Reduction started at: 20070925-150654 Reading data from /net/moana/export/data/janw/janw/rxh3/rxh3-20070830-175217.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 = 2403.4 max = 2432.5 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 34.000 mm ----------------- Data Summary --------------------- Number of samples: 370025 This is a 80 GHz map Number of frequencies: 16 Frequencies (GHz): 80.344000 80.345000 80.346000 80.348000 80.350000 80.351000 80.352000 80.354000 80.356000 80.357000 80.358000 80.360000 80.362000 80.363000 80.364000 80.366000 item min max mean loreal -3.09570 3.13965 0.03323 loimag -3.29346 3.10059 -0.04489 hireal -5.00000 4.99756 0.77133 hiimag -5.00000 4.99756 0.11119 xpos -2432.49041 2417.07563 -11.74048 ypos -2403.35510 2403.49905 -0.00441 plock160 1.33301 2.57568 2.02311 lorefpwr 0.43945 1.60400 1.22139 losigpwr -4.58984 -0.13428 -4.40969 hirefpwr 0.50293 1.65771 1.27299 hisigpwr -4.49219 4.99756 -0.58640 encltemp 32.05566 34.59473 32.64735 flags 0.00000 256.00000 2.76738 phi-lock -1.01074 0.17334 -0.42272 sindex 0.00000 128.00000 63.61104 time 0.00000 2947.98727 1473.09862 zeropt 0.00000 0.00488 0.00277 !!!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 = 40.00665 arcsec Mean row spacing = 40.00667 arcsec (alternate estimator) Mean tracking incline = -0.05007 arcsec Mean pointing range = 0.75665 arcsec Mean pointing rms = 0.12832 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (13.0, 14.0 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Doing geometric phase correction Status bits counts: bit: 0 1 2 3 4 5 6 7 8 set: 0 0 0 0 0 0 0 0 4000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22679 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22679 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 = 2432.49 arcsec Grid extent = 2540 arcsec lambda_min = 0.00373034 scale = 0.00129965 Diffraction scale lambda/D = 51.3099 arcsec Gridding function extent = 307.859 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 153.93 arcsec Airy first null at 62.5811 arcsec Gridding frequency index 0 lambda = 0.00373136 metres, scale = 0.00129929 radians per metre Gridding real part of frequency 0... Gridding imag part of frequency 0... Pattern is holo(res.pattern0) Weights in holo(obs.real,wt0) and holo(obs.imag,wt0) Maximum amplitude = 3.07487 at (0.0, 0.0) arcsec Real: mean = -0.00245128 sum of squares = 870.777 Imag: mean = -0.00280405 sum of squares = 1031.1 Gridding frequency index 1 lambda = 0.00373131 metres, scale = 0.00129931 radians per metre Gridding real part of frequency 1... Gridding imag part of frequency 1... Pattern is holo(res.pattern1) Weights in holo(obs.real,wt1) and holo(obs.imag,wt1) Maximum amplitude = 3.07398 at (0.0, 0.0) arcsec Real: mean = -0.00226775 sum of squares = 909.632 Imag: mean = -0.00289689 sum of squares = 991.809 Gridding frequency index 2 lambda = 0.00373127 metres, scale = 0.00129933 radians per metre Gridding real part of frequency 2... Gridding imag part of frequency 2... Pattern is holo(res.pattern2) Weights in holo(obs.real,wt2) and holo(obs.imag,wt2) Maximum amplitude = 3.08386 at (0.0, 0.0) arcsec Real: mean = -0.0020407 sum of squares = 956.742 Imag: mean = -0.00295632 sum of squares = 944.161 Gridding frequency index 3 lambda = 0.00373118 metres, scale = 0.00129936 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 = 3.08441 at (0.0, 0.0) arcsec Real: mean = -0.00152668 sum of squares = 1038.14 Imag: mean = -0.0029455 sum of squares = 861.657 Gridding frequency index 4 lambda = 0.00373108 metres, scale = 0.00129939 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 = 3.09669 at (0.0, 0.0) arcsec Real: mean = -0.00104487 sum of squares = 1054.45 Imag: mean = -0.00256189 sum of squares = 845.914 Gridding frequency index 5 lambda = 0.00373104 metres, scale = 0.00129941 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 = 3.10527 at (0.0, 0.0) arcsec Real: mean = -0.000940574 sum of squares = 1034.36 Imag: mean = -0.00232542 sum of squares = 866.46 Gridding frequency index 6 lambda = 0.00373099 metres, scale = 0.00129942 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 = 3.10386 at (0.0, 0.0) arcsec Real: mean = -0.00090409 sum of squares = 1000.35 Imag: mean = -0.0020822 sum of squares = 901.713 Gridding frequency index 7 lambda = 0.0037309 metres, scale = 0.00129946 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 = 3.10584 at (0.0, -40.005973566966176) arcsec Real: mean = -0.00101892 sum of squares = 913.889 Imag: mean = -0.00159261 sum of squares = 989.671 Gridding frequency index 8 lambda = 0.0037308 metres, scale = 0.00129949 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 = 3.10581 at (0.0, -40.004977848573851) arcsec Real: mean = -0.00130785 sum of squares = 853.912 Imag: mean = -0.00120869 sum of squares = 1051.79 Gridding frequency index 9 lambda = 0.00373076 metres, scale = 0.0012995 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 = 3.10255 at (0.0, -40.004480007964467) arcsec Real: mean = -0.00149278 sum of squares = 848.348 Imag: mean = -0.00107753 sum of squares = 1057.47 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 = 3.0958 at (0.0, -40.003982179745641) arcsec Real: mean = -0.00170782 sum of squares = 862.174 Imag: mean = -0.000948519 sum of squares = 1044.79 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 = 3.07558 at (0.0, -40.002986560477851) arcsec Real: mean = -0.0021558 sum of squares = 933.095 Imag: mean = -0.000877136 sum of squares = 975.297 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 = 3.06112 at (0.0, 0.0) arcsec Real: mean = -0.00273989 sum of squares = 1020.01 Imag: mean = -0.00105911 sum of squares = 892.052 Gridding frequency index 13 lambda = 0.00373048 metres, scale = 0.0012996 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 = 3.07569 at (0.0, 0.0) arcsec Real: mean = -0.00297902 sum of squares = 1049.55 Imag: mean = -0.00125222 sum of squares = 863.619 Gridding frequency index 14 lambda = 0.00373043 metres, scale = 0.00129962 radians per metre Gridding real part of frequency 14... Gridding imag part of frequency 14... Pattern is holo(res.pattern14) Weights in holo(obs.real,wt14) and holo(obs.imag,wt14) Maximum amplitude = 3.08073 at (0.0, 0.0) arcsec Real: mean = -0.00312486 sum of squares = 1062.85 Imag: mean = -0.00149569 sum of squares = 853.045 Gridding frequency index 15 lambda = 0.00373034 metres, scale = 0.00129965 radians per metre Gridding real part of frequency 15... Gridding imag part of frequency 15... Pattern is holo(res.pattern15) Weights in holo(obs.real,wt15) and holo(obs.imag,wt15) Maximum amplitude = 3.09366 at (0.0, 0.0) arcsec Real: mean = -0.00329105 sum of squares = 1030.67 Imag: mean = -0.00199031 sum of squares = 891.666 Masking frequency index 0 Mask scale size = 3.06021 Masking frequency index 1 Mask scale size = 3.06025 Masking frequency index 2 Mask scale size = 3.06029 Masking frequency index 3 Mask scale size = 3.06037 Masking frequency index 4 Mask scale size = 3.06044 Masking frequency index 5 Mask scale size = 3.06048 Masking frequency index 6 Mask scale size = 3.06052 Masking frequency index 7 Mask scale size = 3.06059 Masking frequency index 8 Mask scale size = 3.06067 Masking frequency index 9 Mask scale size = 3.06071 Masking frequency index 10 Mask scale size = 3.06075 Masking frequency index 11 Mask scale size = 3.06082 Masking frequency index 12 Mask scale size = 3.0609 Masking frequency index 13 Mask scale size = 3.06094 Masking frequency index 14 Mask scale size = 3.06097 Masking frequency index 15 Mask scale size = 3.06105 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.234375 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.224609 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.251465 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.0170898 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.231934 Median point-to-point PLL voltage change: 0.0170898 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -1.4252 102.42 Freq 1: Shift, scale = -1.647 102.85 Freq 2: Shift, scale = -1.868 103.49 Freq 3: Shift, scale = -2.3087 104.77 Freq 4: Shift, scale = -2.7477 105.87 Freq 5: Shift, scale = -2.9656 106.3 Freq 6: Shift, scale = 3.1012 106.59 Freq 7: Shift, scale = 2.6692 107.27 Freq 8: Shift, scale = 2.2396 107.3 Freq 9: Shift, scale = 2.0233 107.12 Freq 10: Shift, scale = 1.8059 106.63 Freq 11: Shift, scale = 1.3738 105.68 Freq 12: Shift, scale = 0.94026 104.57 Freq 13: Shift, scale = 0.72464 103.84 Freq 14: Shift, scale = 0.50704 103.29 Freq 15: Shift, scale = 0.068518 102.4 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: -0.323 radians x offset: -0.635 arcsec y offset: 0.126 arcsec defocus: 0.0105 mm Estimated x pointing error is 12.36 arcsec (used 13 arcsec) Estimated y pointing error is 14.13 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.326 radians x offset: -0.618 arcsec y offset: 0.121 arcsec defocus: 0.0109 mm Estimated x pointing error is 12.38 arcsec (used 13 arcsec) Estimated y pointing error is 14.12 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.328 radians x offset: -0.592 arcsec y offset: 0.114 arcsec defocus: 0.0109 mm Estimated x pointing error is 12.41 arcsec (used 13 arcsec) Estimated y pointing error is 14.11 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 3 Minimiser fit code = 3 piston: -0.331 radians x offset: -0.547 arcsec y offset: 0.0876 arcsec defocus: 0.011 mm Estimated x pointing error is 12.45 arcsec (used 13 arcsec) Estimated y pointing error is 14.09 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.333 radians x offset: -0.539 arcsec y offset: 0.0466 arcsec defocus: 0.0108 mm Estimated x pointing error is 12.46 arcsec (used 13 arcsec) Estimated y pointing error is 14.05 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 5 Minimiser fit code = 3 piston: -0.332 radians x offset: -0.536 arcsec y offset: 0.0295 arcsec defocus: 0.0105 mm Estimated x pointing error is 12.46 arcsec (used 13 arcsec) Estimated y pointing error is 14.03 arcsec (used 14 arcsec) Estimated defocus error is 3.011 mm (used 3 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.329 radians x offset: -0.538 arcsec y offset: 0.0184 arcsec defocus: 0.00941 mm Estimated x pointing error is 12.46 arcsec (used 13 arcsec) Estimated y pointing error is 14.02 arcsec (used 14 arcsec) Estimated defocus error is 3.009 mm (used 3 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.323 radians x offset: -0.554 arcsec y offset: 0.00344 arcsec defocus: 0.00741 mm Estimated x pointing error is 12.45 arcsec (used 13 arcsec) Estimated y pointing error is 14 arcsec (used 14 arcsec) Estimated defocus error is 3.007 mm (used 3 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.314 radians x offset: -0.576 arcsec y offset: 0.00898 arcsec defocus: 0.00573 mm Estimated x pointing error is 12.42 arcsec (used 13 arcsec) Estimated y pointing error is 14.01 arcsec (used 14 arcsec) Estimated defocus error is 3.006 mm (used 3 mm) Fitting frequency 9 Minimiser fit code = 3 piston: -0.311 radians x offset: -0.585 arcsec y offset: 0.0213 arcsec defocus: 0.00579 mm Estimated x pointing error is 12.42 arcsec (used 13 arcsec) Estimated y pointing error is 14.02 arcsec (used 14 arcsec) Estimated defocus error is 3.006 mm (used 3 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.309 radians x offset: -0.591 arcsec y offset: 0.0267 arcsec defocus: 0.00623 mm Estimated x pointing error is 12.41 arcsec (used 13 arcsec) Estimated y pointing error is 14.03 arcsec (used 14 arcsec) Estimated defocus error is 3.006 mm (used 3 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.303 radians x offset: -0.582 arcsec y offset: 0.0522 arcsec defocus: 0.0056 mm Estimated x pointing error is 12.42 arcsec (used 13 arcsec) Estimated y pointing error is 14.05 arcsec (used 14 arcsec) Estimated defocus error is 3.006 mm (used 3 mm) Fitting frequency 12 Minimiser fit code = 3 piston: -0.3 radians x offset: -0.558 arcsec y offset: 0.072 arcsec defocus: 0.00399 mm Estimated x pointing error is 12.44 arcsec (used 13 arcsec) Estimated y pointing error is 14.07 arcsec (used 14 arcsec) Estimated defocus error is 3.004 mm (used 3 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.298 radians x offset: -0.554 arcsec y offset: 0.0843 arcsec defocus: 0.00291 mm Estimated x pointing error is 12.45 arcsec (used 13 arcsec) Estimated y pointing error is 14.08 arcsec (used 14 arcsec) Estimated defocus error is 3.003 mm (used 3 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.297 radians x offset: -0.549 arcsec y offset: 0.0953 arcsec defocus: 0.00241 mm Estimated x pointing error is 12.45 arcsec (used 13 arcsec) Estimated y pointing error is 14.1 arcsec (used 14 arcsec) Estimated defocus error is 3.002 mm (used 3 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.297 radians x offset: -0.566 arcsec y offset: 0.109 arcsec defocus: 0.0035 mm Estimated x pointing error is 12.43 arcsec (used 13 arcsec) Estimated y pointing error is 14.11 arcsec (used 14 arcsec) Estimated defocus error is 3.004 mm (used 3 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 -0.00108 piston 1 1 -0.01854 tilt_x 1 -1 -0.00067 tilt_y 2 2 0.11350 astigmatism_0 2 0 0.00240 curvature 2 -2 0.01155 astigmatism45 3 3 0.03854 trefoil_0 3 1 -0.04566 coma_x 3 -1 -0.01596 coma_y 3 -3 -0.01661 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 -0.00114 piston 1 1 -0.01851 tilt_x 1 -1 -0.00076 tilt_y 2 2 0.11423 astigmatism_0 2 0 0.00228 curvature 2 -2 0.01284 astigmatism45 3 3 0.03775 trefoil_0 3 1 -0.04557 coma_x 3 -1 -0.01609 coma_y 3 -3 -0.01758 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 -0.00112 piston 1 1 -0.01847 tilt_x 1 -1 -0.00104 tilt_y 2 2 0.11460 astigmatism_0 2 0 0.00232 curvature 2 -2 0.01272 astigmatism45 3 3 0.03653 trefoil_0 3 1 -0.04553 coma_x 3 -1 -0.01665 coma_y 3 -3 -0.01848 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 -0.00103 piston 1 1 -0.01834 tilt_x 1 -1 -0.00145 tilt_y 2 2 0.11503 astigmatism_0 2 0 0.00246 curvature 2 -2 0.01165 astigmatism45 3 3 0.03431 trefoil_0 3 1 -0.04520 coma_x 3 -1 -0.01721 coma_y 3 -3 -0.01985 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 -0.00087 piston 1 1 -0.01874 tilt_x 1 -1 -0.00175 tilt_y 2 2 0.11424 astigmatism_0 2 0 0.00279 curvature 2 -2 0.01124 astigmatism45 3 3 0.03426 trefoil_0 3 1 -0.04608 coma_x 3 -1 -0.01753 coma_y 3 -3 -0.01989 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 -0.00080 piston 1 1 -0.01877 tilt_x 1 -1 -0.00186 tilt_y 2 2 0.11344 astigmatism_0 2 0 0.00296 curvature 2 -2 0.01047 astigmatism45 3 3 0.03449 trefoil_0 3 1 -0.04596 coma_x 3 -1 -0.01774 coma_y 3 -3 -0.01952 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 -0.00075 piston 1 1 -0.01889 tilt_x 1 -1 -0.00213 tilt_y 2 2 0.11269 astigmatism_0 2 0 0.00305 curvature 2 -2 0.01009 astigmatism45 3 3 0.03562 trefoil_0 3 1 -0.04618 coma_x 3 -1 -0.01856 coma_y 3 -3 -0.01830 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 -0.00069 piston 1 1 -0.01918 tilt_x 1 -1 -0.00216 tilt_y 2 2 0.11179 astigmatism_0 2 0 0.00324 curvature 2 -2 0.00918 astigmatism45 3 3 0.03725 trefoil_0 3 1 -0.04689 coma_x 3 -1 -0.01903 coma_y 3 -3 -0.01727 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 -0.00067 piston 1 1 -0.01988 tilt_x 1 -1 -0.00180 tilt_y 2 2 0.11138 astigmatism_0 2 0 0.00342 curvature 2 -2 0.00936 astigmatism45 3 3 0.03852 trefoil_0 3 1 -0.04890 coma_x 3 -1 -0.01867 coma_y 3 -3 -0.01592 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 -0.00066 piston 1 1 -0.02022 tilt_x 1 -1 -0.00141 tilt_y 2 2 0.11165 astigmatism_0 2 0 0.00350 curvature 2 -2 0.00903 astigmatism45 3 3 0.03827 trefoil_0 3 1 -0.05006 coma_x 3 -1 -0.01795 coma_y 3 -3 -0.01650 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 -0.00067 piston 1 1 -0.02035 tilt_x 1 -1 -0.00101 tilt_y 2 2 0.11209 astigmatism_0 2 0 0.00359 curvature 2 -2 0.00891 astigmatism45 3 3 0.03841 trefoil_0 3 1 -0.05040 coma_x 3 -1 -0.01709 coma_y 3 -3 -0.01672 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 -0.00067 piston 1 1 -0.01981 tilt_x 1 -1 -0.00030 tilt_y 2 2 0.11173 astigmatism_0 2 0 0.00366 curvature 2 -2 0.00724 astigmatism45 3 3 0.03704 trefoil_0 3 1 -0.04913 coma_x 3 -1 -0.01535 coma_y 3 -3 -0.01791 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 -0.00067 piston 1 1 -0.01872 tilt_x 1 -1 0.00050 tilt_y 2 2 0.11257 astigmatism_0 2 0 0.00369 curvature 2 -2 0.00504 astigmatism45 3 3 0.03452 trefoil_0 3 1 -0.04621 coma_x 3 -1 -0.01301 coma_y 3 -3 -0.01960 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 -0.00066 piston 1 1 -0.01850 tilt_x 1 -1 0.00079 tilt_y 2 2 0.11311 astigmatism_0 2 0 0.00366 curvature 2 -2 0.00401 astigmatism45 3 3 0.03325 trefoil_0 3 1 -0.04577 coma_x 3 -1 -0.01225 coma_y 3 -3 -0.02098 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 -0.00069 piston 1 1 -0.01810 tilt_x 1 -1 0.00104 tilt_y 2 2 0.11394 astigmatism_0 2 0 0.00358 curvature 2 -2 0.00329 astigmatism45 3 3 0.03238 trefoil_0 3 1 -0.04462 coma_x 3 -1 -0.01157 coma_y 3 -3 -0.02161 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 -0.00070 piston 1 1 -0.01809 tilt_x 1 -1 0.00107 tilt_y 2 2 0.11592 astigmatism_0 2 0 0.00344 curvature 2 -2 0.00307 astigmatism45 3 3 0.03225 trefoil_0 3 1 -0.04439 coma_x 3 -1 -0.01126 coma_y 3 -3 -0.02295 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: 30.1 24.1 24.8 28.3 29.2 36.9 42.9 34.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.4 22.2 23.9 27.3 25.9 31.2 42 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.84 5.53 7.53 9.24 12.2 17 24.1 15.5 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.4 24.1 25.6 28.4 29 36.9 43.2 34.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.7 22.3 24.6 27.3 25.5 31.2 42.3 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.84 5.53 7.55 9.28 12.2 17.1 24.2 15.6 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.4 24.3 26.1 28.7 28.7 36.8 43.4 34.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.7 22.4 25 27.6 25.1 30.9 42.2 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.84 5.54 7.57 9.3 12.2 17.1 24.3 15.6 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.2 24.7 25.7 28.8 28.4 36 43.4 34.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.5 22.8 24.5 27.7 24.5 30.3 41.9 31.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.84 5.53 7.56 9.3 12.3 17.1 24.2 15.6 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.1 24.9 25.4 30.4 28.5 34.3 43.1 34 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.4 23 24.1 29 24.5 29 41.1 31.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.89 5.62 7.64 9.33 12.2 17 24.1 15.6 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 25 25.3 30.5 28.8 33.6 42.7 33.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 23.1 23.8 29.1 24.7 28.5 40.6 31.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.89 5.61 7.62 9.29 12.1 16.9 24 15.5 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28 25 25 30.5 29.1 32.8 42.2 33.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.4 23.1 23.6 29.1 25.1 27.9 40 30.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.91 5.66 7.66 9.29 12.1 16.8 23.9 15.4 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.4 24.8 24.6 30.6 29.5 31.7 41.2 33.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.7 23 23.1 29.4 25.6 27 39 30.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.96 5.73 7.73 9.32 12 16.7 23.8 15.4 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 24.6 24.3 31 29.4 31.7 40.5 33.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 22.7 22.8 30 25.8 26.9 38.5 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.06 5.9 7.91 9.44 12 16.7 23.8 15.4 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 24.3 24.1 31.2 29.3 32 40.5 33.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.2 22.3 22.6 30.4 25.7 27.1 38.5 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.11 5.99 8.01 9.52 12.1 16.7 23.9 15.5 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.1 23.9 23.8 31.6 29.1 32.5 40.6 33.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.3 21.9 22.4 30.9 25.6 27.5 38.6 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.11 5.99 8.02 9.55 12.1 16.8 24 15.5 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.5 23.2 22.6 38.3 28.9 33.7 41 34.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 26.7 21.2 21.1 38 25.3 28.4 39.4 32.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 3.01 5.82 7.82 9.38 12 16.7 23.8 15.4 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.1 22.7 22.8 28.7 28.8 34.4 41.7 33.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.4 20.8 21.4 27.4 25 28.9 40.2 31 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.81 5.48 7.46 9.14 12 16.7 23.7 15.3 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 22.8 23.2 28.2 28.9 34.9 41.8 33.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 27.9 21 21.9 26.9 25 29.4 40.5 31.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.78 5.42 7.4 9.11 12 16.8 23.8 15.3 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.1 22.9 23.6 28.3 28.9 35.3 42.2 33.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 28.5 21.1 22.4 26.9 25 29.7 41 31.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.71 5.3 7.29 9.05 12 16.9 23.9 15.4 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 29.9 23.6 25 28.6 29 35.8 42.9 34.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 29.4 21.8 24 27.3 24.9 30.3 41.4 31.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.69 5.29 7.3 9.12 12.2 17.2 24.2 15.6 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 24.9 21.9 21.2 22.7 26.6 32.6 40.1 31.1 Mean deviation is 0.70912012853905182 microns Taper = 10 dB, Ruze illumination-weighted rms = 30.0 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 = 27.9 micron Centre pixel: 64.0 64.0 Value = 2564.88 (estimate), 3426.02 (perfect) Strehl = 0.56047 Strehl ratio estimate = 0.5605 Estimating beam: f = 900GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 900 GHz Ruze rms = 27.6 micron Centre pixel: 64.0 64.0 Value = 1993.97 (estimate), 3426.02 (perfect) Strehl = 0.338733 Strehl ratio estimate = 0.3387 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.15028 metres panel scale = 3.00000 metres mean frequency = 80.35475 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 11.2 16.2 6.7 20.8 2 1 2 28.8 6.6 26.5 39.7 3 1 3 63.2 -0.6 22.4 67.0 4 1 4 71.8 40.5 22.7 85.5 5 1 5 43.4 7.7 58.7 73.4 6 1 6 50.0 38.3 30.9 70.1 7 1 7 20.1 35.5 29.4 50.3 8 1 8 -0.8 53.4 32.1 62.3 9 1 9 -14.4 7.3 12.9 20.7 10 1 10 29.3 14.9 16.5 36.8 11 1 11 52.4 22.8 27.3 63.3 12 1 12 46.3 13.8 14.2 50.3 13 2 1 0.5 -37.3 -23.0 43.8 14 2 2 -0.4 -11.6 -15.8 19.6 15 2 3 23.5 -27.1 -38.3 52.5 16 2 4 25.7 -24.1 -8.1 36.2 17 2 5 31.2 6.6 10.9 33.7 18 2 6 21.6 22.5 39.0 50.0 19 2 7 6.2 -14.6 26.8 31.2 20 2 8 54.6 27.6 1.4 61.2 21 2 9 39.9 5.3 37.4 54.9 22 2 10 56.8 19.4 12.9 61.4 23 2 11 29.7 -7.9 -6.6 31.4 24 2 12 12.3 -4.8 -16.6 21.2 25 2 13 18.0 8.9 -10.3 22.6 26 2 14 0.1 -15.7 -4.1 16.2 27 2 15 23.8 -15.2 -39.1 48.3 28 2 16 41.4 -18.4 -11.0 46.6 29 2 17 23.9 6.5 -3.1 24.9 30 2 18 20.3 14.0 3.8 25.0 31 2 19 10.6 9.1 -19.5 24.0 32 2 20 22.4 -9.7 -11.0 26.8 33 2 21 14.6 17.5 -15.2 27.4 34 2 22 33.6 -39.2 -57.7 77.5 35 2 23 29.4 -31.4 -24.5 49.5 36 2 24 -4.8 -26.0 -26.9 37.7 37 3 1 -5.3 -25.0 -20.4 32.7 38 3 2 -20.0 -14.6 -36.4 44.0 39 3 3 -7.3 -15.2 -26.5 31.4 40 3 4 12.1 -5.5 -3.6 13.7 41 3 5 1.8 8.2 -4.2 9.4 42 3 6 -14.8 7.5 6.5 17.9 43 3 7 -11.6 2.8 -3.1 12.3 44 3 8 -2.3 1.4 14.8 15.1 45 3 9 24.5 -0.3 -4.8 25.0 46 3 10 15.6 4.6 3.0 16.5 47 3 11 27.6 10.6 -6.3 30.2 48 3 12 -26.4 49.2 5.5 56.1 49 3 13 3.1 3.5 20.7 21.2 50 3 14 45.8 8.7 -2.4 46.7 51 3 15 1.9 7.2 5.6 9.3 52 3 16 37.0 13.1 6.1 39.7 53 3 17 34.8 15.4 -17.1 41.7 54 3 18 22.6 9.6 -0.9 24.6 55 3 19 20.6 11.6 -11.0 26.1 56 3 20 -14.2 10.4 6.9 18.9 57 3 21 -3.9 -7.1 -10.1 13.0 58 3 22 3.4 -5.4 -5.1 8.2 59 3 23 4.1 -0.8 -20.0 20.4 60 3 24 2.3 -7.1 -11.5 13.7 61 3 25 -8.4 -11.6 -23.9 27.9 62 3 26 -11.3 -17.1 -26.9 33.8 63 3 27 -18.0 -22.6 -27.8 40.1 64 3 28 7.0 -6.4 -20.2 22.3 65 3 29 -12.2 -2.3 13.5 18.3 66 3 30 -10.3 -13.9 -5.1 18.1 67 3 31 -23.7 0.3 -15.0 28.1 68 3 32 -4.7 4.4 -16.2 17.4 69 3 33 35.4 2.9 21.7 41.6 70 3 34 21.2 17.7 34.6 44.3 71 3 35 45.9 17.8 10.2 50.3 72 3 36 39.7 2.0 28.6 49.0 73 3 37 -2.2 -3.5 -47.3 47.5 74 3 38 -1.3 8.6 -11.4 14.3 75 3 39 9.5 -10.1 -16.3 21.4 76 3 40 6.3 12.0 -29.1 32.1 77 3 41 16.2 19.9 -17.9 31.2 78 3 42 4.6 4.7 -2.4 7.0 79 3 43 -8.8 3.4 -26.7 28.3 80 3 44 14.6 -10.4 -12.7 21.9 81 3 45 3.3 -20.5 -53.4 57.3 82 3 46 -19.6 -32.3 -44.4 58.3 83 3 47 -48.5 -37.6 -45.6 76.5 84 3 48 -36.2 -35.2 -64.9 82.2 85 4 1 -11.1 -42.6 12.7 45.8 86 4 2 -32.8 -28.0 -22.9 48.8 87 4 3 -13.6 -30.3 -39.1 51.3 88 4 4 -11.4 -10.0 -65.3 67.0 89 4 5 -0.0 -6.1 -22.1 22.9 90 4 6 12.3 -8.9 -26.1 30.2 91 4 7 25.6 -12.0 -9.0 29.6 92 4 8 -4.0 6.6 -27.3 28.4 93 4 9 20.5 -1.9 3.2 20.8 94 4 10 -26.9 0.3 -11.7 29.4 95 4 11 14.1 14.5 21.9 29.8 96 4 12 -25.8 12.6 7.9 29.8 97 4 13 -16.4 -10.5 52.0 55.5 98 4 14 38.7 10.7 23.0 46.3 99 4 15 -8.5 -11.3 -4.5 14.8 100 4 16 -10.2 1.3 -7.3 12.6 101 4 17 -10.7 -7.3 -18.5 22.6 102 4 18 23.9 -19.0 18.6 35.7 103 4 19 -0.3 -22.7 -15.2 27.3 104 4 20 0.1 -1.2 -26.1 26.1 105 4 21 -11.2 -11.2 -15.7 22.3 106 4 22 -37.0 -21.8 72.7 84.5 107 4 23 -17.3 -48.3 -29.6 59.2 108 4 24 14.0 -18.9 -13.7 27.2 109 4 25 -20.3 -19.0 5.2 28.3 110 4 26 -22.9 -34.6 -12.9 43.5 111 4 27 -28.3 -19.2 -6.2 34.8 112 4 28 -29.9 -25.1 -14.1 41.5 113 4 29 -47.2 -13.5 -74.0 88.9 114 4 30 -11.6 -22.4 -25.6 35.9 115 4 31 0.4 -12.9 -5.2 13.9 116 4 32 -21.4 -0.7 8.0 22.9 117 4 33 -31.7 -1.5 -20.5 37.8 118 4 34 10.8 12.3 -17.3 23.8 119 4 35 6.9 38.2 10.3 40.1 120 4 36 4.8 9.3 -0.2 10.5 121 4 37 11.4 14.3 -31.0 36.0 122 4 38 1.0 3.3 -26.4 26.6 123 4 39 -11.7 -6.4 0.8 13.4 124 4 40 25.2 2.7 -37.1 45.0 125 4 41 -18.0 14.4 -45.7 51.2 126 4 42 -8.4 -14.1 -56.9 59.2 127 4 43 -38.3 -23.7 -38.7 59.4 128 4 44 -46.0 -0.3 -21.0 50.6 129 4 45 -8.0 -8.4 -20.5 23.5 130 4 46 -15.2 -32.3 -34.4 49.6 131 4 47 -52.7 -36.0 -60.9 88.3 132 4 48 -52.9 -48.8 -26.8 76.8 133 5 1 3.8 -23.5 -51.4 56.7 134 5 2 14.0 3.8 -80.3 81.6 135 5 3 0.3 1.1 -44.8 44.8 136 5 4 3.2 -10.3 -28.1 30.1 137 5 5 11.6 -1.9 -23.6 26.4 138 5 6 -2.6 3.8 -22.1 22.6 139 5 7 -0.8 27.6 16.0 31.9 140 5 8 -4.6 22.2 -17.2 28.5 141 5 9 -0.5 1.8 25.0 25.0 142 5 10 7.9 41.5 20.2 46.8 143 5 11 30.1 48.5 21.0 60.8 144 5 12 7.9 82.9 11.4 84.0 145 5 13 10.9 51.8 22.1 57.4 146 5 14 43.3 50.2 5.6 66.5 147 5 15 17.9 30.6 20.1 40.8 148 5 16 3.6 17.8 6.0 19.1 149 5 17 -18.8 16.9 23.8 34.7 150 5 18 -4.4 -10.6 112.6 113.2 151 5 19 -35.7 -15.8 -39.0 55.2 152 5 20 -39.0 -32.3 -38.9 63.8 153 5 21 -13.9 -21.7 -50.7 56.8 154 5 22 -31.2 20.8 -49.5 62.1 155 5 23 -35.3 -6.2 -1.7 35.9 156 5 24 -7.8 -15.5 16.1 23.7 157 5 25 -8.7 -15.7 -24.4 30.3 158 5 26 -39.8 -15.3 -30.4 52.4 159 5 27 -25.5 6.2 -32.4 41.7 160 5 28 -26.0 -30.8 -31.1 50.9 161 5 29 2.9 -27.9 -57.5 64.0 162 5 30 -4.2 -21.7 10.2 24.4 163 5 31 -42.6 -22.1 -22.9 53.1 164 5 32 -24.7 15.9 -11.4 31.6 165 5 33 -2.7 38.6 27.9 47.7 166 5 34 -15.8 18.8 11.8 27.2 167 5 35 54.7 65.0 29.6 90.0 168 5 36 16.5 26.8 43.6 53.8 169 5 37 -8.9 46.5 -8.7 48.1 170 5 38 -28.3 28.0 -19.0 44.1 171 5 39 2.5 95.2 -48.3 106.8 172 5 40 -42.7 10.1 -24.4 50.2 173 5 41 0.2 23.0 12.9 26.4 174 5 42 -29.0 2.7 -22.0 36.5 175 5 43 4.0 -0.5 -49.2 49.4 176 5 44 -19.2 3.2 -15.6 25.0 177 5 45 -2.5 3.8 -8.6 9.8 178 5 46 -22.9 9.6 12.0 27.6 179 5 47 -6.2 19.5 -20.0 28.6 180 5 48 -8.0 -5.8 -32.9 34.4 181 6 1 -57.9 -29.0 -33.9 73.1 182 6 2 -51.1 -50.2 -60.0 93.4 183 6 3 2.4 -52.2 -41.9 67.0 184 6 4 -47.3 -27.8 -59.3 80.8 185 6 5 -15.9 -23.1 -57.0 63.5 186 6 6 -10.7 -10.9 -48.2 50.6 187 6 7 -4.3 -16.6 -22.4 28.2 188 6 8 -1.5 24.4 -3.4 24.6 189 6 9 24.0 8.5 47.9 54.3 190 6 10 46.9 29.0 42.2 69.4 191 6 11 46.9 33.9 38.1 69.3 192 6 12 29.9 46.9 12.6 57.0 193 6 13 35.0 43.4 -3.0 55.8 194 6 14 40.1 14.8 -4.5 43.0 195 6 15 48.8 9.5 3.9 49.9 196 6 16 31.1 13.1 51.1 61.2 197 6 17 -6.6 -8.0 -12.4 16.1 198 6 18 11.8 -9.7 -134.6 135.5 199 6 19 15.8 -25.5 -41.7 51.4 200 6 20 -45.6 -14.0 13.9 49.7 201 6 21 -91.9 -43.5 -61.4 118.8 202 6 22 44.3 36.0 -9.2 57.8 203 6 23 18.7 -26.8 -12.4 34.9 204 6 24 -7.5 -14.6 -25.2 30.1 205 6 25 -40.7 -16.9 -53.1 69.1 206 6 26 -7.6 -39.0 -49.8 63.7 207 6 27 -3.6 -36.4 -36.3 51.5 208 6 28 2.9 28.8 187.7 189.9 209 6 29 -76.5 28.0 2.3 81.5 210 6 30 -41.1 -1.7 87.0 96.3 211 6 31 -16.4 -8.6 24.0 30.3 212 6 32 -28.8 2.2 31.9 43.0 213 6 33 45.1 24.9 172.6 180.1 214 6 34 134.8 24.4 94.1 166.2 215 6 35 53.0 18.9 81.3 98.9 216 6 36 46.8 63.7 69.8 105.5 217 6 37 -2.6 40.8 13.5 43.0 218 6 38 7.2 2.6 -21.8 23.1 219 6 39 33.4 24.0 -3.5 41.3 220 6 40 -29.8 40.8 -51.2 72.0 221 6 41 10.0 40.4 4.9 41.9 222 6 42 24.2 15.3 -14.3 32.0 223 6 43 29.9 12.0 23.6 39.9 224 6 44 13.7 10.4 10.3 20.1 225 6 45 30.0 7.2 26.3 40.5 226 6 46 21.8 7.4 61.8 66.0 227 6 47 -40.5 -8.0 14.2 43.7 228 6 48 -49.7 -23.2 6.2 55.2 229 7 1 -72.4 19.5 -28.4 80.2 230 7 2 -55.5 -28.0 -56.1 83.7 231 7 3 -59.8 -27.4 -40.3 77.2 232 7 4 -33.6 -9.7 11.6 36.9 233 7 5 -56.2 -20.7 -39.2 71.6 234 7 6 -45.8 1.1 -61.2 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47 4 11 48 -5 11 49 -8 11 50 1 11 51 -2 11 52 -17 11 53 -12 11 54 10 11 55 0 11 56 1 11 57 1 11 58 6 11 59 16 11 60 8 11 61 -5 11 62 6 11 63 4 11 64 -9 11 65 4 11 66 -4 11 67 -3 11 68 -3 11 69 4 12 1 11 12 2 42 12 3 -10 12 4 1 12 5 -7 12 6 -15 12 7 -7 12 8 12 12 9 -6 12 10 4 12 11 -2 12 12 -12 12 13 8 12 14 5 12 15 6 12 16 18 12 17 2 12 18 6 12 19 31 12 20 -11 12 21 -2 12 22 8 12 23 2 12 24 9 12 25 -10 12 26 -1 12 27 -2 12 28 -8 12 29 -14 12 30 -16 12 31 -6 12 32 5 12 33 -1 12 34 -18 12 35 -11 12 36 -16 12 37 3 12 38 2 12 39 -7 12 40 -10 12 41 -9 12 42 -4 12 43 -2 12 44 1 12 45 0 12 46 -6 12 47 -2 12 48 -2 12 49 -13 12 50 -11 12 51 -14 12 52 -8 12 53 -7 12 54 -1 12 55 -13 12 56 -9 12 57 -6 12 58 4 12 59 14 12 60 4 12 61 -16 12 62 -6 12 63 1 12 64 -11 12 65 9 12 66 -7 12 67 -19 12 68 -10 12 69 -11 Adjuster movements: rms = 35.1 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20070925-150942 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1