Reduction started at: 20041221-055333 Reading data from rxh3-20041219-235811.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 = 2402.6 max = 2425.2 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.760 mm ----------------- Data Summary --------------------- Number of samples: 1466025 This is a 160 GHz map Number of frequencies: 16 Frequencies (GHz): 160.676000 160.680000 160.684000 160.688000 160.692000 160.696000 160.700000 160.704000 160.708000 160.712000 160.716000 160.720000 160.724000 160.728000 160.732000 160.736000 item min max mean loreal -2.69287 2.75635 -0.00262 loimag -2.68799 2.84424 -0.00904 hireal -5.00000 4.99756 0.00552 hiimag -5.00000 4.99756 0.01723 xpos -2425.15445 2410.32621 -10.58231 ypos -2402.69215 2402.59925 -0.00308 plock160 0.93506 2.28271 1.67485 lorefpwr 1.33057 2.88086 2.41442 losigpwr -4.58008 -0.83740 -4.46913 hirefpwr 1.36230 2.88086 2.43216 hisigpwr -4.49707 4.99756 -1.48234 encltemp 31.56738 32.81250 32.09573 flags 0.00000 256.00000 2.44471 phi-lock -1.31104 0.00977 -0.68680 sindex 0.00000 254.00000 126.60925 time 0.00000 6033.99262 2954.70022 zeropt -0.00732 -0.00244 -0.00490 !!!Warning!!! philock max less than 0.2 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 255 rows There are 241 data rows and 14 calibrator rows Calibrator rows: 0 21 42 63 84 105 126 147 168 189 210 231 252 254 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 20.00292 arcsec Mean row spacing = 20.00293 arcsec (alternate estimator) Mean tracking incline = -0.12888 arcsec Mean pointing range = 0.54678 arcsec Mean pointing rms = 0.10858 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (-1.9, 12.2 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Inverting the phase on this 160 GHz map 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 14000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 90354 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 20.0 arcseconds Using a grid of 256 points Grid has even number of points Maximum data offset = 2425.15 arcsec Grid extent = 2550 arcsec lambda_min = 0.00186512 scale = 0.00259937 Diffraction scale lambda/D = 25.6569 arcsec Gridding function extent = 153.941 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 76.9706 arcsec Airy first null at 31.2929 arcsec Gridding frequency index 0 lambda = 0.00186582 metres, scale = 0.0025984 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 = 2.56203 at (0.0, 0.0) arcsec Real: mean = 0.000213459 sum of squares = 2064.4 Imag: mean = 0.000343169 sum of squares = 1909.32 Gridding frequency index 1 lambda = 0.00186577 metres, scale = 0.00259846 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 = 2.58099 at (0.0, 0.0) arcsec Real: mean = 0.00016452 sum of squares = 1999.32 Imag: mean = 0.000205724 sum of squares = 1987.87 Gridding frequency index 2 lambda = 0.00186573 metres, scale = 0.00259852 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 = 2.61123 at (0.0, 0.0) arcsec Real: mean = 0.000103958 sum of squares = 1920.11 Imag: mean = 0.000165075 sum of squares = 2086.78 Gridding frequency index 3 lambda = 0.00186568 metres, scale = 0.00259859 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 = 2.64336 at (0.0, 0.0) arcsec Real: mean = 0.000184128 sum of squares = 2036.39 Imag: mean = -5.59439e-05 sum of squares = 1997.77 Gridding frequency index 4 lambda = 0.00186563 metres, scale = 0.00259865 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 = 2.6501 at (0.0, 0.0) arcsec Real: mean = 0.00038812 sum of squares = 2104.67 Imag: mean = 6.90409e-05 sum of squares = 1961.25 Gridding frequency index 5 lambda = 0.00186559 metres, scale = 0.00259872 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 = 2.63362 at (0.0, 0.0) arcsec Real: mean = 0.000340558 sum of squares = 2008.34 Imag: mean = 0.00011761 sum of squares = 2092.19 Gridding frequency index 6 lambda = 0.00186554 metres, scale = 0.00259878 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 = 2.61566 at (0.0, 0.0) arcsec Real: mean = 0.000451732 sum of squares = 2000.55 Imag: mean = 0.000226142 sum of squares = 2135.69 Gridding frequency index 7 lambda = 0.00186549 metres, scale = 0.00259885 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 = 2.62158 at (0.0, 0.0) arcsec Real: mean = 0.000278243 sum of squares = 2153.21 Imag: mean = 0.000352577 sum of squares = 2024.52 Gridding frequency index 8 lambda = 0.00186545 metres, scale = 0.00259891 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 = 2.65885 at (0.0, 0.0) arcsec Real: mean = 0.000117891 sum of squares = 2153.69 Imag: mean = 0.000288512 sum of squares = 2068.06 Gridding frequency index 9 lambda = 0.0018654 metres, scale = 0.00259898 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 = 2.68906 at (0.0, 0.0) arcsec Real: mean = 0.000126582 sum of squares = 2054.79 Imag: mean = 0.000105482 sum of squares = 2213.86 Gridding frequency index 10 lambda = 0.00186536 metres, scale = 0.00259904 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 = 2.69161 at (0.0, 0.0) arcsec Real: mean = 0.00020817 sum of squares = 2133.2 Imag: mean = 8.9539e-05 sum of squares = 2180.35 Gridding frequency index 11 lambda = 0.00186531 metres, scale = 0.00259911 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 = 2.69533 at (0.0, 0.0) arcsec Real: mean = 0.000274206 sum of squares = 2267.04 Imag: mean = -1.81878e-05 sum of squares = 2092.94 Gridding frequency index 12 lambda = 0.00186526 metres, scale = 0.00259917 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 = 2.69038 at (0.0, 0.0) arcsec Real: mean = 0.000454209 sum of squares = 2195.21 Imag: mean = 0.000100421 sum of squares = 2216.69 Gridding frequency index 13 lambda = 0.00186522 metres, scale = 0.00259924 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 = 2.67618 at (0.0, 0.0) arcsec Real: mean = 0.00044138 sum of squares = 2147.46 Imag: mean = 0.000220505 sum of squares = 2317.67 Gridding frequency index 14 lambda = 0.00186517 metres, scale = 0.0025993 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 = 2.69605 at (0.0, 0.0) arcsec Real: mean = 0.000351784 sum of squares = 2290.49 Imag: mean = 0.000382986 sum of squares = 2236.11 Gridding frequency index 15 lambda = 0.00186512 metres, scale = 0.00259937 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 = 2.73582 at (0.0, 0.0) arcsec Real: mean = 0.000208833 sum of squares = 2374.25 Imag: mean = 0.000296898 sum of squares = 2211.59 Masking frequency index 0 Mask scale size = 6.11804 Masking frequency index 1 Mask scale size = 6.1182 Masking frequency index 2 Mask scale size = 6.11835 Masking frequency index 3 Mask scale size = 6.1185 Masking frequency index 4 Mask scale size = 6.11865 Masking frequency index 5 Mask scale size = 6.11881 Masking frequency index 6 Mask scale size = 6.11896 Masking frequency index 7 Mask scale size = 6.11911 Masking frequency index 8 Mask scale size = 6.11926 Masking frequency index 9 Mask scale size = 6.11941 Masking frequency index 10 Mask scale size = 6.11957 Masking frequency index 11 Mask scale size = 6.11972 Masking frequency index 12 Mask scale size = 6.11987 Masking frequency index 13 Mask scale size = 6.12002 Masking frequency index 14 Mask scale size = 6.12018 Masking frequency index 15 Mask scale size = 6.12033 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.197754 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.178223 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.197754 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.231934 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.239258 Median point-to-point PLL voltage change: 0.00976562 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -2.579 126.75 Freq 1: Shift, scale = 2.8415 126.79 Freq 2: Shift, scale = 1.9823 127.14 Freq 3: Shift, scale = 1.1202 127.4 Freq 4: Shift, scale = 0.25686 128.17 Freq 5: Shift, scale = -0.61201 129.15 Freq 6: Shift, scale = -1.483 129.09 Freq 7: Shift, scale = -2.3397 128.88 Freq 8: Shift, scale = 3.0911 129.85 Freq 9: Shift, scale = 2.2283 131.17 Freq 10: Shift, scale = 1.3622 132.25 Freq 11: Shift, scale = 0.49114 133.07 Freq 12: Shift, scale = -0.37602 133.23 Freq 13: Shift, scale = -1.2346 133.44 Freq 14: Shift, scale = -2.0975 134.24 Freq 15: Shift, scale = -2.9613 135.35 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: -0.114 radians x offset: 0.061 arcsec y offset: 0.011 arcsec defocus: 0.00774 mm Estimated x pointing error is -1.839 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.21 arcsec (used 12.2 arcsec) Estimated defocus error is 2.768 mm (used 2.76 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.113 radians x offset: 0.0579 arcsec y offset: 0.0132 arcsec defocus: 0.00777 mm Estimated x pointing error is -1.842 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.21 arcsec (used 12.2 arcsec) Estimated defocus error is 2.768 mm (used 2.76 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.109 radians x offset: 0.0583 arcsec y offset: 0.0204 arcsec defocus: 0.00704 mm Estimated x pointing error is -1.842 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.22 arcsec (used 12.2 arcsec) Estimated defocus error is 2.767 mm (used 2.76 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.108 radians x offset: 0.0456 arcsec y offset: 0.0285 arcsec defocus: 0.00702 mm Estimated x pointing error is -1.854 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.23 arcsec (used 12.2 arcsec) Estimated defocus error is 2.767 mm (used 2.76 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.108 radians x offset: 0.0431 arcsec y offset: 0.0236 arcsec defocus: 0.00605 mm Estimated x pointing error is -1.857 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.22 arcsec (used 12.2 arcsec) Estimated defocus error is 2.766 mm (used 2.76 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.112 radians x offset: 0.0361 arcsec y offset: 0.0201 arcsec defocus: 0.00677 mm Estimated x pointing error is -1.864 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.22 arcsec (used 12.2 arcsec) Estimated defocus error is 2.767 mm (used 2.76 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.12 radians x offset: 0.0323 arcsec y offset: 0.0212 arcsec defocus: 0.0069 mm Estimated x pointing error is -1.868 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.22 arcsec (used 12.2 arcsec) Estimated defocus error is 2.767 mm (used 2.76 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.114 radians x offset: 0.0344 arcsec y offset: 0.0265 arcsec defocus: 0.0059 mm Estimated x pointing error is -1.866 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.23 arcsec (used 12.2 arcsec) Estimated defocus error is 2.766 mm (used 2.76 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.105 radians x offset: 0.0331 arcsec y offset: 0.0242 arcsec defocus: 0.00452 mm Estimated x pointing error is -1.867 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.22 arcsec (used 12.2 arcsec) Estimated defocus error is 2.765 mm (used 2.76 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.105 radians x offset: 0.0285 arcsec y offset: 0.0143 arcsec defocus: 0.00354 mm Estimated x pointing error is -1.872 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.21 arcsec (used 12.2 arcsec) Estimated defocus error is 2.764 mm (used 2.76 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.107 radians x offset: 0.0148 arcsec y offset: 0.00232 arcsec defocus: 0.0043 mm Estimated x pointing error is -1.885 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.2 arcsec (used 12.2 arcsec) Estimated defocus error is 2.764 mm (used 2.76 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.115 radians x offset: 0.00941 arcsec y offset: -0.000935 arcsec defocus: 0.00319 mm Estimated x pointing error is -1.891 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.2 arcsec (used 12.2 arcsec) Estimated defocus error is 2.763 mm (used 2.76 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.119 radians x offset: 0.00101 arcsec y offset: -0.0075 arcsec defocus: 0.00206 mm Estimated x pointing error is -1.899 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.19 arcsec (used 12.2 arcsec) Estimated defocus error is 2.762 mm (used 2.76 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.114 radians x offset: -0.00536 arcsec y offset: -0.0167 arcsec defocus: 0.00164 mm Estimated x pointing error is -1.905 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.18 arcsec (used 12.2 arcsec) Estimated defocus error is 2.762 mm (used 2.76 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.112 radians x offset: -0.0216 arcsec y offset: -0.0288 arcsec defocus: 0.0015 mm Estimated x pointing error is -1.922 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.17 arcsec (used 12.2 arcsec) Estimated defocus error is 2.762 mm (used 2.76 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.11 radians x offset: -0.0278 arcsec y offset: -0.0469 arcsec defocus: 0.00154 mm Estimated x pointing error is -1.928 arcsec (used -1.9 arcsec) Estimated y pointing error is 12.15 arcsec (used 12.2 arcsec) Estimated defocus error is 2.762 mm (used 2.76 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 -0.00443 piston 1 1 0.01017 tilt_x 1 -1 0.04313 tilt_y 2 2 -0.04313 astigmatism_0 2 0 -0.01826 curvature 2 -2 0.00541 astigmatism45 3 3 -0.03504 trefoil_0 3 1 0.03386 coma_x 3 -1 0.17247 coma_y 3 -3 -0.09999 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 -0.00437 piston 1 1 0.01005 tilt_x 1 -1 0.04319 tilt_y 2 2 -0.04296 astigmatism_0 2 0 -0.01823 curvature 2 -2 0.00617 astigmatism45 3 3 -0.03531 trefoil_0 3 1 0.03383 coma_x 3 -1 0.17348 coma_y 3 -3 -0.10003 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 -0.00430 piston 1 1 0.00995 tilt_x 1 -1 0.04301 tilt_y 2 2 -0.04211 astigmatism_0 2 0 -0.01804 curvature 2 -2 0.00669 astigmatism45 3 3 -0.03595 trefoil_0 3 1 0.03390 coma_x 3 -1 0.17339 coma_y 3 -3 -0.10237 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 -0.00423 piston 1 1 0.00930 tilt_x 1 -1 0.04255 tilt_y 2 2 -0.04201 astigmatism_0 2 0 -0.01785 curvature 2 -2 0.00635 astigmatism45 3 3 -0.03696 trefoil_0 3 1 0.03192 coma_x 3 -1 0.17199 coma_y 3 -3 -0.10526 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 -0.00429 piston 1 1 0.00970 tilt_x 1 -1 0.04280 tilt_y 2 2 -0.04260 astigmatism_0 2 0 -0.01804 curvature 2 -2 0.00633 astigmatism45 3 3 -0.03683 trefoil_0 3 1 0.03291 coma_x 3 -1 0.17272 coma_y 3 -3 -0.10513 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 -0.00436 piston 1 1 0.00970 tilt_x 1 -1 0.04288 tilt_y 2 2 -0.04339 astigmatism_0 2 0 -0.01819 curvature 2 -2 0.00719 astigmatism45 3 3 -0.03531 trefoil_0 3 1 0.03277 coma_x 3 -1 0.17323 coma_y 3 -3 -0.10417 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 -0.00434 piston 1 1 0.01019 tilt_x 1 -1 0.04328 tilt_y 2 2 -0.04429 astigmatism_0 2 0 -0.01831 curvature 2 -2 0.00777 astigmatism45 3 3 -0.03466 trefoil_0 3 1 0.03445 coma_x 3 -1 0.17563 coma_y 3 -3 -0.10420 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 -0.00413 piston 1 1 0.01042 tilt_x 1 -1 0.04299 tilt_y 2 2 -0.04314 astigmatism_0 2 0 -0.01797 curvature 2 -2 0.00889 astigmatism45 3 3 -0.03598 trefoil_0 3 1 0.03589 coma_x 3 -1 0.17479 coma_y 3 -3 -0.10632 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 -0.00390 piston 1 1 0.01073 tilt_x 1 -1 0.04278 tilt_y 2 2 -0.04124 astigmatism_0 2 0 -0.01758 curvature 2 -2 0.00930 astigmatism45 3 3 -0.03648 trefoil_0 3 1 0.03762 coma_x 3 -1 0.17362 coma_y 3 -3 -0.10821 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 -0.00387 piston 1 1 0.01038 tilt_x 1 -1 0.04259 tilt_y 2 2 -0.04059 astigmatism_0 2 0 -0.01749 curvature 2 -2 0.00941 astigmatism45 3 3 -0.03490 trefoil_0 3 1 0.03618 coma_x 3 -1 0.17234 coma_y 3 -3 -0.10703 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 -0.00393 piston 1 1 0.01013 tilt_x 1 -1 0.04262 tilt_y 2 2 -0.04133 astigmatism_0 2 0 -0.01775 curvature 2 -2 0.00885 astigmatism45 3 3 -0.03374 trefoil_0 3 1 0.03468 coma_x 3 -1 0.17311 coma_y 3 -3 -0.10559 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 -0.00405 piston 1 1 0.01091 tilt_x 1 -1 0.04230 tilt_y 2 2 -0.04149 astigmatism_0 2 0 -0.01800 curvature 2 -2 0.00896 astigmatism45 3 3 -0.03448 trefoil_0 3 1 0.03711 coma_x 3 -1 0.17227 coma_y 3 -3 -0.10519 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 -0.00409 piston 1 1 0.01135 tilt_x 1 -1 0.04253 tilt_y 2 2 -0.04149 astigmatism_0 2 0 -0.01816 curvature 2 -2 0.00827 astigmatism45 3 3 -0.03523 trefoil_0 3 1 0.03869 coma_x 3 -1 0.17324 coma_y 3 -3 -0.10528 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 -0.00402 piston 1 1 0.01133 tilt_x 1 -1 0.04222 tilt_y 2 2 -0.04116 astigmatism_0 2 0 -0.01804 curvature 2 -2 0.00831 astigmatism45 3 3 -0.03424 trefoil_0 3 1 0.03914 coma_x 3 -1 0.17303 coma_y 3 -3 -0.10661 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 -0.00391 piston 1 1 0.01094 tilt_x 1 -1 0.04165 tilt_y 2 2 -0.04170 astigmatism_0 2 0 -0.01785 curvature 2 -2 0.00863 astigmatism45 3 3 -0.03379 trefoil_0 3 1 0.03830 coma_x 3 -1 0.17149 coma_y 3 -3 -0.10784 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 -0.00397 piston 1 1 0.01112 tilt_x 1 -1 0.04210 tilt_y 2 2 -0.04345 astigmatism_0 2 0 -0.01803 curvature 2 -2 0.00817 astigmatism45 3 3 -0.03298 trefoil_0 3 1 0.03869 coma_x 3 -1 0.17313 coma_y 3 -3 -0.10675 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: 21.3 19.7 20.5 24.5 22.9 24.5 36.4 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.5 20.1 18 21.8 22.8 22.6 30.8 24.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.37 9.28 11.4 11.2 8.48 7.43 16 11.3 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22 20.2 21.2 24.7 22.8 24.5 36.4 27.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.2 20.6 18.7 22.1 22.5 22.6 30.6 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.4 9.33 11.5 11.2 8.52 7.44 16.1 11.4 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.3 20.3 20.3 25.4 22.8 24.4 36.2 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 20.6 17.5 22.8 22.5 22.6 30.5 24.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.4 9.33 11.5 11.2 8.54 7.53 16.2 11.4 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.8 20 20.8 25.3 22.9 24.8 36 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22 20.3 18.1 22.7 22.6 22.9 30.6 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.35 9.24 11.4 11.1 8.53 7.67 16.3 11.4 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.3 20.2 20.5 24.9 22.9 24.7 36.1 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.4 20.6 17.8 22.2 22.7 22.8 30.7 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.37 9.29 11.4 11.2 8.57 7.68 16.3 11.5 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.6 20.4 20.9 24.4 22.8 24.4 36.3 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.6 18.3 21.7 22.6 22.5 30.7 24.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.39 9.31 11.5 11.2 8.57 7.64 16.3 11.5 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22 20.2 21.7 24.3 22.7 24.5 36.3 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.2 20.5 18.9 21.5 22.4 22.6 30.5 24.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.47 9.45 11.6 11.4 8.68 7.68 16.4 11.6 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.3 20.1 20.6 24.3 22.7 24.4 36.2 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.3 17.7 21.6 22.5 22.3 30.4 24.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.45 9.42 11.6 11.3 8.68 7.77 16.5 11.6 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.2 20.4 20.6 24.8 22.8 24.6 36.1 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.6 17.7 22.1 22.6 22.6 30.4 24.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.43 9.38 11.6 11.3 8.67 7.81 16.5 11.6 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.8 20.6 20.7 25.3 22.7 24.6 36.2 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22 20.6 17.9 22.7 22.6 22.7 30.7 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.38 9.3 11.5 11.2 8.58 7.7 16.4 11.5 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.9 20.1 20.6 25.1 22.7 24.4 36.3 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.9 20.2 17.8 22.5 22.5 22.6 30.8 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.39 9.32 11.5 11.2 8.57 7.64 16.3 11.5 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.9 20.3 21.6 24.4 22.6 24.4 36 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22 20.5 18.9 21.8 22.4 22.7 30.4 24.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.38 9.3 11.5 11.2 8.56 7.63 16.3 11.5 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.8 20.4 20.4 24.2 22.6 24.5 35.9 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.9 20.5 17.4 21.5 22.4 22.6 30.3 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.42 9.37 11.5 11.3 8.61 7.65 16.4 11.5 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.6 20 20.5 24.3 22.9 24.7 35.9 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.1 17.6 21.6 22.7 22.7 30.3 24.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.42 9.37 11.5 11.3 8.62 7.69 16.4 11.5 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.4 20.1 20.6 24.5 23 24.7 36.1 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.6 20.3 17.9 21.8 22.8 22.7 30.5 24.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.37 9.28 11.4 11.2 8.58 7.75 16.4 11.5 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.5 20.4 20.7 24.6 22.9 24.6 36.5 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.6 18.1 22 22.6 22.6 30.8 24.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.42 9.37 11.5 11.3 8.64 7.74 16.4 11.6 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 20.8 19.3 19.4 23.3 21.5 23.1 35.4 26.3 Mean deviation is -2.2414953540254507 microns Taper = 10 dB, Ruze illumination-weighted rms = 25.4 micron Estimating beam: f = 650GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 650 GHz Ruze rms = 22.8 micron Centre pixel: 128.0 128.0 Value = 12939.3 (estimate), 15687.6 (perfect) Strehl = 0.680306 Strehl ratio estimate = 0.6803 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 = 22.1 micron Centre pixel: 128.0 128.0 Value = 11094.3 (estimate), 15687.6 (perfect) Strehl = 0.500136 Strehl ratio estimate = 0.5001 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.07514 metres panel scale = 3.00000 metres mean frequency = 160.70600 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 -26.7 -3.5 -6.0 27.6 2 1 2 -27.7 5.7 0.9 28.3 3 1 3 -29.9 -7.3 -13.2 33.5 4 1 4 -19.9 -14.1 -9.3 26.1 5 1 5 -16.0 -10.8 -18.2 26.5 6 1 6 -12.8 -11.0 -14.9 22.5 7 1 7 -10.7 -15.3 -15.1 24.0 8 1 8 -17.5 -20.8 -9.4 28.8 9 1 9 -88.5 -5.4 -6.9 89.0 10 1 10 -19.2 -3.0 -7.1 20.7 11 1 11 -22.1 -6.2 -8.7 24.5 12 1 12 -14.8 -5.4 -5.2 16.5 13 2 1 -8.3 7.1 12.6 16.7 14 2 2 -1.8 10.9 5.5 12.3 15 2 3 -8.9 4.0 1.3 9.8 16 2 4 -5.1 1.4 -1.0 5.4 17 2 5 -7.0 8.2 3.5 11.4 18 2 6 -6.4 8.7 7.0 12.8 19 2 7 -19.9 -2.9 0.2 20.1 20 2 8 -2.2 13.3 -3.0 13.8 21 2 9 -11.6 -6.2 -4.7 13.9 22 2 10 -2.5 -4.3 -11.1 12.1 23 2 11 -8.1 -12.3 -16.1 21.9 24 2 12 -12.5 -15.0 -23.3 30.5 25 2 13 -14.1 -12.0 -17.5 25.4 26 2 14 -17.4 -25.7 -17.0 35.3 27 2 15 -4.7 -14.4 -12.3 19.5 28 2 16 1.0 -11.3 -1.7 11.5 29 2 17 -9.3 0.9 -4.1 10.2 30 2 18 -1.7 -7.5 -5.3 9.3 31 2 19 -8.0 4.0 5.1 10.3 32 2 20 -4.1 8.5 0.8 9.4 33 2 21 -5.0 -2.6 2.7 6.2 34 2 22 -12.0 4.6 3.9 13.4 35 2 23 3.4 0.6 11.4 11.9 36 2 24 -9.9 0.7 5.6 11.4 37 3 1 9.1 13.4 12.5 20.5 38 3 2 13.1 17.0 15.6 26.5 39 3 3 14.6 16.3 17.1 27.8 40 3 4 17.1 21.3 24.0 36.4 41 3 5 7.2 18.6 19.8 28.1 42 3 6 5.7 14.9 23.0 28.0 43 3 7 3.0 13.9 16.4 21.7 44 3 8 2.5 13.8 18.3 23.1 45 3 9 11.0 13.8 3.6 18.0 46 3 10 4.2 7.4 10.1 13.2 47 3 11 -0.6 7.5 -5.9 9.6 48 3 12 2.4 16.5 -2.1 16.8 49 3 13 -1.2 10.2 -7.4 12.7 50 3 14 0.8 3.8 -11.9 12.5 51 3 15 -2.8 0.5 -6.1 6.7 52 3 16 6.4 0.1 -6.7 9.3 53 3 17 -3.5 0.2 -9.4 10.1 54 3 18 -8.8 -6.6 -6.6 12.8 55 3 19 -7.8 -5.9 -9.3 13.5 56 3 20 -13.7 -6.1 -6.4 16.3 57 3 21 -17.1 -5.5 -11.1 21.1 58 3 22 -16.7 -11.0 -9.8 22.3 59 3 23 -19.2 -14.4 -11.7 26.6 60 3 24 -19.0 -17.1 -13.8 29.1 61 3 25 -16.9 -15.7 -15.7 27.9 62 3 26 -28.6 -15.5 -13.4 35.2 63 3 27 -16.1 -15.3 -11.6 25.1 64 3 28 -12.1 -7.6 -11.5 18.3 65 3 29 -16.5 -7.4 -4.0 18.5 66 3 30 -13.0 -25.7 -2.3 28.9 67 3 31 -8.9 -4.0 -4.4 10.7 68 3 32 -4.8 5.0 -14.9 16.4 69 3 33 10.5 8.0 10.2 16.7 70 3 34 3.4 1.9 14.9 15.4 71 3 35 7.3 -0.7 5.4 9.1 72 3 36 1.5 18.4 4.1 18.9 73 3 37 -0.7 18.7 -5.7 19.6 74 3 38 7.1 13.6 12.3 19.6 75 3 39 2.2 13.4 15.6 20.7 76 3 40 3.6 15.2 14.9 21.6 77 3 41 6.0 17.2 26.4 32.1 78 3 42 7.6 20.2 24.8 32.9 79 3 43 7.5 17.2 22.1 29.0 80 3 44 16.4 15.6 19.4 29.8 81 3 45 15.3 16.6 14.5 26.9 82 3 46 16.7 13.4 17.2 27.4 83 3 47 10.5 13.6 13.5 21.9 84 3 48 10.9 15.5 9.9 21.4 85 4 1 25.8 20.3 17.2 37.1 86 4 2 24.7 23.9 12.8 36.7 87 4 3 25.9 22.3 26.8 43.4 88 4 4 19.2 25.9 18.0 36.9 89 4 5 18.4 25.6 20.9 37.8 90 4 6 17.1 20.9 19.1 33.0 91 4 7 18.9 18.0 14.7 30.0 92 4 8 15.4 16.9 3.8 23.1 93 4 9 3.1 18.0 1.8 18.4 94 4 10 4.6 4.6 -4.3 7.8 95 4 11 -0.0 5.4 -11.7 12.9 96 4 12 -6.2 4.7 -12.8 15.0 97 4 13 -4.5 1.1 -8.7 9.9 98 4 14 0.4 -2.3 -10.4 10.6 99 4 15 -7.7 -8.0 -19.1 22.1 100 4 16 -9.3 -6.3 -15.1 18.8 101 4 17 -10.0 -5.6 -13.5 17.7 102 4 18 -2.9 -4.4 -10.3 11.6 103 4 19 -5.9 -5.3 -10.8 13.4 104 4 20 -3.7 2.3 -9.6 10.5 105 4 21 -3.1 0.7 1.4 3.5 106 4 22 -19.5 -6.0 2.7 20.6 107 4 23 -16.6 -4.6 0.7 17.3 108 4 24 -16.9 -9.1 1.6 19.2 109 4 25 -17.5 -4.2 46.7 50.1 110 4 26 -18.4 -9.2 -1.0 20.6 111 4 27 -6.5 -11.0 5.0 13.7 112 4 28 -0.6 -0.8 1.3 1.7 113 4 29 -2.5 3.9 -46.4 46.6 114 4 30 -2.6 1.4 -4.6 5.5 115 4 31 3.7 0.9 -2.3 4.4 116 4 32 -5.7 0.2 2.0 6.1 117 4 33 -8.5 2.0 -9.5 12.9 118 4 34 10.7 12.3 -11.6 20.1 119 4 35 9.1 4.6 0.9 10.3 120 4 36 6.0 12.4 -4.6 14.6 121 4 37 16.7 17.3 7.3 25.1 122 4 38 12.2 17.4 -1.1 21.2 123 4 39 20.3 18.3 14.9 31.1 124 4 40 17.2 29.0 11.7 35.7 125 4 41 30.1 26.3 10.8 41.4 126 4 42 19.9 25.8 16.9 36.8 127 4 43 20.1 22.6 20.7 36.6 128 4 44 17.8 26.0 21.2 37.9 129 4 45 25.7 25.2 18.2 40.4 130 4 46 29.0 20.3 15.3 38.6 131 4 47 26.1 20.1 11.0 34.8 132 4 48 27.3 20.6 8.3 35.2 133 5 1 10.2 5.4 4.4 12.4 134 5 2 7.3 11.5 6.2 14.9 135 5 3 23.2 10.3 15.7 29.8 136 5 4 18.2 15.9 11.4 26.7 137 5 5 19.0 14.2 2.1 23.8 138 5 6 27.2 15.2 0.7 31.2 139 5 7 20.7 19.0 6.3 28.7 140 5 8 13.4 10.4 4.0 17.5 141 5 9 4.3 6.3 -1.7 7.8 142 5 10 1.5 2.3 -5.8 6.4 143 5 11 -5.9 1.8 -17.5 18.6 144 5 12 -6.9 -3.7 -16.8 18.6 145 5 13 -6.3 -4.9 -11.4 13.9 146 5 14 -9.7 -12.0 -19.6 25.0 147 5 15 -12.7 -17.0 -24.1 32.2 148 5 16 -14.8 -9.1 -21.2 27.4 149 5 17 -9.1 -2.7 -5.9 11.2 150 5 18 -7.7 -3.1 206.4 206.6 151 5 19 -5.1 -2.9 -5.3 7.8 152 5 20 -1.4 8.4 -4.8 9.8 153 5 21 3.9 9.7 0.6 10.5 154 5 22 -0.1 0.2 0.9 0.9 155 5 23 -7.8 1.6 6.3 10.1 156 5 24 -4.1 3.0 6.0 7.9 157 5 25 -3.7 2.4 5.2 6.8 158 5 26 -3.7 2.2 4.4 6.2 159 5 27 6.6 5.1 0.4 8.4 160 5 28 5.8 11.0 10.2 16.1 161 5 29 8.1 10.4 -1.7 13.3 162 5 30 3.6 -2.3 8.9 9.9 163 5 31 5.0 2.6 -9.1 10.7 164 5 32 -0.7 -6.7 -13.3 14.9 165 5 33 4.2 1.5 -8.0 9.2 166 5 34 -5.9 -21.2 -27.9 35.5 167 5 35 6.4 -18.6 -14.4 24.4 168 5 36 15.7 0.2 -10.8 19.1 169 5 37 20.7 -3.7 -0.4 21.1 170 5 38 7.8 6.1 -13.5 16.8 171 5 39 19.0 7.0 4.5 20.7 172 5 40 17.6 8.1 -4.4 19.9 173 5 41 22.0 11.8 20.8 32.5 174 5 42 22.3 19.6 3.8 30.0 175 5 43 22.1 17.5 -8.4 29.4 176 5 44 22.8 13.9 -8.1 27.9 177 5 45 13.6 11.5 -3.0 18.1 178 5 46 10.9 2.1 -0.4 11.2 179 5 47 0.4 0.6 -6.9 6.9 180 5 48 0.3 7.2 -8.4 11.1 181 6 1 9.8 -14.4 -23.7 29.4 182 6 2 5.9 0.4 -25.2 25.9 183 6 3 9.1 -4.4 -8.8 13.4 184 6 4 7.5 9.9 -12.9 17.9 185 6 5 8.1 1.6 0.3 8.2 186 6 6 8.9 5.7 0.5 10.6 187 6 7 2.9 4.2 -1.8 5.4 188 6 8 7.6 9.0 -0.9 11.8 189 6 9 6.7 5.0 -1.6 8.5 190 6 10 2.5 -1.0 2.6 3.7 191 6 11 -11.5 0.1 -16.3 20.0 192 6 12 -10.3 -10.1 -15.5 21.2 193 6 13 -6.0 -12.0 -24.4 27.8 194 6 14 -16.6 -15.5 -20.8 30.8 195 6 15 -11.0 -20.4 -25.1 34.2 196 6 16 2.1 -5.6 -25.0 25.7 197 6 17 -12.5 -8.3 -14.6 20.9 198 6 18 -12.1 1.4 -11.4 16.7 199 6 19 -2.1 0.6 0.6 2.2 200 6 20 -9.1 20.8 15.6 27.6 201 6 21 2.8 22.3 16.1 27.6 202 6 22 6.0 23.5 21.0 32.0 203 6 23 15.8 26.6 32.9 45.1 204 6 24 11.6 24.8 25.3 37.2 205 6 25 13.2 25.6 11.4 31.0 206 6 26 20.3 25.2 23.1 39.7 207 6 27 16.4 27.3 20.3 37.8 208 6 28 4.5 15.5 20.2 25.9 209 6 29 -6.1 23.5 -9.1 25.9 210 6 30 0.8 -4.0 35.5 35.7 211 6 31 -6.5 -9.0 -28.5 30.6 212 6 32 -18.5 -19.7 -18.9 33.0 213 6 33 -16.3 -13.3 -33.7 39.7 214 6 34 -5.5 -7.1 -10.1 13.5 215 6 35 -11.2 -21.2 -26.9 36.1 216 6 36 -12.3 20.5 -16.7 29.1 217 6 37 -1.1 -3.1 -4.5 5.5 218 6 38 -4.3 -1.0 -9.9 10.8 219 6 39 2.5 1.6 -4.1 5.1 220 6 40 -1.8 4.6 -4.4 6.6 221 6 41 3.6 2.9 -16.6 17.3 222 6 42 7.5 -8.3 -24.9 27.3 223 6 43 2.1 -10.6 -13.2 17.1 224 6 44 5.2 -4.3 -11.8 13.6 225 6 45 -0.2 0.0 -27.7 27.7 226 6 46 1.6 -10.7 -30.4 32.3 227 6 47 -3.0 -12.9 -30.4 33.2 228 6 48 -3.7 -17.6 -27.8 33.1 229 7 1 -28.0 -72.2 -132.9 153.8 230 7 2 -30.2 -53.3 -130.4 144.1 231 7 3 -1.0 -56.8 -90.1 106.6 232 7 4 2.2 -17.4 -83.4 85.2 233 7 5 -2.8 -19.0 -28.6 34.4 234 7 6 2.1 -5.5 -21.7 22.5 235 7 7 -3.4 -6.3 -12.0 13.9 236 7 8 -0.9 6.8 -58.3 58.7 237 7 9 -0.9 2.0 -3.5 4.1 238 7 10 -0.3 -3.1 -5.1 6.0 239 7 11 -13.7 -6.4 -16.0 22.1 240 7 12 -14.9 -11.3 -15.2 24.1 241 7 13 -20.4 -14.2 -25.9 35.9 242 7 14 -21.0 -13.1 -22.9 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276 7 48 -35.4 114.3 -118.1 168.1 Creating sector-motor-move file sector motor steps 1 1 -25 1 2 -5 1 3 0 1 4 -3 1 5 3 1 6 2 1 7 -27 1 8 -17 1 9 0 1 10 -2 1 11 -1 1 12 2 1 13 -40 1 14 -16 1 15 -9 1 16 -7 1 17 0 1 18 1 1 19 -40 1 20 -22 1 21 -8 1 22 -7 1 23 -4 1 24 3 1 25 3 1 26 4 1 27 5 1 28 5 1 29 7 1 30 5 1 31 4 1 32 3 1 33 7 1 34 8 1 35 6 1 36 7 1 37 1 1 38 3 1 39 2 1 40 3 1 41 7 1 42 7 1 43 1 1 44 1 1 45 3 1 46 5 1 47 6 1 48 7 1 49 5 1 50 5 1 51 4 1 52 1 1 53 3 1 54 0 1 55 4 1 56 5 1 57 4 1 58 -1 1 59 -8 1 60 -1 1 61 3 1 62 4 1 63 2 1 64 1 1 65 -2 1 66 3 1 67 7 1 68 6 1 69 5 2 1 -17 2 2 2 2 3 0 2 4 0 2 5 2 2 6 2 2 7 -3 2 8 -1 2 9 -1 2 10 0 2 11 1 2 12 0 2 13 -6 2 14 -1 2 15 0 2 16 0 2 17 1 2 18 2 2 19 -8 2 20 -5 2 21 0 2 22 0 2 23 0 2 24 2 2 25 1 2 26 3 2 27 4 2 28 1 2 29 5 2 30 4 2 31 1 2 32 5 2 33 6 2 34 4 2 35 5 2 36 5 2 37 0 2 38 4 2 39 8 2 40 5 2 41 6 2 42 5 2 43 0 2 44 4 2 45 5 2 46 6 2 47 7 2 48 5 2 49 5 2 50 4 2 51 0 2 52 0 2 53 0 2 54 -1 2 55 7 2 56 4 2 57 1 2 58 1 2 59 -8 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-8 12 23 0 12 24 0 12 25 -2 12 26 2 12 27 0 12 28 2 12 29 6 12 30 8 12 31 -2 12 32 0 12 33 0 12 34 3 12 35 6 12 36 8 12 37 0 12 38 0 12 39 3 12 40 4 12 41 6 12 42 8 12 43 0 12 44 3 12 45 4 12 46 5 12 47 7 12 48 7 12 49 4 12 50 4 12 51 3 12 52 1 12 53 0 12 54 -3 12 55 5 12 56 4 12 57 5 12 58 -1 12 59 -4 12 60 -1 12 61 4 12 62 5 12 63 4 12 64 2 12 65 1 12 66 3 12 67 3 12 68 4 12 69 3 Adjuster movements: rms = 22.7 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20041221-061445 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1