Reduction started at: 20050708-133134 Reading data from rxh3-20050704-233528.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 = 2401.7 max = 7634670370.4 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 34.170 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 -3.12012 3.09814 -0.00416 loimag -3.14941 3.14209 -0.00904 hireal -5.00000 4.99756 -0.00398 hiimag -5.00000 4.99756 0.01909 xpos -7634670370.35370 2411.29335 -2603879.94265 ypos -2401.71418 11090087.98063 3782.52463 plock160 0.58594 1.97510 1.34430 lorefpwr 0.98145 2.83691 2.30215 losigpwr -4.54834 -0.19775 -4.35453 hirefpwr 1.02295 2.82715 2.32307 hisigpwr -4.46289 4.99756 -1.76623 encltemp 31.59180 32.86133 32.12999 flags 0.00000 256.00000 2.44471 phi-lock -1.70654 -0.34668 -1.07595 sindex 0.00000 254.00000 126.60925 time 0.00000 19150776.97328 9468.32322 zeropt -0.00732 -0.00488 -0.00603 !!!Warning!!! philock max less than 0.2 !!!Warning!!! philock min less than -1.5 ---------------------------------------------------- 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 = 20.00265 arcsec Mean row spacing = 20.00266 arcsec (alternate estimator) Mean tracking incline = -0.17129 arcsec Mean pointing range = 0.66726 arcsec Mean pointing rms = 0.13685 arcsec This map *probably* has non-inclined rows !!!Warning!!! Bad tracking on row 97: range = 7.34463 > 4.0 !!!Warning!!! Bad tracking on row 97: rms = 2.18824 > 2.0 Applying pointing shifts: (-0.7, 13.0 ) 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 = 7.63467e+09 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 = 3.0319 at (0.0, 0.0) arcsec Real: mean = 0.000144678 sum of squares = 1905.18 Imag: mean = -0.000128388 sum of squares = 1990 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 = 3.06233 at (0.0, 0.0) arcsec Real: mean = 0.000220984 sum of squares = 2019.12 Imag: mean = -0.000142094 sum of squares = 1893.14 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 = 3.09612 at (0.0, 0.0) arcsec Real: mean = 0.000427454 sum of squares = 1986.14 Imag: mean = -0.000106184 sum of squares = 1952.5 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 = 3.07389 at (0.0, 0.0) arcsec Real: mean = 0.000472487 sum of squares = 1906.55 Imag: mean = 8.37682e-05 sum of squares = 2056.41 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 = 3.02882 at (0.0, 0.0) arcsec Real: mean = 0.000327324 sum of squares = 1993.92 Imag: mean = 0.000182098 sum of squares = 1989.36 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 = 3.0351 at (0.0, 0.0) arcsec Real: mean = 0.000194324 sum of squares = 2076.47 Imag: mean = 0.000230221 sum of squares = 1937.15 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 = 3.08729 at (0.0, 0.0) arcsec Real: mean = 4.3313e-05 sum of squares = 1995.52 Imag: mean = 0.000133162 sum of squares = 2050.55 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 = 3.09938 at (0.0, 0.0) arcsec Real: mean = 5.74849e-05 sum of squares = 1971.71 Imag: mean = -6.91982e-05 sum of squares = 2107.82 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 = 3.12905 at (0.0, 0.0) arcsec Real: mean = 0.000220073 sum of squares = 2098.41 Imag: mean = -0.00016469 sum of squares = 2009.97 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 = 3.15163 at (0.0, 0.0) arcsec Real: mean = 0.000371616 sum of squares = 2117.19 Imag: mean = -0.000123261 sum of squares = 2022.64 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 = 3.14446 at (0.0, 0.0) arcsec Real: mean = 0.000514936 sum of squares = 2020.26 Imag: mean = 1.84733e-05 sum of squares = 2154.22 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 = 3.10468 at (0.0, 0.0) arcsec Real: mean = 0.000440286 sum of squares = 2073.84 Imag: mean = 0.00024436 sum of squares = 2139.94 Gridding frequency index 12 lambda = 0.00186526 metres, scale = 0.00259917 radians per metre Gridding real part of frequency 12... Gridding imag part of frequency 12... Pattern is holo(res.pattern12) Weights in holo(obs.real,wt12) and holo(obs.imag,wt12) Maximum amplitude = 3.09646 at (0.0, 0.0) arcsec Real: mean = 0.000293433 sum of squares = 2198.2 Imag: mean = 0.000273705 sum of squares = 2058.21 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 = 3.13498 at (0.0, 0.0) arcsec Real: mean = -3.32942e-06 sum of squares = 2161.84 Imag: mean = 0.000253327 sum of squares = 2141.62 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 = 3.19441 at (0.0, 0.0) arcsec Real: mean = 2.8711e-05 sum of squares = 2088.5 Imag: mean = -6.45833e-05 sum of squares = 2261.05 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 = 3.2224 at (0.0, 0.0) arcsec Real: mean = 0.000135294 sum of squares = 2220.25 Imag: mean = -7.92883e-05 sum of squares = 2183.98 Masking frequency index 0 Mask scale size = 6.11579 Masking frequency index 1 Mask scale size = 6.11594 Masking frequency index 2 Mask scale size = 6.11609 Masking frequency index 3 Mask scale size = 6.11625 Masking frequency index 4 Mask scale size = 6.1164 Masking frequency index 5 Mask scale size = 6.11655 Masking frequency index 6 Mask scale size = 6.1167 Masking frequency index 7 Mask scale size = 6.11686 Masking frequency index 8 Mask scale size = 6.11701 Masking frequency index 9 Mask scale size = 6.11716 Masking frequency index 10 Mask scale size = 6.11731 Masking frequency index 11 Mask scale size = 6.11746 Masking frequency index 12 Mask scale size = 6.11762 Masking frequency index 13 Mask scale size = 6.11777 Masking frequency index 14 Mask scale size = 6.11792 Masking frequency index 15 Mask scale size = 6.11807 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.239258 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.231934 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: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.239258 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 1.4899 126.5 Freq 1: Shift, scale = 0.61918 126.39 Freq 2: Shift, scale = -0.24151 127.36 Freq 3: Shift, scale = -1.1044 127.71 Freq 4: Shift, scale = -1.9743 127.47 Freq 5: Shift, scale = -2.8376 127.26 Freq 6: Shift, scale = 2.5834 127.43 Freq 7: Shift, scale = 1.7318 128.72 Freq 8: Shift, scale = 0.86693 129.36 Freq 9: Shift, scale = -0.0063293 130.16 Freq 10: Shift, scale = -0.87233 131.06 Freq 11: Shift, scale = -1.7343 130.24 Freq 12: Shift, scale = -2.5939 130.27 Freq 13: Shift, scale = 2.8311 131.53 Freq 14: Shift, scale = 1.9589 133.01 Freq 15: Shift, scale = 1.0931 134.14 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: -0.261 radians x offset: 0.0308 arcsec y offset: 0.0222 arcsec defocus: -0.000166 mm Estimated x pointing error is -0.6692 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.02 arcsec (used 13 arcsec) Estimated defocus error is 3.17 mm (used 3.17 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.268 radians x offset: 0.0134 arcsec y offset: 0.042 arcsec defocus: 0.000515 mm Estimated x pointing error is -0.6866 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.04 arcsec (used 13 arcsec) Estimated defocus error is 3.171 mm (used 3.17 mm) Fitting frequency 2 Minimiser fit code = 1 piston: -0.266 radians x offset: 0.00946 arcsec y offset: 0.0501 arcsec defocus: -0.000305 mm Estimated x pointing error is -0.6905 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.05 arcsec (used 13 arcsec) Estimated defocus error is 3.17 mm (used 3.17 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.264 radians x offset: 0.00813 arcsec y offset: 0.0453 arcsec defocus: 0.000426 mm Estimated x pointing error is -0.6919 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.05 arcsec (used 13 arcsec) Estimated defocus error is 3.17 mm (used 3.17 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.27 radians x offset: 0.00731 arcsec y offset: 0.0341 arcsec defocus: 0.000588 mm Estimated x pointing error is -0.6927 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.03 arcsec (used 13 arcsec) Estimated defocus error is 3.171 mm (used 3.17 mm) Fitting frequency 5 Minimiser fit code = 3 piston: -0.271 radians x offset: -0.00184 arcsec y offset: 0.0305 arcsec defocus: -0.00115 mm Estimated x pointing error is -0.7018 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.03 arcsec (used 13 arcsec) Estimated defocus error is 3.169 mm (used 3.17 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.27 radians x offset: -0.00989 arcsec y offset: 0.0351 arcsec defocus: -0.000937 mm Estimated x pointing error is -0.7099 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.04 arcsec (used 13 arcsec) Estimated defocus error is 3.169 mm (used 3.17 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.26 radians x offset: -0.0209 arcsec y offset: 0.0434 arcsec defocus: -0.00185 mm Estimated x pointing error is -0.7209 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.04 arcsec (used 13 arcsec) Estimated defocus error is 3.168 mm (used 3.17 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.26 radians x offset: -0.0253 arcsec y offset: 0.0237 arcsec defocus: -0.00129 mm Estimated x pointing error is -0.7253 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.02 arcsec (used 13 arcsec) Estimated defocus error is 3.169 mm (used 3.17 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.27 radians x offset: -0.0329 arcsec y offset: 0.0111 arcsec defocus: -0.00183 mm Estimated x pointing error is -0.7329 arcsec (used -0.7 arcsec) Estimated y pointing error is 13.01 arcsec (used 13 arcsec) Estimated defocus error is 3.168 mm (used 3.17 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.273 radians x offset: -0.0374 arcsec y offset: 0.00348 arcsec defocus: -0.0031 mm Estimated x pointing error is -0.7374 arcsec (used -0.7 arcsec) Estimated y pointing error is 13 arcsec (used 13 arcsec) Estimated defocus error is 3.167 mm (used 3.17 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.272 radians x offset: -0.0531 arcsec y offset: -0.000463 arcsec defocus: -0.00315 mm Estimated x pointing error is -0.7531 arcsec (used -0.7 arcsec) Estimated y pointing error is 13 arcsec (used 13 arcsec) Estimated defocus error is 3.167 mm (used 3.17 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.266 radians x offset: -0.057 arcsec y offset: -0.015 arcsec defocus: -0.00278 mm Estimated x pointing error is -0.757 arcsec (used -0.7 arcsec) Estimated y pointing error is 12.98 arcsec (used 13 arcsec) Estimated defocus error is 3.167 mm (used 3.17 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.261 radians x offset: -0.0648 arcsec y offset: -0.0238 arcsec defocus: -0.00423 mm Estimated x pointing error is -0.7648 arcsec (used -0.7 arcsec) Estimated y pointing error is 12.98 arcsec (used 13 arcsec) Estimated defocus error is 3.166 mm (used 3.17 mm) Fitting frequency 14 Minimiser fit code = 3 piston: -0.268 radians x offset: -0.0697 arcsec y offset: -0.0414 arcsec defocus: -0.00543 mm Estimated x pointing error is -0.7697 arcsec (used -0.7 arcsec) Estimated y pointing error is 12.96 arcsec (used 13 arcsec) Estimated defocus error is 3.165 mm (used 3.17 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.269 radians x offset: -0.0804 arcsec y offset: -0.0382 arcsec defocus: -0.00567 mm Estimated x pointing error is -0.7804 arcsec (used -0.7 arcsec) Estimated y pointing error is 12.96 arcsec (used 13 arcsec) Estimated defocus error is 3.164 mm (used 3.17 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 -0.00185 piston 1 1 -0.00286 tilt_x 1 -1 -0.00881 tilt_y 2 2 -0.07468 astigmatism_0 2 0 -0.00217 curvature 2 -2 -0.00296 astigmatism45 3 3 -0.04179 trefoil_0 3 1 -0.01034 coma_x 3 -1 -0.03142 coma_y 3 -3 0.09474 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 -0.00186 piston 1 1 -0.00239 tilt_x 1 -1 -0.00853 tilt_y 2 2 -0.07417 astigmatism_0 2 0 -0.00215 curvature 2 -2 -0.00558 astigmatism45 3 3 -0.04367 trefoil_0 3 1 -0.00897 coma_x 3 -1 -0.03079 coma_y 3 -3 0.09279 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 -0.00183 piston 1 1 -0.00214 tilt_x 1 -1 -0.00871 tilt_y 2 2 -0.07217 astigmatism_0 2 0 -0.00205 curvature 2 -2 -0.00562 astigmatism45 3 3 -0.04410 trefoil_0 3 1 -0.00850 coma_x 3 -1 -0.03214 coma_y 3 -3 0.09057 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 -0.00186 piston 1 1 -0.00239 tilt_x 1 -1 -0.00847 tilt_y 2 2 -0.07250 astigmatism_0 2 0 -0.00208 curvature 2 -2 -0.00407 astigmatism45 3 3 -0.04220 trefoil_0 3 1 -0.00944 coma_x 3 -1 -0.03103 coma_y 3 -3 0.09106 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 -0.00184 piston 1 1 -0.00213 tilt_x 1 -1 -0.00793 tilt_y 2 2 -0.07377 astigmatism_0 2 0 -0.00206 curvature 2 -2 -0.00235 astigmatism45 3 3 -0.04282 trefoil_0 3 1 -0.00863 coma_x 3 -1 -0.02898 coma_y 3 -3 0.09211 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 -0.00190 piston 1 1 -0.00191 tilt_x 1 -1 -0.00796 tilt_y 2 2 -0.07481 astigmatism_0 2 0 -0.00228 curvature 2 -2 -0.00419 astigmatism45 3 3 -0.04205 trefoil_0 3 1 -0.00822 coma_x 3 -1 -0.02876 coma_y 3 -3 0.09163 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 -0.00189 piston 1 1 -0.00132 tilt_x 1 -1 -0.00876 tilt_y 2 2 -0.07432 astigmatism_0 2 0 -0.00225 curvature 2 -2 -0.00397 astigmatism45 3 3 -0.04230 trefoil_0 3 1 -0.00607 coma_x 3 -1 -0.03227 coma_y 3 -3 0.09080 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 -0.00195 piston 1 1 -0.00095 tilt_x 1 -1 -0.00895 tilt_y 2 2 -0.07237 astigmatism_0 2 0 -0.00230 curvature 2 -2 -0.00534 astigmatism45 3 3 -0.04430 trefoil_0 3 1 -0.00471 coma_x 3 -1 -0.03418 coma_y 3 -3 0.08889 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 -0.00198 piston 1 1 -0.00122 tilt_x 1 -1 -0.00853 tilt_y 2 2 -0.07281 astigmatism_0 2 0 -0.00226 curvature 2 -2 -0.00467 astigmatism45 3 3 -0.04139 trefoil_0 3 1 -0.00632 coma_x 3 -1 -0.03254 coma_y 3 -3 0.09024 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 -0.00194 piston 1 1 -0.00137 tilt_x 1 -1 -0.00858 tilt_y 2 2 -0.07453 astigmatism_0 2 0 -0.00219 curvature 2 -2 -0.00485 astigmatism45 3 3 -0.03900 trefoil_0 3 1 -0.00749 coma_x 3 -1 -0.03220 coma_y 3 -3 0.09268 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 -0.00193 piston 1 1 -0.00105 tilt_x 1 -1 -0.00851 tilt_y 2 2 -0.07424 astigmatism_0 2 0 -0.00228 curvature 2 -2 -0.00553 astigmatism45 3 3 -0.04003 trefoil_0 3 1 -0.00587 coma_x 3 -1 -0.03189 coma_y 3 -3 0.09132 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 -0.00194 piston 1 1 -0.00071 tilt_x 1 -1 -0.00841 tilt_y 2 2 -0.07421 astigmatism_0 2 0 -0.00228 curvature 2 -2 -0.00563 astigmatism45 3 3 -0.04151 trefoil_0 3 1 -0.00469 coma_x 3 -1 -0.03201 coma_y 3 -3 0.09164 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 -0.00199 piston 1 1 -0.00026 tilt_x 1 -1 -0.00865 tilt_y 2 2 -0.07413 astigmatism_0 2 0 -0.00230 curvature 2 -2 -0.00569 astigmatism45 3 3 -0.03970 trefoil_0 3 1 -0.00368 coma_x 3 -1 -0.03297 coma_y 3 -3 0.08940 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 -0.00205 piston 1 1 -0.00092 tilt_x 1 -1 -0.00846 tilt_y 2 2 -0.07426 astigmatism_0 2 0 -0.00235 curvature 2 -2 -0.00468 astigmatism45 3 3 -0.03798 trefoil_0 3 1 -0.00629 coma_x 3 -1 -0.03221 coma_y 3 -3 0.08879 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 -0.00206 piston 1 1 -0.00112 tilt_x 1 -1 -0.00864 tilt_y 2 2 -0.07589 astigmatism_0 2 0 -0.00229 curvature 2 -2 -0.00385 astigmatism45 3 3 -0.03680 trefoil_0 3 1 -0.00710 coma_x 3 -1 -0.03254 coma_y 3 -3 0.09139 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 -0.00201 piston 1 1 -0.00125 tilt_x 1 -1 -0.00881 tilt_y 2 2 -0.07571 astigmatism_0 2 0 -0.00235 curvature 2 -2 -0.00467 astigmatism45 3 3 -0.03734 trefoil_0 3 1 -0.00726 coma_x 3 -1 -0.03278 coma_y 3 -3 0.09212 trefoil_30 Averaged 16 maps to make holo(res.mean_surface) Computing differences from mean surface (phase) Unweighted rms analysis, frequency 0 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.1 20.9 17.8 22.2 22.3 24.1 34 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.2 20.9 17.8 22 21.8 22.9 30.9 24 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.03 1.9 2.74 3.79 5.44 8.05 11.8 7.38 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.6 20.5 18.8 22.3 22.4 23.6 34.5 25.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.5 18.7 22.2 21.9 22.6 31.2 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1 1.85 2.68 3.73 5.4 7.99 11.7 7.31 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.9 20.2 18.4 22.2 22.2 24 34.7 25.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21 20.2 18.4 22.1 21.8 23 31.3 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.03 1.9 2.72 3.71 5.3 7.82 11.5 7.18 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.6 20.5 18.2 21.8 22.1 24.2 34.2 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 20.7 20.5 18.2 21.6 21.7 23.1 30.9 24 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.01 1.86 2.68 3.69 5.29 7.81 11.4 7.16 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.8 20.7 17.8 21.2 22.2 24.2 33.7 25.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21 20.8 17.8 21 21.7 22.9 30.6 23.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.945 1.76 2.58 3.65 5.33 7.92 11.6 7.23 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21 20.4 17.8 21.1 22.2 23.7 33.9 25 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.1 20.5 17.8 21 21.7 22.6 30.7 23.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.936 1.74 2.58 3.66 5.35 7.93 11.6 7.24 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.6 18.4 21.9 22.3 23.6 34.4 25.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.8 20.6 18.4 21.8 21.8 22.6 31.1 24.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.02 1.88 2.71 3.74 5.35 7.89 11.5 7.23 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.5 20.7 18.8 22.8 22.1 23.6 34.4 25.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.7 18.8 22.7 21.7 22.7 31.1 24.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.07 1.96 2.78 3.74 5.28 7.76 11.4 7.15 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.1 20.5 18.1 22.3 21.8 24.2 34.3 25.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.3 20.6 18.1 22.3 21.4 23.1 30.9 24.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.03 1.89 2.71 3.71 5.28 7.78 11.4 7.14 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.6 20.5 17.9 21.7 21.9 24.2 34 25.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 20.8 20.6 17.9 21.6 21.5 22.9 30.7 23.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.03 1.89 2.73 3.75 5.37 7.91 11.6 7.26 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.8 20.7 17.6 21.2 22 23.8 33.9 25 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 20.9 20.7 17.6 21 21.6 22.6 30.7 23.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.01 1.86 2.69 3.72 5.33 7.86 11.5 7.21 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.5 20.5 20.4 21 22.1 23.5 34.2 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.7 20.5 20.4 20.9 21.7 22.6 30.8 24 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.01 1.86 2.69 3.72 5.35 7.9 11.6 7.24 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21.4 20.3 18.8 21.6 22.1 23.5 34.5 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.6 20.3 18.8 21.5 21.8 22.6 31 24 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.03 1.9 2.72 3.72 5.29 7.78 11.4 7.14 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 21 20.4 18 22.2 21.9 23.8 34.1 25.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21.1 20.4 18 22.1 21.6 22.7 30.8 23.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.02 1.88 2.7 3.7 5.26 7.73 11.3 7.09 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.6 20.8 18 21.9 21.9 24.3 33.9 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 20.8 20.8 18 21.8 21.5 23.1 30.6 23.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.04 1.91 2.75 3.77 5.37 7.89 11.5 7.23 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 20.8 20.5 17.8 22.2 22.2 23.9 34.1 25.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 21 20.6 17.8 22.1 21.7 22.8 30.8 23.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.05 1.92 2.76 3.78 5.39 7.92 11.6 7.26 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 19.7 19.6 16.9 20.6 21.2 22.8 33 24.2 Mean deviation is -0.91938218845802755 microns Taper = 10 dB, Ruze illumination-weighted rms = 23.3 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 = 20.4 micron Centre pixel: 128.0 128.0 Value = 13440.5 (estimate), 15687.6 (perfect) Strehl = 0.734034 Strehl ratio estimate = 0.734 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 = 19.8 micron Centre pixel: 128.0 128.0 Value = 11879.9 (estimate), 15687.6 (perfect) Strehl = 0.57347 Strehl ratio estimate = 0.5735 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 1.2 2.4 -8.7 9.1 2 1 2 12.7 -8.3 2.9 15.4 3 1 3 10.7 -3.8 -2.2 11.5 4 1 4 8.3 6.1 10.2 14.5 5 1 5 -13.1 3.1 5.3 14.4 6 1 6 16.9 -12.0 -10.4 23.2 7 1 7 4.2 -0.1 -6.1 7.4 8 1 8 6.1 0.9 3.9 7.3 9 1 9 -40.8 13.4 6.0 43.3 10 1 10 13.2 7.8 3.6 15.7 11 1 11 13.8 9.5 -3.1 17.0 12 1 12 25.2 4.6 5.9 26.3 13 2 1 10.2 -4.7 -3.8 11.9 14 2 2 8.9 -2.3 -7.5 11.9 15 2 3 -3.8 -5.2 -16.7 17.9 16 2 4 -5.1 -1.6 -6.1 8.1 17 2 5 -9.4 -8.3 -7.6 14.7 18 2 6 3.7 -1.3 1.5 4.2 19 2 7 -13.5 -7.2 7.0 16.8 20 2 8 4.5 18.3 5.1 19.5 21 2 9 6.7 3.3 0.9 7.5 22 2 10 4.7 -1.4 -1.8 5.2 23 2 11 -4.8 -4.7 -2.9 7.3 24 2 12 -15.2 -4.1 -10.3 18.9 25 2 13 -7.4 8.5 -4.0 11.9 26 2 14 -12.3 -13.4 0.6 18.3 27 2 15 5.5 1.6 -5.8 8.1 28 2 16 3.4 5.8 4.4 8.0 29 2 17 15.4 7.4 5.4 17.9 30 2 18 11.9 6.4 -8.2 15.8 31 2 19 7.6 14.4 -10.5 19.4 32 2 20 9.4 -2.9 -3.0 10.3 33 2 21 1.0 -3.0 -11.7 12.1 34 2 22 0.6 -18.5 -19.8 27.2 35 2 23 17.9 -14.1 -10.0 24.9 36 2 24 6.0 -11.6 -0.1 13.1 37 3 1 -3.1 2.9 -2.9 5.1 38 3 2 -0.3 2.4 -3.6 4.3 39 3 3 1.5 0.1 -12.8 12.9 40 3 4 11.2 2.9 1.2 11.7 41 3 5 -1.6 1.6 -18.0 18.2 42 3 6 1.0 -1.5 -5.6 5.9 43 3 7 3.9 -2.9 -10.8 11.8 44 3 8 0.1 4.4 -1.5 4.6 45 3 9 0.3 -1.5 -10.7 10.9 46 3 10 4.5 -3.1 -4.1 6.9 47 3 11 -6.4 -1.6 -17.9 19.1 48 3 12 -5.5 10.2 -4.8 12.5 49 3 13 -6.8 2.1 2.8 7.6 50 3 14 9.9 3.3 -3.3 10.9 51 3 15 14.4 4.9 7.2 16.8 52 3 16 13.5 6.1 1.1 14.8 53 3 17 5.5 9.8 0.1 11.2 54 3 18 10.6 8.3 13.4 19.0 55 3 19 13.4 6.6 0.5 14.9 56 3 20 -2.2 8.1 3.3 9.0 57 3 21 -2.0 7.6 -9.6 12.4 58 3 22 7.8 0.9 -3.1 8.4 59 3 23 -0.6 1.2 -10.0 10.1 60 3 24 10.7 -1.7 -4.5 11.7 61 3 25 3.1 2.4 -12.6 13.2 62 3 26 -1.5 -2.7 -3.0 4.3 63 3 27 7.1 -4.5 -11.8 14.5 64 3 28 13.9 5.1 -8.0 16.8 65 3 29 10.8 7.4 6.0 14.4 66 3 30 11.5 -11.1 16.0 22.6 67 3 31 -2.6 10.2 8.1 13.3 68 3 32 -1.0 3.2 5.8 6.7 69 3 33 18.2 4.2 5.8 19.5 70 3 34 19.7 9.2 21.1 30.3 71 3 35 -0.4 7.4 -4.4 8.6 72 3 36 13.3 7.8 -0.1 15.4 73 3 37 -9.3 6.4 -28.0 30.2 74 3 38 -6.3 9.6 -11.5 16.3 75 3 39 -0.4 -1.1 -16.0 16.0 76 3 40 -3.2 6.2 -11.9 13.7 77 3 41 -1.6 6.3 -4.5 7.9 78 3 42 2.7 2.2 4.5 5.7 79 3 43 2.6 -4.2 0.7 5.0 80 3 44 8.7 0.5 -0.6 8.7 81 3 45 0.5 0.0 -12.3 12.3 82 3 46 3.7 -2.2 -6.0 7.4 83 3 47 -5.9 -3.5 -4.5 8.2 84 3 48 0.5 3.3 -16.9 17.2 85 4 1 -1.6 -4.1 9.9 10.8 86 4 2 0.6 2.6 0.9 2.8 87 4 3 5.6 5.0 2.3 7.9 88 4 4 1.4 5.6 -18.5 19.4 89 4 5 -2.0 3.4 -4.1 5.7 90 4 6 -5.1 -0.1 -3.4 6.2 91 4 7 -8.7 -3.6 -1.1 9.4 92 4 8 -6.6 -0.5 -15.4 16.7 93 4 9 4.4 2.0 -7.3 8.7 94 4 10 -33.2 -3.6 -13.7 36.1 95 4 11 -6.8 -2.2 -18.8 20.1 96 4 12 -9.0 3.3 -12.5 15.7 97 4 13 0.3 3.7 1.6 4.1 98 4 14 4.2 -2.6 -15.8 16.6 99 4 15 -2.3 -2.3 -2.5 4.1 100 4 16 -0.9 8.3 -0.9 8.4 101 4 17 8.1 2.4 -5.2 9.9 102 4 18 2.2 1.5 -0.7 2.8 103 4 19 -14.6 0.8 2.7 14.9 104 4 20 2.5 7.8 1.7 8.3 105 4 21 11.3 8.5 8.9 16.7 106 4 22 -17.9 4.4 6.1 19.4 107 4 23 -8.7 -0.3 11.5 14.4 108 4 24 0.9 4.9 8.3 9.7 109 4 25 -12.9 9.4 29.8 33.8 110 4 26 -9.3 -6.8 -7.0 13.4 111 4 27 0.6 -3.0 1.0 3.2 112 4 28 -2.3 -1.4 1.1 2.9 113 4 29 -11.5 2.0 -52.6 53.9 114 4 30 -2.0 -3.1 10.6 11.2 115 4 31 2.1 -0.1 -10.4 10.6 116 4 32 5.0 3.8 -2.5 6.8 117 4 33 -7.1 13.9 -3.0 15.8 118 4 34 6.5 4.5 -1.2 8.0 119 4 35 1.2 10.6 -12.9 16.8 120 4 36 -0.4 -2.2 4.7 5.2 121 4 37 -10.3 8.1 -3.9 13.7 122 4 38 -12.7 2.2 -15.2 19.9 123 4 39 -7.0 -7.6 -4.8 11.4 124 4 40 15.5 -0.9 -7.2 17.1 125 4 41 -7.6 7.2 -25.1 27.3 126 4 42 -15.6 -7.8 -20.0 26.6 127 4 43 -13.8 -6.7 -16.8 22.7 128 4 44 -11.6 -3.4 -13.3 17.9 129 4 45 5.4 1.7 -17.1 18.1 130 4 46 -2.0 -5.7 -18.1 19.1 131 4 47 -5.1 -11.0 6.0 13.5 132 4 48 -12.4 -4.1 -1.9 13.2 133 5 1 13.5 13.4 14.0 23.6 134 5 2 9.7 8.1 10.1 16.2 135 5 3 1.7 18.4 13.3 22.8 136 5 4 0.4 3.6 3.5 5.1 137 5 5 1.3 1.0 -2.8 3.3 138 5 6 1.8 -1.0 -2.8 3.4 139 5 7 -1.9 9.8 2.7 10.4 140 5 8 -3.0 2.3 -10.4 11.0 141 5 9 -6.7 -5.1 -7.4 11.2 142 5 10 0.9 -7.8 -3.8 8.8 143 5 11 -4.6 -1.7 -6.9 8.5 144 5 12 -8.1 7.2 -14.2 17.9 145 5 13 0.4 0.7 0.4 0.9 146 5 14 -7.9 1.6 -12.3 14.6 147 5 15 0.6 5.6 -10.6 12.0 148 5 16 -5.0 3.0 -9.3 11.0 149 5 17 -0.8 6.4 36.7 37.2 150 5 18 6.1 4.8 210.3 210.4 151 5 19 -15.9 2.4 1.6 16.2 152 5 20 -11.1 -1.2 -6.3 12.8 153 5 21 -1.2 10.2 15.0 18.1 154 5 22 -8.3 7.1 13.9 17.7 155 5 23 -7.6 6.5 22.9 25.0 156 5 24 3.1 1.3 16.5 16.8 157 5 25 -1.9 6.8 9.7 12.1 158 5 26 -9.2 -3.7 6.9 12.1 159 5 27 -10.9 1.1 -4.4 11.8 160 5 28 -7.5 3.0 8.0 11.4 161 5 29 1.3 2.4 -12.3 12.6 162 5 30 2.7 -8.0 5.1 9.9 163 5 31 2.2 -1.3 -2.0 3.3 164 5 32 -9.5 -4.2 7.6 12.9 165 5 33 14.2 16.3 7.3 22.8 166 5 34 7.5 3.0 -1.7 8.2 167 5 35 3.7 7.6 7.5 11.3 168 5 36 13.7 0.1 8.9 16.4 169 5 37 12.7 8.6 -14.7 21.2 170 5 38 -7.4 3.2 -12.7 15.0 171 5 39 0.9 13.6 -14.3 19.8 172 5 40 -13.1 -5.2 -11.2 18.0 173 5 41 3.9 -2.5 -4.1 6.2 174 5 42 -8.9 -9.1 -26.5 29.4 175 5 43 -20.0 -9.5 -17.7 28.3 176 5 44 -8.7 0.6 -15.0 17.4 177 5 45 8.2 3.5 -7.7 11.8 178 5 46 -6.0 9.0 1.9 11.0 179 5 47 3.3 0.8 -5.9 6.9 180 5 48 -1.6 18.7 1.4 18.8 181 6 1 14.9 22.2 24.0 35.9 182 6 2 5.3 18.1 24.6 31.0 183 6 3 4.3 12.0 11.6 17.3 184 6 4 8.3 9.2 0.2 12.4 185 6 5 6.2 5.9 -12.0 14.7 186 6 6 9.7 -0.6 5.0 11.0 187 6 7 -5.6 -2.5 -17.3 18.4 188 6 8 5.7 -9.0 4.1 11.4 189 6 9 -3.6 -15.3 -21.5 26.7 190 6 10 -9.2 -9.2 -8.5 15.6 191 6 11 -7.9 -18.8 -15.9 25.8 192 6 12 -8.4 -7.7 -24.9 27.3 193 6 13 -1.0 -9.3 -27.9 29.4 194 6 14 -6.1 -5.5 -31.3 32.3 195 6 15 -9.7 -16.4 -9.4 21.3 196 6 16 2.1 11.3 -0.6 11.5 197 6 17 -0.2 -2.2 -4.0 4.5 198 6 18 13.0 6.6 -37.4 40.2 199 6 19 11.4 -1.7 24.2 26.8 200 6 20 5.6 18.5 24.4 31.1 201 6 21 9.1 13.8 -2.5 16.7 202 6 22 16.4 6.3 -0.9 17.6 203 6 23 15.0 5.5 11.1 19.4 204 6 24 10.1 6.9 3.1 12.6 205 6 25 -5.5 1.8 -19.7 20.5 206 6 26 -7.9 -2.4 -0.6 8.3 207 6 27 1.7 2.9 5.9 6.7 208 6 28 -3.4 3.7 11.1 12.2 209 6 29 -0.1 41.4 -14.9 44.0 210 6 30 -3.8 5.3 58.3 58.6 211 6 31 -13.9 0.6 -11.1 17.8 212 6 32 -4.2 -12.3 -4.9 13.9 213 6 33 -5.0 4.8 -0.5 6.9 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12 53 -3 12 54 1 12 55 -1 12 56 0 12 57 1 12 58 1 12 59 7 12 60 1 12 61 -3 12 62 0 12 63 0 12 64 -1 12 65 5 12 66 -3 12 67 -5 12 68 1 12 69 0 Adjuster movements: rms = 18.8 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050708-135930 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1