Reduction started at: 20050213-215257 Reading data from /net/moana/export/data/janw/rxh3/rxh3-20050213-205300.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 = 2402.5 max = 2430.4 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.950 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 2.99316 -0.03564 loimag -3.13965 3.02002 0.01515 hireal -5.00000 4.99756 -0.61296 hiimag -5.00000 4.99756 -0.20034 xpos -2430.44603 2419.92033 -8.27366 ypos -2402.59839 2402.52881 -0.00268 plock160 0.81299 2.26807 1.61637 lorefpwr 0.24902 1.63330 1.20546 losigpwr -4.59473 -0.37842 -4.41214 hirefpwr 0.32959 1.67725 1.26597 hisigpwr -4.49463 4.99756 -0.67069 encltemp 31.68945 32.88574 32.18443 flags 0.00000 256.00000 2.76738 phi-lock -1.25732 0.11475 -0.58185 sindex 0.00000 128.00000 63.61104 time 0.00000 2947.99698 1473.09589 zeropt -0.00732 -0.00244 -0.00489 !!!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 = 40.00601 arcsec Mean row spacing = 40.00603 arcsec (alternate estimator) Mean tracking incline = 0.05092 arcsec Mean pointing range = 0.62386 arcsec Mean pointing rms = 0.10938 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (2.3, 14.1 ) 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: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22682 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22682 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 = 2430.45 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 = 2.96039 at (0.0, 0.0) arcsec Real: mean = 0.00228903 sum of squares = 992.278 Imag: mean = -0.00102231 sum of squares = 1019.39 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 = 2.91486 at (0.0, 0.0) arcsec Real: mean = 0.00181792 sum of squares = 1070.35 Imag: mean = -0.00124773 sum of squares = 942.057 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 = 2.88556 at (0.0, 0.0) arcsec Real: mean = 0.00150252 sum of squares = 1102.45 Imag: mean = -0.0015069 sum of squares = 909.25 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 = 2.88659 at (0.0, 0.0) arcsec Real: mean = 0.00131494 sum of squares = 1066.55 Imag: mean = -0.00189834 sum of squares = 944.332 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 = 2.89295 at (0.0, 0.0) arcsec Real: mean = 0.00133023 sum of squares = 990.837 Imag: mean = -0.00234617 sum of squares = 1018.69 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 = 2.91387 at (0.0, 0.0) arcsec Real: mean = 0.00151839 sum of squares = 924.236 Imag: mean = -0.00274352 sum of squares = 1084.58 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 = 2.92702 at (0.0, 0.0) arcsec Real: mean = 0.00184533 sum of squares = 912.596 Imag: mean = -0.00298599 sum of squares = 1095.99 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 = 2.96808 at (0.0, 0.0) arcsec Real: mean = 0.00214835 sum of squares = 966.941 Imag: mean = -0.00315195 sum of squares = 1042.96 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 = 3.00785 at (0.0, 0.0) arcsec Real: mean = 0.00261283 sum of squares = 1050.08 Imag: mean = -0.00328225 sum of squares = 962.091 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 = 3.05408 at (0.0, 0.0) arcsec Real: mean = 0.0032163 sum of squares = 1104.66 Imag: mean = -0.00307326 sum of squares = 911.522 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 = 3.07247 at (0.0, 0.0) arcsec Real: mean = 0.00370025 sum of squares = 1088.29 Imag: mean = -0.00254786 sum of squares = 932.809 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 = 3.07943 at (0.0, 0.0) arcsec Real: mean = 0.00366491 sum of squares = 1012.59 Imag: mean = -0.0017744 sum of squares = 1013.57 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 = 3.05281 at (0.0, 0.0) arcsec Real: mean = 0.0032466 sum of squares = 938.271 Imag: mean = -0.00131373 sum of squares = 1090.67 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 = 3.02349 at (0.0, 0.0) arcsec Real: mean = 0.00275993 sum of squares = 920.867 Imag: mean = -0.00128155 sum of squares = 1109.22 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 = 2.98342 at (0.0, 0.0) arcsec Real: mean = 0.00258103 sum of squares = 973.365 Imag: mean = -0.00142237 sum of squares = 1057.77 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 = 2.96445 at (0.0, 0.0) arcsec Real: mean = 0.00249947 sum of squares = 1058.17 Imag: mean = -0.00141215 sum of squares = 976.467 Masking frequency index 0 Mask scale size = 3.05893 Masking frequency index 1 Mask scale size = 3.05901 Masking frequency index 2 Mask scale size = 3.05908 Masking frequency index 3 Mask scale size = 3.05916 Masking frequency index 4 Mask scale size = 3.05924 Masking frequency index 5 Mask scale size = 3.05931 Masking frequency index 6 Mask scale size = 3.05939 Masking frequency index 7 Mask scale size = 3.05947 Masking frequency index 8 Mask scale size = 3.05954 Masking frequency index 9 Mask scale size = 3.05962 Masking frequency index 10 Mask scale size = 3.05969 Masking frequency index 11 Mask scale size = 3.05977 Masking frequency index 12 Mask scale size = 3.05985 Masking frequency index 13 Mask scale size = 3.05992 Masking frequency index 14 Mask scale size = 3.06 Masking frequency index 15 Mask scale size = 3.06007 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: 0.180664 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.197754 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.180664 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: 0.19043 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.0170898 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 1.5625 107.63 Freq 1: Shift, scale = 1.1315 109.24 Freq 2: Shift, scale = 0.69765 109.77 Freq 3: Shift, scale = 0.26196 109.41 Freq 4: Shift, scale = -0.17049 108.1 Freq 5: Shift, scale = -0.60098 106.45 Freq 6: Shift, scale = -1.0319 104.79 Freq 7: Shift, scale = -1.4694 103.35 Freq 8: Shift, scale = -1.9114 102.52 Freq 9: Shift, scale = -2.3545 102.2 Freq 10: Shift, scale = -2.8039 102.52 Freq 11: Shift, scale = 3.0323 103.5 Freq 12: Shift, scale = 2.5851 105.11 Freq 13: Shift, scale = 2.1435 107.14 Freq 14: Shift, scale = 1.706 108.72 Freq 15: Shift, scale = 1.2718 110.19 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: -0.161 radians x offset: 0.0043 arcsec y offset: -0.0301 arcsec defocus: 0.000349 mm Estimated x pointing error is 2.304 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.07 arcsec (used 14.1 arcsec) Estimated defocus error is 2.95 mm (used 2.95 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.153 radians x offset: -0.00444 arcsec y offset: -0.0644 arcsec defocus: -0.000985 mm Estimated x pointing error is 2.296 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.04 arcsec (used 14.1 arcsec) Estimated defocus error is 2.949 mm (used 2.95 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.148 radians x offset: -0.0243 arcsec y offset: -0.0937 arcsec defocus: -0.00169 mm Estimated x pointing error is 2.276 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.01 arcsec (used 14.1 arcsec) Estimated defocus error is 2.948 mm (used 2.95 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.145 radians x offset: -0.0251 arcsec y offset: -0.0938 arcsec defocus: -0.00163 mm Estimated x pointing error is 2.275 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.01 arcsec (used 14.1 arcsec) Estimated defocus error is 2.948 mm (used 2.95 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.139 radians x offset: -0.0223 arcsec y offset: -0.0834 arcsec defocus: -0.0021 mm Estimated x pointing error is 2.278 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.02 arcsec (used 14.1 arcsec) Estimated defocus error is 2.948 mm (used 2.95 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.132 radians x offset: -0.00398 arcsec y offset: -0.0708 arcsec defocus: -0.00168 mm Estimated x pointing error is 2.296 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.03 arcsec (used 14.1 arcsec) Estimated defocus error is 2.948 mm (used 2.95 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.127 radians x offset: 0.00888 arcsec y offset: -0.0383 arcsec defocus: -0.00473 mm Estimated x pointing error is 2.309 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.06 arcsec (used 14.1 arcsec) Estimated defocus error is 2.945 mm (used 2.95 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.128 radians x offset: 0.00454 arcsec y offset: -0.0159 arcsec defocus: -0.00594 mm Estimated x pointing error is 2.305 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.08 arcsec (used 14.1 arcsec) Estimated defocus error is 2.944 mm (used 2.95 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.134 radians x offset: 0.00626 arcsec y offset: 0.00187 arcsec defocus: -0.00683 mm Estimated x pointing error is 2.306 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.1 arcsec (used 14.1 arcsec) Estimated defocus error is 2.943 mm (used 2.95 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.141 radians x offset: -0.00892 arcsec y offset: -0.000964 arcsec defocus: -0.00846 mm Estimated x pointing error is 2.291 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.1 arcsec (used 14.1 arcsec) Estimated defocus error is 2.942 mm (used 2.95 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.151 radians x offset: -0.0203 arcsec y offset: -0.0104 arcsec defocus: -0.00672 mm Estimated x pointing error is 2.28 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.09 arcsec (used 14.1 arcsec) Estimated defocus error is 2.943 mm (used 2.95 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.159 radians x offset: -0.017 arcsec y offset: -0.0436 arcsec defocus: -0.0053 mm Estimated x pointing error is 2.283 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.06 arcsec (used 14.1 arcsec) Estimated defocus error is 2.945 mm (used 2.95 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.167 radians x offset: 0.00327 arcsec y offset: -0.0742 arcsec defocus: -0.00391 mm Estimated x pointing error is 2.303 arcsec (used 2.3 arcsec) Estimated y pointing error is 14.03 arcsec (used 14.1 arcsec) Estimated defocus error is 2.946 mm (used 2.95 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.17 radians x offset: 0.0332 arcsec y offset: -0.102 arcsec defocus: -0.00385 mm Estimated x pointing error is 2.333 arcsec (used 2.3 arcsec) Estimated y pointing error is 14 arcsec (used 14.1 arcsec) Estimated defocus error is 2.946 mm (used 2.95 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.171 radians x offset: 0.0598 arcsec y offset: -0.129 arcsec defocus: -0.00647 mm Estimated x pointing error is 2.36 arcsec (used 2.3 arcsec) Estimated y pointing error is 13.97 arcsec (used 14.1 arcsec) Estimated defocus error is 2.944 mm (used 2.95 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.168 radians x offset: 0.0789 arcsec y offset: -0.139 arcsec defocus: -0.00904 mm Estimated x pointing error is 2.379 arcsec (used 2.3 arcsec) Estimated y pointing error is 13.96 arcsec (used 14.1 arcsec) Estimated defocus error is 2.941 mm (used 2.95 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 -0.00048 piston 1 1 -0.00215 tilt_x 1 -1 0.01545 tilt_y 2 2 0.07661 astigmatism_0 2 0 0.00007 curvature 2 -2 -0.00038 astigmatism45 3 3 0.00706 trefoil_0 3 1 -0.02535 coma_x 3 -1 0.04564 coma_y 3 -3 -0.01469 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 -0.00061 piston 1 1 -0.00390 tilt_x 1 -1 0.01471 tilt_y 2 2 0.07599 astigmatism_0 2 0 -0.00040 curvature 2 -2 -0.00001 astigmatism45 3 3 0.00905 trefoil_0 3 1 -0.03013 coma_x 3 -1 0.04317 coma_y 3 -3 -0.01350 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 -0.00514 tilt_x 1 -1 0.01454 tilt_y 2 2 0.07637 astigmatism_0 2 0 -0.00068 curvature 2 -2 -0.00083 astigmatism45 3 3 0.01074 trefoil_0 3 1 -0.03368 coma_x 3 -1 0.04235 coma_y 3 -3 -0.01364 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 -0.00073 piston 1 1 -0.00549 tilt_x 1 -1 0.01461 tilt_y 2 2 0.07723 astigmatism_0 2 0 -0.00073 curvature 2 -2 -0.00148 astigmatism45 3 3 0.01064 trefoil_0 3 1 -0.03500 coma_x 3 -1 0.04217 coma_y 3 -3 -0.01459 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 -0.00068 piston 1 1 -0.00504 tilt_x 1 -1 0.01536 tilt_y 2 2 0.07777 astigmatism_0 2 0 -0.00037 curvature 2 -2 -0.00251 astigmatism45 3 3 0.00951 trefoil_0 3 1 -0.03373 coma_x 3 -1 0.04413 coma_y 3 -3 -0.01676 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 -0.00061 piston 1 1 -0.00417 tilt_x 1 -1 0.01644 tilt_y 2 2 0.07750 astigmatism_0 2 0 0.00016 curvature 2 -2 -0.00314 astigmatism45 3 3 0.00783 trefoil_0 3 1 -0.03087 coma_x 3 -1 0.04717 coma_y 3 -3 -0.01832 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 -0.00055 piston 1 1 -0.00275 tilt_x 1 -1 0.01763 tilt_y 2 2 0.07775 astigmatism_0 2 0 0.00061 curvature 2 -2 -0.00294 astigmatism45 3 3 0.00570 trefoil_0 3 1 -0.02662 coma_x 3 -1 0.05056 coma_y 3 -3 -0.01912 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 -0.00053 piston 1 1 -0.00198 tilt_x 1 -1 0.01859 tilt_y 2 2 0.07801 astigmatism_0 2 0 0.00075 curvature 2 -2 -0.00171 astigmatism45 3 3 0.00454 trefoil_0 3 1 -0.02428 coma_x 3 -1 0.05308 coma_y 3 -3 -0.01928 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 -0.00048 piston 1 1 -0.00095 tilt_x 1 -1 0.01921 tilt_y 2 2 0.07827 astigmatism_0 2 0 0.00086 curvature 2 -2 -0.00094 astigmatism45 3 3 0.00300 trefoil_0 3 1 -0.02148 coma_x 3 -1 0.05508 coma_y 3 -3 -0.01849 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 -0.00044 piston 1 1 -0.00067 tilt_x 1 -1 0.01886 tilt_y 2 2 0.07862 astigmatism_0 2 0 0.00071 curvature 2 -2 -0.00075 astigmatism45 3 3 0.00309 trefoil_0 3 1 -0.02109 coma_x 3 -1 0.05446 coma_y 3 -3 -0.01771 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 -0.00046 piston 1 1 -0.00138 tilt_x 1 -1 0.01807 tilt_y 2 2 0.07839 astigmatism_0 2 0 0.00035 curvature 2 -2 0.00027 astigmatism45 3 3 0.00429 trefoil_0 3 1 -0.02330 coma_x 3 -1 0.05219 coma_y 3 -3 -0.01480 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 -0.00049 piston 1 1 -0.00227 tilt_x 1 -1 0.01718 tilt_y 2 2 0.07766 astigmatism_0 2 0 -0.00000 curvature 2 -2 -0.00062 astigmatism45 3 3 0.00563 trefoil_0 3 1 -0.02603 coma_x 3 -1 0.04991 coma_y 3 -3 -0.01302 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 -0.00056 piston 1 1 -0.00257 tilt_x 1 -1 0.01632 tilt_y 2 2 0.07811 astigmatism_0 2 0 -0.00028 curvature 2 -2 -0.00052 astigmatism45 3 3 0.00711 trefoil_0 3 1 -0.02722 coma_x 3 -1 0.04742 coma_y 3 -3 -0.01123 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 -0.00062 piston 1 1 -0.00281 tilt_x 1 -1 0.01582 tilt_y 2 2 0.07863 astigmatism_0 2 0 -0.00048 curvature 2 -2 -0.00124 astigmatism45 3 3 0.00699 trefoil_0 3 1 -0.02828 coma_x 3 -1 0.04604 coma_y 3 -3 -0.01108 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 -0.00067 piston 1 1 -0.00251 tilt_x 1 -1 0.01574 tilt_y 2 2 0.07959 astigmatism_0 2 0 -0.00053 curvature 2 -2 -0.00231 astigmatism45 3 3 0.00623 trefoil_0 3 1 -0.02781 coma_x 3 -1 0.04586 coma_y 3 -3 -0.01223 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 -0.00071 piston 1 1 -0.00268 tilt_x 1 -1 0.01654 tilt_y 2 2 0.08125 astigmatism_0 2 0 -0.00056 curvature 2 -2 -0.00320 astigmatism45 3 3 0.00596 trefoil_0 3 1 -0.02872 coma_x 3 -1 0.04814 coma_y 3 -3 -0.01578 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: 33.8 22.1 23.5 26.2 22.6 26.4 35.2 28.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33 20.6 22.5 24.9 22.2 23.2 33 26.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.01 5.7 7.33 8.03 8.74 11.2 16.8 11.1 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.8 21.7 23.3 24.5 22.4 26 35.1 28.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32 20.2 22.3 23.1 21.9 22.9 33.2 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.04 5.74 7.37 8.04 8.7 11.1 16.7 11.1 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.8 21.6 22.9 23.3 22.2 26 34.9 28 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31 20.1 22 21.7 21.6 22.7 33.2 26.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.12 5.89 7.55 8.2 8.79 11.2 16.9 11.2 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.3 21.3 22.4 22.8 22.6 26 34.9 28.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.4 19.8 21.5 21.1 21.9 22.5 33.2 26.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.16 5.96 7.64 8.31 8.9 11.3 17.1 11.3 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29 21.2 21.8 23 23 26.3 34.8 28.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28 19.6 21 21.4 22.4 22.5 33 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.2 6.04 7.74 8.42 9 11.4 17.3 11.5 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28 21.3 21.5 23.6 23.6 26.7 34.8 28.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 19.7 20.7 22.2 23.1 22.8 32.8 27 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.25 6.13 7.84 8.5 9.03 11.4 17.4 11.5 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.4 22 21.2 24.3 23.7 27.1 34.9 29 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 20.2 20.2 23.1 23.4 23.2 32.9 27.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.29 6.21 7.94 8.59 9.09 11.4 17.5 11.6 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.6 22.4 21 25.1 23.7 27.4 35.9 29.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.4 20.5 19.8 23.9 23.4 23.6 33.6 27.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.36 6.33 8.1 8.73 9.17 11.5 17.6 11.7 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.7 22.9 22.3 26.1 23.9 27.7 36.8 29.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 21 21 25 23.5 24 34.4 28.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.4 6.41 8.19 8.81 9.21 11.5 17.7 11.7 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.2 23.5 23.7 27.5 24.1 27.9 37.5 30.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.1 21.7 22.5 26.5 23.6 24.5 35.1 28.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.36 6.34 8.11 8.74 9.2 11.5 17.6 11.7 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.1 23.7 24.7 28.9 24.1 27.9 37.5 30.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.2 21.9 23.6 28 23.6 24.6 35.2 28.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.29 6.21 7.95 8.58 9.09 11.4 17.4 11.6 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.7 23.5 25.4 32.3 23.8 27.6 37.2 30.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.9 21.8 24.5 31.4 23.3 24.4 34.9 29.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.24 6.12 7.83 8.46 8.97 11.3 17.2 11.4 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.4 22.8 25.5 34.8 23.3 27 36.3 30.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.6 21.2 24.7 33.5 22.9 23.7 34.1 29 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.15 5.95 7.64 8.3 8.93 11.3 17.1 11.3 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.9 22.3 24.1 29.7 22.9 26.5 35.3 29.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.2 20.8 23.4 28.2 22.5 23.1 33.1 27.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.12 5.89 7.57 8.26 8.95 11.4 17.2 11.4 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.4 21.7 23 27.2 22.6 26.5 34.5 28.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.6 20.2 22.1 25.7 22.3 22.7 32.2 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.09 5.85 7.54 8.26 9.02 11.5 17.3 11.5 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.8 21.4 23.2 25.5 22.5 27.1 34.2 28.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.9 19.8 22.2 23.9 22.3 23.1 31.8 26.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.23 6.11 7.85 8.59 9.3 11.8 17.9 11.8 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 27.8 20.8 19.9 21.6 21.4 25.4 34 26.9 Mean deviation is 0.81009298207397862 microns Taper = 10 dB, Ruze illumination-weighted rms = 26.2 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 = 24.3 micron Centre pixel: 64.0 64.0 Value = 2751.9 (estimate), 3426.12 (perfect) Strehl = 0.64515 Strehl ratio estimate = 0.6452 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 = 24.0 micron Centre pixel: 64.0 64.0 Value = 2277.68 (estimate), 3426.12 (perfect) Strehl = 0.441956 Strehl ratio estimate = 0.442 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 -24.5 21.4 29.7 44.0 2 1 2 -23.8 29.3 28.3 47.1 3 1 3 -19.6 38.1 -22.6 48.5 4 1 4 -27.8 1.5 -6.1 28.5 5 1 5 -39.5 21.3 31.1 54.6 6 1 6 -62.7 -1.4 -8.8 63.3 7 1 7 -55.2 -10.1 23.1 60.7 8 1 8 -55.5 18.0 45.9 74.2 9 1 9 -70.1 9.2 14.7 72.2 10 1 10 -36.6 3.6 32.5 49.1 11 1 11 3.7 7.8 32.4 33.6 12 1 12 -2.5 37.0 26.0 45.3 13 2 1 13.9 3.7 0.3 14.4 14 2 2 5.9 31.0 18.4 36.6 15 2 3 43.3 -7.8 6.7 44.5 16 2 4 24.5 14.6 14.9 32.2 17 2 5 5.0 9.4 22.3 24.7 18 2 6 0.4 47.3 51.4 69.9 19 2 7 11.7 28.3 20.6 37.0 20 2 8 26.9 31.7 14.5 44.0 21 2 9 3.9 10.1 10.9 15.3 22 2 10 3.6 9.9 -6.6 12.5 23 2 11 -0.5 7.9 1.3 8.1 24 2 12 -15.6 11.6 1.7 19.5 25 2 13 -25.3 -23.4 -21.7 40.7 26 2 14 -17.1 -3.4 -10.1 20.2 27 2 15 -15.5 -9.6 1.3 18.3 28 2 16 17.4 -15.3 -2.2 23.3 29 2 17 14.8 4.0 18.5 24.0 30 2 18 2.6 23.2 35.6 42.5 31 2 19 17.0 5.5 20.7 27.4 32 2 20 17.3 3.3 15.9 23.8 33 2 21 21.5 11.0 12.7 27.3 34 2 22 62.7 18.3 12.0 66.4 35 2 23 37.6 1.1 2.1 37.7 36 2 24 16.1 -4.2 7.8 18.4 37 3 1 2.1 13.3 32.4 35.1 38 3 2 3.3 9.8 27.0 28.9 39 3 3 -9.5 8.1 26.3 29.1 40 3 4 5.7 -2.4 29.0 29.6 41 3 5 2.6 13.6 30.4 33.4 42 3 6 -2.2 4.2 13.5 14.3 43 3 7 -2.0 3.6 1.0 4.2 44 3 8 2.6 4.2 10.2 11.3 45 3 9 17.1 3.0 20.9 27.2 46 3 10 -1.7 14.6 4.5 15.4 47 3 11 38.8 23.4 27.1 52.8 48 3 12 5.3 42.8 21.9 48.4 49 3 13 -4.1 30.7 20.4 37.1 50 3 14 15.8 9.6 13.0 22.6 51 3 15 -3.4 11.2 18.1 21.6 52 3 16 16.7 11.6 24.1 31.5 53 3 17 9.4 19.6 12.6 25.2 54 3 18 14.1 12.7 13.9 23.5 55 3 19 9.5 16.3 4.8 19.5 56 3 20 23.0 4.3 -4.3 23.8 57 3 21 12.5 -5.4 6.6 15.2 58 3 22 -18.2 -11.1 -4.9 21.8 59 3 23 8.4 -5.0 -12.8 16.1 60 3 24 -35.0 -18.4 -18.3 43.5 61 3 25 -20.7 -23.1 -14.4 34.2 62 3 26 -16.2 -9.9 -19.3 27.1 63 3 27 -11.7 -6.7 2.9 13.8 64 3 28 4.6 -11.7 1.4 12.7 65 3 29 22.8 -4.4 -11.1 25.7 66 3 30 -10.2 -14.5 -20.4 27.0 67 3 31 3.0 -1.9 -10.8 11.4 68 3 32 11.6 10.9 1.1 16.0 69 3 33 30.5 3.1 9.4 32.0 70 3 34 8.4 11.1 2.8 14.2 71 3 35 45.7 10.5 2.6 47.0 72 3 36 8.2 21.9 -7.1 24.5 73 3 37 34.8 25.7 22.1 48.6 74 3 38 29.2 17.8 18.5 38.9 75 3 39 29.0 22.3 15.6 39.8 76 3 40 24.2 1.9 14.8 28.4 77 3 41 23.9 9.4 -2.2 25.8 78 3 42 -3.1 15.5 -1.5 15.8 79 3 43 8.7 16.4 5.6 19.4 80 3 44 11.0 11.5 7.3 17.5 81 3 45 21.8 -1.3 22.4 31.2 82 3 46 6.1 8.4 13.7 17.2 83 3 47 26.5 9.2 32.2 42.7 84 3 48 -9.0 12.2 24.4 28.7 85 4 1 18.7 -21.8 -19.2 34.6 86 4 2 -22.5 -7.9 -3.9 24.1 87 4 3 7.5 -19.5 -33.3 39.3 88 4 4 11.6 -11.9 -24.1 29.3 89 4 5 18.8 -5.3 -4.9 20.1 90 4 6 14.2 4.6 11.7 19.0 91 4 7 8.9 6.1 19.2 22.0 92 4 8 -1.6 8.0 -2.4 8.5 93 4 9 7.7 2.5 6.8 10.6 94 4 10 6.8 7.2 4.8 11.0 95 4 11 -14.5 28.0 30.3 43.7 96 4 12 38.4 21.1 5.8 44.2 97 4 13 15.9 11.1 2.9 19.6 98 4 14 -20.8 12.2 3.9 24.4 99 4 15 6.7 6.9 12.9 16.2 100 4 16 5.4 -3.8 17.0 18.2 101 4 17 10.5 8.9 12.8 18.8 102 4 18 19.1 -14.6 2.2 24.1 103 4 19 -1.4 -13.3 -16.3 21.1 104 4 20 -19.8 -18.3 -1.4 27.0 105 4 21 -17.6 -26.8 -3.4 32.2 106 4 22 3.6 -16.0 -10.5 19.5 107 4 23 -24.4 -33.0 -29.0 50.2 108 4 24 41.9 -19.6 2.2 46.3 109 4 25 35.5 -21.0 38.3 56.3 110 4 26 -31.3 -3.2 17.8 36.2 111 4 27 -36.7 -13.9 -16.0 42.3 112 4 28 -26.4 -21.7 -10.6 35.8 113 4 29 -30.8 -20.4 -57.7 68.5 114 4 30 -30.4 -28.9 -17.0 45.3 115 4 31 -0.7 -30.2 -4.0 30.5 116 4 32 -11.6 -8.1 -15.6 21.1 117 4 33 -7.8 -17.2 -15.9 24.7 118 4 34 5.0 4.7 -1.4 7.0 119 4 35 -44.4 1.1 -10.7 45.7 120 4 36 -12.0 -2.8 6.5 13.9 121 4 37 43.2 6.2 12.7 45.5 122 4 38 -5.1 8.9 19.8 22.3 123 4 39 2.6 -2.1 9.1 9.7 124 4 40 -0.5 -10.0 9.8 14.0 125 4 41 -14.0 -8.7 4.7 17.1 126 4 42 10.9 -8.0 8.0 15.7 127 4 43 11.3 -7.1 22.5 26.2 128 4 44 1.7 -1.8 -0.0 2.4 129 4 45 -5.6 -8.1 -4.8 11.0 130 4 46 -1.1 -19.5 -14.4 24.3 131 4 47 -20.8 -15.3 -56.5 62.1 132 4 48 13.2 -23.3 -21.4 34.3 133 5 1 -28.4 -22.2 10.0 37.4 134 5 2 4.6 23.1 -26.7 35.6 135 5 3 -29.8 -17.3 -43.1 55.2 136 5 4 -12.4 -18.6 18.6 29.1 137 5 5 -13.0 -13.2 1.2 18.6 138 5 6 6.4 -3.9 -24.9 26.0 139 5 7 36.4 -12.1 -9.0 39.4 140 5 8 18.1 8.3 17.2 26.3 141 5 9 3.8 6.3 22.7 23.8 142 5 10 10.2 18.9 7.2 22.7 143 5 11 23.2 6.8 5.0 24.7 144 5 12 -6.2 2.3 20.0 21.1 145 5 13 -1.2 3.2 19.2 19.5 146 5 14 11.7 25.3 -6.0 28.5 147 5 15 0.9 19.6 20.0 28.1 148 5 16 2.9 -1.6 4.3 5.4 149 5 17 -0.1 -18.1 -29.2 34.3 150 5 18 -9.8 -20.0 188.8 190.1 151 5 19 -20.2 -15.5 8.9 26.9 152 5 20 -5.8 -4.4 -2.8 7.8 153 5 21 -8.2 -13.0 -10.8 18.7 154 5 22 -1.8 12.3 -38.6 40.6 155 5 23 6.9 4.8 -38.3 39.2 156 5 24 -4.9 -9.9 -31.0 32.9 157 5 25 -6.3 -13.3 -23.8 28.0 158 5 26 -4.2 -4.6 -37.4 38.0 159 5 27 -0.6 4.0 2.6 4.8 160 5 28 -4.1 -12.6 3.6 13.7 161 5 29 -16.8 -9.1 0.8 19.1 162 5 30 -9.5 -10.1 -13.0 19.0 163 5 31 -14.9 -8.2 -3.3 17.3 164 5 32 -13.2 -20.7 -10.8 26.8 165 5 33 -10.5 -36.8 5.0 38.6 166 5 34 -26.7 10.2 -27.7 39.8 167 5 35 -15.9 9.5 -18.0 25.8 168 5 36 0.1 10.7 19.7 22.4 169 5 37 -10.1 3.7 12.5 16.5 170 5 38 -2.0 10.4 -15.4 18.7 171 5 39 -2.3 23.8 -41.6 48.0 172 5 40 -7.0 -10.5 -8.6 15.3 173 5 41 -3.3 -9.0 -12.7 15.9 174 5 42 2.8 -13.1 -3.7 13.9 175 5 43 3.9 -10.2 -18.4 21.4 176 5 44 -8.1 -17.3 -27.7 33.6 177 5 45 3.9 -22.8 -33.3 40.6 178 5 46 -12.8 -31.2 3.2 33.9 179 5 47 4.0 -4.5 -25.1 25.8 180 5 48 -16.8 -25.5 6.6 31.2 181 6 1 -28.2 -55.8 -28.0 68.6 182 6 2 -14.6 -37.6 -52.1 65.9 183 6 3 9.1 -39.8 -9.7 42.0 184 6 4 -11.3 -30.9 -16.3 36.7 185 6 5 -2.8 -14.9 -16.5 22.4 186 6 6 -17.6 -24.5 -0.7 30.2 187 6 7 -9.9 -22.6 5.5 25.3 188 6 8 4.9 9.7 -32.6 34.3 189 6 9 21.9 12.9 74.2 78.4 190 6 10 53.4 10.5 45.0 70.6 191 6 11 3.4 4.6 4.8 7.5 192 6 12 7.8 6.8 13.3 16.9 193 6 13 7.7 18.1 29.6 35.5 194 6 14 -6.8 -1.3 13.1 14.8 195 6 15 31.2 7.7 18.2 37.0 196 6 16 18.5 -24.5 21.0 37.1 197 6 17 -3.7 -14.8 9.2 17.8 198 6 18 -5.8 -17.8 30.6 35.9 199 6 19 -16.8 -14.2 21.8 31.0 200 6 20 6.4 -18.0 -2.1 19.2 201 6 21 -46.3 -19.1 -58.5 76.9 202 6 22 5.7 -21.0 28.5 35.8 203 6 23 -33.3 -10.6 -15.6 38.3 204 6 24 -27.2 -30.0 -4.5 40.8 205 6 25 -19.7 -27.4 3.0 33.9 206 6 26 -12.2 -8.1 -17.4 22.8 207 6 27 17.8 -21.8 19.2 34.1 208 6 28 18.0 26.8 163.3 166.5 209 6 29 3.8 6.5 34.9 35.7 210 6 30 -7.0 -10.0 46.2 47.8 211 6 31 -1.0 -6.6 40.0 40.5 212 6 32 -2.1 0.8 3.9 4.5 213 6 33 -0.1 -14.1 122.8 123.6 214 6 34 60.0 4.4 68.0 90.8 215 6 35 -9.8 9.5 34.6 37.2 216 6 36 5.2 48.0 40.8 63.2 217 6 37 -5.1 19.9 40.2 45.1 218 6 38 9.0 13.3 21.3 26.7 219 6 39 31.2 -1.3 41.0 51.6 220 6 40 -10.5 3.4 64.6 65.5 221 6 41 -16.9 -0.2 9.6 19.4 222 6 42 -26.6 -11.9 21.2 36.0 223 6 43 -23.6 -11.4 -1.6 26.3 224 6 44 -29.4 -15.7 -6.8 34.0 225 6 45 -32.3 -38.1 58.6 77.0 226 6 46 -10.4 -45.5 27.6 54.2 227 6 47 -25.4 -36.4 -31.7 54.5 228 6 48 -29.9 -59.6 -34.3 75.0 229 7 1 -47.2 -30.9 -42.4 70.6 230 7 2 -23.6 -36.4 -41.1 59.7 231 7 3 -8.7 -48.5 4.5 49.4 232 7 4 -10.0 27.5 24.8 38.4 233 7 5 6.8 -10.5 77.3 78.3 234 7 6 2.6 22.3 59.7 63.8 235 7 7 -20.8 17.8 40.2 48.7 236 7 8 -18.8 28.0 10.2 35.2 237 7 9 41.9 -4.6 76.3 87.2 238 7 10 41.3 35.6 48.3 72.8 239 7 11 8.0 46.5 6.0 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46 -0.4 -18.0 -1.6 18.1 275 7 47 -11.1 -19.3 -38.8 44.7 276 7 48 -26.9 95.7 -23.0 102.0 Creating sector-motor-move file sector motor steps 1 1 7 1 2 8 1 3 -3 1 4 -4 1 5 -9 1 6 -3 1 7 1 1 8 -14 1 9 -2 1 10 -2 1 11 -12 1 12 2 1 13 -12 1 14 -11 1 15 -7 1 16 -15 1 17 -11 1 18 -4 1 19 -13 1 20 -9 1 21 -14 1 22 -8 1 23 -17 1 24 -8 1 25 5 1 26 -5 1 27 -3 1 28 -7 1 29 -3 1 30 3 1 31 -13 1 32 -5 1 33 -9 1 34 -10 1 35 -5 1 36 2 1 37 -8 1 38 7 1 39 1 1 40 -1 1 41 -2 1 42 -6 1 43 3 1 44 -6 1 45 -8 1 46 -5 1 47 -6 1 48 5 1 49 8 1 50 2 1 51 -2 1 52 5 1 53 9 1 54 1 1 55 8 1 56 3 1 57 1 1 58 6 1 59 -7 1 60 9 1 61 9 1 62 4 1 63 0 1 64 -2 1 65 4 1 66 0 1 67 8 1 68 0 1 69 1 2 1 3 2 2 8 2 3 -5 2 4 -9 2 5 2 2 6 1 2 7 12 2 8 5 2 9 -6 2 10 1 2 11 -6 2 12 -3 2 13 18 2 14 6 2 15 0 2 16 0 2 17 -7 2 18 -5 2 19 23 2 20 -3 2 21 2 2 22 -5 2 23 -4 2 24 0 2 25 5 2 26 2 2 27 5 2 28 0 2 29 2 2 30 0 2 31 -2 2 32 -3 2 33 11 2 34 5 2 35 1 2 36 2 2 37 -7 2 38 -1 2 39 1 2 40 3 2 41 1 2 42 4 2 43 0 2 44 -4 2 45 -3 2 46 -1 2 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16 8 12 17 -13 12 18 -3 12 19 20 12 20 -16 12 21 0 12 22 17 12 23 -11 12 24 -9 12 25 2 12 26 -7 12 27 -5 12 28 -6 12 29 -7 12 30 4 12 31 -7 12 32 -1 12 33 1 12 34 -17 12 35 -4 12 36 -6 12 37 0 12 38 -9 12 39 -3 12 40 -4 12 41 -5 12 42 0 12 43 -10 12 44 -6 12 45 1 12 46 -1 12 47 -2 12 48 -1 12 49 9 12 50 2 12 51 8 12 52 2 12 53 -1 12 54 4 12 55 4 12 56 2 12 57 1 12 58 11 12 59 0 12 60 7 12 61 6 12 62 0 12 63 6 12 64 1 12 65 11 12 66 0 12 67 7 12 68 3 12 69 -2 Adjuster movements: rms = 28.1 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050213-215850 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1