0.01430 astigmatism45 3 3 -0.01043 trefoil_0 3 1 -0.00335 coma_x 3 -1 0.00296 coma_y 3 -3 0.00017 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 -0.00082 piston 1 1 0.00466 tilt_x 1 -1 0.00209 tilt_y 2 2 0.06226 astigmatism_0 2 0 -0.00169 curvature 2 -2 0.01452 astigmatism45 3 3 -0.01247 trefoil_0 3 1 -0.00208 coma_x 3 -1 0.00370 coma_y 3 -3 -0.00130 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 -0.00075 piston 1 1 0.00465 tilt_x 1 -1 0.00235 tilt_y 2 2 0.06269 astigmatism_0 2 0 -0.00148 curvature 2 -2 0.01432 astigmatism45 3 3 -0.01409 trefoil_0 3 1 -0.00204 coma_x 3 -1 0.00477 coma_y 3 -3 -0.00118 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 -0.00067 piston 1 1 0.00463 tilt_x 1 -1 0.00260 tilt_y 2 2 0.06255 astigmatism_0 2 0 -0.00118 curvature 2 -2 0.01372 astigmatism45 3 3 -0.01403 trefoil_0 3 1 -0.00177 coma_x 3 -1 0.00576 coma_y 3 -3 -0.00082 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: 28.6 18.4 19.5 28 25.6 30.4 38 30.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.6 18 19.1 27.3 25.1 28.1 37.5 29.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.47 1.29 2.42 4.03 6.1 8.57 11.5 7.57 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.7 18.2 19.6 31.7 25.7 30.5 38.3 31.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.7 17.8 19.2 31.1 25.2 28.2 37.9 30.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.502 1.34 2.48 4.1 6.19 8.7 11.6 7.69 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 17.8 19.4 35.2 25.7 30.5 37.9 31.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 17.4 19 34.7 25.2 28.2 37.6 31 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.403 1.21 2.37 4.02 6.15 8.66 11.6 7.63 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.1 17.8 19 36 25.7 30.5 37.3 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27 17.4 18.7 35.3 25.1 28.1 37.3 31 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.12 2.36 3.58 5.16 7.27 10 13.6 9.05 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.3 18.2 18.9 32.6 25.8 30.9 37.1 31.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.2 17.7 18.5 32 25.2 28.5 37 30.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.09 2.29 3.49 5.05 7.14 9.87 13.4 8.88 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28 18.7 19.4 30.2 26.2 31.3 37.3 31 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 18.2 19.1 29.6 25.6 29 37.2 30.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.01 2.15 3.36 4.96 7.1 9.83 13.3 8.82 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29 18.6 20.5 28.7 26.4 31.7 38.2 31.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.9 18.1 20.1 28.2 25.8 29.4 38 30.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.992 2.14 3.35 4.98 7.15 9.91 13.4 8.89 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.4 18.7 21.4 27.3 26.4 31.9 38.7 31 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 30.3 18.2 21.1 26.6 25.8 29.6 38.4 30.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.895 1.99 3.22 4.9 7.14 9.93 13.4 8.86 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32 18.7 21.7 25.7 26.3 31.8 39.1 30.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.9 18.3 21.4 24.9 25.7 29.4 38.7 30 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.779 1.81 3.07 4.83 7.14 9.97 13.4 8.87 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33 18.6 21.6 24.9 25.9 31.3 38.7 30.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33 18.2 21.4 24 25.4 28.9 38.3 29.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.668 1.63 2.87 4.62 6.9 9.66 12.9 8.57 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33 18.2 20.7 24.5 25.7 30.9 38.2 29.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33 17.8 20.5 23.6 25.1 28.5 37.7 29 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.526 1.44 2.69 4.49 6.81 9.58 12.8 8.46 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.9 17.9 19.4 24.9 25.3 30.5 37.8 29.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.9 17.5 19.1 24 24.7 28.2 37.3 28.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.464 1.33 2.54 4.28 6.52 9.18 12.3 8.11 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.4 18 19.1 25.1 25.2 30.5 37.4 29.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 30.4 17.6 18.7 24.4 24.6 28.1 36.8 28.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.418 1.26 2.47 4.2 6.43 9.07 12.1 8 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.8 18 19.2 25.9 25.2 30.4 37.1 29.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.8 17.7 18.8 25.2 24.6 28 36.4 28.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.411 1.26 2.47 4.21 6.46 9.13 12.2 8.05 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.6 17.9 19.3 26.9 25.1 30.4 36.8 29.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.6 17.6 18.9 26.3 24.4 27.9 36.1 28.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.447 1.3 2.52 4.25 6.52 9.21 12.3 8.13 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.8 17.8 19.4 30.2 25.3 30.4 36.5 30.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.8 17.4 19 29.6 24.6 27.9 35.8 29.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.479 1.34 2.54 4.25 6.5 9.17 12.3 8.1 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 26.1 16.5 17.7 21.8 24.5 29.6 36.3 28.4 Mean deviation is -0.58744942195848704 microns Taper = 10 dB, Ruze illumination-weighted rms = 27.4 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 = 24.1 micron Centre pixel: 64.0 64.0 Value = 2988.36 (estimate), 3708.89 (perfect) Strehl = 0.6492 Strehl ratio estimate = 0.6492 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 = 23.3 micron Centre pixel: 64.0 64.0 Value = 2524.11 (estimate), 3708.89 (perfect) Strehl = 0.463159 Strehl ratio estimate = 0.4632 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 -36.3 -7.5 -4.1 37.3 2 1 2 -25.1 -1.8 8.6 26.6 3 1 3 -2.5 5.3 -22.0 22.8 4 1 4 -10.9 -7.6 -30.5 33.3 5 1 5 -42.7 8.2 41.3 60.0 6 1 6 -38.4 -3.2 -12.1 40.4 7 1 7 -36.4 -11.5 24.0 45.1 8 1 8 -43.1 26.9 41.3 65.4 9 1 9 -102.1 -6.3 10.1 102.8 10 1 10 -32.5 9.3 23.5 41.1 11 1 11 -6.7 0.3 2.1 7.0 12 1 12 -29.8 -7.1 -2.1 30.7 13 2 1 3.5 -15.1 -12.1 19.7 14 2 2 -7.2 12.0 0.1 14.0 15 2 3 12.4 -14.0 -17.8 25.8 16 2 4 -1.7 -13.6 -2.0 13.9 17 2 5 3.8 1.3 6.8 7.9 18 2 6 -8.7 26.7 31.3 42.1 19 2 7 -11.0 14.9 14.6 23.6 20 2 8 4.9 20.6 9.6 23.2 21 2 9 12.5 -2.0 -3.4 13.1 22 2 10 -0.6 0.4 -2.7 2.8 23 2 11 -19.7 1.1 2.1 19.8 24 2 12 -23.9 1.6 -12.9 27.2 25 2 13 -27.4 -9.6 -15.8 33.1 26 2 14 -24.3 -19.8 2.4 31.4 27 2 15 -7.0 -1.0 -11.0 13.1 28 2 16 13.7 -11.1 -4.8 18.3 29 2 17 9.3 -5.7 -3.2 11.4 30 2 18 6.0 11.8 10.6 16.9 31 2 19 0.1 -0.0 6.4 6.4 32 2 20 11.7 -13.9 -15.7 24.0 33 2 21 1.2 -5.9 -20.6 21.5 34 2 22 8.1 -22.1 -16.1 28.5 35 2 23 0.5 -10.1 2.0 10.3 36 2 24 -3.8 -8.0 -9.7 13.1 37 3 1 8.1 11.1 4.7 14.5 38 3 2 11.7 13.2 2.4 17.8 39 3 3 -1.7 7.3 5.0 9.0 40 3 4 8.7 7.2 32.0 33.9 41 3 5 -3.5 23.4 26.5 35.5 42 3 6 -16.7 8.7 24.9 31.3 43 3 7 -17.6 6.7 -0.0 18.8 44 3 8 -5.1 9.8 2.6 11.4 45 3 9 7.3 8.4 4.7 12.1 46 3 10 -4.1 14.2 -0.9 14.8 47 3 11 25.6 19.7 11.9 34.4 48 3 12 10.0 31.4 9.4 34.3 49 3 13 5.3 26.0 40.4 48.3 50 3 14 22.9 13.5 60.4 66.0 51 3 15 -5.1 10.7 24.4 27.1 52 3 16 7.7 16.8 25.7 31.7 53 3 17 12.4 24.2 25.1 37.0 54 3 18 10.7 19.8 30.1 37.6 55 3 19 18.0 21.1 15.3 31.7 56 3 20 17.4 18.4 12.7 28.3 57 3 21 14.9 7.6 10.9 20.0 58 3 22 1.1 1.1 6.4 6.5 59 3 23 5.1 0.9 -12.7 13.7 60 3 24 -16.4 -10.3 -24.7 31.3 61 3 25 -7.9 -14.6 -20.1 26.1 62 3 26 -12.5 2.3 -8.7 15.4 63 3 27 -1.6 2.4 4.4 5.3 64 3 28 30.8 14.2 0.4 33.9 65 3 29 30.8 17.7 4.0 35.7 66 3 30 6.2 2.8 2.8 7.3 67 3 31 -2.0 17.0 23.4 29.0 68 3 32 12.4 25.6 14.3 31.8 69 3 33 15.7 24.1 25.3 38.3 70 3 34 12.4 6.7 14.3 20.1 71 3 35 51.8 16.7 3.3 54.5 72 3 36 26.1 24.1 8.9 36.7 73 3 37 27.3 20.4 -11.0 35.8 74 3 38 21.3 11.5 3.7 24.4 75 3 39 6.4 11.5 -4.7 14.0 76 3 40 24.2 3.7 5.3 25.1 77 3 41 6.1 6.6 9.7 13.2 78 3 42 -9.7 18.1 9.5 22.6 79 3 43 -4.0 17.8 9.1 20.4 80 3 44 20.5 17.3 9.7 28.6 81 3 45 23.6 8.7 9.5 26.9 82 3 46 8.5 9.0 3.4 12.8 83 3 47 16.4 8.8 -3.7 19.0 84 3 48 -1.0 12.2 -15.2 19.5 85 4 1 -19.9 -24.1 -5.4 31.8 86 4 2 7.1 -16.5 -50.3 53.4 87 4 3 3.5 -13.1 -29.0 32.1 88 4 4 8.3 3.8 -35.8 37.0 89 4 5 20.8 4.4 -17.2 27.3 90 4 6 27.5 10.6 -12.2 31.9 91 4 7 29.8 10.2 5.9 32.1 92 4 8 11.9 14.0 -3.4 18.7 93 4 9 8.6 5.7 -6.9 12.4 94 4 10 1.0 12.0 -17.2 21.0 95 4 11 -3.6 10.9 -41.0 42.6 96 4 12 -26.1 -3.9 5.2 26.9 97 4 13 22.7 11.6 21.3 33.2 98 4 14 19.9 1.6 -28.5 34.8 99 4 15 13.3 12.6 20.2 27.2 100 4 16 6.0 22.8 20.8 31.4 101 4 17 20.3 29.8 22.4 42.5 102 4 18 44.8 7.4 27.6 53.1 103 4 19 16.2 6.4 -18.7 25.6 104 4 20 7.0 -1.6 -12.5 14.4 105 4 21 -8.1 -8.6 -4.8 12.8 106 4 22 -28.4 -1.8 4.6 28.8 107 4 23 -28.0 -11.4 -25.0 39.3 108 4 24 -19.5 -12.1 6.2 23.8 109 4 25 -32.6 -10.1 34.9 48.9 110 4 26 -23.4 -13.3 -30.9 41.0 111 4 27 -16.9 -9.3 4.4 19.8 112 4 28 -14.2 -7.5 4.3 16.7 113 4 29 -24.5 6.0 -39.1 46.6 114 4 30 -11.2 -6.3 8.6 15.4 115 4 31 10.2 -6.6 8.1 14.6 116 4 32 7.3 19.6 6.0 21.7 117 4 33 12.0 13.6 18.2 25.7 118 4 34 17.7 12.5 16.2 27.1 119 4 35 -26.5 4.2 -47.8 54.8 120 4 36 -15.2 2.1 -11.6 19.2 121 4 37 20.7 9.4 2.3 22.8 122 4 38 6.6 -5.4 -20.4 22.1 123 4 39 5.9 7.5 -5.2 10.9 124 4 40 -9.2 9.4 -5.0 14.1 125 4 41 7.5 21.5 16.6 28.2 126 4 42 37.3 5.1 6.6 38.2 127 4 43 14.7 4.1 -2.5 15.5 128 4 44 4.2 10.3 -3.3 11.6 129 4 45 1.8 3.6 -15.5 16.0 130 4 46 2.0 -15.1 -23.5 28.0 131 4 47 -14.8 -17.1 -46.5 51.7 132 4 48 -15.3 -20.1 -18.6 31.4 133 5 1 -3.9 -3.8 -7.1 8.9 134 5 2 -10.0 -4.1 -9.1 14.1 135 5 3 -14.8 -14.4 -29.7 36.1 136 5 4 0.8 0.9 8.0 8.1 137 5 5 -7.8 4.3 0.6 8.9 138 5 6 10.2 9.4 -12.9 19.0 139 5 7 14.0 11.5 2.9 18.3 140 5 8 9.3 17.1 -5.9 20.4 141 5 9 6.4 7.6 4.7 11.0 142 5 10 -7.7 -19.5 -31.9 38.2 143 5 11 2.7 -5.0 12.2 13.4 144 5 12 -15.1 17.6 10.3 25.4 145 5 13 -0.4 12.6 8.0 15.0 146 5 14 -6.8 12.4 6.5 15.6 147 5 15 14.1 -2.8 -14.6 20.5 148 5 16 22.5 21.6 14.5 34.4 149 5 17 10.3 15.0 -11.6 21.6 150 5 18 -3.1 -4.9 214.8 214.8 151 5 19 -10.5 -3.9 11.2 15.9 152 5 20 -6.5 12.2 -2.7 14.1 153 5 21 9.7 9.4 -3.3 13.9 154 5 22 3.3 -21.2 -34.3 40.5 155 5 23 -16.0 -11.5 -33.2 38.6 156 5 24 0.7 -20.3 -47.0 51.2 157 5 25 2.8 -20.7 -52.4 56.4 158 5 26 -3.8 -6.9 -36.0 36.8 159 5 27 10.2 -31.4 -41.1 52.7 160 5 28 20.9 8.4 -22.0 31.5 161 5 29 19.5 10.3 -0.7 22.1 162 5 30 9.2 5.5 15.8 19.1 163 5 31 -0.7 6.8 10.3 12.4 164 5 32 -3.7 6.1 1.0 7.2 165 5 33 8.1 0.6 -2.1 8.4 166 5 34 15.4 -12.4 -34.1 39.5 167 5 35 -7.2 0.6 0.2 7.3 168 5 36 -0.8 7.5 -27.0 28.0 169 5 37 5.4 5.0 -10.1 12.5 170 5 38 2.5 -9.4 -9.7 13.7 171 5 39 -0.2 -1.0 -40.1 40.1 172 5 40 4.1 14.9 -10.0 18.4 173 5 41 8.3 12.0 -16.1 21.7 174 5 42 5.2 1.1 -9.7 11.1 175 5 43 12.0 2.5 -12.9 17.8 176 5 44 1.9 4.9 -9.7 11.0 177 5 45 11.7 1.6 -23.9 26.7 178 5 46 10.8 -27.3 -46.7 55.2 179 5 47 -2.3 -24.1 -28.2 37.1 180 5 48 -6.8 -5.3 -26.9 28.2 181 6 1 -9.8 -34.8 -35.1 50.4 182 6 2 -3.5 -29.1 -52.8 60.4 183 6 3 -24.8 -15.1 -42.1 51.2 184 6 4 -38.1 1.7 -100.7 107.7 185 6 5 -2.1 -7.2 -15.8 17.5 186 6 6 1.1 -7.4 -18.0 19.5 187 6 7 -2.0 -9.2 -15.2 17.8 188 6 8 -8.6 -3.4 -20.9 22.9 189 6 9 -16.2 7.0 -45.6 48.8 190 6 10 -36.9 16.8 -3.5 40.7 191 6 11 -9.6 10.6 -13.8 19.9 192 6 12 4.5 15.7 -6.9 17.8 193 6 13 0.3 9.4 -2.0 9.6 194 6 14 -10.0 11.3 1.4 15.2 195 6 15 -14.6 18.3 4.7 23.9 196 6 16 -3.5 -1.0 -47.9 48.0 197 6 17 -15.6 -7.9 0.3 17.5 198 6 18 2.2 -0.3 12.9 13.1 199 6 19 -3.4 -7.5 8.4 11.8 200 6 20 13.0 -10.0 -6.5 17.6 201 6 21 -47.6 -11.7 -63.9 80.6 202 6 22 -69.9 -26.5 -2.6 74.8 203 6 23 -59.5 -26.2 -1.0 65.1 204 6 24 -71.5 -33.7 0.5 79.1 205 6 25 -73.7 -35.3 -18.2 83.7 206 6 26 -61.2 -28.3 -16.6 69.4 207 6 27 -76.4 -18.4 -7.4 78.9 208 6 28 -61.6 -32.0 -71.2 99.4 209 6 29 -18.4 -0.9 -31.3 36.3 210 6 30 -0.5 -0.8 38.3 38.3 211 6 31 12.7 -0.9 7.3 14.7 212 6 32 2.8 -13.5 6.5 15.2 213 6 33 -39.5 4.2 -84.8 93.6 214 6 34 -125.5 32.0 -25.8 132.0 215 6 35 -0.6 14.5 40.9 43.4 216 6 36 -4.0 25.9 51.7 58.0 217 6 37 -7.3 13.2 40.4 43.1 218 6 38 -7.1 -5.4 6.2 10.9 219 6 39 -36.5 16.9 10.0 41.5 220 6 40 -31.9 9.2 -40.0 52.0 221 6 41 -10.4 14.1 7.1 18.9 222 6 42 2.7 0.8 36.9 37.1 223 6 43 6.2 -1.3 -1.6 6.6 224 6 44 -11.9 0.8 -0.6 12.0 225 6 45 -51.1 13.8 -97.0 110.5 226 6 46 -77.8 -4.2 -20.9 80.7 227 6 47 -35.8 -28.0 -35.0 57.4 228 6 48 -41.5 -36.4 -39.4 67.8 229 7 1 -36.2 -8.7 -26.8 45.9 230 7 2 -41.9 -20.4 -42.3 62.9 231 7 3 -12.4 -13.6 -16.3 24.6 232 7 4 2.2 -69.6 46.8 83.9 233 7 5 7.0 -11.5 30.2 33.1 234 7 6 1.8 35.0 24.1 42.5 235 7 7 -21.5 25.5 33.4 47.2 236 7 8 36.5 -4.3 -43.3 56.8 237 7 9 34.6 -74.3 40.8 91.5 238 7 10 34.9 21.7 25.8 48.5 239 7 11 9.5 18.6 -18.3 27.8 240 7 12 6.0 29.4 17.4 34.7 241 7 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-19.1 5.8 -51.8 55.5 276 7 48 -23.8 121.3 -19.5 125.2 Creating sector-motor-move file sector motor steps 1 1 14 1 2 -21 1 3 0 1 4 -30 1 5 0 1 6 -11 1 7 -4 1 8 -4 1 9 -3 1 10 -12 1 11 -4 1 12 -7 1 13 -12 1 14 -6 1 15 -12 1 16 -16 1 17 -8 1 18 -1 1 19 -8 1 20 -2 1 21 -11 1 22 -10 1 23 -10 1 24 -2 1 25 2 1 26 0 1 27 0 1 28 -10 1 29 1 1 30 2 1 31 -9 1 32 -4 1 33 -4 1 34 -8 1 35 -4 1 36 1 1 37 -2 1 38 -1 1 39 -3 1 40 -15 1 41 -5 1 42 2 1 43 -2 1 44 -1 1 45 -1 1 46 -1 1 47 -7 1 48 -6 1 49 1 1 50 2 1 51 0 1 52 0 1 53 3 1 54 -2 1 55 0 1 56 4 1 57 3 1 58 -2 1 59 -11 1 60 -1 1 61 1 1 62 3 1 63 2 1 64 -4 1 65 1 1 66 -3 1 67 9 1 68 2 1 69 2 2 1 -13 2 2 -1 2 3 11 2 4 -6 2 5 -1 2 6 -2 2 7 10 2 8 7 2 9 -6 2 10 -4 2 11 -2 2 12 0 2 13 7 2 14 10 2 15 0 2 16 -5 2 17 -2 2 18 0 2 19 9 2 20 -3 2 21 2 2 22 -4 2 23 -2 2 24 0 2 25 -1 2 26 5 2 27 2 2 28 -1 2 29 4 2 30 3 2 31 0 2 32 3 2 33 4 2 34 1 2 35 3 2 36 9 2 37 -3 2 38 2 2 39 3 2 40 -3 2 41 3 2 42 8 2 43 0 2 44 1 2 45 -2 2 46 -5 2 47 1 2 48 6 2 49 0 2 50 2 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36 1 10 37 -2 10 38 -2 10 39 0 10 40 -6 10 41 -1 10 42 2 10 43 -3 10 44 1 10 45 1 10 46 0 10 47 2 10 48 6 10 49 -1 10 50 3 10 51 1 10 52 -4 10 53 -4 10 54 3 10 55 1 10 56 3 10 57 6 10 58 2 10 59 -9 10 60 7 10 61 -3 10 62 6 10 63 8 10 64 -1 10 65 0 10 66 1 10 67 1 10 68 1 10 69 7 11 1 -3 11 2 0 11 3 3 11 4 0 11 5 0 11 6 -3 11 7 -13 11 8 4 11 9 -10 11 10 0 11 11 0 11 12 1 11 13 5 11 14 4 11 15 7 11 16 11 11 17 0 11 18 0 11 19 4 11 20 6 11 21 19 11 22 2 11 23 4 11 24 -3 11 25 -2 11 26 1 11 27 0 11 28 -1 11 29 3 11 30 1 11 31 -3 11 32 0 11 33 3 11 34 0 11 35 1 11 36 4 11 37 -2 11 38 0 11 39 1 11 40 2 11 41 1 11 42 11 11 43 -4 11 44 3 11 45 2 11 46 5 11 47 6 11 48 2 11 49 2 11 50 5 11 51 -1 11 52 -4 11 53 -6 11 54 2 11 55 2 11 56 5 11 57 -2 11 58 0 11 59 -2 11 60 0 11 61 2 11 62 2 11 63 1 11 64 -3 11 65 0 11 66 -6 11 67 2 11 68 5 11 69 6 12 1 -5 12 2 37 12 3 -7 12 4 -12 12 5 -11 12 6 -12 12 7 -15 12 8 1 12 9 -5 12 10 -10 12 11 -8 12 12 -10 12 13 -5 12 14 1 12 15 3 12 16 -6 12 17 -1 12 18 -23 12 19 5 12 20 -20 12 21 2 12 22 -29 12 23 4 12 24 -15 12 25 -8 12 26 -1 12 27 -2 12 28 -5 12 29 -6 12 30 -4 12 31 -8 12 32 -7 12 33 0 12 34 -14 12 35 -5 12 36 -4 12 37 -14 12 38 -8 12 39 3 12 40 -7 12 41 -4 12 42 0 12 43 -7 12 44 0 12 45 3 12 46 -4 12 47 1 12 48 0 12 49 -1 12 50 2 12 51 5 12 52 -2 12 53 -2 12 54 -1 12 55 1 12 56 2 12 57 2 12 58 -2 12 59 -9 12 60 0 12 61 2 12 62 2 12 63 7 12 64 -4 12 65 0 12 66 0 12 67 -4 12 68 3 12 69 0 Adjuster movements: rms = 25.5 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20040809-144721 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1