Reduction started at: 20050421-230054 Reading data from /net/moana/export/data/janw/rxh3/rxh3-20050420-172845.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 = 2402.0 max = 2433.0 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.840 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 -3.03711 3.05176 -0.03422 loimag -3.17871 3.09082 0.00297 hireal -5.00000 4.99756 -0.39596 hiimag -5.00000 4.99756 -0.26610 xpos -2432.19303 2432.99049 -3.19180 ypos -2402.03054 2402.07013 -0.02432 plock160 0.19531 1.70410 1.02463 lorefpwr 0.16602 1.58447 1.13791 losigpwr -4.52637 -0.29297 -4.33696 hirefpwr 0.23193 1.61377 1.18472 hisigpwr -4.42627 4.99756 -0.87620 encltemp 31.66504 32.93457 32.22123 flags 0.00000 256.00000 2.76738 phi-lock -1.76270 -0.36377 -1.08601 sindex 0.00000 128.00000 63.61104 time 0.00000 2043.98983 1016.77184 zeropt -0.00732 -0.00488 -0.00551 !!!Warning!!! philock max less than 0.2 !!!Warning!!! philock min less than -1.5 ---------------------------------------------------- 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 = 40.00553 arcsec Mean row spacing = 40.00555 arcsec (alternate estimator) Mean tracking incline = 0.40114 arcsec Mean pointing range = 1.43553 arcsec Mean pointing rms = 0.26652 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (1.7, 13.7 ) 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: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22671 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22671 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 = 2432.99 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 = 2.87779 at (0.0, 0.0) arcsec Real: mean = 0.000664957 sum of squares = 832.75 Imag: mean = -0.002591 sum of squares = 1003.04 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 = 2.91824 at (0.0, 0.0) arcsec Real: mean = 0.00110526 sum of squares = 826.567 Imag: mean = -0.00299027 sum of squares = 1010.14 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 = 2.96268 at (0.0, 0.0) arcsec Real: mean = 0.00173599 sum of squares = 887.573 Imag: mean = -0.00305187 sum of squares = 952.416 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 = 3.01531 at (0.0, 0.0) arcsec Real: mean = 0.00222081 sum of squares = 972.965 Imag: mean = -0.00281472 sum of squares = 869.624 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 = 3.05193 at (0.0, 0.0) arcsec Real: mean = 0.00249648 sum of squares = 1023.98 Imag: mean = -0.0024547 sum of squares = 824.464 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 = 3.07149 at (0.0, 0.0) arcsec Real: mean = 0.00264986 sum of squares = 1001.04 Imag: mean = -0.00197276 sum of squares = 852.977 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 = 3.05411 at (0.0, 0.0) arcsec Real: mean = 0.00262112 sum of squares = 921.984 Imag: mean = -0.0016152 sum of squares = 936.389 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 = 3.0294 at (0.0, 0.0) arcsec Real: mean = 0.00249363 sum of squares = 849.397 Imag: mean = -0.00123443 sum of squares = 1011.76 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 = 2.98376 at (0.0, 0.0) arcsec Real: mean = 0.00216701 sum of squares = 839.015 Imag: mean = -0.000825575 sum of squares = 1025.83 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 = 2.94858 at (0.0, 0.0) arcsec Real: mean = 0.0016132 sum of squares = 894.92 Imag: mean = -0.000651128 sum of squares = 972.391 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 = 2.92168 at (0.0, -40.004977724682043) arcsec Real: mean = 0.00111809 sum of squares = 979.672 Imag: mean = -0.000926211 sum of squares = 889.504 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 = 2.9124 at (0.0, -40.00398208063713) arcsec Real: mean = 0.000912435 sum of squares = 1031.49 Imag: mean = -0.00136838 sum of squares = 840.696 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 = 2.91785 at (0.0, -40.002986486150171) arcsec Real: mean = 0.000809901 sum of squares = 1016.19 Imag: mean = -0.00166025 sum of squares = 858.241 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 = 2.89731 at (0.0, -40.001990941217464) arcsec Real: mean = 0.000678821 sum of squares = 945.693 Imag: mean = -0.00191289 sum of squares = 930.26 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 = 2.91749 at (0.0, 0.0) arcsec Real: mean = 0.000870978 sum of squares = 868.458 Imag: mean = -0.00243007 sum of squares = 1009.61 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 = 2.9257 at (0.0, 0.0) arcsec Real: mean = 0.00127316 sum of squares = 839.698 Imag: mean = -0.0028691 sum of squares = 1040.96 Masking frequency index 0 Mask scale size = 3.0583 Masking frequency index 1 Mask scale size = 3.05837 Masking frequency index 2 Mask scale size = 3.05845 Masking frequency index 3 Mask scale size = 3.05853 Masking frequency index 4 Mask scale size = 3.0586 Masking frequency index 5 Mask scale size = 3.05868 Masking frequency index 6 Mask scale size = 3.05875 Masking frequency index 7 Mask scale size = 3.05883 Masking frequency index 8 Mask scale size = 3.05891 Masking frequency index 9 Mask scale size = 3.05898 Masking frequency index 10 Mask scale size = 3.05906 Masking frequency index 11 Mask scale size = 3.05914 Masking frequency index 12 Mask scale size = 3.05921 Masking frequency index 13 Mask scale size = 3.05929 Masking frequency index 14 Mask scale size = 3.05936 Masking frequency index 15 Mask scale size = 3.05944 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.234375 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.183105 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.187988 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: 0.209961 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.170898 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.197754 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.180664 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0195312 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -0.72592 101.42 Freq 1: Shift, scale = -1.1656 99.958 Freq 2: Shift, scale = -1.6057 98.914 Freq 3: Shift, scale = -2.0445 98.416 Freq 4: Shift, scale = -2.4883 99.031 Freq 5: Shift, scale = -2.9415 100.03 Freq 6: Shift, scale = 2.8888 101.21 Freq 7: Shift, scale = 2.4427 102.57 Freq 8: Shift, scale = 2.0026 103.86 Freq 9: Shift, scale = 1.5695 104.63 Freq 10: Shift, scale = 1.1391 104.92 Freq 11: Shift, scale = 0.71369 105.16 Freq 12: Shift, scale = 0.28376 105.64 Freq 13: Shift, scale = -0.14828 104.8 Freq 14: Shift, scale = -0.58599 103.58 Freq 15: Shift, scale = -1.0197 101.88 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: -0.231 radians x offset: -0.115 arcsec y offset: 0.118 arcsec defocus: 0.00423 mm Estimated x pointing error is 1.585 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.82 arcsec (used 13.7 arcsec) Estimated defocus error is 2.844 mm (used 2.84 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.235 radians x offset: -0.125 arcsec y offset: 0.136 arcsec defocus: 0.00101 mm Estimated x pointing error is 1.575 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.84 arcsec (used 13.7 arcsec) Estimated defocus error is 2.841 mm (used 2.84 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.238 radians x offset: -0.148 arcsec y offset: 0.134 arcsec defocus: 0.000761 mm Estimated x pointing error is 1.552 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.83 arcsec (used 13.7 arcsec) Estimated defocus error is 2.841 mm (used 2.84 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.24 radians x offset: -0.161 arcsec y offset: 0.164 arcsec defocus: -0.000243 mm Estimated x pointing error is 1.539 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.86 arcsec (used 13.7 arcsec) Estimated defocus error is 2.84 mm (used 2.84 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.246 radians x offset: -0.179 arcsec y offset: 0.154 arcsec defocus: 0.000218 mm Estimated x pointing error is 1.521 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.85 arcsec (used 13.7 arcsec) Estimated defocus error is 2.84 mm (used 2.84 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.26 radians x offset: -0.176 arcsec y offset: 0.149 arcsec defocus: 0.00298 mm Estimated x pointing error is 1.524 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.85 arcsec (used 13.7 arcsec) Estimated defocus error is 2.843 mm (used 2.84 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.273 radians x offset: -0.167 arcsec y offset: 0.129 arcsec defocus: 0.00608 mm Estimated x pointing error is 1.533 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.83 arcsec (used 13.7 arcsec) Estimated defocus error is 2.846 mm (used 2.84 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.281 radians x offset: -0.128 arcsec y offset: 0.0877 arcsec defocus: 0.0047 mm Estimated x pointing error is 1.572 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.79 arcsec (used 13.7 arcsec) Estimated defocus error is 2.845 mm (used 2.84 mm) Fitting frequency 8 Minimiser fit code = 3 piston: -0.283 radians x offset: -0.0838 arcsec y offset: 0.0909 arcsec defocus: 0.00521 mm Estimated x pointing error is 1.616 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.79 arcsec (used 13.7 arcsec) Estimated defocus error is 2.845 mm (used 2.84 mm) Fitting frequency 9 Minimiser fit code = 3 piston: -0.28 radians x offset: -0.0583 arcsec y offset: 0.0761 arcsec defocus: 0.002 mm Estimated x pointing error is 1.642 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.78 arcsec (used 13.7 arcsec) Estimated defocus error is 2.842 mm (used 2.84 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.272 radians x offset: -0.0271 arcsec y offset: 0.055 arcsec defocus: -0.000309 mm Estimated x pointing error is 1.673 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.75 arcsec (used 13.7 arcsec) Estimated defocus error is 2.84 mm (used 2.84 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.26 radians x offset: -0.0467 arcsec y offset: 0.0394 arcsec defocus: -0.00386 mm Estimated x pointing error is 1.653 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.74 arcsec (used 13.7 arcsec) Estimated defocus error is 2.836 mm (used 2.84 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.251 radians x offset: -0.0333 arcsec y offset: 0.0048 arcsec defocus: -0.00458 mm Estimated x pointing error is 1.667 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.7 arcsec (used 13.7 arcsec) Estimated defocus error is 2.835 mm (used 2.84 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.244 radians x offset: -0.0389 arcsec y offset: 0.0252 arcsec defocus: -0.00438 mm Estimated x pointing error is 1.661 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.73 arcsec (used 13.7 arcsec) Estimated defocus error is 2.836 mm (used 2.84 mm) Fitting frequency 14 Minimiser fit code = 3 piston: -0.242 radians x offset: -0.0363 arcsec y offset: 0.0529 arcsec defocus: -0.00399 mm Estimated x pointing error is 1.664 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.75 arcsec (used 13.7 arcsec) Estimated defocus error is 2.836 mm (used 2.84 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.235 radians x offset: -0.0232 arcsec y offset: 0.0661 arcsec defocus: -0.000589 mm Estimated x pointing error is 1.677 arcsec (used 1.7 arcsec) Estimated y pointing error is 13.77 arcsec (used 13.7 arcsec) Estimated defocus error is 2.839 mm (used 2.84 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 -0.00059 piston 1 1 -0.00752 tilt_x 1 -1 -0.01171 tilt_y 2 2 0.05295 astigmatism_0 2 0 -0.00138 curvature 2 -2 0.04267 astigmatism45 3 3 0.02632 trefoil_0 3 1 -0.03827 coma_x 3 -1 -0.04790 coma_y 3 -3 -0.02887 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 -0.00053 piston 1 1 -0.00664 tilt_x 1 -1 -0.01111 tilt_y 2 2 0.05268 astigmatism_0 2 0 -0.00106 curvature 2 -2 0.04179 astigmatism45 3 3 0.02539 trefoil_0 3 1 -0.03567 coma_x 3 -1 -0.04575 coma_y 3 -3 -0.02974 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 -0.00054 piston 1 1 -0.00556 tilt_x 1 -1 -0.01032 tilt_y 2 2 0.05354 astigmatism_0 2 0 -0.00092 curvature 2 -2 0.04221 astigmatism45 3 3 0.02150 trefoil_0 3 1 -0.03276 coma_x 3 -1 -0.04299 coma_y 3 -3 -0.03075 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 -0.00058 piston 1 1 -0.00470 tilt_x 1 -1 -0.00971 tilt_y 2 2 0.05379 astigmatism_0 2 0 -0.00093 curvature 2 -2 0.04110 astigmatism45 3 3 0.01844 trefoil_0 3 1 -0.03054 coma_x 3 -1 -0.04088 coma_y 3 -3 -0.03213 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 -0.00066 piston 1 1 -0.00442 tilt_x 1 -1 -0.00986 tilt_y 2 2 0.05412 astigmatism_0 2 0 -0.00129 curvature 2 -2 0.04104 astigmatism45 3 3 0.01490 trefoil_0 3 1 -0.03015 coma_x 3 -1 -0.04106 coma_y 3 -3 -0.03126 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 -0.00071 piston 1 1 -0.00394 tilt_x 1 -1 -0.01042 tilt_y 2 2 0.05433 astigmatism_0 2 0 -0.00147 curvature 2 -2 0.04023 astigmatism45 3 3 0.01338 trefoil_0 3 1 -0.02912 coma_x 3 -1 -0.04211 coma_y 3 -3 -0.03120 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 -0.00079 piston 1 1 -0.00429 tilt_x 1 -1 -0.01140 tilt_y 2 2 0.05608 astigmatism_0 2 0 -0.00181 curvature 2 -2 0.04078 astigmatism45 3 3 0.01472 trefoil_0 3 1 -0.03066 coma_x 3 -1 -0.04565 coma_y 3 -3 -0.03074 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 -0.00089 piston 1 1 -0.00510 tilt_x 1 -1 -0.01206 tilt_y 2 2 0.05613 astigmatism_0 2 0 -0.00228 curvature 2 -2 0.04199 astigmatism45 3 3 0.01766 trefoil_0 3 1 -0.03309 coma_x 3 -1 -0.04825 coma_y 3 -3 -0.02835 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 -0.00094 piston 1 1 -0.00551 tilt_x 1 -1 -0.01295 tilt_y 2 2 0.05769 astigmatism_0 2 0 -0.00254 curvature 2 -2 0.04230 astigmatism45 3 3 0.02101 trefoil_0 3 1 -0.03467 coma_x 3 -1 -0.05115 coma_y 3 -3 -0.02829 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 -0.00089 piston 1 1 -0.00603 tilt_x 1 -1 -0.01242 tilt_y 2 2 0.05858 astigmatism_0 2 0 -0.00258 curvature 2 -2 0.04303 astigmatism45 3 3 0.02110 trefoil_0 3 1 -0.03650 coma_x 3 -1 -0.05013 coma_y 3 -3 -0.02805 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 -0.00080 piston 1 1 -0.00644 tilt_x 1 -1 -0.01156 tilt_y 2 2 0.05816 astigmatism_0 2 0 -0.00235 curvature 2 -2 0.04228 astigmatism45 3 3 0.02237 trefoil_0 3 1 -0.03772 coma_x 3 -1 -0.04748 coma_y 3 -3 -0.02850 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 -0.00073 piston 1 1 -0.00666 tilt_x 1 -1 -0.01110 tilt_y 2 2 0.05911 astigmatism_0 2 0 -0.00217 curvature 2 -2 0.04140 astigmatism45 3 3 0.02292 trefoil_0 3 1 -0.03855 coma_x 3 -1 -0.04574 coma_y 3 -3 -0.02942 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 -0.00058 piston 1 1 -0.00632 tilt_x 1 -1 -0.01107 tilt_y 2 2 0.05867 astigmatism_0 2 0 -0.00159 curvature 2 -2 0.03993 astigmatism45 3 3 0.02022 trefoil_0 3 1 -0.03721 coma_x 3 -1 -0.04491 coma_y 3 -3 -0.02781 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 -0.00051 piston 1 1 -0.00611 tilt_x 1 -1 -0.01063 tilt_y 2 2 0.05836 astigmatism_0 2 0 -0.00117 curvature 2 -2 0.03927 astigmatism45 3 3 0.01658 trefoil_0 3 1 -0.03625 coma_x 3 -1 -0.04339 coma_y 3 -3 -0.02849 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 -0.00046 piston 1 1 -0.00593 tilt_x 1 -1 -0.01025 tilt_y 2 2 0.05733 astigmatism_0 2 0 -0.00079 curvature 2 -2 0.03724 astigmatism45 3 3 0.01424 trefoil_0 3 1 -0.03520 coma_x 3 -1 -0.04164 coma_y 3 -3 -0.03115 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 -0.00042 piston 1 1 -0.00515 tilt_x 1 -1 -0.01013 tilt_y 2 2 0.05645 astigmatism_0 2 0 -0.00052 curvature 2 -2 0.03569 astigmatism45 3 3 0.01179 trefoil_0 3 1 -0.03245 coma_x 3 -1 -0.04056 coma_y 3 -3 -0.03198 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: 25.9 20.9 21.4 23.9 24.5 26.3 42.8 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25.1 18.6 20.6 22.4 23.1 24.2 40.5 28.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.53 6.6 8.3 8.68 8.81 10.8 16.5 11.1 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26 20.7 20.8 24.2 24.5 26.7 42.6 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25.1 18.6 20 22.7 23.2 24.6 40.5 28.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.34 6.26 7.89 8.31 8.6 10.7 16.2 10.9 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 21 20.5 24.4 24.9 27.2 42.2 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26 18.8 19.8 23.1 23.6 25 40.5 29 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.12 5.85 7.43 7.93 8.47 10.7 16 10.7 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 21.1 20.5 24.8 25 27.9 41.9 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 19.2 19.7 23.7 23.6 25.6 40.6 29.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.94 5.54 7.06 7.61 8.3 10.6 15.7 10.5 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 20.9 21.2 25.4 25 28.1 42.5 30.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 19 20.4 24.5 23.4 25.9 41.2 29.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.94 5.53 7.05 7.6 8.26 10.5 15.6 10.4 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29 21 21.8 26.1 25.1 28.3 42.5 30.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.2 19 21.1 25.4 23.6 26 41.4 29.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.95 5.55 7.07 7.61 8.23 10.5 15.5 10.4 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.2 20.8 22.5 27.1 24.9 27.8 43.1 31 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.5 18.6 21.8 26.3 23.4 25.3 41.9 29.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.17 5.95 7.55 8.04 8.53 10.7 16 10.8 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.7 21.3 22.3 26.6 24.4 27.8 43.5 31 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31 19.1 21.8 25.7 23 25.1 42 29.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.37 6.32 7.99 8.43 8.73 10.8 16.3 11 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.8 21.6 21.7 27.2 23.9 27 43.1 30.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 30 19.1 21.2 25.8 22.6 24.2 41.1 28.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.56 6.66 8.4 8.81 9.02 11.1 16.8 11.4 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.4 21.5 19.8 26.8 23.8 26.5 43.2 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.6 19.1 19.3 25.2 22.5 23.8 40.9 28.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.57 6.69 8.44 8.88 9.11 11.2 17 11.5 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.3 21.6 20.4 26 23.8 26.2 42.7 30.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.5 19.1 19.7 24.3 22.8 23.7 40.2 28.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.49 6.54 8.26 8.72 9.01 11.2 16.9 11.4 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 21.7 20.5 25.1 23.7 25.8 42.8 30 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.1 19.3 19.7 23.4 22.8 23.5 40.3 28.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.45 6.46 8.17 8.64 9.01 11.2 17 11.4 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.1 21.3 21 24.1 24 25.5 42.4 30 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.4 18.9 20.2 22.5 23.1 23.5 39.9 28.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.36 6.3 7.97 8.44 8.79 11 16.5 11.1 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.5 20.8 21.2 23.4 24.1 25.7 42 30 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25.7 18.6 20.3 21.9 23.1 23.6 40 28.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.26 6.11 7.75 8.23 8.64 10.8 16.2 10.9 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 25.6 20.2 21.4 22.9 24.7 26.2 41.8 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25 18.2 20.5 21.6 23.6 23.9 40.3 28.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.14 5.9 7.48 7.96 8.41 10.6 15.9 10.6 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.4 19.8 21.1 23.1 24.7 27 41.5 30.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25.6 17.9 20.1 22 23.5 24.7 40.3 29 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3 5.63 7.14 7.63 8.17 10.4 15.5 10.4 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 23.6 19.6 18.6 21.8 22.9 25.4 41 28.6 Mean deviation is 0.62411446868681508 microns Taper = 10 dB, Ruze illumination-weighted rms = 27.3 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 = 2762.84 (estimate), 3426.12 (perfect) Strehl = 0.650291 Strehl ratio estimate = 0.6503 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 = 23.5 micron Centre pixel: 64.0 64.0 Value = 2314.19 (estimate), 3426.12 (perfect) Strehl = 0.45624 Strehl ratio estimate = 0.4562 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 -9.8 -9.2 -13.9 19.3 2 1 2 3.1 -11.3 24.0 26.7 3 1 3 30.8 8.1 -7.9 32.8 4 1 4 35.3 4.0 4.5 35.8 5 1 5 13.7 12.9 58.0 61.0 6 1 6 37.7 23.3 30.3 53.7 7 1 7 9.4 39.4 32.9 52.1 8 1 8 9.0 38.6 50.3 64.0 9 1 9 -35.9 14.6 14.0 41.2 10 1 10 7.0 22.0 16.4 28.3 11 1 11 25.1 24.3 12.4 37.1 12 1 12 16.3 1.2 -2.2 16.5 13 2 1 -2.8 -25.5 -23.9 35.1 14 2 2 -8.5 -10.0 -16.5 21.1 15 2 3 11.0 -27.2 -32.2 43.6 16 2 4 8.9 -12.2 -8.9 17.6 17 2 5 21.3 -3.8 24.1 32.4 18 2 6 10.9 29.5 41.5 52.1 19 2 7 -7.4 12.8 20.0 24.9 20 2 8 37.2 18.7 -1.4 41.7 21 2 9 27.2 5.0 19.8 34.0 22 2 10 28.5 10.8 15.7 34.2 23 2 11 19.4 3.4 0.8 19.7 24 2 12 11.0 2.5 -4.0 12.0 25 2 13 25.9 13.1 -2.4 29.1 26 2 14 13.4 -6.5 11.0 18.5 27 2 15 33.8 0.8 -13.1 36.3 28 2 16 30.8 4.8 1.7 31.2 29 2 17 21.9 6.7 -2.1 23.0 30 2 18 14.7 13.8 -2.8 20.4 31 2 19 8.4 -6.4 -6.2 12.3 32 2 20 21.6 -11.5 -3.1 24.6 33 2 21 18.6 5.9 -22.4 29.7 34 2 22 15.3 -39.5 -40.8 58.8 35 2 23 24.1 -23.1 -24.6 41.5 36 2 24 -0.4 -29.5 -27.9 40.6 37 3 1 -22.6 -0.5 -22.0 31.5 38 3 2 -9.2 -12.9 -21.5 26.8 39 3 3 -10.4 -13.8 -28.0 32.9 40 3 4 -1.2 -1.4 7.2 7.4 41 3 5 -20.3 10.4 -10.2 25.0 42 3 6 -20.5 -2.3 -3.2 20.9 43 3 7 -2.8 -4.2 -22.0 22.6 44 3 8 -0.1 12.5 7.2 14.4 45 3 9 24.6 1.3 -8.2 25.9 46 3 10 15.8 15.4 -1.8 22.2 47 3 11 30.8 18.5 3.8 36.2 48 3 12 14.8 43.9 6.3 46.7 49 3 13 -13.6 31.6 10.8 36.1 50 3 14 15.2 13.4 6.2 21.2 51 3 15 5.9 16.3 17.3 24.5 52 3 16 29.8 21.9 17.3 40.8 53 3 17 32.4 26.5 5.4 42.2 54 3 18 29.4 20.7 18.3 40.4 55 3 19 26.2 18.3 -19.7 37.6 56 3 20 8.9 13.8 -2.0 16.5 57 3 21 7.6 6.0 -15.3 18.1 58 3 22 0.3 -3.4 -10.8 11.3 59 3 23 4.2 0.8 -10.6 11.4 60 3 24 -10.4 1.7 -17.9 20.8 61 3 25 -5.7 -0.9 -3.7 6.9 62 3 26 -6.5 1.9 -2.1 7.1 63 3 27 -6.1 -2.6 -13.8 15.3 64 3 28 24.0 7.7 -18.8 31.4 65 3 29 17.7 8.4 -6.2 20.5 66 3 30 12.1 -8.9 -23.9 28.2 67 3 31 2.7 3.6 -10.3 11.2 68 3 32 8.1 9.7 -13.0 18.1 69 3 33 19.5 10.2 12.0 25.0 70 3 34 24.1 11.4 15.1 30.7 71 3 35 35.5 13.9 -16.0 41.3 72 3 36 20.5 14.5 -3.7 25.4 73 3 37 5.8 11.5 -39.6 41.6 74 3 38 16.2 19.8 -12.0 28.3 75 3 39 18.4 7.0 -17.3 26.2 76 3 40 15.7 11.7 -17.8 26.4 77 3 41 10.5 17.6 -4.6 21.0 78 3 42 0.8 5.2 -8.3 9.8 79 3 43 -12.3 2.3 -6.7 14.2 80 3 44 17.2 8.2 -10.4 21.7 81 3 45 8.5 0.3 -6.8 10.9 82 3 46 -3.4 -6.5 -17.6 19.1 83 3 47 -7.4 -13.4 -18.6 24.1 84 3 48 -21.9 -3.1 -45.2 50.4 85 4 1 14.6 -27.8 -16.1 35.3 86 4 2 -18.5 -36.9 -33.7 53.3 87 4 3 -19.4 -30.1 -53.9 64.8 88 4 4 -7.4 -9.7 -72.7 73.7 89 4 5 5.9 -2.2 -34.3 34.8 90 4 6 12.1 -3.3 -24.4 27.4 91 4 7 10.4 -3.8 -0.8 11.1 92 4 8 -7.7 12.8 -25.5 29.6 93 4 9 9.1 6.1 -5.3 12.2 94 4 10 -14.9 6.0 -16.2 22.8 95 4 11 -3.5 12.0 4.5 13.2 96 4 12 3.0 24.5 -1.1 24.7 97 4 13 -2.0 4.4 42.0 42.2 98 4 14 3.6 19.0 6.9 20.6 99 4 15 4.7 -0.2 6.9 8.3 100 4 16 -8.1 22.5 7.5 25.1 101 4 17 8.6 17.0 -13.8 23.5 102 4 18 25.0 -7.7 -0.1 26.2 103 4 19 -2.7 -8.2 -20.8 22.5 104 4 20 -2.2 -4.9 -28.7 29.2 105 4 21 -4.6 -10.6 -13.2 17.6 106 4 22 -51.4 -10.4 5.5 52.8 107 4 23 -35.2 -29.0 -8.3 46.4 108 4 24 19.1 4.8 13.0 23.6 109 4 25 3.6 5.2 34.2 34.8 110 4 26 -18.4 -3.2 9.7 21.0 111 4 27 -17.3 -6.1 -6.0 19.3 112 4 28 -16.8 -23.0 -3.8 28.7 113 4 29 -41.8 -11.3 -68.2 80.7 114 4 30 -31.0 -28.9 -15.2 45.0 115 4 31 -31.0 -28.5 -19.5 46.4 116 4 32 -29.8 -0.2 -30.5 42.6 117 4 33 -21.7 0.0 -3.0 21.9 118 4 34 7.0 -6.1 -15.9 18.4 119 4 35 -26.4 9.6 -26.0 38.3 120 4 36 -23.6 0.6 -16.0 28.5 121 4 37 17.2 11.1 -3.7 20.8 122 4 38 -2.5 -2.0 2.4 4.0 123 4 39 -10.4 0.5 6.3 12.2 124 4 40 6.3 -1.3 -5.7 8.6 125 4 41 -13.5 24.6 -15.6 32.1 126 4 42 0.7 -10.8 -21.9 24.4 127 4 43 -7.6 -14.0 -21.9 27.1 128 4 44 -16.4 4.1 -18.3 24.9 129 4 45 -7.2 -7.6 -33.7 35.3 130 4 46 -22.1 -26.9 -35.3 49.6 131 4 47 -30.0 -40.7 -81.7 96.1 132 4 48 -21.3 -33.4 -32.6 51.3 133 5 1 -20.9 5.6 -2.6 21.8 134 5 2 11.9 12.9 -33.4 37.7 135 5 3 -39.8 2.2 -40.6 56.9 136 5 4 -22.2 -13.8 -11.8 28.7 137 5 5 -23.1 -14.9 -39.1 47.9 138 5 6 -7.0 -5.0 -39.7 40.6 139 5 7 -1.8 7.9 -3.3 8.8 140 5 8 2.8 24.3 -20.9 32.2 141 5 9 5.2 8.9 6.8 12.4 142 5 10 -2.0 26.5 -1.9 26.6 143 5 11 13.3 18.6 -2.6 23.0 144 5 12 -7.1 38.8 2.7 39.5 145 5 13 -4.3 20.2 6.0 21.5 146 5 14 17.7 43.7 -12.8 48.9 147 5 15 13.7 31.7 14.7 37.6 148 5 16 4.6 25.4 -1.2 25.9 149 5 17 -8.5 20.5 29.2 36.7 150 5 18 0.3 -12.1 201.0 201.4 151 5 19 -27.8 -13.0 -20.9 37.1 152 5 20 -25.9 2.5 -22.6 34.5 153 5 21 -8.9 8.5 -5.5 13.5 154 5 22 -13.8 20.9 -19.7 31.9 155 5 23 -3.3 15.7 -16.3 22.9 156 5 24 16.2 6.4 -2.3 17.5 157 5 25 13.5 7.8 -6.6 17.0 158 5 26 -1.1 18.1 -19.2 26.4 159 5 27 4.5 30.0 -14.0 33.4 160 5 28 0.4 -7.6 3.4 8.3 161 5 29 -9.1 0.3 -26.3 27.8 162 5 30 -14.7 -26.7 -10.9 32.4 163 5 31 -22.7 -21.3 -27.5 41.5 164 5 32 -30.3 -21.2 -12.2 39.0 165 5 33 3.0 -8.8 0.6 9.4 166 5 34 -18.4 -5.2 -4.3 19.6 167 5 35 -0.9 20.1 -1.3 20.2 168 5 36 -3.0 11.4 -10.1 15.5 169 5 37 10.2 28.6 -20.8 36.9 170 5 38 1.0 19.1 -18.5 26.6 171 5 39 -3.2 60.7 -53.5 81.0 172 5 40 -9.1 18.9 -12.5 24.4 173 5 41 15.1 26.0 6.7 30.8 174 5 42 -10.8 -10.5 -21.8 26.5 175 5 43 -13.7 -4.0 -39.7 42.2 176 5 44 -5.4 4.1 -32.9 33.6 177 5 45 3.8 2.5 -29.9 30.3 178 5 46 -18.8 -11.3 45.7 50.7 179 5 47 12.4 9.7 -42.6 45.5 180 5 48 -20.8 9.2 -18.0 29.0 181 6 1 -22.3 -15.6 -41.3 49.5 182 6 2 -24.4 -20.8 -53.7 62.5 183 6 3 2.8 -29.5 -32.6 44.1 184 6 4 -40.3 -18.4 -58.6 73.5 185 6 5 -19.2 -16.8 -50.0 56.2 186 6 6 -16.7 -7.6 -35.4 39.9 187 6 7 -10.3 -15.2 -41.0 44.9 188 6 8 -14.8 10.0 -28.9 34.0 189 6 9 12.6 4.9 38.7 41.0 190 6 10 26.7 11.6 20.4 35.6 191 6 11 11.3 5.7 -17.2 21.4 192 6 12 3.3 24.2 -13.1 27.7 193 6 13 8.4 24.0 -22.1 33.7 194 6 14 -3.1 9.7 -27.8 29.6 195 6 15 15.4 -5.1 8.9 18.5 196 6 16 8.4 15.3 27.6 32.6 197 6 17 -29.1 -0.2 -26.2 39.2 198 6 18 -13.3 2.8 -91.3 92.3 199 6 19 -0.3 -11.9 9.5 15.2 200 6 20 -10.5 14.1 25.1 30.6 201 6 21 -54.6 0.9 -74.0 92.0 202 6 22 20.3 -11.1 -3.5 23.4 203 6 23 -8.7 -9.3 26.4 29.3 204 6 24 -21.6 3.0 -0.3 21.8 205 6 25 -37.5 1.2 -37.3 52.9 206 6 26 -29.1 -7.3 -13.6 33.0 207 6 27 -27.7 -10.8 -6.8 30.5 208 6 28 -4.6 36.4 172.1 176.0 209 6 29 -62.8 24.9 -26.1 72.4 210 6 30 -46.7 -11.1 38.9 61.8 211 6 31 -29.9 -13.3 -3.9 32.9 212 6 32 -37.1 -37.3 -7.9 53.2 213 6 33 7.6 -18.1 142.9 144.2 214 6 34 63.3 2.2 43.6 76.9 215 6 35 5.1 -0.5 29.3 29.7 216 6 36 -6.7 37.1 29.4 47.8 217 6 37 -5.3 30.6 38.5 49.5 218 6 38 16.2 14.1 7.1 22.6 219 6 39 39.1 12.3 47.3 62.5 220 6 40 -10.6 39.8 40.6 57.8 221 6 41 -8.8 35.1 0.7 36.2 222 6 42 11.6 10.7 32.1 35.8 223 6 43 -8.4 1.9 34.1 35.1 224 6 44 -15.7 16.2 14.4 26.8 225 6 45 -14.2 19.7 75.5 79.3 226 6 46 19.3 -6.5 41.2 46.0 227 6 47 -26.0 -17.6 -36.1 47.9 228 6 48 -24.0 -17.2 -16.2 33.7 229 7 1 -46.6 49.0 1.3 67.6 230 7 2 -44.8 -1.7 -25.6 51.6 231 7 3 -36.7 -0.5 -14.4 39.4 232 7 4 -23.6 34.9 13.8 44.4 233 7 5 -33.3 -7.4 5.8 34.6 234 7 6 -32.9 29.5 -9.6 45.3 235 7 7 -30.8 17.5 -4.3 35.7 236 7 8 -17.8 41.5 -8.6 46.0 237 7 9 43.5 13.5 52.3 69.4 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15 12 2 49 12 3 1 12 4 -4 12 5 -5 12 6 -7 12 7 0 12 8 17 12 9 3 12 10 -11 12 11 -5 12 12 -7 12 13 13 12 14 14 12 15 3 12 16 12 12 17 -1 12 18 5 12 19 25 12 20 -3 12 21 3 12 22 23 12 23 6 12 24 -4 12 25 -5 12 26 2 12 27 -6 12 28 -9 12 29 -10 12 30 -6 12 31 -13 12 32 2 12 33 3 12 34 -25 12 35 -12 12 36 -9 12 37 14 12 38 -3 12 39 -5 12 40 -10 12 41 -8 12 42 -6 12 43 -9 12 44 0 12 45 1 12 46 -10 12 47 -2 12 48 -2 12 49 -5 12 50 -4 12 51 -2 12 52 -8 12 53 -9 12 54 0 12 55 -5 12 56 -1 12 57 -1 12 58 0 12 59 4 12 60 0 12 61 -2 12 62 0 12 63 2 12 64 -7 12 65 7 12 66 -7 12 67 -13 12 68 0 12 69 -6 Adjuster movements: rms = 30.4 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050421-230700 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1