Reduction started at: 20050223-112020 Reading data from rxh3-20050213-214437.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 = 2402.3 max = 2421.6 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 34.100 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 -3.02734 2.91016 -0.00080 loimag -3.26416 3.00049 -0.00851 hireal -5.00000 4.99756 0.01002 hiimag -5.00000 4.99756 0.02540 xpos -2421.55433 2410.74594 -10.78326 ypos -2402.46804 2402.33885 0.00136 plock160 0.93262 2.26562 1.65673 lorefpwr 1.53076 3.01758 2.53996 losigpwr -4.59961 -0.28076 -4.48161 hirefpwr 1.57227 3.00537 2.55670 hisigpwr -4.51416 4.99756 -1.46078 encltemp 31.66504 32.98340 32.18816 flags 0.00000 256.00000 2.44471 phi-lock -1.19385 0.10986 -0.58348 sindex 0.00000 254.00000 126.60925 time 0.00000 5877.01784 2937.61926 zeropt -0.00732 -0.00244 -0.00489 !!!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 = 20.00295 arcsec Mean row spacing = 20.00296 arcsec (alternate estimator) Mean tracking incline = -0.17305 arcsec Mean pointing range = 0.61955 arcsec Mean pointing rms = 0.11994 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (1.2, 9.9 ) 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: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 90361 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 90361 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 = 2421.55 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 = 2.87489 at (0.0, 0.0) arcsec Real: mean = 0.000540684 sum of squares = 2063.12 Imag: mean = 0.000145425 sum of squares = 2247.03 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 = 2.839 at (0.0, 0.0) arcsec Real: mean = 0.000404365 sum of squares = 2150.51 Imag: mean = 0.00024793 sum of squares = 2159.62 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 = 2.83524 at (0.0, 0.0) arcsec Real: mean = 0.000237598 sum of squares = 2245.87 Imag: mean = 0.000155451 sum of squares = 2074.15 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 = 2.85106 at (0.0, 0.0) arcsec Real: mean = 0.000346933 sum of squares = 2141.87 Imag: mean = 7.02927e-05 sum of squares = 2190.26 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 = 2.88401 at (0.0, 0.0) arcsec Real: mean = 0.000218095 sum of squares = 2084.86 Imag: mean = 4.97557e-05 sum of squares = 2262.12 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 = 2.91875 at (0.0, 0.0) arcsec Real: mean = 0.000384773 sum of squares = 2233.08 Imag: mean = -0.000145704 sum of squares = 2128.63 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 = 2.93203 at (0.0, 0.0) arcsec Real: mean = 0.000531655 sum of squares = 2254.01 Imag: mean = 5.87298e-05 sum of squares = 2127.24 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 = 2.91268 at (0.0, 0.0) arcsec Real: mean = 0.000446409 sum of squares = 2128.82 Imag: mean = 9.25385e-05 sum of squares = 2281.13 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 = 2.88007 at (0.0, 0.0) arcsec Real: mean = 0.000502868 sum of squares = 2173.03 Imag: mean = 0.000157306 sum of squares = 2263.98 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 = 2.88102 at (0.0, 0.0) arcsec Real: mean = 0.000371871 sum of squares = 2316.97 Imag: mean = 0.00026309 sum of squares = 2147.83 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 = 2.90252 at (0.0, 0.0) arcsec Real: mean = 0.000231707 sum of squares = 2263.24 Imag: mean = 0.000149477 sum of squares = 2227.88 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 = 2.92962 at (0.0, 0.0) arcsec Real: mean = 0.000253022 sum of squares = 2160.65 Imag: mean = -2.03871e-06 sum of squares = 2360.43 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 = 2.95873 at (0.0, 0.0) arcsec Real: mean = 0.000401746 sum of squares = 2288.89 Imag: mean = -5.07196e-05 sum of squares = 2265.06 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 = 2.97007 at (0.0, 0.0) arcsec Real: mean = 0.000432514 sum of squares = 2383.37 Imag: mean = -2.00524e-05 sum of squares = 2207 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 = 2.94983 at (0.0, 0.0) arcsec Real: mean = 0.000578925 sum of squares = 2268.84 Imag: mean = -3.07219e-05 sum of squares = 2356.12 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 = 2.91532 at (0.0, 0.0) arcsec Real: mean = 0.000608118 sum of squares = 2245.74 Imag: mean = 0.000241764 sum of squares = 2410.3 Masking frequency index 0 Mask scale size = 6.11738 Masking frequency index 1 Mask scale size = 6.11753 Masking frequency index 2 Mask scale size = 6.11769 Masking frequency index 3 Mask scale size = 6.11784 Masking frequency index 4 Mask scale size = 6.11799 Masking frequency index 5 Mask scale size = 6.11814 Masking frequency index 6 Mask scale size = 6.11829 Masking frequency index 7 Mask scale size = 6.11845 Masking frequency index 8 Mask scale size = 6.1186 Masking frequency index 9 Mask scale size = 6.11875 Masking frequency index 10 Mask scale size = 6.1189 Masking frequency index 11 Mask scale size = 6.11906 Masking frequency index 12 Mask scale size = 6.11921 Masking frequency index 13 Mask scale size = 6.11936 Masking frequency index 14 Mask scale size = 6.11951 Masking frequency index 15 Mask scale size = 6.11967 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.249023 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.234375 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.222168 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: 0.00976562 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.236816 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.205078 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -1.0484 134.33 Freq 1: Shift, scale = -1.9191 133.85 Freq 2: Shift, scale = -2.7857 132.64 Freq 3: Shift, scale = 2.6385 133.04 Freq 4: Shift, scale = 1.7755 133.26 Freq 5: Shift, scale = 0.91438 133.94 Freq 6: Shift, scale = 0.047707 134.77 Freq 7: Shift, scale = -0.82353 134.57 Freq 8: Shift, scale = -1.6848 133.82 Freq 9: Shift, scale = -2.5424 134.86 Freq 10: Shift, scale = 2.8774 135.44 Freq 11: Shift, scale = 2.018 135.85 Freq 12: Shift, scale = 1.1536 136.82 Freq 13: Shift, scale = 0.28714 136.98 Freq 14: Shift, scale = -0.57371 137.68 Freq 15: Shift, scale = -1.4395 138 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: -0.12 radians x offset: -0.0468 arcsec y offset: 0.0206 arcsec defocus: -0.00055 mm Estimated x pointing error is 1.153 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.921 arcsec (used 9.9 arcsec) Estimated defocus error is 3.099 mm (used 3.1 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.127 radians x offset: -0.0555 arcsec y offset: 0.0476 arcsec defocus: 2.77e-05 mm Estimated x pointing error is 1.144 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.948 arcsec (used 9.9 arcsec) Estimated defocus error is 3.1 mm (used 3.1 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.127 radians x offset: -0.0554 arcsec y offset: 0.0573 arcsec defocus: 0.00189 mm Estimated x pointing error is 1.145 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.957 arcsec (used 9.9 arcsec) Estimated defocus error is 3.102 mm (used 3.1 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.122 radians x offset: -0.0513 arcsec y offset: 0.0491 arcsec defocus: 0.00148 mm Estimated x pointing error is 1.149 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.949 arcsec (used 9.9 arcsec) Estimated defocus error is 3.101 mm (used 3.1 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.121 radians x offset: -0.051 arcsec y offset: 0.0315 arcsec defocus: 0.000154 mm Estimated x pointing error is 1.149 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.932 arcsec (used 9.9 arcsec) Estimated defocus error is 3.1 mm (used 3.1 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.118 radians x offset: -0.0564 arcsec y offset: 0.0282 arcsec defocus: -0.00108 mm Estimated x pointing error is 1.144 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.928 arcsec (used 9.9 arcsec) Estimated defocus error is 3.099 mm (used 3.1 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.121 radians x offset: -0.0658 arcsec y offset: 0.0546 arcsec defocus: -0.000606 mm Estimated x pointing error is 1.134 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.955 arcsec (used 9.9 arcsec) Estimated defocus error is 3.099 mm (used 3.1 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.128 radians x offset: -0.0746 arcsec y offset: 0.0746 arcsec defocus: 0.000717 mm Estimated x pointing error is 1.125 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.975 arcsec (used 9.9 arcsec) Estimated defocus error is 3.101 mm (used 3.1 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.125 radians x offset: -0.0785 arcsec y offset: 0.065 arcsec defocus: 0.000904 mm Estimated x pointing error is 1.121 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.965 arcsec (used 9.9 arcsec) Estimated defocus error is 3.101 mm (used 3.1 mm) Fitting frequency 9 Minimiser fit code = 3 piston: -0.122 radians x offset: -0.0864 arcsec y offset: 0.035 arcsec defocus: -0.00122 mm Estimated x pointing error is 1.114 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.935 arcsec (used 9.9 arcsec) Estimated defocus error is 3.099 mm (used 3.1 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.124 radians x offset: -0.0959 arcsec y offset: 0.0248 arcsec defocus: -0.00337 mm Estimated x pointing error is 1.104 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.925 arcsec (used 9.9 arcsec) Estimated defocus error is 3.097 mm (used 3.1 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.12 radians x offset: -0.0944 arcsec y offset: 0.0305 arcsec defocus: -0.00265 mm Estimated x pointing error is 1.106 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.93 arcsec (used 9.9 arcsec) Estimated defocus error is 3.097 mm (used 3.1 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.119 radians x offset: -0.113 arcsec y offset: 0.0543 arcsec defocus: -0.000413 mm Estimated x pointing error is 1.087 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.954 arcsec (used 9.9 arcsec) Estimated defocus error is 3.1 mm (used 3.1 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.124 radians x offset: -0.12 arcsec y offset: 0.0393 arcsec defocus: -0.00126 mm Estimated x pointing error is 1.08 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.939 arcsec (used 9.9 arcsec) Estimated defocus error is 3.099 mm (used 3.1 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.123 radians x offset: -0.119 arcsec y offset: 0.00869 arcsec defocus: -0.00382 mm Estimated x pointing error is 1.081 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.909 arcsec (used 9.9 arcsec) Estimated defocus error is 3.096 mm (used 3.1 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.124 radians x offset: -0.127 arcsec y offset: -0.0112 arcsec defocus: -0.00381 mm Estimated x pointing error is 1.073 arcsec (used 1.2 arcsec) Estimated y pointing error is 9.889 arcsec (used 9.9 arcsec) Estimated defocus error is 3.096 mm (used 3.1 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 -0.00047 piston 1 1 0.00836 tilt_x 1 -1 0.01196 tilt_y 2 2 0.00988 astigmatism_0 2 0 0.00153 curvature 2 -2 -0.09201 astigmatism45 3 3 0.04675 trefoil_0 3 1 0.00509 coma_x 3 -1 0.03803 coma_y 3 -3 0.02654 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 -0.00033 piston 1 1 0.00826 tilt_x 1 -1 0.01256 tilt_y 2 2 0.01493 astigmatism_0 2 0 0.00175 curvature 2 -2 -0.09158 astigmatism45 3 3 0.04516 trefoil_0 3 1 0.00590 coma_x 3 -1 0.03968 coma_y 3 -3 0.01995 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 -0.00023 piston 1 1 0.00859 tilt_x 1 -1 0.01376 tilt_y 2 2 0.01904 astigmatism_0 2 0 0.00175 curvature 2 -2 -0.09119 astigmatism45 3 3 0.04257 trefoil_0 3 1 0.00734 coma_x 3 -1 0.04384 coma_y 3 -3 0.01603 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 -0.00020 piston 1 1 0.00849 tilt_x 1 -1 0.01345 tilt_y 2 2 0.01750 astigmatism_0 2 0 0.00183 curvature 2 -2 -0.09199 astigmatism45 3 3 0.04259 trefoil_0 3 1 0.00702 coma_x 3 -1 0.04355 coma_y 3 -3 0.01801 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 -0.00026 piston 1 1 0.00805 tilt_x 1 -1 0.01210 tilt_y 2 2 0.01191 astigmatism_0 2 0 0.00195 curvature 2 -2 -0.09103 astigmatism45 3 3 0.04429 trefoil_0 3 1 0.00526 coma_x 3 -1 0.03919 coma_y 3 -3 0.02287 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 -0.00036 piston 1 1 0.00786 tilt_x 1 -1 0.01145 tilt_y 2 2 0.01024 astigmatism_0 2 0 0.00191 curvature 2 -2 -0.09035 astigmatism45 3 3 0.04443 trefoil_0 3 1 0.00483 coma_x 3 -1 0.03676 coma_y 3 -3 0.02286 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 -0.00035 piston 1 1 0.00774 tilt_x 1 -1 0.01226 tilt_y 2 2 0.01446 astigmatism_0 2 0 0.00179 curvature 2 -2 -0.09072 astigmatism45 3 3 0.04330 trefoil_0 3 1 0.00476 coma_x 3 -1 0.03915 coma_y 3 -3 0.01721 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 -0.00023 piston 1 1 0.00795 tilt_x 1 -1 0.01339 tilt_y 2 2 0.01887 astigmatism_0 2 0 0.00188 curvature 2 -2 -0.09043 astigmatism45 3 3 0.04223 trefoil_0 3 1 0.00577 coma_x 3 -1 0.04292 coma_y 3 -3 0.01392 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 -0.00024 piston 1 1 0.00887 tilt_x 1 -1 0.01359 tilt_y 2 2 0.01588 astigmatism_0 2 0 0.00186 curvature 2 -2 -0.09078 astigmatism45 3 3 0.04301 trefoil_0 3 1 0.00862 coma_x 3 -1 0.04418 coma_y 3 -3 0.01641 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 -0.00033 piston 1 1 0.00923 tilt_x 1 -1 0.01257 tilt_y 2 2 0.01037 astigmatism_0 2 0 0.00188 curvature 2 -2 -0.08986 astigmatism45 3 3 0.04476 trefoil_0 3 1 0.00972 coma_x 3 -1 0.04125 coma_y 3 -3 0.02015 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 -0.00041 piston 1 1 0.00884 tilt_x 1 -1 0.01131 tilt_y 2 2 0.00775 astigmatism_0 2 0 0.00190 curvature 2 -2 -0.08867 astigmatism45 3 3 0.04548 trefoil_0 3 1 0.00866 coma_x 3 -1 0.03710 coma_y 3 -3 0.02086 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 -0.00042 piston 1 1 0.00893 tilt_x 1 -1 0.01200 tilt_y 2 2 0.01218 astigmatism_0 2 0 0.00174 curvature 2 -2 -0.08968 astigmatism45 3 3 0.04471 trefoil_0 3 1 0.00922 coma_x 3 -1 0.03912 coma_y 3 -3 0.01505 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 -0.00034 piston 1 1 0.00863 tilt_x 1 -1 0.01239 tilt_y 2 2 0.01714 astigmatism_0 2 0 0.00175 curvature 2 -2 -0.09106 astigmatism45 3 3 0.04335 trefoil_0 3 1 0.00860 coma_x 3 -1 0.04046 coma_y 3 -3 0.01070 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 -0.00041 piston 1 1 0.00952 tilt_x 1 -1 0.01211 tilt_y 2 2 0.01449 astigmatism_0 2 0 0.00163 curvature 2 -2 -0.09192 astigmatism45 3 3 0.04485 trefoil_0 3 1 0.01069 coma_x 3 -1 0.04021 coma_y 3 -3 0.01351 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 -0.00054 piston 1 1 0.01002 tilt_x 1 -1 0.01127 tilt_y 2 2 0.00910 astigmatism_0 2 0 0.00149 curvature 2 -2 -0.09216 astigmatism45 3 3 0.04656 trefoil_0 3 1 0.01154 coma_x 3 -1 0.03721 coma_y 3 -3 0.02015 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 -0.00050 piston 1 1 0.00932 tilt_x 1 -1 0.01129 tilt_y 2 2 0.00798 astigmatism_0 2 0 0.00171 curvature 2 -2 -0.09088 astigmatism45 3 3 0.04746 trefoil_0 3 1 0.00962 coma_x 3 -1 0.03732 coma_y 3 -3 0.02114 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: 23.6 23.2 19.7 23.2 23.3 25.4 32 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 22.9 19.6 23 23.3 24.2 30.2 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.2 2.2 3.11 4.05 5.32 7.26 10.1 6.63 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.6 23.2 20 23.4 23.1 25.2 31.9 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.1 22.9 19.9 23.2 23.1 24.1 30.2 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.25 2.29 3.2 4.1 5.3 7.17 10 6.58 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 23.6 20.4 23.7 23.2 25.1 31.7 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 23.3 20.3 23.5 23.2 24 30 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.38 2.5 3.43 4.26 5.33 7.12 9.99 6.6 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.5 20.8 23.9 23.3 25.1 31.7 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 23.2 20.7 23.8 23.3 24 30 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.37 2.48 3.42 4.26 5.36 7.16 10 6.63 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 23.4 20.2 24.6 23.3 24.9 31.8 26.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 23.1 20.1 24.5 23.3 23.8 30.2 25.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.23 2.25 3.16 4.06 5.26 7.12 9.94 6.52 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 23.3 19.6 24.1 23.2 25.2 31.7 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 23 19.5 24 23.2 24.1 30.2 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.16 2.13 3.02 3.95 5.19 7.06 9.83 6.44 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.6 20.1 23.9 23.1 25.3 31.8 26.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.6 23.3 20 23.7 23.1 24.2 30.3 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.23 2.25 3.15 4.04 5.22 7.05 9.82 6.46 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 23.8 20.5 23.7 23.2 25.2 31.8 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 23.5 20.3 23.6 23.2 24.1 30.2 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.35 2.44 3.36 4.19 5.27 7.04 9.87 6.51 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.6 21 23.7 23.4 25.1 31.8 26.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 23.3 20.8 23.5 23.5 24 30.1 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.4 2.52 3.45 4.26 5.3 7.06 9.94 6.56 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.7 20.8 23.7 23.3 24.9 31.8 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.7 23.3 20.6 23.6 23.4 23.8 30.1 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.32 2.39 3.29 4.13 5.22 7.02 9.86 6.49 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.3 23.5 19.9 23.6 23.1 24.7 31.7 26.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 23.2 19.8 23.5 23.1 23.8 30.1 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.19 2.17 3.05 3.94 5.11 6.94 9.7 6.36 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.3 23.5 20.4 24.3 22.9 24.9 31.8 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 23.2 20.2 24.2 23 23.9 30.2 25.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.25 2.28 3.18 4.04 5.18 6.97 9.75 6.41 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.4 23.8 20.7 24.4 22.9 25.1 31.7 26.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.5 20.5 24.3 23 24 30.2 25.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.29 2.34 3.26 4.13 5.26 7.06 9.86 6.5 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.1 23.6 20.7 23.8 23.2 25 31.7 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.6 23.3 20.5 23.6 23.2 24 30.1 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.29 2.36 3.28 4.16 5.31 7.13 9.97 6.57 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 23.3 20.7 23.7 23.2 25.1 31.8 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 23 20.5 23.6 23.2 24 30 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.21 2.23 3.14 4.07 5.3 7.19 10 6.58 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.3 19.7 22.9 23.1 25.1 31.7 26.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 22.9 19.5 22.8 23.1 24.1 30 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.2 2.2 3.1 4.02 5.24 7.13 9.96 6.52 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 23 22.7 19.4 22.8 22.4 24.3 30.9 25.6 Mean deviation is 0.30227266183608192 microns Taper = 10 dB, Ruze illumination-weighted rms = 25.1 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 = 22.7 micron Centre pixel: 128.0 128.0 Value = 12951 (estimate), 15687.6 (perfect) Strehl = 0.681538 Strehl ratio estimate = 0.6815 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 = 11074.4 (estimate), 15687.6 (perfect) Strehl = 0.498345 Strehl ratio estimate = 0.4983 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 -8.3 8.6 10.3 15.8 2 1 2 -16.4 16.7 3.6 23.7 3 1 3 -29.4 13.3 -11.3 34.2 4 1 4 -32.2 3.7 4.4 32.7 5 1 5 -22.6 -1.2 -16.3 27.9 6 1 6 -47.5 -11.3 -18.5 52.2 7 1 7 -22.0 -25.0 -11.4 35.3 8 1 8 -23.3 -5.4 4.4 24.3 9 1 9 -54.8 1.5 18.8 57.9 10 1 10 -16.5 2.6 16.3 23.3 11 1 11 -16.0 1.5 9.0 18.4 12 1 12 9.1 10.7 5.5 15.1 13 2 1 2.9 12.8 12.8 18.3 14 2 2 5.4 17.2 13.3 22.4 15 2 3 7.3 15.0 23.7 29.0 16 2 4 0.4 19.1 16.0 25.0 17 2 5 -14.2 13.9 4.7 20.4 18 2 6 -7.5 16.1 10.0 20.4 19 2 7 5.9 15.8 16.0 23.3 20 2 8 21.8 24.1 16.0 36.2 21 2 9 -19.4 11.6 7.9 23.9 22 2 10 -11.8 8.9 -0.7 14.8 23 2 11 -8.3 9.4 5.3 13.6 24 2 12 -9.2 11.8 7.7 16.8 25 2 13 -15.3 -16.1 -4.9 22.8 26 2 14 -3.5 7.5 1.7 8.4 27 2 15 -16.4 8.2 18.9 26.3 28 2 16 -1.6 6.7 15.1 16.6 29 2 17 2.9 13.5 22.3 26.3 30 2 18 4.6 15.2 37.5 40.7 31 2 19 15.3 17.3 32.6 40.0 32 2 20 8.1 20.0 19.3 29.0 33 2 21 3.4 13.7 15.2 20.8 34 2 22 16.2 29.6 27.6 43.6 35 2 23 12.6 15.4 13.9 24.3 36 2 24 4.5 -2.2 15.2 16.0 37 3 1 12.2 3.4 23.5 26.7 38 3 2 9.5 8.2 21.8 25.2 39 3 3 5.4 10.3 23.0 25.8 40 3 4 3.0 7.6 7.7 11.2 41 3 5 10.9 5.4 20.8 24.1 42 3 6 12.7 7.2 9.2 17.3 43 3 7 8.7 7.1 10.0 15.1 44 3 8 7.3 4.4 8.1 11.7 45 3 9 5.9 10.8 19.2 22.8 46 3 10 0.7 7.0 14.3 16.0 47 3 11 9.1 7.2 6.9 13.5 48 3 12 13.9 8.9 3.4 16.8 49 3 13 16.8 11.2 7.8 21.6 50 3 14 4.4 4.6 1.5 6.5 51 3 15 1.6 5.4 -1.6 5.8 52 3 16 0.3 9.6 9.3 13.4 53 3 17 -1.9 8.2 5.4 10.0 54 3 18 3.9 1.4 2.3 4.8 55 3 19 -4.2 5.3 12.6 14.3 56 3 20 9.0 2.0 4.3 10.1 57 3 21 3.4 6.2 7.9 10.6 58 3 22 -2.8 -2.8 -3.1 5.1 59 3 23 5.9 0.5 -4.2 7.3 60 3 24 -7.9 -5.8 2.9 10.2 61 3 25 -2.0 -6.7 -3.4 7.8 62 3 26 -8.2 -3.2 -12.0 14.9 63 3 27 9.7 1.4 8.7 13.1 64 3 28 -2.2 2.8 11.8 12.3 65 3 29 8.7 6.3 2.8 11.1 66 3 30 -0.5 -15.7 -2.8 16.0 67 3 31 20.1 3.7 5.1 21.1 68 3 32 18.5 19.2 13.3 29.7 69 3 33 17.5 15.5 10.4 25.6 70 3 34 -0.9 9.8 2.5 10.2 71 3 35 27.7 6.7 21.2 35.5 72 3 36 5.5 21.5 10.6 24.6 73 3 37 36.5 23.5 37.1 57.1 74 3 38 18.2 2.4 12.1 22.0 75 3 39 12.1 10.1 20.1 25.5 76 3 40 17.2 0.2 17.4 24.5 77 3 41 11.0 0.1 -3.3 11.5 78 3 42 -2.5 3.0 -4.3 5.8 79 3 43 5.4 1.6 5.0 7.6 80 3 44 -3.1 0.1 -0.6 3.2 81 3 45 1.7 -1.4 8.9 9.1 82 3 46 9.2 3.6 10.5 14.4 83 3 47 18.0 4.4 21.0 28.0 84 3 48 9.3 3.5 28.5 30.2 85 4 1 8.7 -2.7 -14.9 17.4 86 4 2 2.9 2.4 -3.4 5.1 87 4 3 12.8 1.3 6.9 14.6 88 4 4 6.1 -0.1 17.7 18.7 89 4 5 8.1 1.3 9.3 12.5 90 4 6 -1.7 7.4 11.4 13.7 91 4 7 -2.0 6.2 5.9 8.8 92 4 8 5.6 0.3 1.8 5.9 93 4 9 -0.6 0.9 0.2 1.1 94 4 10 10.0 2.1 6.1 11.9 95 4 11 -5.2 6.7 6.9 10.9 96 4 12 11.0 1.2 3.4 11.6 97 4 13 2.9 2.8 -14.0 14.6 98 4 14 -5.1 -5.0 -0.9 7.2 99 4 15 0.0 0.7 1.6 1.7 100 4 16 6.9 -9.9 0.9 12.2 101 4 17 5.0 -3.5 4.2 7.5 102 4 18 1.0 -7.5 -8.6 11.5 103 4 19 0.1 -5.6 -7.2 9.1 104 4 20 -4.1 -10.9 3.8 12.3 105 4 21 -10.7 -13.3 -2.9 17.3 106 4 22 21.5 -10.4 -19.3 30.7 107 4 23 4.5 -6.0 -24.7 25.8 108 4 24 4.5 -16.2 -16.1 23.3 109 4 25 10.3 -17.5 40.7 45.5 110 4 26 -0.3 -0.7 -6.5 6.6 111 4 27 -3.7 -6.9 -8.1 11.2 112 4 28 -5.0 -0.8 -1.5 5.3 113 4 29 8.4 -5.1 -46.5 47.5 114 4 30 2.0 1.3 -6.6 7.0 115 4 31 19.1 -1.9 5.9 20.1 116 4 32 12.0 0.1 3.1 12.4 117 4 33 20.0 -8.3 -3.0 21.9 118 4 34 9.7 4.0 12.7 16.5 119 4 35 3.7 -5.9 9.6 11.9 120 4 36 19.8 11.2 10.8 25.1 121 4 37 19.6 1.2 2.5 19.8 122 4 38 -4.7 -0.1 7.5 8.9 123 4 39 5.2 -0.6 -9.8 11.1 124 4 40 -13.9 -7.6 -7.1 17.3 125 4 41 -5.2 -19.6 -2.3 20.4 126 4 42 -1.6 -2.8 8.1 8.7 127 4 43 -3.3 1.1 15.2 15.6 128 4 44 -2.5 -6.2 0.9 6.7 129 4 45 -7.6 -6.6 2.1 10.3 130 4 46 1.3 -5.9 1.2 6.2 131 4 47 3.9 -2.7 -18.2 18.8 132 4 48 14.5 -4.5 -8.4 17.3 133 5 1 -14.2 -20.1 -3.2 24.8 134 5 2 -15.3 -5.6 -1.3 16.4 135 5 3 0.9 -21.3 -7.4 22.5 136 5 4 -4.5 -3.0 15.2 16.2 137 5 5 1.0 -1.5 14.8 14.9 138 5 6 4.9 -3.0 0.1 5.8 139 5 7 14.0 -13.7 -8.3 21.3 140 5 8 4.4 -8.6 17.4 19.9 141 5 9 -8.9 -5.3 5.8 11.9 142 5 10 2.7 -1.5 0.4 3.1 143 5 11 -5.9 -5.6 0.5 8.2 144 5 12 -1.7 -14.9 2.6 15.2 145 5 13 0.7 -10.7 3.0 11.2 146 5 14 -7.9 -8.4 0.4 11.5 147 5 15 -8.8 -9.0 1.8 12.7 148 5 16 -4.1 -18.3 -3.0 19.0 149 5 17 -2.9 -22.0 -36.3 42.5 150 5 18 -13.2 -15.2 196.5 197.5 151 5 19 -12.9 -10.6 -2.1 16.8 152 5 20 -2.2 -11.8 -7.9 14.3 153 5 21 -8.0 -22.5 -19.9 31.1 154 5 22 -8.0 -12.1 -18.7 23.7 155 5 23 -6.4 -13.1 -22.4 26.7 156 5 24 -14.8 -10.1 -22.2 28.5 157 5 25 -13.0 -15.0 -7.8 21.3 158 5 26 -12.3 -9.7 -6.3 16.9 159 5 27 2.5 -3.4 8.4 9.4 160 5 28 -5.3 2.8 10.0 11.6 161 5 29 -4.1 2.1 16.3 16.9 162 5 30 1.6 7.3 1.6 7.6 163 5 31 3.7 4.9 6.9 9.3 164 5 32 7.0 -7.1 -5.6 11.4 165 5 33 -8.7 -17.0 -6.0 20.0 166 5 34 0.9 1.4 -10.5 10.6 167 5 35 -8.3 -15.8 -11.4 21.1 168 5 36 7.0 -13.7 10.9 18.9 169 5 37 -11.3 -20.0 13.3 26.5 170 5 38 -9.6 -16.9 -10.9 22.2 171 5 39 -8.0 -30.0 -11.9 33.2 172 5 40 -14.5 -20.3 -15.0 29.1 173 5 41 -16.3 -23.3 -5.7 29.0 174 5 42 -2.4 -10.4 3.3 11.2 175 5 43 3.5 -8.8 -4.3 10.4 176 5 44 -9.7 -22.2 -9.5 26.0 177 5 45 -20.2 -25.0 -3.1 32.3 178 5 46 -11.7 -30.1 -17.5 36.8 179 5 47 -19.4 -19.5 -1.8 27.6 180 5 48 -11.9 -24.5 -3.4 27.5 181 6 1 -9.8 -15.8 18.1 25.9 182 6 2 -5.2 2.3 16.2 17.2 183 6 3 -10.5 3.2 22.3 24.9 184 6 4 -3.6 3.6 20.3 20.9 185 6 5 0.1 6.1 23.5 24.3 186 6 6 -4.5 -6.8 17.5 19.3 187 6 7 -5.2 -1.5 17.3 18.2 188 6 8 5.9 -2.2 -0.0 6.3 189 6 9 9.5 4.9 18.5 21.4 190 6 10 13.1 3.1 18.8 23.1 191 6 11 -8.0 -2.7 8.8 12.2 192 6 12 -2.5 -8.3 18.9 20.8 193 6 13 0.6 0.4 25.0 25.0 194 6 14 -12.6 -1.4 13.1 18.2 195 6 15 3.7 7.5 0.2 8.4 196 6 16 13.7 -17.7 2.8 22.6 197 6 17 4.0 -9.1 6.4 11.9 198 6 18 -4.2 -17.3 23.8 29.8 199 6 19 -19.3 -8.8 -13.8 25.3 200 6 20 -4.2 -26.4 -27.3 38.2 201 6 21 -5.3 -16.3 -4.7 17.8 202 6 22 -19.6 -14.6 -0.6 24.4 203 6 23 -19.2 -7.7 -26.9 34.0 204 6 24 -10.8 -10.3 -7.7 16.8 205 6 25 9.7 -9.5 24.2 27.8 206 6 26 11.1 12.7 1.0 16.9 207 6 27 28.6 9.2 24.6 38.8 208 6 28 22.1 15.0 20.8 33.8 209 6 29 48.0 12.2 36.8 61.7 210 6 30 23.2 2.3 47.7 53.1 211 6 31 7.4 4.9 12.7 15.4 212 6 32 14.9 9.4 1.7 17.7 213 6 33 -6.2 -10.6 0.0 12.3 214 6 34 -14.2 2.5 -0.5 14.4 215 6 35 -16.8 -8.6 -9.0 20.9 216 6 36 4.6 17.2 2.1 17.9 217 6 37 -8.7 -9.5 -5.9 14.2 218 6 38 -19.4 -4.7 -0.7 20.0 219 6 39 -13.4 -10.4 -10.5 20.0 220 6 40 -12.1 -12.6 9.4 19.9 221 6 41 -11.2 -17.5 8.6 22.5 222 6 42 -23.9 -19.3 -0.4 30.7 223 6 43 -17.3 -15.5 -20.5 30.9 224 6 44 -21.6 -15.0 -7.7 27.4 225 6 45 -29.1 -26.4 0.6 39.3 226 6 46 -29.7 -13.6 6.3 33.2 227 6 47 -11.2 -7.7 12.7 18.6 228 6 48 -16.9 -22.2 6.4 28.6 229 7 1 -0.5 -28.3 -13.3 31.3 230 7 2 14.2 -5.5 6.5 16.6 231 7 3 29.9 -9.6 26.1 40.8 232 7 4 16.7 10.5 21.2 29.0 233 7 5 33.3 20.1 65.1 75.9 234 7 6 28.8 19.0 64.6 73.3 235 7 7 1.5 21.6 39.3 44.9 236 7 8 -1.7 3.3 -4.1 5.5 237 7 9 0.2 13.6 28.0 31.1 238 7 10 17.3 10.7 34.4 40.0 239 7 11 -0.3 21.9 21.4 30.6 240 7 12 4.1 5.7 20.3 21.5 241 7 13 26.1 14.7 29.9 42.3 242 7 14 10.0 2.8 18.9 21.5 243 7 15 17.4 15.7 22.5 32.5 244 7 16 1.6 6.7 26.7 27.6 245 7 17 -3.9 7.2 14.9 17.0 246 7 18 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12 51 5 12 52 4 12 53 0 12 54 1 12 55 3 12 56 1 12 57 2 12 58 3 12 59 2 12 60 1 12 61 2 12 62 0 12 63 0 12 64 3 12 65 3 12 66 4 12 67 8 12 68 1 12 69 2 Adjuster movements: rms = 19.7 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050223-114820 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1