Reduction started at: 20041118-103655 Reading data from rxh3-20041118-010140.fits Reduction ID: default Read keywords into global array holo_keys Read binary table data into global array holo_data Finished reading data Converted positions to arcsec, times to elapsed seconds, and reversed x-axis Pattern extent: min = 2402.5 max = 2422.7 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.890 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 -3.12744 2.97607 -0.00027 loimag -3.31055 3.08105 -0.00684 hireal -5.00000 4.99756 0.01118 hiimag -5.00000 4.99756 0.02640 xpos -2422.70217 2410.39581 -10.21542 ypos -2402.48129 2402.46045 -0.00156 plock160 1.55273 2.84912 2.26158 lorefpwr 1.55518 3.09082 2.63425 losigpwr -4.65088 -0.29541 -4.53709 hirefpwr 1.61621 3.09814 2.65877 hisigpwr -4.57031 4.99756 -1.47302 encltemp 28.68652 30.22461 29.45261 flags 0.00000 257.00000 2.56970 phi-lock -0.80566 0.48828 -0.20149 sindex 0.00000 254.00000 126.60925 time 0.00000 5876.99217 2937.60853 zeropt -0.00732 -0.00244 -0.00485 ---------------------------------------------------- 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 = 20.00298 arcsec Mean row spacing = 20.00299 arcsec (alternate estimator) Mean tracking incline = -0.11688 arcsec Mean pointing range = 0.55741 arcsec Mean pointing rms = 0.10518 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (-6.4, 18.5 ) 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: 183249 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 = 2422.7 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 = 3.00923 at (0.0, 0.0) arcsec Real: mean = 0.000376537 sum of squares = 2082.19 Imag: mean = 0.000392915 sum of squares = 2268.51 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 = 2.97552 at (0.0, 0.0) arcsec Real: mean = 0.000163834 sum of squares = 2165.76 Imag: mean = 0.000573021 sum of squares = 2196.43 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 = 2.975 at (0.0, 0.0) arcsec Real: mean = -3.3683e-05 sum of squares = 2282.49 Imag: mean = 0.000424268 sum of squares = 2095.61 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 = 2.99462 at (0.0, 0.0) arcsec Real: mean = -8.75923e-05 sum of squares = 2181.75 Imag: mean = 0.000312732 sum of squares = 2208.96 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 = 3.04259 at (0.0, 0.0) arcsec Real: mean = -5.46823e-05 sum of squares = 2109.19 Imag: mean = 7.26272e-05 sum of squares = 2303.07 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 = 3.06973 at (0.0, 0.0) arcsec Real: mean = 0.000201195 sum of squares = 2264.19 Imag: mean = -4.2757e-06 sum of squares = 2170.1 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 = 3.07456 at (0.0, 0.0) arcsec Real: mean = 0.000395896 sum of squares = 2303.82 Imag: mean = 0.000177737 sum of squares = 2157.21 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 = 3.06228 at (0.0, 0.0) arcsec Real: mean = 0.000344636 sum of squares = 2177.9 Imag: mean = 0.000348399 sum of squares = 2314.36 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 = 3.03184 at (0.0, 0.0) arcsec Real: mean = 0.000311061 sum of squares = 2199.37 Imag: mean = 0.000479852 sum of squares = 2324.85 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 = 3.03558 at (0.0, 0.0) arcsec Real: mean = 3.62901e-05 sum of squares = 2372.15 Imag: mean = 0.000590974 sum of squares = 2188.99 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 = 3.07307 at (0.0, 0.0) arcsec Real: mean = -7.98084e-05 sum of squares = 2330.17 Imag: mean = 0.000343992 sum of squares = 2271.78 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 = 3.10576 at (0.0, 0.0) arcsec Real: mean = -7.72167e-05 sum of squares = 2220.12 Imag: mean = 0.000172312 sum of squares = 2424.68 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 = 3.12405 at (0.0, 0.0) arcsec Real: mean = 0.000158871 sum of squares = 2341 Imag: mean = 2.58952e-05 sum of squares = 2341.66 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 = 3.14628 at (0.0, 0.0) arcsec Real: mean = 0.000310099 sum of squares = 2459.2 Imag: mean = 0.00017017 sum of squares = 2260.58 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 = 3.13775 at (0.0, 0.0) arcsec Real: mean = 0.000409747 sum of squares = 2345.91 Imag: mean = 0.000227705 sum of squares = 2417.1 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 = 3.10874 at (0.0, 0.0) arcsec Real: mean = 0.000360644 sum of squares = 2310.25 Imag: mean = 0.000561514 sum of squares = 2497.98 Masking frequency index 0 Mask scale size = 6.11769 Masking frequency index 1 Mask scale size = 6.11784 Masking frequency index 2 Mask scale size = 6.118 Masking frequency index 3 Mask scale size = 6.11815 Masking frequency index 4 Mask scale size = 6.1183 Masking frequency index 5 Mask scale size = 6.11845 Masking frequency index 6 Mask scale size = 6.1186 Masking frequency index 7 Mask scale size = 6.11876 Masking frequency index 8 Mask scale size = 6.11891 Masking frequency index 9 Mask scale size = 6.11906 Masking frequency index 10 Mask scale size = 6.11921 Masking frequency index 11 Mask scale size = 6.11937 Masking frequency index 12 Mask scale size = 6.11952 Masking frequency index 13 Mask scale size = 6.11967 Masking frequency index 14 Mask scale size = 6.11982 Masking frequency index 15 Mask scale size = 6.11997 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.224609 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.241699 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.231934 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.202637 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: 0.219727 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00976562 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -1.0053 133.84 Freq 1: Shift, scale = -1.867 134.26 Freq 2: Shift, scale = -2.7416 134.63 Freq 3: Shift, scale = 2.6757 133.35 Freq 4: Shift, scale = 1.824 133.57 Freq 5: Shift, scale = 0.96452 135.34 Freq 6: Shift, scale = 0.098352 136.21 Freq 7: Shift, scale = -0.77577 136.81 Freq 8: Shift, scale = -1.6467 135.26 Freq 9: Shift, scale = -2.4981 134.81 Freq 10: Shift, scale = 2.9343 137.08 Freq 11: Shift, scale = 2.0691 139.31 Freq 12: Shift, scale = 1.1929 139.84 Freq 13: Shift, scale = 0.32359 139.2 Freq 14: Shift, scale = -0.53652 139 Freq 15: Shift, scale = -1.3939 139.42 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: -0.249 radians x offset: 0.0378 arcsec y offset: 0.0203 arcsec defocus: 0.00613 mm Estimated x pointing error is -6.362 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.52 arcsec (used 18.5 arcsec) Estimated defocus error is 2.896 mm (used 2.89 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.247 radians x offset: 0.029 arcsec y offset: 0.0289 arcsec defocus: 0.00598 mm Estimated x pointing error is -6.371 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.53 arcsec (used 18.5 arcsec) Estimated defocus error is 2.896 mm (used 2.89 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.256 radians x offset: 0.0288 arcsec y offset: -0.00237 arcsec defocus: 0.00569 mm Estimated x pointing error is -6.371 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.5 arcsec (used 18.5 arcsec) Estimated defocus error is 2.896 mm (used 2.89 mm) Fitting frequency 3 Minimiser fit code = 3 piston: -0.259 radians x offset: 0.0359 arcsec y offset: -0.0219 arcsec defocus: 0.00389 mm Estimated x pointing error is -6.364 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.48 arcsec (used 18.5 arcsec) Estimated defocus error is 2.894 mm (used 2.89 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.246 radians x offset: 0.0194 arcsec y offset: -0.00617 arcsec defocus: 0.00458 mm Estimated x pointing error is -6.381 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.49 arcsec (used 18.5 arcsec) Estimated defocus error is 2.895 mm (used 2.89 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.241 radians x offset: 0.0144 arcsec y offset: 0.0182 arcsec defocus: 0.00594 mm Estimated x pointing error is -6.386 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.52 arcsec (used 18.5 arcsec) Estimated defocus error is 2.896 mm (used 2.89 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.245 radians x offset: -0.000362 arcsec y offset: 0.0324 arcsec defocus: 0.00531 mm Estimated x pointing error is -6.4 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.53 arcsec (used 18.5 arcsec) Estimated defocus error is 2.895 mm (used 2.89 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.256 radians x offset: 0.0013 arcsec y offset: 0.00954 arcsec defocus: 0.00433 mm Estimated x pointing error is -6.399 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.51 arcsec (used 18.5 arcsec) Estimated defocus error is 2.894 mm (used 2.89 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.263 radians x offset: 0.00107 arcsec y offset: -0.00952 arcsec defocus: 0.00369 mm Estimated x pointing error is -6.399 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.49 arcsec (used 18.5 arcsec) Estimated defocus error is 2.894 mm (used 2.89 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.251 radians x offset: -0.00707 arcsec y offset: 0.000804 arcsec defocus: 0.00368 mm Estimated x pointing error is -6.407 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.5 arcsec (used 18.5 arcsec) Estimated defocus error is 2.894 mm (used 2.89 mm) Fitting frequency 10 Minimiser fit code = 2 piston: -0.239 radians x offset: -0.0114 arcsec y offset: 0.0291 arcsec defocus: 0.00397 mm Estimated x pointing error is -6.411 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.53 arcsec (used 18.5 arcsec) Estimated defocus error is 2.894 mm (used 2.89 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.242 radians x offset: -0.0101 arcsec y offset: 0.0254 arcsec defocus: 0.00348 mm Estimated x pointing error is -6.41 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.53 arcsec (used 18.5 arcsec) Estimated defocus error is 2.893 mm (used 2.89 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.254 radians x offset: -0.0254 arcsec y offset: 0.000823 arcsec defocus: 0.00274 mm Estimated x pointing error is -6.425 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.5 arcsec (used 18.5 arcsec) Estimated defocus error is 2.893 mm (used 2.89 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.262 radians x offset: -0.0268 arcsec y offset: -0.0227 arcsec defocus: 0.0007 mm Estimated x pointing error is -6.427 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.48 arcsec (used 18.5 arcsec) Estimated defocus error is 2.891 mm (used 2.89 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.259 radians x offset: -0.0364 arcsec y offset: -0.0138 arcsec defocus: 0.000656 mm Estimated x pointing error is -6.436 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.49 arcsec (used 18.5 arcsec) Estimated defocus error is 2.891 mm (used 2.89 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.252 radians x offset: -0.0499 arcsec y offset: 0.00652 arcsec defocus: 0.00246 mm Estimated x pointing error is -6.45 arcsec (used -6.4 arcsec) Estimated y pointing error is 18.51 arcsec (used 18.5 arcsec) Estimated defocus error is 2.892 mm (used 2.89 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 -0.00183 piston 1 1 0.01783 tilt_x 1 -1 0.00300 tilt_y 2 2 -0.05993 astigmatism_0 2 0 -0.00066 curvature 2 -2 -0.01549 astigmatism45 3 3 0.02967 trefoil_0 3 1 0.04123 coma_x 3 -1 0.01985 coma_y 3 -3 0.00754 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 -0.00179 piston 1 1 0.01799 tilt_x 1 -1 0.00280 tilt_y 2 2 -0.05887 astigmatism_0 2 0 -0.00058 curvature 2 -2 -0.01425 astigmatism45 3 3 0.02923 trefoil_0 3 1 0.04226 coma_x 3 -1 0.01840 coma_y 3 -3 0.00771 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 -0.00178 piston 1 1 0.01818 tilt_x 1 -1 0.00243 tilt_y 2 2 -0.06144 astigmatism_0 2 0 -0.00047 curvature 2 -2 -0.01168 astigmatism45 3 3 0.03126 trefoil_0 3 1 0.04250 coma_x 3 -1 0.01704 coma_y 3 -3 0.01149 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 -0.00177 piston 1 1 0.01790 tilt_x 1 -1 0.00157 tilt_y 2 2 -0.06417 astigmatism_0 2 0 -0.00028 curvature 2 -2 -0.01103 astigmatism45 3 3 0.03359 trefoil_0 3 1 0.04116 coma_x 3 -1 0.01481 coma_y 3 -3 0.01429 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 -0.00171 piston 1 1 0.01698 tilt_x 1 -1 0.00179 tilt_y 2 2 -0.06286 astigmatism_0 2 0 -0.00019 curvature 2 -2 -0.01258 astigmatism45 3 3 0.03250 trefoil_0 3 1 0.03883 coma_x 3 -1 0.01654 coma_y 3 -3 0.01098 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 -0.00174 piston 1 1 0.01696 tilt_x 1 -1 0.00267 tilt_y 2 2 -0.05936 astigmatism_0 2 0 -0.00041 curvature 2 -2 -0.01437 astigmatism45 3 3 0.02853 trefoil_0 3 1 0.03987 coma_x 3 -1 0.01953 coma_y 3 -3 0.00403 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 -0.00175 piston 1 1 0.01647 tilt_x 1 -1 0.00252 tilt_y 2 2 -0.05817 astigmatism_0 2 0 -0.00040 curvature 2 -2 -0.01440 astigmatism45 3 3 0.02800 trefoil_0 3 1 0.03845 coma_x 3 -1 0.01834 coma_y 3 -3 0.00286 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 -0.00186 piston 1 1 0.01694 tilt_x 1 -1 0.00215 tilt_y 2 2 -0.06233 astigmatism_0 2 0 -0.00042 curvature 2 -2 -0.01218 astigmatism45 3 3 0.03161 trefoil_0 3 1 0.03885 coma_x 3 -1 0.01718 coma_y 3 -3 0.00750 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 -0.00182 piston 1 1 0.01729 tilt_x 1 -1 0.00191 tilt_y 2 2 -0.06550 astigmatism_0 2 0 -0.00026 curvature 2 -2 -0.00991 astigmatism45 3 3 0.03333 trefoil_0 3 1 0.03986 coma_x 3 -1 0.01762 coma_y 3 -3 0.00921 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 -0.00177 piston 1 1 0.01746 tilt_x 1 -1 0.00223 tilt_y 2 2 -0.06456 astigmatism_0 2 0 -0.00029 curvature 2 -2 -0.00994 astigmatism45 3 3 0.03111 trefoil_0 3 1 0.04118 coma_x 3 -1 0.01943 coma_y 3 -3 0.00647 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 -0.00175 piston 1 1 0.01752 tilt_x 1 -1 0.00275 tilt_y 2 2 -0.06084 astigmatism_0 2 0 -0.00040 curvature 2 -2 -0.01229 astigmatism45 3 3 0.02917 trefoil_0 3 1 0.04211 coma_x 3 -1 0.02063 coma_y 3 -3 0.00179 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 -0.00171 piston 1 1 0.01767 tilt_x 1 -1 0.00305 tilt_y 2 2 -0.05854 astigmatism_0 2 0 -0.00038 curvature 2 -2 -0.01180 astigmatism45 3 3 0.02969 trefoil_0 3 1 0.04277 coma_x 3 -1 0.02077 coma_y 3 -3 0.00053 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 -0.00174 piston 1 1 0.01707 tilt_x 1 -1 0.00199 tilt_y 2 2 -0.06153 astigmatism_0 2 0 -0.00015 curvature 2 -2 -0.01067 astigmatism45 3 3 0.03218 trefoil_0 3 1 0.04013 coma_x 3 -1 0.01644 coma_y 3 -3 0.00566 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 -0.00177 piston 1 1 0.01775 tilt_x 1 -1 0.00157 tilt_y 2 2 -0.06498 astigmatism_0 2 0 -0.00016 curvature 2 -2 -0.01004 astigmatism45 3 3 0.03362 trefoil_0 3 1 0.04161 coma_x 3 -1 0.01576 coma_y 3 -3 0.00927 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 -0.00177 piston 1 1 0.01810 tilt_x 1 -1 0.00193 tilt_y 2 2 -0.06304 astigmatism_0 2 0 -0.00034 curvature 2 -2 -0.01128 astigmatism45 3 3 0.03172 trefoil_0 3 1 0.04324 coma_x 3 -1 0.01757 coma_y 3 -3 0.00601 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 -0.00178 piston 1 1 0.01818 tilt_x 1 -1 0.00303 tilt_y 2 2 -0.06020 astigmatism_0 2 0 -0.00048 curvature 2 -2 -0.01286 astigmatism45 3 3 0.02988 trefoil_0 3 1 0.04424 coma_x 3 -1 0.02141 coma_y 3 -3 0.00150 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: 24.2 23.5 20.2 24.2 24.6 24.3 35.7 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.4 20.2 24.2 24.7 24.5 33.5 26.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.41 2.48 3.19 3.54 3.8 4.79 7.18 4.79 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 23 20.1 24 24.6 24.1 35.4 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 22.9 20.2 24 24.6 24.3 33.2 26.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.42 2.49 3.2 3.53 3.75 4.69 7.08 4.73 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 23 19.9 23.8 24.4 24.1 35.2 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 22.9 20 23.7 24.4 24.3 33 26.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.41 2.48 3.2 3.56 3.86 4.89 7.32 4.88 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.3 23.2 19.9 24.2 24.5 24.3 35.3 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.3 23.1 20 24.2 24.4 24.4 33.1 26.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.35 2.39 3.1 3.53 3.96 5.13 7.58 5.01 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 23.5 20 25.2 24.6 24.3 35.5 27.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 23.3 20.1 25.2 24.6 24.4 33.4 26.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.3 2.3 3 3.42 3.87 5.01 7.37 4.88 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 23.7 20.1 24.8 24.5 24.2 35.5 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 23.5 20.1 24.8 24.5 24.4 33.3 26.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.37 2.41 3.11 3.45 3.72 4.69 7.02 4.68 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.4 23.6 20.2 24.2 24.5 24 35.1 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.4 23.5 20.3 24.2 24.5 24.2 33 26.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.31 2.31 2.99 3.34 3.63 4.6 6.85 4.57 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.1 23.2 19.9 23.9 24.4 24 35 26.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.1 20 23.9 24.4 24.1 32.8 26.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.31 2.32 3.01 3.42 3.83 4.93 7.27 4.82 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.4 20 23.7 24.3 24 35.3 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.3 20.1 23.6 24.3 24.1 32.9 26.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.34 2.38 3.1 3.53 3.98 5.15 7.59 5.03 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 23.6 20.4 23.9 24.5 24.1 35.6 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 23.5 20.5 23.9 24.4 24.2 33.3 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.4 2.48 3.2 3.6 3.95 5.03 7.48 4.98 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 25 23.5 20.3 24.4 24.3 24.1 35.5 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25 23.4 20.4 24.4 24.3 24.2 33.3 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.44 2.54 3.26 3.59 3.82 4.77 7.18 4.81 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 23.3 20.1 24.7 24.2 24 35.2 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 23.2 20.2 24.8 24.3 24.2 33 26.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.46 2.57 3.29 3.59 3.74 4.63 7.04 4.72 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.4 20.1 24.6 24.3 24.2 35.1 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.3 20.1 24.6 24.3 24.3 32.9 26.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.34 2.36 3.06 3.44 3.8 4.86 7.22 4.8 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.4 20 24 24.4 24.2 35.3 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24 23.3 20 24 24.4 24.3 33 26.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.37 2.42 3.15 3.57 3.98 5.13 7.59 5.03 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.3 20.1 23.9 24.4 24.3 35.7 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.1 23.2 20.1 23.9 24.4 24.5 33.5 26.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.44 2.53 3.26 3.63 3.93 4.96 7.43 4.95 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.3 20.3 24 24.5 24.3 35.6 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.2 23.1 20.4 24 24.6 24.5 33.3 26.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.51 2.65 3.39 3.7 3.85 4.76 7.24 4.86 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 23.5 22.4 19.1 22.4 23.7 23.2 34.3 26.1 Mean deviation is 0.049232392759689998 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 = 22.6 micron Centre pixel: 128.0 128.0 Value = 12977.7 (estimate), 15687.6 (perfect) Strehl = 0.684354 Strehl ratio estimate = 0.6844 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 = 21.9 micron Centre pixel: 128.0 128.0 Value = 11143.2 (estimate), 15687.6 (perfect) Strehl = 0.504549 Strehl ratio estimate = 0.5045 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 -0.1 4.4 -0.6 4.5 2 1 2 8.0 -3.3 -7.1 11.2 3 1 3 14.6 2.9 8.5 17.2 4 1 4 11.0 15.5 -25.0 31.4 5 1 5 -16.6 3.7 24.1 29.5 6 1 6 1.5 2.7 -0.9 3.3 7 1 7 24.4 -2.4 10.8 26.8 8 1 8 -6.1 23.6 22.2 33.0 9 1 9 -69.2 -6.9 25.8 74.2 10 1 10 21.6 22.2 17.3 35.5 11 1 11 14.3 3.1 4.6 15.4 12 1 12 -2.7 8.5 1.6 9.1 13 2 1 18.1 1.2 -0.2 18.2 14 2 2 12.9 1.6 3.8 13.5 15 2 3 11.1 1.3 -3.0 11.5 16 2 4 7.2 1.9 11.6 13.8 17 2 5 -2.7 16.8 4.9 17.7 18 2 6 1.6 -1.4 -3.6 4.2 19 2 7 18.0 17.9 -11.1 27.7 20 2 8 -4.2 10.1 19.0 21.9 21 2 9 7.1 -0.6 -6.2 9.4 22 2 10 2.2 2.1 3.6 4.7 23 2 11 -1.2 0.6 5.2 5.4 24 2 12 3.7 2.7 -0.1 4.6 25 2 13 -0.9 -3.5 2.8 4.6 26 2 14 3.5 4.6 10.3 11.8 27 2 15 -0.2 8.4 5.2 9.9 28 2 16 4.8 9.1 2.9 10.7 29 2 17 24.8 -5.5 8.5 26.8 30 2 18 9.4 23.6 2.5 25.6 31 2 19 18.1 -3.5 32.3 37.2 32 2 20 15.4 6.9 -6.2 18.0 33 2 21 4.8 22.8 23.0 32.7 34 2 22 18.2 6.0 9.3 21.3 35 2 23 7.7 6.6 22.7 24.8 36 2 24 17.2 3.6 2.8 17.8 37 3 1 11.2 -2.2 1.7 11.5 38 3 2 4.7 1.0 5.7 7.4 39 3 3 0.4 -0.8 -3.2 3.3 40 3 4 -4.9 -3.8 -1.7 6.5 41 3 5 10.1 1.5 1.9 10.4 42 3 6 -4.7 -0.2 -0.5 4.7 43 3 7 -9.1 -1.5 -0.2 9.2 44 3 8 5.5 -2.5 -18.7 19.6 45 3 9 7.1 3.3 0.2 7.8 46 3 10 -1.9 -6.1 -1.2 6.6 47 3 11 4.8 -1.7 10.7 11.9 48 3 12 13.0 -18.6 12.1 25.7 49 3 13 4.6 -18.1 16.9 25.2 50 3 14 20.4 4.9 6.1 21.9 51 3 15 1.0 -2.0 -1.7 2.8 52 3 16 4.2 -4.0 7.1 9.2 53 3 17 -3.9 -0.5 4.7 6.2 54 3 18 7.8 -4.8 5.2 10.5 55 3 19 3.5 0.9 -2.9 4.6 56 3 20 10.1 -5.7 -9.8 15.2 57 3 21 -1.2 -7.7 -1.1 7.9 58 3 22 -1.5 -8.3 -1.1 8.5 59 3 23 -12.1 -9.1 -0.9 15.2 60 3 24 -3.6 -11.1 1.9 11.8 61 3 25 -1.6 -10.6 -3.5 11.3 62 3 26 -21.5 -11.3 -1.4 24.3 63 3 27 -2.4 -9.3 -6.0 11.3 64 3 28 9.3 -3.7 -12.2 15.8 65 3 29 27.7 -3.3 -20.5 34.7 66 3 30 13.0 -14.9 -10.9 22.5 67 3 31 14.7 8.4 12.5 21.0 68 3 32 8.4 9.6 19.0 22.9 69 3 33 4.7 3.0 -3.4 6.5 70 3 34 5.5 16.3 -15.2 22.9 71 3 35 1.1 18.3 11.6 21.7 72 3 36 1.7 -5.0 9.0 10.4 73 3 37 28.4 -8.8 7.3 30.7 74 3 38 -4.0 -3.7 -2.4 6.0 75 3 39 5.9 2.2 10.0 11.8 76 3 40 34.9 -1.5 1.0 34.9 77 3 41 -3.4 -12.8 -4.3 13.9 78 3 42 -11.1 6.1 3.7 13.2 79 3 43 5.6 1.3 -4.4 7.2 80 3 44 10.6 -2.4 -5.5 12.2 81 3 45 8.3 -5.7 0.5 10.1 82 3 46 9.5 1.1 1.3 9.7 83 3 47 10.5 2.7 2.4 11.1 84 3 48 11.3 2.7 9.7 15.1 85 4 1 -4.9 7.3 18.9 20.8 86 4 2 3.5 10.1 12.1 16.2 87 4 3 -0.3 3.3 5.9 6.8 88 4 4 -4.1 -6.2 13.2 15.2 89 4 5 -10.9 -6.8 -2.5 13.1 90 4 6 -5.6 -13.3 -14.2 20.3 91 4 7 2.7 -15.4 -23.6 28.3 92 4 8 -1.2 -10.5 -9.8 14.4 93 4 9 -9.5 -16.4 -14.5 23.9 94 4 10 -3.7 -6.6 -11.3 13.6 95 4 11 3.1 -10.5 8.8 14.1 96 4 12 0.9 -17.1 -1.2 17.1 97 4 13 0.8 -14.5 5.2 15.4 98 4 14 -5.5 -3.8 -1.4 6.8 99 4 15 -0.2 0.9 11.6 11.7 100 4 16 8.0 -0.7 -0.5 8.0 101 4 17 1.8 -2.7 2.9 4.4 102 4 18 -15.8 3.5 18.2 24.3 103 4 19 -2.6 -0.8 14.2 14.5 104 4 20 4.2 2.2 5.0 6.9 105 4 21 0.5 -4.0 -2.8 4.9 106 4 22 6.9 -2.0 -8.7 11.3 107 4 23 -0.7 -3.3 -2.3 4.1 108 4 24 -4.7 -6.0 0.5 7.6 109 4 25 -7.2 -4.5 47.4 48.2 110 4 26 -2.2 -4.9 -4.4 6.9 111 4 27 -8.3 -4.6 -5.7 11.0 112 4 28 4.7 -1.9 -5.3 7.4 113 4 29 2.2 3.8 -38.6 38.8 114 4 30 -9.2 -0.3 23.1 24.8 115 4 31 -14.7 -1.2 13.1 19.7 116 4 32 11.6 -0.3 -6.1 13.1 117 4 33 15.9 7.6 2.0 17.7 118 4 34 -5.3 -3.3 -1.0 6.4 119 4 35 -14.0 6.3 -26.3 30.5 120 4 36 19.6 -15.0 21.3 32.6 121 4 37 5.4 -27.5 4.6 28.4 122 4 38 15.5 -10.3 11.0 21.7 123 4 39 -0.1 1.6 -15.0 15.1 124 4 40 -12.6 -9.9 -8.7 18.3 125 4 41 6.4 -5.2 9.5 12.6 126 4 42 12.5 -12.6 -5.9 18.7 127 4 43 -3.7 -10.3 4.2 11.7 128 4 44 -16.0 -3.8 5.0 17.2 129 4 45 -4.8 -7.4 12.8 15.5 130 4 46 2.6 0.2 2.4 3.6 131 4 47 -4.8 5.2 12.2 14.1 132 4 48 -8.9 8.1 11.7 16.8 133 5 1 11.6 3.2 -8.9 15.0 134 5 2 22.2 3.2 -9.7 24.4 135 5 3 -15.0 0.6 -16.9 22.7 136 5 4 7.7 2.8 -10.1 12.9 137 5 5 -4.9 -1.2 16.9 17.6 138 5 6 -3.7 -5.8 1.8 7.1 139 5 7 -19.9 -8.8 -6.3 22.7 140 5 8 -19.0 -25.6 -1.7 32.0 141 5 9 -3.2 -20.3 -4.6 21.1 142 5 10 -4.8 -15.1 -6.3 17.1 143 5 11 8.9 -24.6 4.8 26.6 144 5 12 -5.6 -11.0 -2.2 12.5 145 5 13 -3.3 -8.4 -8.2 12.2 146 5 14 -3.8 -5.0 -5.3 8.2 147 5 15 1.4 -5.0 -7.2 8.9 148 5 16 -9.5 1.8 -2.6 10.0 149 5 17 1.3 6.2 -2.4 6.7 150 5 18 5.4 6.1 221.3 221.5 151 5 19 0.1 1.8 11.7 11.8 152 5 20 5.4 1.9 2.4 6.2 153 5 21 13.4 -1.0 -3.2 13.8 154 5 22 15.5 -0.9 -7.0 17.0 155 5 23 3.3 -6.0 -20.0 21.2 156 5 24 -4.8 -16.7 -21.3 27.5 157 5 25 1.0 -16.5 -20.2 26.2 158 5 26 7.0 -5.0 -7.5 11.4 159 5 27 13.0 -13.5 -5.3 19.5 160 5 28 12.1 0.6 -6.5 13.8 161 5 29 10.6 2.5 -2.1 11.1 162 5 30 3.6 8.4 13.1 15.9 163 5 31 3.2 7.8 8.7 12.1 164 5 32 11.3 6.8 7.1 15.0 165 5 33 -13.5 -2.6 -2.5 14.0 166 5 34 4.7 -4.2 -3.0 7.0 167 5 35 -9.3 7.0 -35.6 37.5 168 5 36 -8.3 -2.3 -23.1 24.7 169 5 37 -14.5 -28.7 1.7 32.2 170 5 38 10.7 -25.1 -5.6 27.9 171 5 39 -5.9 -9.4 -4.9 12.1 172 5 40 -10.0 -5.7 -8.5 14.3 173 5 41 -5.9 -13.9 -10.7 18.5 174 5 42 1.5 -0.5 5.3 5.6 175 5 43 9.7 1.3 27.8 29.5 176 5 44 3.7 7.5 28.3 29.5 177 5 45 10.7 7.3 9.8 16.3 178 5 46 18.0 12.6 -7.9 23.4 179 5 47 29.5 5.2 -1.4 29.9 180 5 48 11.2 0.9 4.8 12.2 181 6 1 5.8 -12.1 -11.9 17.9 182 6 2 8.0 -11.3 -6.1 15.1 183 6 3 4.2 -6.3 -17.3 18.9 184 6 4 -2.6 -10.6 -15.0 18.6 185 6 5 -7.9 -8.0 14.7 18.5 186 6 6 -2.3 3.6 5.1 6.7 187 6 7 -1.5 -0.3 14.6 14.7 188 6 8 -0.9 -8.1 17.7 19.5 189 6 9 -22.0 -3.1 1.6 22.3 190 6 10 -10.2 -1.3 -9.8 14.2 191 6 11 -11.3 -8.0 0.9 13.9 192 6 12 -1.9 -9.5 -2.4 10.0 193 6 13 -5.7 -13.1 2.3 14.5 194 6 14 -11.4 -9.8 -5.3 15.9 195 6 15 -0.8 -4.0 6.7 7.8 196 6 16 30.4 -10.4 6.7 32.8 197 6 17 2.1 -10.0 -1.9 10.4 198 6 18 3.5 -7.7 12.4 15.0 199 6 19 -15.0 -8.4 -19.5 26.0 200 6 20 2.7 -28.0 -35.5 45.3 201 6 21 -4.7 -23.3 16.2 28.8 202 6 22 -33.7 -19.8 17.4 42.8 203 6 23 -27.5 -13.6 17.9 35.5 204 6 24 -28.1 -2.4 21.5 35.4 205 6 25 -25.4 -6.0 31.6 41.0 206 6 26 -26.2 -6.3 27.5 38.5 207 6 27 -19.7 -9.3 23.5 32.1 208 6 28 -5.7 -13.5 1.1 14.7 209 6 29 11.8 -16.1 -11.8 23.2 210 6 30 9.7 1.2 44.8 45.9 211 6 31 18.1 -1.8 3.1 18.4 212 6 32 23.5 4.1 1.1 23.9 213 6 33 3.2 -0.9 -13.5 13.9 214 6 34 -13.6 -7.0 1.7 15.4 215 6 35 -13.7 3.0 -12.5 18.8 216 6 36 2.9 5.9 5.2 8.3 217 6 37 -8.9 -15.6 -22.9 29.0 218 6 38 -16.2 -18.1 -18.0 30.3 219 6 39 -2.7 -5.5 -36.1 36.6 220 6 40 -12.8 -19.6 -10.6 25.7 221 6 41 3.6 -11.6 17.9 21.6 222 6 42 10.0 8.7 12.7 18.3 223 6 43 24.5 11.7 -2.3 27.2 224 6 44 6.5 5.0 2.1 8.5 225 6 45 4.8 3.6 -14.1 15.3 226 6 46 23.2 -5.0 -5.2 24.3 227 6 47 7.8 -10.8 -2.8 13.7 228 6 48 -12.8 -8.7 -14.6 21.2 229 7 1 14.8 12.3 47.7 51.5 230 7 2 11.6 24.8 57.3 63.5 231 7 3 3.3 29.8 43.0 52.5 232 7 4 6.8 1.9 42.7 43.2 233 7 5 -20.2 7.9 67.2 70.6 234 7 6 11.6 19.9 40.7 46.8 235 7 7 17.8 22.6 77.3 82.4 236 7 8 28.9 19.3 -16.6 38.5 237 7 9 -3.6 13.9 22.4 26.6 238 7 10 2.0 -4.0 30.0 30.3 239 7 11 -7.2 4.0 19.2 20.9 240 7 12 -2.2 -3.3 26.8 27.1 241 7 13 2.9 9.1 27.2 28.8 242 7 14 2.3 3.6 21.5 21.9 243 7 15 8.0 2.2 22.7 24.2 244 7 16 5.4 -8.0 21.2 23.3 245 7 17 -18.6 -6.9 -3.6 20.1 246 7 18 -13.0 -29.5 -17.0 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3 12 47 -2 12 48 -1 12 49 0 12 50 0 12 51 3 12 52 0 12 53 1 12 54 5 12 55 0 12 56 0 12 57 2 12 58 2 12 59 0 12 60 0 12 61 0 12 62 -1 12 63 2 12 64 0 12 65 2 12 66 6 12 67 2 12 68 0 12 69 3 Adjuster movements: rms = 20.1 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20041118-110224 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1