Reduction started at: 20050627-132653 Reading data from /net/moana/export/data/janw/rxh3/rxh3-20050626-082528.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 = 2361.2 max = 2431.9 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.990 mm ----------------- Data Summary --------------------- Number of samples: 366500 This is a 80 GHz map Number of frequencies: 16 Frequencies (GHz): 80.338000 80.340000 80.342000 80.344000 80.346000 80.348000 80.350000 80.352000 80.354000 80.356000 80.358000 80.360000 80.362000 80.364000 80.366000 80.368000 item min max mean loreal -3.11279 3.11035 -0.03133 loimag -3.28369 3.20068 -0.00666 hireal -5.00000 4.99756 -0.23641 hiimag -5.00000 4.99756 -0.26683 xpos -2431.45056 2431.88720 -2.69626 ypos -2361.20147 2401.71789 19.78157 plock160 0.55176 1.99707 1.33569 lorefpwr -0.03174 1.59668 1.08085 losigpwr -4.55566 -0.14893 -4.30604 hirefpwr 0.04150 1.64307 1.13624 hisigpwr -4.46045 4.99756 -1.14706 encltemp 31.59180 32.81250 32.11464 flags 0.00000 256.00000 2.44475 phi-lock -1.67969 -0.30518 -1.02561 sindex 0.00000 126.00000 62.21460 time 0.00000 2015.97891 998.92698 zeropt -0.00732 -0.00488 -0.00598 !!!Warning!!! philock max less than 0.2 !!!Warning!!! philock min less than -1.5 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 127 rows There are 120 data rows and 7 calibrator rows Calibrator rows: 19 40 61 82 103 124 126 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 40.00482 arcsec Mean row spacing = 40.00484 arcsec (alternate estimator) Mean tracking incline = 0.75380 arcsec Mean pointing range = 1.50355 arcsec Mean pointing rms = 0.30621 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (-1.3, 15.9 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 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 3500 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22495 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22495 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 40.0 arcseconds Using a grid of 128 points Grid has even number of points Maximum data offset = 2431.89 arcsec Grid extent = 2540 arcsec lambda_min = 0.00373025 scale = 0.00129968 Diffraction scale lambda/D = 51.3137 arcsec Gridding function extent = 307.882 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 153.941 arcsec Airy first null at 62.5858 arcsec Gridding frequency index 0 lambda = 0.00373164 metres, scale = 0.0012992 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 = 3.05159 at (0.0, -40.01493689163285) arcsec Real: mean = 0.00155338 sum of squares = 821.101 Imag: mean = -0.00296118 sum of squares = 1017.23 Gridding frequency index 1 lambda = 0.00373155 metres, scale = 0.00129923 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 = 3.05747 at (0.0, -40.013940751804832) arcsec Real: mean = 0.00230761 sum of squares = 858.647 Imag: mean = -0.00324745 sum of squares = 981.277 Gridding frequency index 2 lambda = 0.00373145 metres, scale = 0.00129926 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 = 3.06003 at (0.0, 0.0) arcsec Real: mean = 0.00289939 sum of squares = 942.055 Imag: mean = -0.00307927 sum of squares = 899.853 Gridding frequency index 3 lambda = 0.00373136 metres, scale = 0.00129929 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 = 3.12157 at (0.0, 0.0) arcsec Real: mean = 0.00319077 sum of squares = 1011.36 Imag: mean = -0.00238535 sum of squares = 834.291 Gridding frequency index 4 lambda = 0.00373127 metres, scale = 0.00129933 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 = 3.13212 at (0.0, 0.0) arcsec Real: mean = 0.00337674 sum of squares = 1019.01 Imag: mean = -0.00201573 sum of squares = 833.636 Gridding frequency index 5 lambda = 0.00373118 metres, scale = 0.00129936 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 = 3.15069 at (0.0, 0.0) arcsec Real: mean = 0.00338983 sum of squares = 956.804 Imag: mean = -0.00172749 sum of squares = 901.102 Gridding frequency index 6 lambda = 0.00373108 metres, scale = 0.00129939 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 = 3.13766 at (0.0, -40.008960796515247) arcsec Real: mean = 0.00322786 sum of squares = 874.968 Imag: mean = -0.00111101 sum of squares = 988.151 Gridding frequency index 7 lambda = 0.00373099 metres, scale = 0.00129942 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 = 3.13302 at (0.0, -40.007964954201512) arcsec Real: mean = 0.00296596 sum of squares = 834.453 Imag: mean = -0.000638324 sum of squares = 1030.79 Gridding frequency index 8 lambda = 0.0037309 metres, scale = 0.00129946 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 = 3.13232 at (0.0, -40.006969161460532) arcsec Real: mean = 0.00248706 sum of squares = 868.283 Imag: mean = -0.000637198 sum of squares = 1000.08 Gridding frequency index 9 lambda = 0.0037308 metres, scale = 0.00129949 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 = 3.12803 at (0.0, -40.005973418288612) arcsec Real: mean = 0.00185815 sum of squares = 947.736 Imag: mean = -0.000677991 sum of squares = 922.591 Gridding frequency index 10 lambda = 0.00373071 metres, scale = 0.00129952 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 = 3.13275 at (0.0, -40.004977724682043) arcsec Real: mean = 0.00144479 sum of squares = 1017.76 Imag: mean = -0.000883859 sum of squares = 853.734 Gridding frequency index 11 lambda = 0.00373062 metres, scale = 0.00129955 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 = 3.12717 at (0.0, -40.00398208063713) arcsec Real: mean = 0.00127374 sum of squares = 1031.22 Imag: mean = -0.00144559 sum of squares = 842.736 Gridding frequency index 12 lambda = 0.00373053 metres, scale = 0.00129959 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 = 3.11758 at (0.0, -40.002986486150171) arcsec Real: mean = 0.00116475 sum of squares = 977.801 Imag: mean = -0.00190908 sum of squares = 897.861 Gridding frequency index 13 lambda = 0.00373043 metres, scale = 0.00129962 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 = 3.10983 at (0.0, -40.001990941217464) arcsec Real: mean = 0.00130755 sum of squares = 897.78 Imag: mean = -0.00235393 sum of squares = 981.531 Gridding frequency index 14 lambda = 0.00373034 metres, scale = 0.00129965 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 = 3.08905 at (0.0, -40.000995445835301) arcsec Real: mean = 0.00187503 sum of squares = 846.215 Imag: mean = -0.00293133 sum of squares = 1037.19 Gridding frequency index 15 lambda = 0.00373025 metres, scale = 0.00129968 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 = 3.09035 at (0.0, -40.0) arcsec Real: mean = 0.00248704 sum of squares = 860.197 Imag: mean = -0.00295713 sum of squares = 1025.59 Masking frequency index 0 Mask scale size = 3.00631 Masking frequency index 1 Mask scale size = 3.00639 Masking frequency index 2 Mask scale size = 3.00646 Masking frequency index 3 Mask scale size = 3.00654 Masking frequency index 4 Mask scale size = 3.00661 Masking frequency index 5 Mask scale size = 3.00669 Masking frequency index 6 Mask scale size = 3.00676 Masking frequency index 7 Mask scale size = 3.00684 Masking frequency index 8 Mask scale size = 3.00691 Masking frequency index 9 Mask scale size = 3.00699 Masking frequency index 10 Mask scale size = 3.00706 Masking frequency index 11 Mask scale size = 3.00714 Masking frequency index 12 Mask scale size = 3.00721 Masking frequency index 13 Mask scale size = 3.00729 Masking frequency index 14 Mask scale size = 3.00736 Masking frequency index 15 Mask scale size = 3.00744 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.234375 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.231934 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.234375 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.224609 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.214844 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.0219727 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.0219727 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = -1.0834 99.365 Freq 1: Shift, scale = -1.5272 98.147 Freq 2: Shift, scale = -1.9684 97.317 Freq 3: Shift, scale = -2.4134 96.884 Freq 4: Shift, scale = -2.8568 98.107 Freq 5: Shift, scale = 2.9779 99.132 Freq 6: Shift, scale = 2.5267 101.08 Freq 7: Shift, scale = 2.0809 101.95 Freq 8: Shift, scale = 1.644 102.89 Freq 9: Shift, scale = 1.2184 103.9 Freq 10: Shift, scale = 0.79225 104.34 Freq 11: Shift, scale = 0.36331 104.56 Freq 12: Shift, scale = -0.066257 103.87 Freq 13: Shift, scale = -0.49957 102.91 Freq 14: Shift, scale = -0.9358 101.29 Freq 15: Shift, scale = -1.3718 99.88 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 = 3 piston: -0.339 radians x offset: 0.0115 arcsec y offset: 0.141 arcsec defocus: -0.00672 mm Estimated x pointing error is -1.289 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.04 arcsec (used 15.9 arcsec) Estimated defocus error is 2.983 mm (used 2.99 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.346 radians x offset: 0.0234 arcsec y offset: 0.16 arcsec defocus: -0.00761 mm Estimated x pointing error is -1.277 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.06 arcsec (used 15.9 arcsec) Estimated defocus error is 2.982 mm (used 2.99 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.35 radians x offset: 0.00885 arcsec y offset: 0.165 arcsec defocus: -0.00821 mm Estimated x pointing error is -1.291 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.07 arcsec (used 15.9 arcsec) Estimated defocus error is 2.982 mm (used 2.99 mm) Fitting frequency 3 Minimiser fit code = 3 piston: -0.358 radians x offset: 0.0141 arcsec y offset: 0.159 arcsec defocus: -0.00772 mm Estimated x pointing error is -1.286 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.06 arcsec (used 15.9 arcsec) Estimated defocus error is 2.982 mm (used 2.99 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.362 radians x offset: -0.0133 arcsec y offset: 0.166 arcsec defocus: -0.00716 mm Estimated x pointing error is -1.313 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.07 arcsec (used 15.9 arcsec) Estimated defocus error is 2.983 mm (used 2.99 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.373 radians x offset: -0.00103 arcsec y offset: 0.157 arcsec defocus: -0.0047 mm Estimated x pointing error is -1.301 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.06 arcsec (used 15.9 arcsec) Estimated defocus error is 2.985 mm (used 2.99 mm) Fitting frequency 6 Minimiser fit code = 3 piston: -0.385 radians x offset: 0.0133 arcsec y offset: 0.14 arcsec defocus: -0.00368 mm Estimated x pointing error is -1.287 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.04 arcsec (used 15.9 arcsec) Estimated defocus error is 2.986 mm (used 2.99 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.392 radians x offset: 0.0265 arcsec y offset: 0.107 arcsec defocus: -0.00369 mm Estimated x pointing error is -1.273 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.01 arcsec (used 15.9 arcsec) Estimated defocus error is 2.986 mm (used 2.99 mm) Fitting frequency 8 Minimiser fit code = 3 piston: -0.391 radians x offset: 0.0442 arcsec y offset: 0.0676 arcsec defocus: -0.00629 mm Estimated x pointing error is -1.256 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.97 arcsec (used 15.9 arcsec) Estimated defocus error is 2.984 mm (used 2.99 mm) Fitting frequency 9 Minimiser fit code = 3 piston: -0.38 radians x offset: 0.0836 arcsec y offset: 0.0468 arcsec defocus: -0.00909 mm Estimated x pointing error is -1.216 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.95 arcsec (used 15.9 arcsec) Estimated defocus error is 2.981 mm (used 2.99 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.369 radians x offset: 0.064 arcsec y offset: 0.0427 arcsec defocus: -0.0129 mm Estimated x pointing error is -1.236 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.94 arcsec (used 15.9 arcsec) Estimated defocus error is 2.977 mm (used 2.99 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.362 radians x offset: 0.103 arcsec y offset: 0.0519 arcsec defocus: -0.0165 mm Estimated x pointing error is -1.197 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.95 arcsec (used 15.9 arcsec) Estimated defocus error is 2.974 mm (used 2.99 mm) Fitting frequency 12 Minimiser fit code = 3 piston: -0.352 radians x offset: 0.0637 arcsec y offset: 0.0542 arcsec defocus: -0.0158 mm Estimated x pointing error is -1.236 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.95 arcsec (used 15.9 arcsec) Estimated defocus error is 2.974 mm (used 2.99 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.346 radians x offset: 0.0957 arcsec y offset: 0.0839 arcsec defocus: -0.015 mm Estimated x pointing error is -1.204 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.98 arcsec (used 15.9 arcsec) Estimated defocus error is 2.975 mm (used 2.99 mm) Fitting frequency 14 Minimiser fit code = 3 piston: -0.342 radians x offset: 0.103 arcsec y offset: 0.0878 arcsec defocus: -0.0115 mm Estimated x pointing error is -1.197 arcsec (used -1.3 arcsec) Estimated y pointing error is 15.99 arcsec (used 15.9 arcsec) Estimated defocus error is 2.979 mm (used 2.99 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.339 radians x offset: 0.126 arcsec y offset: 0.111 arcsec defocus: -0.01 mm Estimated x pointing error is -1.174 arcsec (used -1.3 arcsec) Estimated y pointing error is 16.01 arcsec (used 15.9 arcsec) Estimated defocus error is 2.98 mm (used 2.99 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 0.00128 piston 1 1 -0.00411 tilt_x 1 -1 -0.00180 tilt_y 2 2 -0.03256 astigmatism_0 2 0 0.00509 curvature 2 -2 0.04490 astigmatism45 3 3 -0.03647 trefoil_0 3 1 -0.01037 coma_x 3 -1 -0.01588 coma_y 3 -3 0.01189 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 0.00126 piston 1 1 -0.00320 tilt_x 1 -1 -0.00045 tilt_y 2 2 -0.03393 astigmatism_0 2 0 0.00529 curvature 2 -2 0.04850 astigmatism45 3 3 -0.03706 trefoil_0 3 1 -0.00716 coma_x 3 -1 -0.01267 coma_y 3 -3 0.01450 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 0.00121 piston 1 1 -0.00230 tilt_x 1 -1 0.00069 tilt_y 2 2 -0.03210 astigmatism_0 2 0 0.00528 curvature 2 -2 0.04913 astigmatism45 3 3 -0.03737 trefoil_0 3 1 -0.00507 coma_x 3 -1 -0.00942 coma_y 3 -3 0.01361 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 0.00112 piston 1 1 -0.00185 tilt_x 1 -1 0.00149 tilt_y 2 2 -0.03195 astigmatism_0 2 0 0.00505 curvature 2 -2 0.05061 astigmatism45 3 3 -0.03618 trefoil_0 3 1 -0.00357 coma_x 3 -1 -0.00792 coma_y 3 -3 0.01240 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 0.00104 piston 1 1 -0.00252 tilt_x 1 -1 0.00176 tilt_y 2 2 -0.02943 astigmatism_0 2 0 0.00469 curvature 2 -2 0.04901 astigmatism45 3 3 -0.03573 trefoil_0 3 1 -0.00590 coma_x 3 -1 -0.00687 coma_y 3 -3 0.01344 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 0.00097 piston 1 1 -0.00287 tilt_x 1 -1 0.00082 tilt_y 2 2 -0.03080 astigmatism_0 2 0 0.00422 curvature 2 -2 0.04920 astigmatism45 3 3 -0.03663 trefoil_0 3 1 -0.00678 coma_x 3 -1 -0.01016 coma_y 3 -3 0.01260 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 0.00090 piston 1 1 -0.00364 tilt_x 1 -1 0.00011 tilt_y 2 2 -0.02993 astigmatism_0 2 0 0.00392 curvature 2 -2 0.04815 astigmatism45 3 3 -0.03782 trefoil_0 3 1 -0.00917 coma_x 3 -1 -0.01190 coma_y 3 -3 0.01205 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 0.00094 piston 1 1 -0.00364 tilt_x 1 -1 -0.00031 tilt_y 2 2 -0.03142 astigmatism_0 2 0 0.00402 curvature 2 -2 0.04767 astigmatism45 3 3 -0.03798 trefoil_0 3 1 -0.00896 coma_x 3 -1 -0.01325 coma_y 3 -3 0.01307 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 0.00099 piston 1 1 -0.00396 tilt_x 1 -1 -0.00174 tilt_y 2 2 -0.03002 astigmatism_0 2 0 0.00402 curvature 2 -2 0.04495 astigmatism45 3 3 -0.03912 trefoil_0 3 1 -0.01019 coma_x 3 -1 -0.01660 coma_y 3 -3 0.01257 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 0.00106 piston 1 1 -0.00398 tilt_x 1 -1 -0.00137 tilt_y 2 2 -0.03128 astigmatism_0 2 0 0.00429 curvature 2 -2 0.04516 astigmatism45 3 3 -0.04156 trefoil_0 3 1 -0.01008 coma_x 3 -1 -0.01528 coma_y 3 -3 0.01515 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 0.00113 piston 1 1 -0.00422 tilt_x 1 -1 -0.00178 tilt_y 2 2 -0.03059 astigmatism_0 2 0 0.00443 curvature 2 -2 0.04526 astigmatism45 3 3 -0.04300 trefoil_0 3 1 -0.01145 coma_x 3 -1 -0.01610 coma_y 3 -3 0.01409 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 0.00110 piston 1 1 -0.00414 tilt_x 1 -1 -0.00125 tilt_y 2 2 -0.03020 astigmatism_0 2 0 0.00443 curvature 2 -2 0.04581 astigmatism45 3 3 -0.04171 trefoil_0 3 1 -0.01099 coma_x 3 -1 -0.01465 coma_y 3 -3 0.01363 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 0.00108 piston 1 1 -0.00422 tilt_x 1 -1 -0.00006 tilt_y 2 2 -0.02748 astigmatism_0 2 0 0.00459 curvature 2 -2 0.04652 astigmatism45 3 3 -0.04071 trefoil_0 3 1 -0.01167 coma_x 3 -1 -0.01109 coma_y 3 -3 0.01310 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 0.00107 piston 1 1 -0.00440 tilt_x 1 -1 0.00100 tilt_y 2 2 -0.02656 astigmatism_0 2 0 0.00460 curvature 2 -2 0.04621 astigmatism45 3 3 -0.03992 trefoil_0 3 1 -0.01205 coma_x 3 -1 -0.00817 coma_y 3 -3 0.01284 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 0.00110 piston 1 1 -0.00472 tilt_x 1 -1 0.00211 tilt_y 2 2 -0.02745 astigmatism_0 2 0 0.00477 curvature 2 -2 0.04570 astigmatism45 3 3 -0.03827 trefoil_0 3 1 -0.01278 coma_x 3 -1 -0.00496 coma_y 3 -3 0.01138 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 0.00116 piston 1 1 -0.00382 tilt_x 1 -1 0.00250 tilt_y 2 2 -0.02950 astigmatism_0 2 0 0.00501 curvature 2 -2 0.04502 astigmatism45 3 3 -0.03987 trefoil_0 3 1 -0.00975 coma_x 3 -1 -0.00381 coma_y 3 -3 0.01120 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: 35.3 28.9 22.6 27.8 28.5 30.3 42.7 33.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35.4 29.1 22.8 28.1 27.9 28.8 39.3 32.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.11 2.27 3.39 4.76 6.52 8.99 12.6 8.16 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.9 27.8 21.9 27.3 28.3 30.5 43.3 33.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35 28 22.1 27.5 27.6 28.6 40 32.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.87 1.91 3.11 4.75 6.82 9.52 13.2 8.5 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.6 27.4 21.2 26.8 28.7 30.4 43.6 33.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 34.7 27.6 21.3 27 28.1 28.7 40.3 32.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.662 1.59 2.82 4.55 6.73 9.45 13 8.36 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.9 27.7 20.6 26.6 28.3 29.8 44 33.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35 28 20.7 26.8 27.7 28.2 40.9 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.56 1.46 2.73 4.54 6.77 9.51 12.9 8.36 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.9 27.4 20.9 26.4 27.9 29.7 44.3 33.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.9 27.6 21 26.6 27.4 28.4 41.2 31.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.572 1.45 2.67 4.4 6.53 9.17 12.5 8.08 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.8 28.1 21.8 26.7 27.9 29.8 44.5 33.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.9 28.3 21.9 26.9 27.2 28.7 41.1 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.74 1.7 2.9 4.57 6.66 9.31 12.8 8.25 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 33.6 28.6 22.2 27 28 29.8 44.2 33.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 33.7 28.8 22.3 27.2 27.4 28.7 40.7 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.89 1.92 3.08 4.65 6.61 9.2 12.7 8.22 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 32.1 28.9 22.6 27.1 28.1 29.7 44 33.3 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32.2 29.1 22.7 27.4 27.4 28.4 40.5 31.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.945 2.01 3.17 4.72 6.67 9.28 12.9 8.31 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.9 29.4 22.5 27.1 27.9 29.7 44.3 33.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 31.1 29.6 22.7 27.2 27.5 28.4 40.9 32 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.14 2.3 3.41 4.77 6.5 8.98 12.6 8.16 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 30.8 30.3 21.8 29.2 28.5 29.7 43.8 33.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 30.9 30.5 22 29.4 27.9 28 40.5 32.3 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.07 2.2 3.34 4.79 6.65 9.28 13.1 8.4 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 31.8 31 21.8 29.6 28.3 29.9 43.9 33.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 32 31.2 22.1 29.8 27.9 28.1 40.4 32.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.15 2.34 3.47 4.88 6.7 9.31 13.2 8.47 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.4 30.9 22.8 29.6 29.1 30 43.3 34.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 34.5 31.1 23.1 29.9 28.5 28.1 40.2 32.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.07 2.2 3.34 4.79 6.64 9.25 13 8.37 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 35.1 30.4 23 29.2 28.6 30.6 42.8 34.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35.2 30.6 23.2 29.4 28.2 28.7 39.7 32.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.946 1.99 3.12 4.62 6.5 9.07 12.7 8.17 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 35.9 29.6 23 27.8 28.7 30.3 42.4 33.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 36 29.8 23.1 28 28.1 28.5 39.5 32.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.86 1.85 2.97 4.49 6.39 8.93 12.5 8.01 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 35.8 28.7 22.4 26.9 28.4 30.3 42.7 33.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35.9 28.8 22.5 27.1 27.9 28.6 39.8 32.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.813 1.77 2.88 4.41 6.3 8.81 12.2 7.88 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 35.2 28.2 21.9 26 28.2 30.3 42.8 33.5 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35.2 28.3 22 26.3 27.6 28.8 39.9 32.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 0.64 1.51 2.66 4.29 6.34 8.96 12.4 7.96 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 30.7 27.9 19.9 25.1 26.8 28.3 41.6 31.8 Mean deviation is 1.8060182578168877 microns Taper = 10 dB, Ruze illumination-weighted rms = 31.1 micron Estimating beam: f = 650GHz Taper = 12dB defocus = 0mm Sigma = 4.51193 (Taper = 12 dB) Added 0.0 of Zernike 4 0 (name=spherical_aberration, index = 12) Added 0.0 of Zernike 3 3 (name=trefoil_0, index = 6) f = 650 GHz Ruze rms = 28.5 micron Centre pixel: 64.0 64.0 Value = 2532.41 (estimate), 3426.12 (perfect) Strehl = 0.546341 Strehl ratio estimate = 0.5463 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 = 27.7 micron Centre pixel: 64.0 64.0 Value = 1984.66 (estimate), 3426.12 (perfect) Strehl = 0.335557 Strehl ratio estimate = 0.3356 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.15028 metres panel scale = 3.00000 metres mean frequency = 80.35300 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 51.2 20.7 -10.0 56.1 2 1 2 68.6 0.7 37.5 78.2 3 1 3 93.5 -0.4 13.6 94.5 4 1 4 92.1 25.9 -1.5 95.7 5 1 5 9.3 6.8 65.0 66.0 6 1 6 61.2 17.3 20.4 66.8 7 1 7 9.2 23.0 -1.9 24.8 8 1 8 21.4 37.2 61.1 74.6 9 1 9 -1.9 16.8 30.6 35.0 10 1 10 71.1 40.4 25.1 85.6 11 1 11 83.2 64.8 32.5 110.3 12 1 12 82.1 14.8 28.3 88.1 13 2 1 50.7 -29.0 -29.7 65.5 14 2 2 43.1 -39.7 -31.8 66.7 15 2 3 54.7 -21.6 -46.8 75.2 16 2 4 20.7 -30.4 -15.2 39.8 17 2 5 63.5 -19.3 6.3 66.7 18 2 6 51.3 -0.7 14.4 53.3 19 2 7 7.5 -17.6 -4.9 19.7 20 2 8 76.2 -36.4 -45.1 95.7 21 2 9 31.5 -26.7 -10.3 42.6 22 2 10 -5.1 -9.7 17.3 20.5 23 2 11 0.9 -15.7 -0.3 15.7 24 2 12 -2.7 -37.4 -47.2 60.3 25 2 13 6.0 7.9 -19.8 22.2 26 2 14 2.9 -56.8 -4.1 57.0 27 2 15 28.5 -2.2 -35.2 45.3 28 2 16 -2.1 14.7 -9.1 17.4 29 2 17 19.8 -20.3 -21.6 35.6 30 2 18 55.4 -7.2 -29.7 63.3 31 2 19 3.3 -4.4 -35.1 35.5 32 2 20 59.8 -49.5 -23.2 81.0 33 2 21 60.5 6.1 -41.4 73.6 34 2 22 9.2 -67.3 -78.4 103.7 35 2 23 86.2 -31.5 -12.9 92.7 36 2 24 57.5 -35.8 -45.9 81.9 37 3 1 -2.6 9.0 -24.5 26.2 38 3 2 -8.7 14.9 -30.6 35.1 39 3 3 2.1 16.1 -42.5 45.5 40 3 4 0.9 5.3 -19.6 20.3 41 3 5 -22.4 2.7 -47.1 52.2 42 3 6 -21.7 3.7 -28.3 35.8 43 3 7 -9.1 1.5 -52.2 53.0 44 3 8 0.1 -0.0 -34.1 34.1 45 3 9 12.7 -8.6 -51.4 53.6 46 3 10 17.4 11.9 -27.0 34.3 47 3 11 -5.0 5.1 -43.1 43.7 48 3 12 1.8 22.4 -26.3 34.6 49 3 13 -31.5 11.3 -30.3 45.2 50 3 14 -5.6 4.1 -42.6 43.2 51 3 15 -15.2 3.7 -16.9 23.0 52 3 16 -4.1 9.4 -26.6 28.5 53 3 17 22.1 4.6 -29.4 37.1 54 3 18 12.8 23.3 -9.6 28.2 55 3 19 18.1 17.3 -57.4 62.6 56 3 20 -30.3 -0.7 -15.6 34.1 57 3 21 -19.2 0.4 -47.2 51.0 58 3 22 -8.0 5.6 -8.2 12.8 59 3 23 -35.3 7.2 -27.6 45.4 60 3 24 -5.1 -6.6 -32.8 33.8 61 3 25 -18.2 -7.9 -15.8 25.4 62 3 26 -40.5 8.6 8.6 42.3 63 3 27 -42.5 5.0 -22.2 48.2 64 3 28 -5.4 4.4 -48.7 49.2 65 3 29 -12.6 -3.9 -7.3 15.0 66 3 30 8.2 5.9 -34.1 35.6 67 3 31 -20.7 22.1 -10.3 32.0 68 3 32 -18.5 -9.4 -33.4 39.3 69 3 33 -13.0 12.4 -9.7 20.4 70 3 34 17.9 4.3 -6.2 19.4 71 3 35 19.3 14.9 -59.0 63.8 72 3 36 42.1 11.7 -25.4 50.6 73 3 37 -30.1 10.7 -74.3 80.9 74 3 38 -21.8 20.6 -46.1 55.0 75 3 39 12.8 9.8 -47.8 50.5 76 3 40 4.1 7.1 -65.8 66.3 77 3 41 7.5 2.5 -28.0 29.1 78 3 42 5.0 18.4 -25.9 32.2 79 3 43 -7.8 19.4 -22.4 30.6 80 3 44 40.6 10.3 -13.8 44.1 81 3 45 20.2 16.2 -47.7 54.2 82 3 46 12.9 21.0 -37.0 44.5 83 3 47 -34.1 8.8 -30.2 46.4 84 3 48 12.4 6.3 -45.1 47.2 85 4 1 16.5 -14.5 6.1 22.8 86 4 2 7.8 -16.2 -85.2 87.1 87 4 3 -22.5 -7.7 -70.6 74.5 88 4 4 0.5 5.5 -106.2 106.4 89 4 5 9.3 8.1 -54.0 55.4 90 4 6 -0.9 7.8 -43.5 44.3 91 4 7 -3.5 1.5 -20.3 20.6 92 4 8 -31.2 6.3 -50.6 59.8 93 4 9 -25.9 -0.6 -41.3 48.7 94 4 10 -44.9 10.8 -62.7 77.9 95 4 11 -25.4 -4.3 -54.8 60.6 96 4 12 -46.6 8.4 -42.9 63.9 97 4 13 -35.4 -5.8 22.2 42.2 98 4 14 -7.0 11.8 -27.9 31.1 99 4 15 -40.2 -12.5 -29.4 51.3 100 4 16 -57.8 24.5 -28.5 68.9 101 4 17 -24.0 10.3 -45.4 52.4 102 4 18 8.1 2.8 -9.0 12.4 103 4 19 -31.5 -4.9 -38.2 49.7 104 4 20 -8.9 -2.5 -43.1 44.0 105 4 21 -16.0 -12.2 -10.6 22.8 106 4 22 -94.3 -5.5 35.7 101.0 107 4 23 -52.6 -26.8 4.3 59.2 108 4 24 -40.2 11.5 34.0 53.9 109 4 25 -64.8 14.8 34.1 74.7 110 4 26 -30.6 -7.6 -8.4 32.6 111 4 27 -37.4 -1.7 20.5 42.7 112 4 28 -36.1 -24.4 5.9 44.0 113 4 29 -45.2 -11.1 -82.6 94.8 114 4 30 -40.6 -3.6 -2.5 40.8 115 4 31 -48.7 0.3 -30.6 57.5 116 4 32 -44.3 2.7 -26.9 51.9 117 4 33 -43.3 25.9 16.0 52.9 118 4 34 -4.4 -18.3 -25.5 31.7 119 4 35 -40.1 16.7 -71.8 83.9 120 4 36 -62.4 7.1 -87.5 107.7 121 4 37 -18.9 21.3 -29.3 40.8 122 4 38 -10.1 -13.9 -49.0 51.9 123 4 39 -26.1 14.6 -22.4 37.4 124 4 40 -14.6 -3.2 -32.5 35.8 125 4 41 -24.7 41.1 -34.3 58.9 126 4 42 -9.4 11.0 -59.6 61.4 127 4 43 -29.0 3.7 -69.5 75.4 128 4 44 7.0 16.4 -44.7 48.1 129 4 45 9.2 10.0 -74.4 75.7 130 4 46 -29.1 -10.3 -75.4 81.5 131 4 47 -0.2 -24.0 -157.0 158.9 132 4 48 -26.9 -18.4 -24.6 40.8 133 5 1 16.6 44.9 -11.1 49.1 134 5 2 34.7 39.8 -36.5 64.2 135 5 3 -25.7 52.8 -32.1 66.9 136 5 4 -15.0 2.8 -28.0 31.9 137 5 5 -27.1 -2.1 -77.1 81.8 138 5 6 -13.9 8.1 -68.7 70.6 139 5 7 -9.5 38.7 -21.0 45.0 140 5 8 -10.4 32.7 -58.9 68.2 141 5 9 -4.7 12.2 -41.8 43.8 142 5 10 -31.5 36.1 -27.7 55.4 143 5 11 -14.3 6.6 -20.7 26.0 144 5 12 -37.4 40.0 -39.0 67.2 145 5 13 -21.4 14.8 -39.7 47.4 146 5 14 -24.0 40.8 -42.0 63.3 147 5 15 -1.3 30.0 0.3 30.0 148 5 16 -14.1 32.6 -28.8 45.7 149 5 17 -9.9 29.7 55.1 63.4 150 5 18 -0.1 3.7 175.6 175.6 151 5 19 -13.1 4.5 -27.7 31.0 152 5 20 -28.8 1.7 -28.0 40.2 153 5 21 -6.9 26.5 14.9 31.2 154 5 22 -8.9 44.6 29.1 54.0 155 5 23 -11.1 30.2 10.4 33.8 156 5 24 43.7 20.3 21.6 52.8 157 5 25 38.4 22.3 1.0 44.4 158 5 26 -4.4 25.4 -7.6 26.9 159 5 27 21.8 58.6 -46.0 77.6 160 5 28 4.6 6.1 4.8 9.0 161 5 29 13.4 11.6 -26.2 31.6 162 5 30 -14.8 -14.5 40.8 45.7 163 5 31 -11.5 -5.0 -38.8 40.8 164 5 32 -44.2 -25.2 -14.4 52.9 165 5 33 13.1 15.2 -11.0 22.9 166 5 34 -19.6 2.3 23.5 30.7 167 5 35 -9.1 31.3 -17.1 36.8 168 5 36 -45.0 4.4 -47.3 65.5 169 5 37 11.0 44.2 -46.1 64.8 170 5 38 -15.4 -7.6 -39.7 43.3 171 5 39 -11.5 95.6 -76.3 122.9 172 5 40 -37.5 21.8 -54.1 69.4 173 5 41 23.1 50.6 -27.2 61.9 174 5 42 -28.1 -4.6 -64.0 70.1 175 5 43 -31.3 6.5 -62.4 70.1 176 5 44 -8.6 22.6 -60.1 64.8 177 5 45 17.8 36.1 -48.1 62.7 178 5 46 -3.5 39.5 21.7 45.2 179 5 47 25.6 22.4 -62.0 70.7 180 5 48 -0.5 48.6 -42.2 64.3 181 6 1 6.4 22.3 -37.1 43.8 182 6 2 2.6 23.0 -62.5 66.7 183 6 3 -2.3 16.6 -48.0 50.9 184 6 4 -41.0 23.0 -88.3 100.1 185 6 5 -29.0 6.2 -60.7 67.5 186 6 6 -14.4 11.7 -62.3 65.0 187 6 7 -17.5 -3.5 -84.3 86.2 188 6 8 -27.0 -2.4 -49.1 56.1 189 6 9 -29.9 -23.6 -87.5 95.5 190 6 10 -9.0 8.8 -28.6 31.2 191 6 11 3.6 0.6 -52.1 52.2 192 6 12 -24.7 2.8 -51.5 57.2 193 6 13 -8.0 9.4 -61.5 62.8 194 6 14 -27.6 14.7 -58.7 66.5 195 6 15 4.3 -15.3 -29.6 33.6 196 6 16 -32.5 26.5 -34.1 54.0 197 6 17 -39.2 -9.7 -19.9 45.0 198 6 18 -17.8 29.9 -101.8 107.6 199 6 19 34.4 8.9 37.7 51.8 200 6 20 2.2 47.9 81.7 94.7 201 6 21 -40.0 33.2 -72.9 89.5 202 6 22 36.7 37.0 22.4 56.7 203 6 23 11.4 29.9 88.2 93.8 204 6 24 -11.4 20.4 27.3 35.9 205 6 25 -52.9 19.2 -47.5 73.7 206 6 26 -37.0 -17.9 -12.1 42.8 207 6 27 -62.6 -19.9 -49.1 82.0 208 6 28 -15.2 -2.9 2.0 15.6 209 6 29 -64.2 24.6 -63.5 93.6 210 6 30 -37.1 23.0 29.4 52.6 211 6 31 -26.6 27.5 6.0 38.8 212 6 32 -54.1 -54.4 31.7 83.0 213 6 33 -18.0 10.0 144.2 145.7 214 6 34 70.0 16.6 14.5 73.4 215 6 35 -18.3 23.7 4.7 30.3 216 6 36 -27.1 26.0 23.6 44.3 217 6 37 -6.1 39.7 32.3 51.6 218 6 38 -0.5 3.7 -15.8 16.2 219 6 39 39.5 25.9 7.9 47.9 220 6 40 -5.9 34.6 -57.4 67.3 221 6 41 -22.8 20.6 -35.9 47.3 222 6 42 10.3 17.7 -4.4 21.0 223 6 43 -24.2 13.2 22.1 35.4 224 6 44 -23.2 24.5 -11.3 35.6 225 6 45 -26.2 54.3 -17.1 62.6 226 6 46 11.4 41.8 0.7 43.3 227 6 47 -8.7 14.8 -44.7 47.9 228 6 48 -5.2 30.0 -20.3 36.6 229 7 1 -8.8 103.2 36.8 109.9 230 7 2 -39.8 55.7 2.3 68.5 231 7 3 -26.2 63.8 17.4 71.1 232 7 4 10.9 37.6 62.5 73.8 233 7 5 -28.9 5.2 3.8 29.6 234 7 6 -30.2 38.4 -15.9 51.4 235 7 7 -41.7 18.7 -33.8 56.8 236 7 8 -18.9 -1.4 -34.6 39.5 237 7 9 17.1 -104.4 65.0 124.1 238 7 10 -11.1 26.4 -32.7 43.4 239 7 11 -3.5 -7.8 -43.0 43.9 240 7 12 -1.6 25.3 14.1 29.0 241 7 13 -48.4 13.6 -25.9 56.5 242 7 14 -21.0 30.7 -12.8 39.3 243 7 15 -15.5 -10.6 -14.1 23.5 244 7 16 25.0 -82.1 25.2 89.4 245 7 17 17.0 -18.3 47.5 53.7 246 7 18 5.6 72.3 1.1 72.6 247 7 19 50.1 41.0 76.8 100.5 248 7 20 34.9 -0.9 52.4 62.9 249 7 21 76.8 11.1 117.8 141.0 250 7 22 4.3 -19.5 34.3 39.7 251 7 23 62.6 43.4 30.5 82.0 252 7 24 -1.5 38.3 52.7 65.2 253 7 25 -59.3 29.9 -0.2 66.4 254 7 26 -13.7 24.4 -23.0 36.2 255 7 27 2.0 13.9 -54.8 56.5 256 7 28 -37.4 -90.9 262.9 280.7 257 7 29 -23.5 3.1 -30.5 38.7 258 7 30 -40.1 -54.9 -43.0 80.5 259 7 31 -48.8 -29.2 -88.7 105.4 260 7 32 5.9 -19.0 -77.1 79.6 261 7 33 -26.9 -394.8 115.2 412.1 262 7 34 28.3 -13.1 -55.5 63.7 263 7 35 10.8 46.8 -21.8 52.7 264 7 36 14.3 20.9 -6.2 26.1 265 7 37 11.8 54.9 -1.8 56.2 266 7 38 14.8 9.9 -20.1 26.8 267 7 39 73.9 62.6 -41.4 105.3 268 7 40 65.5 -12.8 17.5 69.0 269 7 41 14.4 21.2 -2.0 25.7 270 7 42 30.6 18.9 -38.4 52.6 271 7 43 -40.2 65.2 -73.2 105.9 272 7 44 8.7 35.1 -20.4 41.5 273 7 45 19.9 -25.2 60.6 68.5 274 7 46 31.2 67.1 13.2 75.1 275 7 47 50.8 89.0 -19.5 104.3 276 7 48 42.1 220.3 38.3 227.6 Creating sector-motor-move file sector motor steps 1 1 19 1 2 11 1 3 3 1 4 -27 1 5 7 1 6 -12 1 7 5 1 8 19 1 9 -8 1 10 -14 1 11 5 1 12 0 1 13 0 1 14 17 1 15 -12 1 16 -19 1 17 7 1 18 0 1 19 11 1 20 31 1 21 -2 1 22 -11 1 23 6 1 24 1 1 25 -8 1 26 0 1 27 -4 1 28 -32 1 29 1 1 30 0 1 31 -9 1 32 16 1 33 -7 1 34 -21 1 35 -2 1 36 -6 1 37 -11 1 38 12 1 39 10 1 40 -26 1 41 -4 1 42 2 1 43 -3 1 44 13 1 45 5 1 46 1 1 47 -4 1 48 5 1 49 -13 1 50 4 1 51 0 1 52 -9 1 53 -12 1 54 13 1 55 -9 1 56 4 1 57 -2 1 58 6 1 59 15 1 60 -3 1 61 -7 1 62 2 1 63 0 1 64 -6 1 65 15 1 66 -9 1 67 -6 1 68 1 1 69 0 2 1 -10 2 2 0 2 3 -5 2 4 -15 2 5 0 2 6 -8 2 7 -10 2 8 5 2 9 -12 2 10 -25 2 11 -1 2 12 -5 2 13 -4 2 14 11 2 15 -9 2 16 -19 2 17 3 2 18 -4 2 19 1 2 20 1 2 21 -8 2 22 -18 2 23 1 2 24 -8 2 25 -18 2 26 10 2 27 -3 2 28 -15 2 29 1 2 30 -9 2 31 -6 2 32 11 2 33 -2 2 34 -6 2 35 0 2 36 -1 2 37 -21 2 38 2 2 39 -4 2 40 -13 2 41 2 2 42 0 2 43 -23 2 44 0 2 45 -8 2 46 -16 2 47 2 2 48 2 2 49 -16 2 50 0 2 51 -2 2 52 -4 2 53 -9 2 54 6 2 55 -8 2 56 1 2 57 -6 2 58 0 2 59 21 2 60 11 2 61 -14 2 62 0 2 63 -6 2 64 -5 2 65 16 2 66 -14 2 67 -10 2 68 0 2 69 0 3 1 4 3 2 7 3 3 0 3 4 -15 3 5 0 3 6 -7 3 7 -13 3 8 -2 3 9 -1 3 10 -15 3 11 0 3 12 1 3 13 -10 3 14 8 3 15 -3 3 16 -8 3 17 2 3 18 -2 3 19 19 3 20 -32 3 21 5 3 22 -26 3 23 -7 3 24 -9 3 25 -11 3 26 12 3 27 -11 3 28 -13 3 29 2 3 30 -14 3 31 -6 3 32 2 3 33 -4 3 34 -16 3 35 -1 3 36 -7 3 37 -8 3 38 11 3 39 -9 3 40 -19 3 41 3 3 42 -13 3 43 -12 3 44 3 3 45 -1 3 46 -12 3 47 0 3 48 -7 3 49 -13 3 50 1 3 51 -1 3 52 4 3 53 0 3 54 15 3 55 -8 3 56 3 3 57 5 3 58 0 3 59 28 3 60 4 3 61 -15 3 62 -2 3 63 3 3 64 -5 3 65 19 3 66 1 3 67 -8 3 68 6 3 69 0 4 1 7 4 2 -25 4 3 7 4 4 -10 4 5 8 4 6 -9 4 7 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0 5 69 -9 6 1 16 6 2 11 6 3 0 6 4 8 6 5 6 6 6 -3 6 7 9 6 8 13 6 9 19 6 10 27 6 11 9 6 12 3 6 13 10 6 14 -5 6 15 1 6 16 6 6 17 11 6 18 11 6 19 36 6 20 3 6 21 23 6 22 -22 6 23 10 6 24 -12 6 25 6 6 26 6 6 27 13 6 28 10 6 29 3 6 30 -12 6 31 3 6 32 9 6 33 -3 6 34 1 6 35 -8 6 36 -16 6 37 8 6 38 13 6 39 -2 6 40 10 6 41 -1 6 42 -28 6 43 4 6 44 8 6 45 -2 6 46 -3 6 47 -3 6 48 -4 6 49 -8 6 50 2 6 51 -10 6 52 -14 6 53 -11 6 54 0 6 55 -2 6 56 1 6 57 -2 6 58 5 6 59 18 6 60 6 6 61 -14 6 62 0 6 63 -5 6 64 2 6 65 0 6 66 0 6 67 -10 6 68 -2 6 69 -1 7 1 80 7 2 -27 7 3 -11 7 4 0 7 5 0 7 6 -4 7 7 -16 7 8 4 7 9 0 7 10 -15 7 11 -6 7 12 -19 7 13 -7 7 14 7 7 15 -4 7 16 -3 7 17 -5 7 18 -11 7 19 0 7 20 9 7 21 -18 7 22 -14 7 23 5 7 24 -16 7 25 1 7 26 1 7 27 1 7 28 1 7 29 -7 7 30 -11 7 31 -14 7 32 17 7 33 6 7 34 6 7 35 0 7 36 -11 7 37 -2 7 38 7 7 39 -1 7 40 -2 7 41 -2 7 42 -9 7 43 0 7 44 6 7 45 11 7 46 10 7 47 4 7 48 -19 7 49 -6 7 50 1 7 51 -13 7 52 -1 7 53 -17 7 54 0 7 55 2 7 56 2 7 57 -12 7 58 7 7 59 2 7 60 0 7 61 -4 7 62 -2 7 63 -5 7 64 0 7 65 1 7 66 -6 7 67 -14 7 68 1 7 69 -1 8 1 -23 8 2 -5 8 3 1 8 4 9 8 5 -16 8 6 -16 8 7 -27 8 8 -8 8 9 -14 8 10 1 8 11 8 8 12 -8 8 13 -13 8 14 -16 8 15 -12 8 16 9 8 17 7 8 18 -11 8 19 -9 8 20 0 8 21 -7 8 22 -19 8 23 7 8 24 -19 8 25 -4 8 26 -7 8 27 -13 8 28 -8 8 29 0 8 30 -13 8 31 -11 8 32 -1 8 33 -3 8 34 -9 8 35 0 8 36 -14 8 37 12 8 38 -4 8 39 -4 8 40 0 8 41 -1 8 42 -12 8 43 -8 8 44 3 8 45 4 8 46 -25 8 47 -3 8 48 -13 8 49 -3 8 50 6 8 51 -6 8 52 -2 8 53 4 8 54 0 8 55 -10 8 56 1 8 57 2 8 58 11 8 59 6 8 60 18 8 61 -2 8 62 -1 8 63 -3 8 64 -6 8 65 8 8 66 -10 8 67 -10 8 68 -2 8 69 -5 9 1 -1 9 2 6 9 3 4 9 4 7 9 5 7 9 6 -8 9 7 -6 9 8 14 9 9 3 9 10 1 9 11 7 9 12 -5 9 13 -17 9 14 -4 9 15 8 9 16 4 9 17 5 9 18 21 9 19 35 9 20 -100 9 21 -8 9 22 44 9 23 3 9 24 -5 9 25 -14 9 26 1 9 27 -13 9 28 -26 9 29 2 9 30 -19 9 31 -5 9 32 9 9 33 -2 9 34 -22 9 35 5 9 36 -12 9 37 7 9 38 0 9 39 -6 9 40 -7 9 41 -5 9 42 -1 9 43 -3 9 44 4 9 45 4 9 46 4 9 47 7 9 48 -13 9 49 -18 9 50 4 9 51 5 9 52 -9 9 53 -2 9 54 16 9 55 -1 9 56 1 9 57 5 9 58 5 9 59 0 9 60 9 9 61 -2 9 62 3 9 63 -3 9 64 -1 9 65 6 9 66 -6 9 67 -7 9 68 3 9 69 12 10 1 5 10 2 -3 10 3 20 10 4 -17 10 5 10 10 6 -1 10 7 -12 10 8 19 10 9 22 10 10 2 10 11 7 10 12 12 10 13 -6 10 14 3 10 15 4 10 16 -4 10 17 1 10 18 0 10 19 0 10 20 16 10 21 3 10 22 9 10 23 12 10 24 -1 10 25 -16 10 26 6 10 27 -11 10 28 -9 10 29 0 10 30 -4 10 31 -23 10 32 29 10 33 -3 10 34 -6 10 35 4 10 36 -7 10 37 -12 10 38 -2 10 39 -4 10 40 -15 10 41 -4 10 42 -3 10 43 -14 10 44 13 10 45 3 10 46 -8 10 47 6 10 48 -5 10 49 -14 10 50 2 10 51 3 10 52 -7 10 53 -15 10 54 18 10 55 -14 10 56 6 10 57 -6 10 58 12 10 59 21 10 60 7 10 61 -22 10 62 3 10 63 -9 10 64 1 10 65 1 10 66 -10 10 67 -20 10 68 2 10 69 1 11 1 -6 11 2 10 11 3 2 11 4 -3 11 5 7 11 6 -7 11 7 -22 11 8 19 11 9 -12 11 10 6 11 11 4 11 12 -7 11 13 -11 11 14 5 11 15 9 11 16 -1 11 17 5 11 18 3 11 19 0 11 20 6 11 21 4 11 22 -11 11 23 6 11 24 -6 11 25 -18 11 26 6 11 27 -2 11 28 -13 11 29 5 11 30 2 11 31 -19 11 32 2 11 33 -9 11 34 -21 11 35 1 11 36 -8 11 37 -19 11 38 -1 11 39 -8 11 40 -18 11 41 3 11 42 -2 11 43 -8 11 44 15 11 45 7 11 46 -10 11 47 12 11 48 -7 11 49 -6 11 50 5 11 51 -2 11 52 -24 11 53 -20 11 54 2 11 55 -7 11 56 5 11 57 1 11 58 19 11 59 25 11 60 9 11 61 -8 11 62 0 11 63 2 11 64 -9 11 65 18 11 66 -12 11 67 -4 11 68 3 11 69 12 12 1 11 12 2 67 12 3 12 12 4 -6 12 5 9 12 6 -1 12 7 -5 12 8 27 12 9 15 12 10 -13 12 11 4 12 12 -2 12 13 4 12 14 20 12 15 9 12 16 0 12 17 12 12 18 3 12 19 18 12 20 -7 12 21 6 12 22 -5 12 23 16 12 24 -8 12 25 -12 12 26 14 12 27 0 12 28 -7 12 29 -5 12 30 -8 12 31 -19 12 32 6 12 33 7 12 34 -48 12 35 -7 12 36 0 12 37 6 12 38 12 12 39 -1 12 40 -23 12 41 -3 12 42 -8 12 43 -14 12 44 11 12 45 5 12 46 -22 12 47 3 12 48 2 12 49 -9 12 50 2 12 51 -10 12 52 -14 12 53 -10 12 54 17 12 55 -11 12 56 6 12 57 3 12 58 4 12 59 25 12 60 8 12 61 -14 12 62 4 12 63 6 12 64 -8 12 65 26 12 66 -3 12 67 -13 12 68 1 12 69 3 !!!Warning!!! Truncated 1 recommended moves exceeding 100 steps !!!Warning!!! sector 9 motor 20:: move = -121 Adjuster movements: rms = 40.1 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050627-133403 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1