Reduction started at: 20050126-120028 Reading data from rxh3-20050126-014223.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 = 2402.4 max = 2424.7 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.790 mm ----------------- Data Summary --------------------- Number of samples: 1466025 This is a 160 GHz map Number of frequencies: 16 Frequencies (GHz): 160.676000 160.680000 160.684000 160.688000 160.692000 160.696000 160.700000 160.704000 160.708000 160.712000 160.716000 160.720000 160.724000 160.728000 160.732000 160.736000 item min max mean loreal -2.47314 2.70020 -0.00233 loimag -2.70264 2.72461 -0.00926 hireal -5.00000 4.99756 0.00788 hiimag -5.00000 4.99756 0.01606 xpos -2424.69510 2406.18160 -13.35894 ypos -2402.36212 2402.46734 -0.00114 plock160 0.93750 2.28760 1.67191 lorefpwr 1.47949 2.93213 2.49618 losigpwr -4.58740 -0.98145 -4.47177 hirefpwr 1.52832 2.91504 2.51203 hisigpwr -4.50439 4.99756 -1.47172 encltemp 31.54297 32.93457 32.08251 flags 0.00000 256.00000 2.44471 phi-lock -1.25732 0.09277 -0.62970 sindex 0.00000 254.00000 126.60925 time 0.00000 5877.00600 2937.61083 zeropt -0.00732 -0.00244 -0.00494 !!!Warning!!! philock max less than 0.2 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 255 rows There are 241 data rows and 14 calibrator rows Calibrator rows: 0 21 42 63 84 105 126 147 168 189 210 231 252 254 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 20.00292 arcsec Mean row spacing = 20.00293 arcsec (alternate estimator) Mean tracking incline = -0.04493 arcsec Mean pointing range = 0.47726 arcsec Mean pointing rms = 0.08377 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (0.50, 12.1 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Inverting the phase on this 160 GHz map Doing geometric phase correction Status bits counts: bit: 0 1 2 3 4 5 6 7 8 set: 0 0 0 0 0 0 0 0 14000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 90354 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 90354 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 20.0 arcseconds Using a grid of 256 points Grid has even number of points Maximum data offset = 2424.7 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 = 2.44265 at (0.0, 0.0) arcsec Real: mean = 0.000490687 sum of squares = 2098.34 Imag: mean = 0.000107096 sum of squares = 2044.72 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 = 2.4674 at (0.0, 0.0) arcsec Real: mean = 0.00029835 sum of squares = 2147.88 Imag: mean = 0.000204456 sum of squares = 2004.99 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 = 2.50029 at (0.0, 0.0) arcsec Real: mean = 0.000155186 sum of squares = 2029.2 Imag: mean = 4.15554e-05 sum of squares = 2135.1 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 = 2.52412 at (0.0, 0.0) arcsec Real: mean = 0.000292752 sum of squares = 2033.56 Imag: mean = -7.07288e-05 sum of squares = 2150.92 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 = 2.54311 at (0.0, 0.0) arcsec Real: mean = 0.000334659 sum of squares = 2174.66 Imag: mean = -6.19501e-05 sum of squares = 2035.6 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 = 2.52501 at (0.0, 0.0) arcsec Real: mean = 0.000406822 sum of squares = 2149.09 Imag: mean = -5.69008e-05 sum of squares = 2085.02 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 = 2.49497 at (0.0, 0.0) arcsec Real: mean = 0.000512449 sum of squares = 2049.2 Imag: mean = -1.92275e-05 sum of squares = 2211.53 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 = 2.48166 at (0.0, 0.0) arcsec Real: mean = 0.000521068 sum of squares = 2133.19 Imag: mean = 0.000220988 sum of squares = 2157.34 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 = 2.49659 at (0.0, 0.0) arcsec Real: mean = 0.000222103 sum of squares = 2245.46 Imag: mean = 0.00018033 sum of squares = 2076.29 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 = 2.5351 at (0.0, 0.0) arcsec Real: mean = 0.000333051 sum of squares = 2160.49 Imag: mean = 5.86523e-05 sum of squares = 2194.93 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 = 2.57086 at (0.0, 0.0) arcsec Real: mean = 0.000208531 sum of squares = 2108.64 Imag: mean = 9.38808e-05 sum of squares = 2280.32 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 = 2.57612 at (0.0, 0.0) arcsec Real: mean = 0.000253932 sum of squares = 2255.25 Imag: mean = -0.000129309 sum of squares = 2165.08 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 = 2.56425 at (0.0, 0.0) arcsec Real: mean = 0.000498208 sum of squares = 2292.08 Imag: mean = -9.29928e-05 sum of squares = 2168.28 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 = 2.54193 at (0.0, 0.0) arcsec Real: mean = 0.000499665 sum of squares = 2190.09 Imag: mean = 6.38896e-05 sum of squares = 2313.03 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 = 2.52424 at (0.0, 0.0) arcsec Real: mean = 0.000489356 sum of squares = 2218.59 Imag: mean = 0.000109205 sum of squares = 2329.56 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 = 2.55976 at (0.0, 0.0) arcsec Real: mean = 0.000414238 sum of squares = 2383.14 Imag: mean = 0.000190837 sum of squares = 2217.58 Masking frequency index 0 Mask scale size = 6.11744 Masking frequency index 1 Mask scale size = 6.11759 Masking frequency index 2 Mask scale size = 6.11774 Masking frequency index 3 Mask scale size = 6.1179 Masking frequency index 4 Mask scale size = 6.11805 Masking frequency index 5 Mask scale size = 6.1182 Masking frequency index 6 Mask scale size = 6.11835 Masking frequency index 7 Mask scale size = 6.11851 Masking frequency index 8 Mask scale size = 6.11866 Masking frequency index 9 Mask scale size = 6.11881 Masking frequency index 10 Mask scale size = 6.11896 Masking frequency index 11 Mask scale size = 6.11912 Masking frequency index 12 Mask scale size = 6.11927 Masking frequency index 13 Mask scale size = 6.11942 Masking frequency index 14 Mask scale size = 6.11957 Masking frequency index 15 Mask scale size = 6.11972 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.224609 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.192871 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.183105 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.209961 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: 0.205078 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.202637 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 = -2.0829 129.02 Freq 1: Shift, scale = -2.9483 129.6 Freq 2: Shift, scale = 2.4683 129.99 Freq 3: Shift, scale = 1.6087 130.15 Freq 4: Shift, scale = 0.74512 130.52 Freq 5: Shift, scale = -0.11729 131.02 Freq 6: Shift, scale = -0.98645 131.43 Freq 7: Shift, scale = -1.8522 131.2 Freq 8: Shift, scale = -2.7079 131.2 Freq 9: Shift, scale = 2.7182 132.3 Freq 10: Shift, scale = 1.8502 133.4 Freq 11: Shift, scale = 0.98465 134.16 Freq 12: Shift, scale = 0.11521 134.75 Freq 13: Shift, scale = -0.75057 134.23 Freq 14: Shift, scale = -1.6061 134.14 Freq 15: Shift, scale = -2.4661 135.46 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: -0.043 radians x offset: 0.0449 arcsec y offset: 0.021 arcsec defocus: -0.000758 mm Estimated x pointing error is 0.5449 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.12 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.0445 radians x offset: 0.0454 arcsec y offset: 0.0199 arcsec defocus: -0.000635 mm Estimated x pointing error is 0.5454 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.12 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.0466 radians x offset: 0.0399 arcsec y offset: 0.0283 arcsec defocus: -3.09e-05 mm Estimated x pointing error is 0.5399 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.13 arcsec (used 12.1 arcsec) Estimated defocus error is 2.79 mm (used 2.79 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.0429 radians x offset: 0.029 arcsec y offset: 0.0415 arcsec defocus: -0.000286 mm Estimated x pointing error is 0.529 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.14 arcsec (used 12.1 arcsec) Estimated defocus error is 2.79 mm (used 2.79 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.043 radians x offset: 0.0296 arcsec y offset: 0.0404 arcsec defocus: -0.00148 mm Estimated x pointing error is 0.5296 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.14 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.0411 radians x offset: 0.0253 arcsec y offset: 0.0389 arcsec defocus: -0.0013 mm Estimated x pointing error is 0.5253 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.14 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.0466 radians x offset: 0.0212 arcsec y offset: 0.0412 arcsec defocus: -0.00104 mm Estimated x pointing error is 0.5212 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.14 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.049 radians x offset: 0.00292 arcsec y offset: 0.0497 arcsec defocus: -0.00105 mm Estimated x pointing error is 0.5029 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.15 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.0419 radians x offset: -0.00511 arcsec y offset: 0.0556 arcsec defocus: -0.000816 mm Estimated x pointing error is 0.4949 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.16 arcsec (used 12.1 arcsec) Estimated defocus error is 2.789 mm (used 2.79 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.0384 radians x offset: -0.00516 arcsec y offset: 0.0446 arcsec defocus: -0.00308 mm Estimated x pointing error is 0.4948 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.14 arcsec (used 12.1 arcsec) Estimated defocus error is 2.787 mm (used 2.79 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.043 radians x offset: 0.00187 arcsec y offset: 0.0289 arcsec defocus: -0.00318 mm Estimated x pointing error is 0.5019 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.13 arcsec (used 12.1 arcsec) Estimated defocus error is 2.787 mm (used 2.79 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.0458 radians x offset: -0.0148 arcsec y offset: 0.0318 arcsec defocus: -0.00344 mm Estimated x pointing error is 0.4852 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.13 arcsec (used 12.1 arcsec) Estimated defocus error is 2.787 mm (used 2.79 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.0524 radians x offset: -0.0269 arcsec y offset: 0.0246 arcsec defocus: -0.00411 mm Estimated x pointing error is 0.4731 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.12 arcsec (used 12.1 arcsec) Estimated defocus error is 2.786 mm (used 2.79 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.0537 radians x offset: -0.0316 arcsec y offset: 0.0156 arcsec defocus: -0.00356 mm Estimated x pointing error is 0.4684 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.12 arcsec (used 12.1 arcsec) Estimated defocus error is 2.786 mm (used 2.79 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.0452 radians x offset: -0.0388 arcsec y offset: -0.000733 arcsec defocus: -0.00421 mm Estimated x pointing error is 0.4612 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.1 arcsec (used 12.1 arcsec) Estimated defocus error is 2.786 mm (used 2.79 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.0401 radians x offset: -0.0409 arcsec y offset: -0.0308 arcsec defocus: -0.00502 mm Estimated x pointing error is 0.4591 arcsec (used 0.5 arcsec) Estimated y pointing error is 12.07 arcsec (used 12.1 arcsec) Estimated defocus error is 2.785 mm (used 2.79 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 -0.00604 piston 1 1 -0.01298 tilt_x 1 -1 0.01298 tilt_y 2 2 -0.10521 astigmatism_0 2 0 -0.01617 curvature 2 -2 -0.05319 astigmatism45 3 3 -0.00013 trefoil_0 3 1 -0.05334 coma_x 3 -1 0.05778 coma_y 3 -3 0.03050 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 -0.00596 piston 1 1 -0.01263 tilt_x 1 -1 0.01285 tilt_y 2 2 -0.10599 astigmatism_0 2 0 -0.01612 curvature 2 -2 -0.05161 astigmatism45 3 3 0.00048 trefoil_0 3 1 -0.05225 coma_x 3 -1 0.05858 coma_y 3 -3 0.03014 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 -0.00588 piston 1 1 -0.01303 tilt_x 1 -1 0.01249 tilt_y 2 2 -0.10439 astigmatism_0 2 0 -0.01577 curvature 2 -2 -0.05236 astigmatism45 3 3 -0.00003 trefoil_0 3 1 -0.05325 coma_x 3 -1 0.05737 coma_y 3 -3 0.02756 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 -0.00585 piston 1 1 -0.01357 tilt_x 1 -1 0.01264 tilt_y 2 2 -0.10291 astigmatism_0 2 0 -0.01575 curvature 2 -2 -0.05291 astigmatism45 3 3 -0.00171 trefoil_0 3 1 -0.05489 coma_x 3 -1 0.05738 coma_y 3 -3 0.02600 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 -0.00588 piston 1 1 -0.01335 tilt_x 1 -1 0.01292 tilt_y 2 2 -0.10273 astigmatism_0 2 0 -0.01597 curvature 2 -2 -0.05131 astigmatism45 3 3 -0.00261 trefoil_0 3 1 -0.05426 coma_x 3 -1 0.05810 coma_y 3 -3 0.02603 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 -0.00592 piston 1 1 -0.01333 tilt_x 1 -1 0.01284 tilt_y 2 2 -0.10439 astigmatism_0 2 0 -0.01607 curvature 2 -2 -0.05124 astigmatism45 3 3 -0.00156 trefoil_0 3 1 -0.05489 coma_x 3 -1 0.05816 coma_y 3 -3 0.02795 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 -0.00588 piston 1 1 -0.01260 tilt_x 1 -1 0.01323 tilt_y 2 2 -0.10619 astigmatism_0 2 0 -0.01606 curvature 2 -2 -0.05053 astigmatism45 3 3 0.00055 trefoil_0 3 1 -0.05337 coma_x 3 -1 0.06055 coma_y 3 -3 0.02842 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 -0.00578 piston 1 1 -0.01256 tilt_x 1 -1 0.01296 tilt_y 2 2 -0.10530 astigmatism_0 2 0 -0.01584 curvature 2 -2 -0.05090 astigmatism45 3 3 0.00105 trefoil_0 3 1 -0.05247 coma_x 3 -1 0.05958 coma_y 3 -3 0.02581 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 -0.00576 piston 1 1 -0.01204 tilt_x 1 -1 0.01316 tilt_y 2 2 -0.10377 astigmatism_0 2 0 -0.01571 curvature 2 -2 -0.05122 astigmatism45 3 3 -0.00135 trefoil_0 3 1 -0.05020 coma_x 3 -1 0.05928 coma_y 3 -3 0.02357 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 -0.00585 piston 1 1 -0.01186 tilt_x 1 -1 0.01327 tilt_y 2 2 -0.10383 astigmatism_0 2 0 -0.01597 curvature 2 -2 -0.05133 astigmatism45 3 3 -0.00175 trefoil_0 3 1 -0.04979 coma_x 3 -1 0.05917 coma_y 3 -3 0.02479 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 -0.00591 piston 1 1 -0.01150 tilt_x 1 -1 0.01268 tilt_y 2 2 -0.10624 astigmatism_0 2 0 -0.01612 curvature 2 -2 -0.05086 astigmatism45 3 3 0.00072 trefoil_0 3 1 -0.04956 coma_x 3 -1 0.05781 coma_y 3 -3 0.02631 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 -0.00583 piston 1 1 -0.01166 tilt_x 1 -1 0.01191 tilt_y 2 2 -0.10604 astigmatism_0 2 0 -0.01589 curvature 2 -2 -0.05116 astigmatism45 3 3 0.00212 trefoil_0 3 1 -0.05059 coma_x 3 -1 0.05558 coma_y 3 -3 0.02586 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 -0.00583 piston 1 1 -0.01146 tilt_x 1 -1 0.01205 tilt_y 2 2 -0.10513 astigmatism_0 2 0 -0.01584 curvature 2 -2 -0.05204 astigmatism45 3 3 0.00122 trefoil_0 3 1 -0.04972 coma_x 3 -1 0.05604 coma_y 3 -3 0.02464 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 -0.00583 piston 1 1 -0.01151 tilt_x 1 -1 0.01260 tilt_y 2 2 -0.10326 astigmatism_0 2 0 -0.01582 curvature 2 -2 -0.05228 astigmatism45 3 3 0.00128 trefoil_0 3 1 -0.04970 coma_x 3 -1 0.05738 coma_y 3 -3 0.02340 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 -0.00586 piston 1 1 -0.01152 tilt_x 1 -1 0.01316 tilt_y 2 2 -0.10381 astigmatism_0 2 0 -0.01593 curvature 2 -2 -0.05193 astigmatism45 3 3 0.00087 trefoil_0 3 1 -0.04979 coma_x 3 -1 0.05889 coma_y 3 -3 0.02443 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 -0.00592 piston 1 1 -0.01122 tilt_x 1 -1 0.01286 tilt_y 2 2 -0.10664 astigmatism_0 2 0 -0.01612 curvature 2 -2 -0.05095 astigmatism45 3 3 0.00198 trefoil_0 3 1 -0.04912 coma_x 3 -1 0.05826 coma_y 3 -3 0.02558 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: 22.8 21.3 17.6 22.2 21.4 24.2 34.1 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.3 21.2 17.5 22 21.4 22.2 29.4 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.43 4.29 5.55 6.24 6.85 8.62 12.6 8.59 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.8 21.6 17.8 22.4 21.6 24.3 34.1 26.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.3 21.4 17.6 22.2 21.6 22.2 29.4 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.42 4.28 5.54 6.23 6.85 8.62 12.6 8.58 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.1 21.6 18.1 22.7 21.6 24.1 34.1 26.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 21.4 17.9 22.5 21.5 22.2 29.5 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.42 4.27 5.52 6.19 6.78 8.51 12.5 8.49 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 21.6 18.9 23.2 21.4 24 34.3 26.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.7 21.4 18.8 23 21.4 22.2 29.7 24.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.45 4.32 5.58 6.22 6.75 8.42 12.4 8.45 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 21.8 18.9 22.7 21.4 24.1 34.3 26.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.6 21.6 18.7 22.6 21.3 22.2 29.7 24.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.45 4.32 5.58 6.21 6.71 8.36 12.3 8.41 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23 21.8 17.7 22.3 21.3 24.2 34 26.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 21.7 17.5 22.1 21.3 22.2 29.4 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.47 4.35 5.62 6.26 6.8 8.49 12.5 8.51 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23 21.7 17.6 22.1 21.4 24.2 34 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 21.4 17.4 21.9 21.4 22.2 29.3 24.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.49 4.39 5.67 6.32 6.87 8.58 12.6 8.6 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.3 21.6 18.2 21.9 21.6 23.9 34 26 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.7 21.3 17.9 21.7 21.6 22 29.3 24.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.45 4.32 5.59 6.24 6.8 8.51 12.5 8.51 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 22 18.8 22.1 21.3 23.8 34.1 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 21.7 18.6 22 21.4 22 29.5 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.4 4.23 5.48 6.14 6.7 8.4 12.3 8.38 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.8 22.1 19.4 22.9 21.1 23.8 34.1 26.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 21.8 19.2 22.8 21.1 22 29.5 24.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.39 4.22 5.46 6.12 6.71 8.41 12.3 8.39 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.4 21.8 18.1 23.4 21.1 24.2 34 26.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.8 21.5 17.9 23.4 21.1 22.2 29.4 24.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.35 4.16 5.4 6.11 6.78 8.56 12.5 8.48 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.9 21.6 17.5 22.8 21.2 24.3 34 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.4 21.3 17.4 22.7 21.3 22.3 29.4 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.32 4.11 5.34 6.06 6.75 8.55 12.4 8.45 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 22.9 21.7 17.7 22.1 21.3 24 34.1 26 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.3 21.4 17.5 21.9 21.4 22.1 29.4 24.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.31 4.1 5.33 6.04 6.73 8.51 12.4 8.41 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.1 21.7 19 21.7 21.3 23.9 34.2 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 21.4 18.8 21.6 21.4 22.1 29.5 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.34 4.14 5.37 6.05 6.67 8.39 12.2 8.34 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.2 21.7 19.3 22.1 21.2 23.9 34.2 26.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.6 21.4 19.1 22 21.2 22.1 29.5 24.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.38 4.2 5.44 6.11 6.71 8.42 12.3 8.4 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 23.1 22 17.7 22.4 21.2 24.1 34 26.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 22.5 21.7 17.5 22.3 21.2 22.1 29.4 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.35 4.16 5.41 6.12 6.79 8.58 12.5 8.49 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 22.3 21 16.6 20 20.3 23 33.3 25 Mean deviation is -2.6403001826834753 microns Taper = 10 dB, Ruze illumination-weighted rms = 24.4 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 = 22.0 micron Centre pixel: 128.0 128.0 Value = 13117.8 (estimate), 15687.6 (perfect) Strehl = 0.69921 Strehl ratio estimate = 0.6992 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 = 21.3 micron Centre pixel: 128.0 128.0 Value = 11356.7 (estimate), 15687.6 (perfect) Strehl = 0.524074 Strehl ratio estimate = 0.5241 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 -29.9 -1.6 -2.7 30.0 2 1 2 -31.8 1.0 -3.6 32.0 3 1 3 -40.9 -2.3 -18.1 44.8 4 1 4 -43.4 -8.5 -1.2 44.2 5 1 5 -40.0 -15.5 -22.6 48.5 6 1 6 -49.4 -30.3 -30.8 65.6 7 1 7 -39.7 -32.8 -29.5 59.3 8 1 8 -39.3 -24.6 -11.8 47.8 9 1 9 -75.3 -8.8 -2.8 75.9 10 1 10 -31.2 -10.2 -5.1 33.2 11 1 11 -33.5 -6.6 -5.6 34.6 12 1 12 -7.5 1.1 -2.8 8.1 13 2 1 -6.8 10.4 10.4 16.2 14 2 2 -4.3 12.8 11.8 17.9 15 2 3 -5.0 9.8 11.8 16.1 16 2 4 -7.5 12.3 8.4 16.6 17 2 5 -14.2 9.2 6.2 18.0 18 2 6 -14.7 13.8 12.9 23.9 19 2 7 -15.9 6.3 12.5 21.2 20 2 8 8.5 24.9 6.7 27.2 21 2 9 -25.3 5.9 3.0 26.2 22 2 10 -20.7 2.6 -7.8 22.3 23 2 11 -19.8 -4.0 -6.1 21.1 24 2 12 -25.8 -1.3 -8.9 27.3 25 2 13 -26.6 -14.2 -10.3 31.9 26 2 14 -20.8 -7.3 -10.2 24.2 27 2 15 -25.2 -2.8 -2.6 25.5 28 2 16 -22.2 -2.2 4.1 22.7 29 2 17 -10.0 -3.2 6.8 12.5 30 2 18 -7.7 5.3 11.4 14.7 31 2 19 -4.9 11.3 15.5 19.8 32 2 20 -11.9 12.3 6.7 18.4 33 2 21 -7.4 2.2 4.2 8.8 34 2 22 1.9 11.5 5.7 12.9 35 2 23 5.3 1.1 4.0 6.7 36 2 24 -7.0 -4.6 13.0 15.5 37 3 1 4.4 11.3 28.5 31.0 38 3 2 4.0 8.4 22.0 23.9 39 3 3 3.7 11.4 16.1 20.0 40 3 4 9.8 13.2 12.1 20.5 41 3 5 8.6 11.2 9.5 17.0 42 3 6 10.4 11.1 13.3 20.2 43 3 7 14.4 10.1 13.5 22.2 44 3 8 6.7 14.0 19.8 25.2 45 3 9 7.0 15.3 19.7 25.9 46 3 10 8.3 14.1 17.8 24.1 47 3 11 7.8 14.3 8.4 18.4 48 3 12 7.9 22.6 7.6 25.1 49 3 13 8.8 18.2 10.8 22.9 50 3 14 11.5 6.6 0.2 13.2 51 3 15 1.2 6.2 2.3 6.7 52 3 16 7.0 7.7 10.3 14.7 53 3 17 0.0 8.2 2.5 8.6 54 3 18 -3.6 4.6 11.0 12.5 55 3 19 -3.1 4.8 10.4 11.9 56 3 20 1.9 4.1 6.6 8.0 57 3 21 -5.1 6.0 -0.5 7.8 58 3 22 -4.5 -2.9 -0.8 5.4 59 3 23 -2.1 -0.7 -2.5 3.3 60 3 24 -7.4 -3.4 1.1 8.2 61 3 25 -4.0 -2.5 -0.5 4.7 62 3 26 -10.2 -4.8 -4.8 12.3 63 3 27 -1.6 -4.5 -4.4 6.5 64 3 28 -4.4 -1.0 -3.6 5.8 65 3 29 -1.2 -0.3 -2.2 2.5 66 3 30 -3.1 -22.3 1.0 22.5 67 3 31 -5.9 -1.1 3.4 6.9 68 3 32 -1.1 5.2 4.3 6.8 69 3 33 4.7 3.6 1.6 6.2 70 3 34 -1.3 7.7 5.5 9.6 71 3 35 10.9 2.0 7.8 13.5 72 3 36 -1.7 16.6 7.0 18.1 73 3 37 12.7 21.2 7.7 25.9 74 3 38 6.2 8.9 6.8 12.8 75 3 39 10.7 1.1 18.0 21.0 76 3 40 5.1 9.7 13.7 17.5 77 3 41 5.8 7.6 1.9 9.8 78 3 42 2.7 5.4 4.7 7.7 79 3 43 2.9 3.4 2.6 5.2 80 3 44 8.8 4.5 -0.5 9.9 81 3 45 5.4 3.7 5.8 8.8 82 3 46 5.5 5.0 12.4 14.4 83 3 47 5.6 4.7 22.8 23.9 84 3 48 1.3 9.6 21.4 23.5 85 4 1 17.1 9.8 7.5 21.1 86 4 2 12.5 12.8 9.2 20.1 87 4 3 19.3 12.0 14.7 27.1 88 4 4 13.0 12.7 11.8 21.7 89 4 5 14.2 13.5 11.2 22.5 90 4 6 8.3 13.6 13.3 20.7 91 4 7 7.3 12.0 13.9 19.8 92 4 8 12.6 13.7 0.6 18.6 93 4 9 18.4 17.8 11.9 28.2 94 4 10 18.0 10.0 13.2 24.4 95 4 11 10.3 15.4 1.8 18.6 96 4 12 18.3 10.8 11.2 24.0 97 4 13 9.0 13.7 0.5 16.5 98 4 14 7.9 5.2 -2.9 9.9 99 4 15 1.5 1.6 0.5 2.3 100 4 16 -0.8 2.9 1.0 3.2 101 4 17 9.2 3.6 0.6 9.9 102 4 18 4.0 1.8 -0.8 4.5 103 4 19 7.8 5.3 8.1 12.5 104 4 20 9.2 6.5 9.7 14.9 105 4 21 9.6 3.6 11.3 15.3 106 4 22 10.6 -0.1 3.1 11.1 107 4 23 3.7 3.2 2.6 5.5 108 4 24 5.6 1.4 2.8 6.4 109 4 25 5.3 1.8 43.3 43.7 110 4 26 3.4 0.1 3.9 5.2 111 4 27 -2.0 -3.0 -7.7 8.5 112 4 28 -2.2 -0.3 -1.1 2.4 113 4 29 1.0 0.1 -49.5 49.5 114 4 30 -3.2 -2.4 -2.7 4.8 115 4 31 2.6 -4.6 -3.0 6.1 116 4 32 7.3 0.9 -8.9 11.6 117 4 33 0.5 3.0 -2.3 3.8 118 4 34 2.7 4.0 -5.9 7.6 119 4 35 4.0 1.8 1.5 4.6 120 4 36 15.6 13.4 11.2 23.4 121 4 37 14.1 6.6 5.5 16.5 122 4 38 -1.1 6.7 -0.3 6.8 123 4 39 9.5 1.9 6.1 11.5 124 4 40 9.8 4.9 -3.5 11.5 125 4 41 2.1 -3.4 -8.7 9.6 126 4 42 -2.0 5.8 0.9 6.2 127 4 43 -2.2 5.1 16.4 17.4 128 4 44 6.0 10.3 3.1 12.3 129 4 45 11.1 9.7 5.4 15.7 130 4 46 12.0 8.4 3.8 15.1 131 4 47 12.1 8.9 3.1 15.3 132 4 48 13.2 9.2 5.4 17.0 133 5 1 9.0 7.1 15.5 19.3 134 5 2 6.3 9.5 10.6 15.6 135 5 3 14.6 6.5 7.1 17.5 136 5 4 4.8 10.0 14.2 18.0 137 5 5 9.7 7.0 9.1 15.0 138 5 6 14.3 3.3 3.0 15.0 139 5 7 16.0 1.9 -3.8 16.5 140 5 8 8.0 4.1 4.2 9.9 141 5 9 3.5 1.4 -0.7 3.9 142 5 10 11.1 5.0 -3.3 12.6 143 5 11 0.3 6.5 -7.9 10.2 144 5 12 2.7 2.4 -9.4 10.1 145 5 13 3.6 -1.3 -4.7 6.0 146 5 14 -2.3 -2.4 -11.0 11.5 147 5 15 -1.1 -5.1 -8.9 10.3 148 5 16 -2.2 -6.0 -9.6 11.5 149 5 17 8.5 -3.0 -6.4 11.1 150 5 18 2.0 -2.0 199.5 199.5 151 5 19 0.3 0.5 5.9 5.9 152 5 20 7.2 4.1 -1.4 8.4 153 5 21 6.8 4.9 3.0 9.0 154 5 22 5.3 9.5 3.0 11.3 155 5 23 4.1 7.9 8.8 12.5 156 5 24 8.1 8.4 6.0 13.1 157 5 25 3.1 6.4 8.7 11.2 158 5 26 -1.1 0.9 7.6 7.7 159 5 27 3.8 7.2 8.1 11.4 160 5 28 -1.8 8.8 17.4 19.6 161 5 29 -4.5 7.6 11.8 14.8 162 5 30 -1.9 -0.0 6.1 6.4 163 5 31 1.4 0.1 -0.6 1.5 164 5 32 -3.3 -5.2 -3.6 7.1 165 5 33 0.4 -6.2 -1.2 6.3 166 5 34 -2.3 -4.6 -7.6 9.2 167 5 35 1.4 -6.7 -8.1 10.6 168 5 36 17.7 -4.3 8.4 20.0 169 5 37 4.5 -6.7 -1.6 8.3 170 5 38 -3.7 -3.3 -14.8 15.6 171 5 39 1.8 -5.3 -13.9 15.0 172 5 40 -9.8 -10.7 -12.9 19.4 173 5 41 1.5 -12.9 6.8 14.7 174 5 42 6.7 -1.5 -6.2 9.3 175 5 43 7.0 -0.9 1.5 7.2 176 5 44 4.6 -2.2 -6.0 7.9 177 5 45 6.8 -4.6 2.8 8.7 178 5 46 7.5 -1.6 -4.0 8.6 179 5 47 2.3 0.6 6.3 6.7 180 5 48 3.1 10.1 5.4 11.9 181 6 1 11.4 7.9 24.6 28.3 182 6 2 12.6 15.0 20.3 28.2 183 6 3 -2.5 10.8 10.4 15.2 184 6 4 6.5 6.9 7.9 12.4 185 6 5 4.7 5.8 -1.6 7.6 186 6 6 4.7 -4.6 1.2 6.7 187 6 7 -5.0 -5.1 -10.1 12.3 188 6 8 5.0 -10.9 -13.7 18.2 189 6 9 5.5 -12.2 -16.8 21.5 190 6 10 2.9 -14.3 -13.4 19.8 191 6 11 -6.0 -17.1 -24.1 30.2 192 6 12 -7.3 -19.2 -20.9 29.3 193 6 13 -1.6 -14.7 -22.8 27.2 194 6 14 -10.0 -19.7 -23.7 32.4 195 6 15 6.1 -18.5 -27.8 33.9 196 6 16 8.9 -14.1 -22.5 27.9 197 6 17 3.5 -14.9 -11.7 19.3 198 6 18 0.8 -9.6 -4.6 10.7 199 6 19 -0.7 -6.1 -8.3 10.3 200 6 20 2.7 -0.6 -8.9 9.3 201 6 21 8.8 5.4 -3.5 10.9 202 6 22 -1.9 11.2 5.3 12.5 203 6 23 7.6 16.8 7.5 19.9 204 6 24 9.2 15.6 14.4 23.2 205 6 25 11.2 15.0 24.5 30.9 206 6 26 15.2 19.9 19.5 31.7 207 6 27 20.8 21.2 29.9 42.2 208 6 28 16.7 16.1 25.1 34.2 209 6 29 35.5 24.1 20.9 47.7 210 6 30 21.0 3.6 47.8 52.3 211 6 31 -0.1 5.7 -3.2 6.6 212 6 32 5.9 -6.8 -5.7 10.7 213 6 33 -5.9 -8.4 -14.0 17.4 214 6 34 1.8 0.2 -0.1 1.8 215 6 35 -7.3 -9.0 -17.4 20.9 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12 56 1 12 57 1 12 58 0 12 59 -2 12 60 0 12 61 1 12 62 1 12 63 1 12 64 3 12 65 1 12 66 1 12 67 6 12 68 2 12 69 0 Adjuster movements: rms = 20.4 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050126-122825 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1