Reduction started at: 20070925-132953 Reading data from rxh3-20070924-015944.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 = 2418.5 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 34.260 mm ----------------- Data Summary --------------------- Number of samples: 1466025 This is a 160 GHz map Number of frequencies: 16 Frequencies (GHz): 160.688000 160.690000 160.692000 160.696000 160.700000 160.702000 160.704000 160.708000 160.712000 160.714000 160.716000 160.720000 160.724000 160.726000 160.728000 160.732000 item min max mean loreal -2.95654 2.91016 0.00590 loimag -3.02002 2.86377 0.00171 hireal -5.00000 4.99756 -0.00497 hiimag -5.00000 4.99756 0.00644 xpos -2418.50218 2410.77923 -9.93080 ypos -2402.62067 2403.20066 -0.00008 plock160 1.44531 2.60742 2.11057 lorefpwr 1.19629 2.93213 2.37423 losigpwr -4.59961 -0.58350 -4.49397 hirefpwr 1.23535 2.91260 2.38772 hisigpwr -4.51172 4.99756 -1.61701 encltemp 32.05566 34.69238 32.64524 flags 0.00000 256.00000 2.44471 phi-lock -1.02295 0.08789 -0.48963 sindex 0.00000 254.00000 126.60925 time 0.00000 5865.00451 2932.08012 zeropt 0.00000 0.00488 0.00366 !!!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 = 20.00316 arcsec Mean row spacing = 20.00316 arcsec (alternate estimator) Mean tracking incline = -0.00188 arcsec Mean pointing range = 0.61876 arcsec Mean pointing rms = 0.10638 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (8.7, 12.0 ) 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: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 90363 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 90363 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 = 2418.5 arcsec Grid extent = 2550 arcsec lambda_min = 0.00186517 scale = 0.0025993 Diffraction scale lambda/D = 25.6549 arcsec Gridding function extent = 153.93 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 76.9648 arcsec Airy first null at 31.2906 arcsec Gridding frequency index 0 lambda = 0.00186568 metres, scale = 0.00259859 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 = 2.6887 at (0.0, 0.0) arcsec Real: mean = 0.000155989 sum of squares = 1758.44 Imag: mean = -0.000861915 sum of squares = 1718.35 Gridding frequency index 1 lambda = 0.00186566 metres, scale = 0.00259862 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 = 2.68646 at (0.0, 0.0) arcsec Real: mean = 0.000187833 sum of squares = 1807.24 Imag: mean = -0.000781954 sum of squares = 1690.84 Gridding frequency index 2 lambda = 0.00186563 metres, scale = 0.00259865 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 = 2.71086 at (0.0, 0.0) arcsec Real: mean = 0.00019378 sum of squares = 1813.84 Imag: mean = -0.00073857 sum of squares = 1702.58 Gridding frequency index 3 lambda = 0.00186559 metres, scale = 0.00259872 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 = 2.73707 at (0.0, 0.0) arcsec Real: mean = 0.000150488 sum of squares = 1734.43 Imag: mean = -0.000701942 sum of squares = 1820.31 Gridding frequency index 4 lambda = 0.00186554 metres, scale = 0.00259878 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 = 2.74671 at (0.0, 0.0) arcsec Real: mean = 0.000257761 sum of squares = 1753.22 Imag: mean = -0.000736137 sum of squares = 1840.53 Gridding frequency index 5 lambda = 0.00186552 metres, scale = 0.00259882 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 = 2.72787 at (0.0, 0.0) arcsec Real: mean = 0.00033591 sum of squares = 1817.25 Imag: mean = -0.000586757 sum of squares = 1798.17 Gridding frequency index 6 lambda = 0.00186549 metres, scale = 0.00259885 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 = 2.76541 at (0.0, 0.0) arcsec Real: mean = 0.000220225 sum of squares = 1875.55 Imag: mean = -0.000421482 sum of squares = 1764.49 Gridding frequency index 7 lambda = 0.00186545 metres, scale = 0.00259891 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 = 2.78514 at (0.0, 0.0) arcsec Real: mean = -0.000185516 sum of squares = 1867.1 Imag: mean = -0.00058265 sum of squares = 1817.21 Gridding frequency index 8 lambda = 0.0018654 metres, scale = 0.00259898 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 = 2.77542 at (0.0, 0.0) arcsec Real: mean = 7.27264e-05 sum of squares = 1803.44 Imag: mean = -0.000861381 sum of squares = 1930.28 Gridding frequency index 9 lambda = 0.00186538 metres, scale = 0.00259901 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 = 2.78648 at (0.0, 0.0) arcsec Real: mean = 0.000155438 sum of squares = 1823.79 Imag: mean = -0.000731009 sum of squares = 1935.81 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 = 2.76665 at (0.0, 0.0) arcsec Real: mean = 4.72374e-05 sum of squares = 1882.13 Imag: mean = -0.0006504 sum of squares = 1900.65 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 = 2.78525 at (0.0, 0.0) arcsec Real: mean = -1.92395e-05 sum of squares = 1981.68 Imag: mean = -0.000932287 sum of squares = 1848.11 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 = 2.81064 at (0.0, 0.0) arcsec Real: mean = 0.000389566 sum of squares = 1924.14 Imag: mean = -0.000904235 sum of squares = 1953.27 Gridding frequency index 13 lambda = 0.00186524 metres, scale = 0.0025992 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 = 2.83304 at (0.0, 0.0) arcsec Real: mean = 0.000431197 sum of squares = 1888.19 Imag: mean = -0.000667168 sum of squares = 2015.81 Gridding frequency index 14 lambda = 0.00186522 metres, scale = 0.00259924 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 = 2.84759 at (0.0, 0.0) arcsec Real: mean = 0.000286743 sum of squares = 1896.32 Imag: mean = -0.000511455 sum of squares = 2031.56 Gridding frequency index 15 lambda = 0.00186517 metres, scale = 0.0025993 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 = 2.87125 at (0.0, 0.0) arcsec Real: mean = 6.85004e-05 sum of squares = 2025.26 Imag: mean = -0.000636274 sum of squares = 1953.38 Masking frequency index 0 Mask scale size = 6.11856 Masking frequency index 1 Mask scale size = 6.11863 Masking frequency index 2 Mask scale size = 6.11871 Masking frequency index 3 Mask scale size = 6.11886 Masking frequency index 4 Mask scale size = 6.11901 Masking frequency index 5 Mask scale size = 6.11909 Masking frequency index 6 Mask scale size = 6.11916 Masking frequency index 7 Mask scale size = 6.11932 Masking frequency index 8 Mask scale size = 6.11947 Masking frequency index 9 Mask scale size = 6.11955 Masking frequency index 10 Mask scale size = 6.11962 Masking frequency index 11 Mask scale size = 6.11977 Masking frequency index 12 Mask scale size = 6.11993 Masking frequency index 13 Mask scale size = 6.12 Masking frequency index 14 Mask scale size = 6.12008 Masking frequency index 15 Mask scale size = 6.12023 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.224609 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.241699 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00732422 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.00732422 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 0.97878 116.41 Freq 1: Shift, scale = 0.54691 116.54 Freq 2: Shift, scale = 0.11578 117.02 Freq 3: Shift, scale = -0.74664 118.24 Freq 4: Shift, scale = -1.6144 118.58 Freq 5: Shift, scale = -2.0448 118.39 Freq 6: Shift, scale = -2.4761 118.81 Freq 7: Shift, scale = 2.9394 119.92 Freq 8: Shift, scale = 2.072 119.88 Freq 9: Shift, scale = 1.6408 119.74 Freq 10: Shift, scale = 1.2131 119.78 Freq 11: Shift, scale = 0.35215 121.02 Freq 12: Shift, scale = -0.51107 122.16 Freq 13: Shift, scale = -0.94253 122.66 Freq 14: Shift, scale = -1.375 123.09 Freq 15: Shift, scale = -2.2439 123.89 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: -0.208 radians x offset: 0.0667 arcsec y offset: 0.0128 arcsec defocus: 3.8e-05 mm Estimated x pointing error is 8.767 arcsec (used 8.7 arcsec) Estimated y pointing error is 12.01 arcsec (used 12 arcsec) Estimated defocus error is 3.26 mm (used 3.26 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.208 radians x offset: 0.057 arcsec y offset: 0.00873 arcsec defocus: 0.00079 mm Estimated x pointing error is 8.757 arcsec (used 8.7 arcsec) Estimated y pointing error is 12.01 arcsec (used 12 arcsec) Estimated defocus error is 3.261 mm (used 3.26 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.207 radians x offset: 0.0495 arcsec y offset: 0.00532 arcsec defocus: 0.000974 mm Estimated x pointing error is 8.75 arcsec (used 8.7 arcsec) Estimated y pointing error is 12.01 arcsec (used 12 arcsec) Estimated defocus error is 3.261 mm (used 3.26 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.208 radians x offset: 0.0532 arcsec y offset: -0.000668 arcsec defocus: -0.000976 mm Estimated x pointing error is 8.753 arcsec (used 8.7 arcsec) Estimated y pointing error is 12 arcsec (used 12 arcsec) Estimated defocus error is 3.259 mm (used 3.26 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.212 radians x offset: 0.0631 arcsec y offset: -0.0101 arcsec defocus: -0.00168 mm Estimated x pointing error is 8.763 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.99 arcsec (used 12 arcsec) Estimated defocus error is 3.258 mm (used 3.26 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.211 radians x offset: 0.0568 arcsec y offset: -0.00722 arcsec defocus: -0.00155 mm Estimated x pointing error is 8.757 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.99 arcsec (used 12 arcsec) Estimated defocus error is 3.258 mm (used 3.26 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.209 radians x offset: 0.0401 arcsec y offset: -0.00283 arcsec defocus: 0.000138 mm Estimated x pointing error is 8.74 arcsec (used 8.7 arcsec) Estimated y pointing error is 12 arcsec (used 12 arcsec) Estimated defocus error is 3.26 mm (used 3.26 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.212 radians x offset: 0.0205 arcsec y offset: 0.00325 arcsec defocus: 0.00139 mm Estimated x pointing error is 8.721 arcsec (used 8.7 arcsec) Estimated y pointing error is 12 arcsec (used 12 arcsec) Estimated defocus error is 3.261 mm (used 3.26 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.217 radians x offset: 0.0141 arcsec y offset: -0.000258 arcsec defocus: 1.87e-05 mm Estimated x pointing error is 8.714 arcsec (used 8.7 arcsec) Estimated y pointing error is 12 arcsec (used 12 arcsec) Estimated defocus error is 3.26 mm (used 3.26 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.217 radians x offset: 0.0154 arcsec y offset: -0.00831 arcsec defocus: -0.000929 mm Estimated x pointing error is 8.715 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.99 arcsec (used 12 arcsec) Estimated defocus error is 3.259 mm (used 3.26 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.213 radians x offset: 0.018 arcsec y offset: -0.0124 arcsec defocus: -0.0019 mm Estimated x pointing error is 8.718 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.99 arcsec (used 12 arcsec) Estimated defocus error is 3.258 mm (used 3.26 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.211 radians x offset: 0.0254 arcsec y offset: -0.0287 arcsec defocus: -0.00375 mm Estimated x pointing error is 8.725 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.97 arcsec (used 12 arcsec) Estimated defocus error is 3.256 mm (used 3.26 mm) Fitting frequency 12 Minimiser fit code = 3 piston: -0.211 radians x offset: 0.0154 arcsec y offset: -0.0281 arcsec defocus: -0.00377 mm Estimated x pointing error is 8.715 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.97 arcsec (used 12 arcsec) Estimated defocus error is 3.256 mm (used 3.26 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.21 radians x offset: 0.00559 arcsec y offset: -0.0184 arcsec defocus: -0.00345 mm Estimated x pointing error is 8.706 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.98 arcsec (used 12 arcsec) Estimated defocus error is 3.257 mm (used 3.26 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.21 radians x offset: -0.00154 arcsec y offset: -0.0101 arcsec defocus: -0.00305 mm Estimated x pointing error is 8.698 arcsec (used 8.7 arcsec) Estimated y pointing error is 11.99 arcsec (used 12 arcsec) Estimated defocus error is 3.257 mm (used 3.26 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.215 radians x offset: -0.00747 arcsec y offset: -0.00464 arcsec defocus: -0.00414 mm Estimated x pointing error is 8.693 arcsec (used 8.7 arcsec) Estimated y pointing error is 12 arcsec (used 12 arcsec) Estimated defocus error is 3.256 mm (used 3.26 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 0.00887 piston 1 1 -0.05899 tilt_x 1 -1 -0.02520 tilt_y 2 2 0.06493 astigmatism_0 2 0 0.02423 curvature 2 -2 0.08765 astigmatism45 3 3 0.04800 trefoil_0 3 1 -0.12687 coma_x 3 -1 -0.05654 coma_y 3 -3 -0.01930 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 0.00876 piston 1 1 -0.05876 tilt_x 1 -1 -0.02488 tilt_y 2 2 0.06453 astigmatism_0 2 0 0.02419 curvature 2 -2 0.08651 astigmatism45 3 3 0.04796 trefoil_0 3 1 -0.12726 coma_x 3 -1 -0.05622 coma_y 3 -3 -0.01950 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 0.00872 piston 1 1 -0.05890 tilt_x 1 -1 -0.02518 tilt_y 2 2 0.06390 astigmatism_0 2 0 0.02441 curvature 2 -2 0.08660 astigmatism45 3 3 0.04841 trefoil_0 3 1 -0.12826 coma_x 3 -1 -0.05742 coma_y 3 -3 -0.01948 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 0.00876 piston 1 1 -0.05894 tilt_x 1 -1 -0.02618 tilt_y 2 2 0.06307 astigmatism_0 2 0 0.02458 curvature 2 -2 0.08856 astigmatism45 3 3 0.04869 trefoil_0 3 1 -0.12815 coma_x 3 -1 -0.06015 coma_y 3 -3 -0.01885 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 0.00884 piston 1 1 -0.05904 tilt_x 1 -1 -0.02628 tilt_y 2 2 0.06333 astigmatism_0 2 0 0.02471 curvature 2 -2 0.08926 astigmatism45 3 3 0.04958 trefoil_0 3 1 -0.12784 coma_x 3 -1 -0.05961 coma_y 3 -3 -0.01932 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 0.00898 piston 1 1 -0.05945 tilt_x 1 -1 -0.02642 tilt_y 2 2 0.06423 astigmatism_0 2 0 0.02495 curvature 2 -2 0.09026 astigmatism45 3 3 0.04964 trefoil_0 3 1 -0.12783 coma_x 3 -1 -0.05907 coma_y 3 -3 -0.01964 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 0.00910 piston 1 1 -0.06000 tilt_x 1 -1 -0.02639 tilt_y 2 2 0.06537 astigmatism_0 2 0 0.02512 curvature 2 -2 0.09029 astigmatism45 3 3 0.04927 trefoil_0 3 1 -0.12857 coma_x 3 -1 -0.05850 coma_y 3 -3 -0.02122 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 0.00907 piston 1 1 -0.05999 tilt_x 1 -1 -0.02499 tilt_y 2 2 0.06771 astigmatism_0 2 0 0.02482 curvature 2 -2 0.08855 astigmatism45 3 3 0.04626 trefoil_0 3 1 -0.12817 coma_x 3 -1 -0.05581 coma_y 3 -3 -0.02244 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 0.00879 piston 1 1 -0.05929 tilt_x 1 -1 -0.02407 tilt_y 2 2 0.06822 astigmatism_0 2 0 0.02424 curvature 2 -2 0.08771 astigmatism45 3 3 0.04496 trefoil_0 3 1 -0.12676 coma_x 3 -1 -0.05497 coma_y 3 -3 -0.02190 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 0.00871 piston 1 1 -0.05938 tilt_x 1 -1 -0.02397 tilt_y 2 2 0.06860 astigmatism_0 2 0 0.02420 curvature 2 -2 0.08799 astigmatism45 3 3 0.04613 trefoil_0 3 1 -0.12737 coma_x 3 -1 -0.05529 coma_y 3 -3 -0.02243 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 0.00876 piston 1 1 -0.05965 tilt_x 1 -1 -0.02462 tilt_y 2 2 0.06813 astigmatism_0 2 0 0.02444 curvature 2 -2 0.08989 astigmatism45 3 3 0.04683 trefoil_0 3 1 -0.12806 coma_x 3 -1 -0.05677 coma_y 3 -3 -0.02266 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 0.00897 piston 1 1 -0.06008 tilt_x 1 -1 -0.02532 tilt_y 2 2 0.06826 astigmatism_0 2 0 0.02477 curvature 2 -2 0.09167 astigmatism45 3 3 0.04753 trefoil_0 3 1 -0.12797 coma_x 3 -1 -0.05780 coma_y 3 -3 -0.02240 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 0.00913 piston 1 1 -0.06038 tilt_x 1 -1 -0.02503 tilt_y 2 2 0.06920 astigmatism_0 2 0 0.02491 curvature 2 -2 0.09082 astigmatism45 3 3 0.04774 trefoil_0 3 1 -0.12755 coma_x 3 -1 -0.05585 coma_y 3 -3 -0.02333 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 0.00922 piston 1 1 -0.06069 tilt_x 1 -1 -0.02481 tilt_y 2 2 0.06983 astigmatism_0 2 0 0.02502 curvature 2 -2 0.09005 astigmatism45 3 3 0.04702 trefoil_0 3 1 -0.12792 coma_x 3 -1 -0.05497 coma_y 3 -3 -0.02333 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 0.00918 piston 1 1 -0.06064 tilt_x 1 -1 -0.02445 tilt_y 2 2 0.06979 astigmatism_0 2 0 0.02494 curvature 2 -2 0.08829 astigmatism45 3 3 0.04655 trefoil_0 3 1 -0.12839 coma_x 3 -1 -0.05454 coma_y 3 -3 -0.02356 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 0.00905 piston 1 1 -0.06034 tilt_x 1 -1 -0.02422 tilt_y 2 2 0.06993 astigmatism_0 2 0 0.02487 curvature 2 -2 0.08742 astigmatism45 3 3 0.04519 trefoil_0 3 1 -0.12787 coma_x 3 -1 -0.05540 coma_y 3 -3 -0.02253 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: 23.3 21.8 19 24.5 22.7 27.2 35.2 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 20.1 18.3 24.3 22.7 26.2 31.3 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.26 7.4 9.2 9.33 8.15 8.56 14.7 10.5 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 21.9 19.2 24.3 22.5 27.3 35.2 26.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.3 18.5 24.1 22.5 26.2 31.2 25.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.27 7.41 9.21 9.33 8.12 8.48 14.6 10.4 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 21.9 19.5 23.9 22.3 27.3 35.3 26.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 20.3 18.7 23.7 22.4 26.3 31.3 25.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.31 7.48 9.29 9.41 8.15 8.48 14.7 10.5 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 21.7 20 24.2 22 27.3 35.7 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.8 20.1 19.3 23.9 22.1 26.4 31.6 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.34 7.54 9.36 9.48 8.22 8.55 14.8 10.6 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 21.6 20.7 24.2 22.1 27.3 36.1 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.9 19.9 20 24 22.2 26.4 31.9 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.32 7.51 9.33 9.46 8.24 8.62 14.8 10.6 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.7 21.5 20.1 24 22.2 27.5 36 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.8 19.8 19.4 23.9 22.3 26.5 31.8 25.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.32 7.5 9.32 9.47 8.28 8.71 14.9 10.6 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 21.5 18.9 24.2 22.9 27.5 35.7 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.6 19.8 18.1 24.1 22.9 26.5 31.6 25.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.33 7.52 9.35 9.5 8.32 8.76 15 10.7 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 21.9 19 24.8 22.7 27.3 35.3 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.2 18.2 24.7 22.7 26.3 31.3 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.29 7.45 9.26 9.41 8.26 8.71 14.9 10.6 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 21.9 19.2 24.5 22.3 27.2 35.3 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.2 18.5 24.4 22.4 26.1 31.4 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.24 7.36 9.16 9.32 8.19 8.65 14.7 10.5 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 21.9 19.5 24.2 22.2 27.2 35.5 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.2 18.8 24.1 22.3 26.1 31.7 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.26 7.4 9.2 9.36 8.23 8.71 14.8 10.5 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 21.8 20.1 23.8 22.1 27.3 35.8 27.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 20.1 19.4 23.6 22.2 26.2 31.9 25.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.29 7.46 9.29 9.45 8.32 8.8 15 10.6 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 24 21.5 20.5 24.1 22.1 27.4 36.2 27.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23 19.8 19.7 23.9 22.2 26.3 32.1 25.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.31 7.48 9.31 9.49 8.38 8.91 15.1 10.7 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 21.7 18.9 24 22.6 27.6 36 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23 19.9 18.2 23.8 22.6 26.5 31.7 25.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.27 7.42 9.24 9.42 8.35 8.91 15.1 10.7 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.6 21.8 18.9 24.1 23.2 27.6 35.6 27.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.7 20.1 18.3 23.9 23.1 26.5 31.4 25.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.27 7.42 9.24 9.42 8.34 8.88 15 10.7 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.5 21.9 19 23.9 22.8 27.5 35.4 27 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.6 20.3 18.4 23.8 22.8 26.3 31.2 25.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.28 7.43 9.25 9.41 8.29 8.79 14.9 10.6 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 22 19.1 23.8 22.5 27.2 35.3 26.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 20.4 18.5 23.8 22.5 26.1 31.3 25.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.27 7.42 9.23 9.39 8.25 8.72 14.9 10.6 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 22.3 20.2 17.3 22 20.7 26.2 34.6 25.7 Mean deviation is 0.49516344892481357 microns Taper = 10 dB, Ruze illumination-weighted rms = 24.8 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 = 22.3 micron Centre pixel: 128.0 128.0 Value = 13033.3 (estimate), 15686.5 (perfect) Strehl = 0.69033 Strehl ratio estimate = 0.6903 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 = 21.7 micron Centre pixel: 128.0 128.0 Value = 11212.6 (estimate), 15686.5 (perfect) Strehl = 0.510929 Strehl ratio estimate = 0.5109 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.07514 metres panel scale = 3.00000 metres mean frequency = 160.70950 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 -8.9 -6.5 -10.4 15.1 2 1 2 11.9 -2.5 9.3 15.4 3 1 3 6.5 -4.3 -2.1 8.1 4 1 4 15.9 -1.7 16.0 22.6 5 1 5 4.6 6.6 17.3 19.1 6 1 6 16.4 4.9 -2.1 17.3 7 1 7 -11.8 11.1 -9.6 18.9 8 1 8 -17.8 -11.4 -11.5 24.1 9 1 9 -62.5 2.7 -13.2 64.0 10 1 10 -12.6 1.0 -6.8 14.3 11 1 11 -7.6 3.4 -8.6 11.9 12 1 12 12.1 -5.6 -0.1 13.3 13 2 1 -4.8 -18.7 -7.5 20.7 14 2 2 -5.7 -9.2 -10.9 15.4 15 2 3 1.6 -9.7 -12.7 16.1 16 2 4 -2.9 -6.0 -2.0 7.0 17 2 5 12.2 5.6 0.5 13.4 18 2 6 3.9 12.1 17.8 21.9 19 2 7 -1.3 3.6 20.7 21.1 20 2 8 26.6 24.9 8.7 37.5 21 2 9 15.2 7.7 13.6 21.8 22 2 10 10.3 6.1 10.4 15.9 23 2 11 -1.3 -3.0 -4.2 5.3 24 2 12 -9.7 -0.5 -4.7 10.7 25 2 13 -3.4 10.3 3.8 11.5 26 2 14 -11.4 -2.9 2.3 12.0 27 2 15 2.6 -6.5 -21.2 22.3 28 2 16 -3.5 -3.6 -11.6 12.6 29 2 17 1.9 -9.2 -11.2 14.6 30 2 18 1.3 -4.0 -24.2 24.6 31 2 19 -12.0 -5.0 -17.1 21.5 32 2 20 -10.5 -3.9 -12.4 16.7 33 2 21 -0.8 -6.5 -23.5 24.4 34 2 22 -9.8 -37.2 -33.9 51.3 35 2 23 2.4 -23.4 -20.6 31.3 36 2 24 -12.1 -19.9 -7.1 24.4 37 3 1 -6.9 6.6 -4.9 10.7 38 3 2 -7.3 -5.2 -11.1 14.3 39 3 3 -4.1 -6.3 -21.3 22.6 40 3 4 3.8 -1.2 -8.6 9.5 41 3 5 -2.9 -0.3 -17.3 17.5 42 3 6 1.7 1.0 -2.8 3.4 43 3 7 9.0 1.2 -2.9 9.5 44 3 8 2.5 10.1 12.2 16.0 45 3 9 9.3 8.4 2.4 12.7 46 3 10 10.8 6.5 9.5 15.8 47 3 11 7.6 7.0 -1.2 10.4 48 3 12 -1.2 20.3 7.8 21.8 49 3 13 -2.8 15.4 7.6 17.4 50 3 14 18.1 7.9 -7.6 21.2 51 3 15 3.9 11.6 9.0 15.2 52 3 16 15.6 9.6 -1.4 18.4 53 3 17 13.8 13.6 1.3 19.4 54 3 18 10.7 11.6 9.0 18.2 55 3 19 13.6 15.6 2.8 20.8 56 3 20 -0.7 11.7 5.3 12.9 57 3 21 -13.6 5.0 -5.6 15.5 58 3 22 0.3 2.8 3.6 4.6 59 3 23 -5.6 2.8 3.7 7.2 60 3 24 11.1 9.9 22.3 26.8 61 3 25 -5.1 10.8 5.0 12.9 62 3 26 -6.1 -4.4 -5.4 9.3 63 3 27 -3.9 -6.6 -11.3 13.6 64 3 28 5.5 1.6 -14.1 15.2 65 3 29 -3.3 3.0 5.1 6.8 66 3 30 -1.4 -12.7 1.5 12.8 67 3 31 -17.6 8.0 -6.8 20.5 68 3 32 -13.1 -2.6 -1.9 13.5 69 3 33 2.7 -5.5 0.4 6.2 70 3 34 -0.7 0.9 7.2 7.2 71 3 35 -3.1 -2.4 -10.5 11.2 72 3 36 -4.7 6.5 -10.1 12.9 73 3 37 -11.7 6.3 -32.3 35.0 74 3 38 -9.5 -2.8 -4.7 11.0 75 3 39 -4.0 -11.6 -11.4 16.8 76 3 40 -16.6 1.0 -24.8 29.9 77 3 41 -13.1 -2.3 -22.7 26.3 78 3 42 -2.3 -3.5 -5.5 6.9 79 3 43 -9.2 -6.0 -14.4 18.1 80 3 44 -5.9 -8.6 -8.9 13.7 81 3 45 -9.8 -8.3 -24.1 27.3 82 3 46 -8.1 -15.8 -13.8 22.5 83 3 47 -24.6 -16.7 -20.1 35.9 84 3 48 -17.6 -16.8 -32.7 40.8 85 4 1 -0.0 -6.8 10.7 12.7 86 4 2 -3.0 -3.2 -11.4 12.2 87 4 3 -0.9 -6.9 -12.0 13.8 88 4 4 -10.6 0.9 -33.5 35.2 89 4 5 3.1 -2.4 -7.1 8.1 90 4 6 -1.6 4.2 -14.0 14.7 91 4 7 2.9 -6.0 5.8 8.9 92 4 8 0.1 10.0 -11.6 15.3 93 4 9 21.8 7.4 9.3 24.9 94 4 10 4.4 9.0 3.5 10.6 95 4 11 9.6 7.4 3.2 12.5 96 4 12 14.9 23.0 11.0 29.5 97 4 13 8.5 9.8 17.8 22.0 98 4 14 16.0 9.7 -1.0 18.8 99 4 15 -0.1 2.3 5.0 5.5 100 4 16 3.9 12.4 5.8 14.3 101 4 17 2.0 -0.1 -0.9 2.2 102 4 18 9.9 4.1 31.3 33.0 103 4 19 13.6 0.2 5.6 14.8 104 4 20 16.0 8.9 -2.2 18.5 105 4 21 -6.1 4.6 3.3 8.3 106 4 22 -4.8 -2.8 99.8 99.9 107 4 23 -0.8 2.8 19.2 19.4 108 4 24 6.6 5.3 0.8 8.5 109 4 25 -9.6 13.5 18.9 25.1 110 4 26 -1.9 -7.6 -12.2 14.5 111 4 27 -6.1 2.4 5.9 8.8 112 4 28 -11.1 -0.7 -0.1 11.2 113 4 29 -11.5 4.3 -57.9 59.2 114 4 30 -5.0 -6.3 13.2 15.4 115 4 31 -12.5 3.1 -7.9 15.1 116 4 32 4.6 1.1 0.6 4.8 117 4 33 -32.1 12.5 -20.8 40.2 118 4 34 -5.0 0.8 -4.9 7.0 119 4 35 -4.0 13.0 6.4 15.1 120 4 36 -9.5 1.1 6.6 11.6 121 4 37 -6.0 14.5 -6.7 17.1 122 4 38 -4.6 5.1 -18.2 19.5 123 4 39 -13.3 0.3 -12.1 18.0 124 4 40 2.9 -0.4 -37.6 37.7 125 4 41 -25.3 11.3 -27.5 39.1 126 4 42 -17.2 1.8 -33.5 37.7 127 4 43 -24.9 -2.2 -31.1 39.9 128 4 44 -16.5 4.1 -26.3 31.3 129 4 45 3.2 2.0 -3.3 5.0 130 4 46 -2.4 -9.1 -11.4 14.7 131 4 47 -13.1 -15.1 6.6 21.0 132 4 48 -21.4 -14.2 -12.4 28.5 133 5 1 24.2 -6.7 -17.7 30.7 134 5 2 -4.4 -12.5 -24.7 28.1 135 5 3 2.1 -8.7 -9.9 13.3 136 5 4 -15.8 -11.2 -27.9 34.0 137 5 5 5.0 -12.5 -15.0 20.1 138 5 6 -1.8 -1.1 -17.0 17.1 139 5 7 14.2 25.1 6.7 29.6 140 5 8 6.2 13.8 -8.0 17.1 141 5 9 8.2 5.2 13.4 16.6 142 5 10 15.1 15.4 5.8 22.3 143 5 11 12.1 20.3 10.3 25.8 144 5 12 16.2 32.9 5.2 37.0 145 5 13 15.1 21.4 7.4 27.2 146 5 14 12.5 10.7 -1.7 16.5 147 5 15 9.6 7.8 -3.7 12.9 148 5 16 1.2 9.0 -2.3 9.3 149 5 17 -3.0 13.3 22.9 26.7 150 5 18 12.1 5.4 131.0 131.7 151 5 19 3.3 1.4 -4.5 5.8 152 5 20 -15.5 -7.4 -6.5 18.4 153 5 21 9.7 0.2 -12.8 16.1 154 5 22 -7.2 1.4 1.2 7.5 155 5 23 -13.3 2.8 14.9 20.2 156 5 24 5.6 3.0 18.5 19.6 157 5 25 12.3 2.0 -7.4 14.5 158 5 26 -15.4 -8.3 -0.8 17.5 159 5 27 -19.1 -7.8 0.8 20.7 160 5 28 -14.6 -4.6 1.2 15.4 161 5 29 2.6 3.2 -26.5 26.8 162 5 30 3.6 -3.4 30.3 30.7 163 5 31 -15.1 -3.6 -17.3 23.2 164 5 32 -15.2 -3.7 7.0 17.1 165 5 33 7.8 23.1 16.6 29.5 166 5 34 -0.8 8.4 17.8 19.7 167 5 35 8.9 28.4 6.7 30.5 168 5 36 7.9 18.4 23.4 30.8 169 5 37 9.8 27.3 -9.9 30.7 170 5 38 -22.7 17.3 -19.0 34.3 171 5 39 -0.8 36.2 13.0 38.5 172 5 40 -41.5 21.2 -14.4 48.8 173 5 41 22.1 23.9 17.8 37.1 174 5 42 -24.2 18.0 -18.1 35.2 175 5 43 7.4 15.7 -3.2 17.6 176 5 44 9.3 15.1 3.6 18.1 177 5 45 22.3 24.1 4.2 33.1 178 5 46 4.8 25.0 7.9 26.6 179 5 47 0.6 9.1 40.5 41.5 180 5 48 -0.8 19.5 6.4 20.5 181 6 1 -17.3 2.8 -12.6 21.6 182 6 2 -21.8 -19.3 -24.1 37.8 183 6 3 -16.0 -26.1 -41.0 51.2 184 6 4 -15.2 -25.3 -49.4 57.6 185 6 5 -11.0 -25.3 -45.7 53.4 186 6 6 -7.6 -10.4 -36.7 38.9 187 6 7 -5.2 -17.0 -20.4 27.1 188 6 8 4.2 -0.8 0.7 4.4 189 6 9 15.3 -9.8 4.2 18.7 190 6 10 11.3 7.7 12.9 18.8 191 6 11 26.7 7.2 22.8 35.9 192 6 12 15.6 7.7 0.8 17.4 193 6 13 15.7 11.9 -14.8 24.6 194 6 14 13.3 -0.8 -16.5 21.2 195 6 15 10.0 -3.8 -12.0 16.1 196 6 16 10.9 10.4 -9.4 17.8 197 6 17 -5.5 -7.1 -18.1 20.2 198 6 18 -1.3 0.6 -89.9 90.0 199 6 19 36.3 -9.8 -25.9 45.7 200 6 20 -22.7 4.3 20.1 30.6 201 6 21 -25.7 -10.3 24.6 37.0 202 6 22 -10.1 68.8 1.3 69.6 203 6 23 16.4 -10.2 9.7 21.6 204 6 24 -2.1 -2.1 -3.1 4.3 205 6 25 -22.8 -5.4 -16.6 28.7 206 6 26 -9.3 -11.6 -9.0 17.4 207 6 27 -17.3 -10.9 -17.5 26.9 208 6 28 -13.3 -12.8 -14.9 23.7 209 6 29 -23.6 16.3 -27.4 39.7 210 6 30 -10.7 -1.7 41.4 42.8 211 6 31 -19.2 -3.9 1.9 19.7 212 6 32 -15.5 2.6 5.9 16.8 213 6 33 -0.9 19.0 6.7 20.1 214 6 34 40.2 18.2 51.2 67.6 215 6 35 32.0 15.1 54.7 65.1 216 6 36 30.2 54.1 52.4 81.1 217 6 37 -12.5 17.4 19.3 28.8 218 6 38 -22.9 -6.4 -25.2 34.6 219 6 39 -17.1 3.6 -3.7 17.9 220 6 40 22.1 19.5 -4.9 29.9 221 6 41 23.9 34.5 20.4 46.7 222 6 42 44.5 24.3 -18.7 54.1 223 6 43 33.5 20.2 29.6 49.0 224 6 44 34.3 27.3 18.7 47.7 225 6 45 34.6 36.1 19.7 53.8 226 6 46 25.4 35.7 22.4 49.2 227 6 47 5.3 18.3 46.3 50.1 228 6 48 6.7 10.3 18.2 22.0 229 7 1 -10.5 16.9 -17.2 26.3 230 7 2 -14.3 -27.3 -24.6 39.4 231 7 3 -50.9 -26.0 -47.3 74.2 232 7 4 -27.5 -39.1 -31.6 57.3 233 7 5 -45.9 -40.9 -71.9 94.6 234 7 6 -34.3 -28.4 -72.9 85.4 235 7 7 -10.0 -37.0 -43.5 58.0 236 7 8 -6.8 -11.0 -47.1 48.9 237 7 9 9.3 -11.8 -18.3 23.7 238 7 10 9.1 -0.3 -20.9 22.8 239 7 11 23.6 -3.4 5.7 24.5 240 7 12 6.7 7.2 -0.1 9.8 241 7 13 -19.0 9.5 -21.6 30.3 242 7 14 -0.1 0.8 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24.1 162.1 -5.0 163.9 Creating sector-motor-move file sector motor steps 1 1 -9 1 2 -11 1 3 -8 1 4 -15 1 5 -7 1 6 -4 1 7 -14 1 8 -7 1 9 -15 1 10 -12 1 11 -8 1 12 -4 1 13 -7 1 14 -8 1 15 -4 1 16 -7 1 17 -5 1 18 -6 1 19 -5 1 20 5 1 21 -3 1 22 -3 1 23 0 1 24 -5 1 25 -8 1 26 -3 1 27 -4 1 28 -10 1 29 0 1 30 -3 1 31 -3 1 32 -2 1 33 0 1 34 -3 1 35 -2 1 36 0 1 37 -7 1 38 -3 1 39 -1 1 40 -3 1 41 0 1 42 0 1 43 -5 1 44 -2 1 45 7 1 46 3 1 47 -2 1 48 0 1 49 -6 1 50 -1 1 51 -1 1 52 -3 1 53 -2 1 54 -1 1 55 -3 1 56 -1 1 57 -2 1 58 -2 1 59 -2 1 60 -3 1 61 -1 1 62 2 1 63 -2 1 64 -2 1 65 -1 1 66 -2 1 67 -2 1 68 0 1 69 1 2 1 -14 2 2 -3 2 3 -2 2 4 0 2 5 0 2 6 1 2 7 -13 2 8 -11 2 9 -3 2 10 -6 2 11 -5 2 12 -1 2 13 -22 2 14 -8 2 15 -10 2 16 -11 2 17 -3 2 18 -2 2 19 -22 2 20 -12 2 21 -14 2 22 -14 2 23 -7 2 24 -3 2 25 -2 2 26 4 2 27 1 2 28 -3 2 29 3 2 30 0 2 31 2 2 32 7 2 33 4 2 34 1 2 35 -1 2 36 0 2 37 -5 2 38 0 2 39 0 2 40 -4 2 41 1 2 42 0 2 43 -4 2 44 -3 2 45 1 2 46 -2 2 47 0 2 48 0 2 49 0 2 50 0 2 51 2 2 52 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12 24 10 12 25 1 12 26 5 12 27 0 12 28 -3 12 29 -4 12 30 -6 12 31 12 12 32 2 12 33 0 12 34 2 12 35 -4 12 36 -4 12 37 2 12 38 7 12 39 1 12 40 -3 12 41 -2 12 42 0 12 43 1 12 44 7 12 45 6 12 46 -1 12 47 0 12 48 0 12 49 -6 12 50 -5 12 51 -7 12 52 -2 12 53 -6 12 54 -3 12 55 -4 12 56 -4 12 57 -2 12 58 -1 12 59 3 12 60 0 12 61 -7 12 62 -2 12 63 -3 12 64 -5 12 65 0 12 66 -6 12 67 -10 12 68 -5 12 69 -5 Adjuster movements: rms = 22.3 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20070925-133952 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1