Reduction started at: 20050421-225042 Reading data from /net/moana/export/data/janw/rxh3/rxh3-20050420-083335.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 = 2361.1 max = 2431.3 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 33.920 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 -2.94189 2.91504 -0.03659 loimag -2.99072 2.96875 0.00008 hireal -5.00000 4.99756 -0.39254 hiimag -5.00000 4.99756 -0.32726 xpos -2431.26618 2427.19391 -3.03269 ypos -2361.08661 2402.20392 19.80250 plock160 0.65674 2.09229 1.43078 lorefpwr 0.21240 1.61865 1.18403 losigpwr -4.58496 -0.53711 -4.38769 hirefpwr 0.31006 1.66748 1.23956 hisigpwr -4.48730 4.99756 -0.85053 encltemp 31.56738 32.76367 32.08295 flags 0.00000 256.00000 2.44475 phi-lock -1.47217 -0.11475 -0.81399 sindex 0.00000 126.00000 62.21460 time 0.00000 2016.99122 999.34903 zeropt -0.00732 -0.00244 -0.00513 !!!Warning!!! philock max less than 0.2 ---------------------------------------------------- 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 = 40.00489 arcsec Mean row spacing = 40.00489 arcsec (alternate estimator) Mean tracking incline = 0.20227 arcsec Mean pointing range = 1.11366 arcsec Mean pointing rms = 0.20128 arcsec This map *probably* has non-inclined rows Applying pointing shifts: (0.6, 13.7 ) 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: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 22496 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 22496 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 = 2431.27 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 = 2.86658 at (-40.01493689163285, -40.01493689163285) arcsec Real: mean = 0.000729852 sum of squares = 1035.36 Imag: mean = -0.00175064 sum of squares = 878.664 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 = 2.84997 at (-40.013940751804832, -40.013940751804832) arcsec Real: mean = 0.00089347 sum of squares = 981.204 Imag: mean = -0.00235084 sum of squares = 932.427 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 = 2.83703 at (0.0, -40.01294466157178) arcsec Real: mean = 0.00134749 sum of squares = 906.845 Imag: mean = -0.00278514 sum of squares = 1005.14 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 = 2.83313 at (0.0, -40.011948620929999) arcsec Real: mean = 0.00156363 sum of squares = 865.524 Imag: mean = -0.00313533 sum of squares = 1046.64 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 = 2.83618 at (0.0, -40.010952629875788) arcsec Real: mean = 0.00218555 sum of squares = 887.807 Imag: mean = -0.00325875 sum of squares = 1025.9 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 = 2.84688 at (0.0, -40.009956688405431) arcsec Real: mean = 0.00294022 sum of squares = 964.247 Imag: mean = -0.0030014 sum of squares = 956.264 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 = 2.86923 at (0.0, -40.008960796515247) arcsec Real: mean = 0.00317776 sum of squares = 1039.17 Imag: mean = -0.00259613 sum of squares = 886.981 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 = 2.88052 at (0.0, -40.007964954201512) arcsec Real: mean = 0.00333534 sum of squares = 1056.22 Imag: mean = -0.00217793 sum of squares = 875.722 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 = 2.89567 at (0.0, -40.006969161460532) arcsec Real: mean = 0.00351285 sum of squares = 1005.54 Imag: mean = -0.00156774 sum of squares = 930.195 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 = 2.9194 at (40.005973418288612, -40.005973418288612) arcsec Real: mean = 0.00312836 sum of squares = 930.009 Imag: mean = -0.00106635 sum of squares = 1010.1 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 = 2.93567 at (40.004977724682043, -40.004977724682043) arcsec Real: mean = 0.00265931 sum of squares = 884.914 Imag: mean = -0.000866001 sum of squares = 1057.43 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 = 2.93184 at (40.00398208063713, -40.00398208063713) arcsec Real: mean = 0.00241155 sum of squares = 904.081 Imag: mean = -0.00073117 sum of squares = 1039.42 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 = 2.91054 at (-40.002986486150171, -40.002986486150171) arcsec Real: mean = 0.00183057 sum of squares = 971.778 Imag: mean = -0.000757393 sum of squares = 974.354 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 = 2.92055 at (-40.001990941217464, -40.001990941217464) arcsec Real: mean = 0.00127602 sum of squares = 1038.77 Imag: mean = -0.00111113 sum of squares = 909.511 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 = 2.89938 at (-40.000995445835301, -40.000995445835301) arcsec Real: mean = 0.00116881 sum of squares = 1064.22 Imag: mean = -0.00155294 sum of squares = 887.997 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 = 2.88446 at (0.0, -40.0) arcsec Real: mean = 0.00117819 sum of squares = 1027.17 Imag: mean = -0.00203012 sum of squares = 926.935 Masking frequency index 0 Mask scale size = 3.00617 Masking frequency index 1 Mask scale size = 3.00624 Masking frequency index 2 Mask scale size = 3.00632 Masking frequency index 3 Mask scale size = 3.00639 Masking frequency index 4 Mask scale size = 3.00647 Masking frequency index 5 Mask scale size = 3.00654 Masking frequency index 6 Mask scale size = 3.00662 Masking frequency index 7 Mask scale size = 3.00669 Masking frequency index 8 Mask scale size = 3.00677 Masking frequency index 9 Mask scale size = 3.00684 Masking frequency index 10 Mask scale size = 3.00692 Masking frequency index 11 Mask scale size = 3.00699 Masking frequency index 12 Mask scale size = 3.00707 Masking frequency index 13 Mask scale size = 3.00714 Masking frequency index 14 Mask scale size = 3.00722 Masking frequency index 15 Mask scale size = 3.00729 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.183105 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.241699 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.244141 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.236816 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.241699 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.227051 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.187988 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.19043 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.185547 Median point-to-point PLL voltage change: 0.0195312 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.202637 Median point-to-point PLL voltage change: 0.0195312 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 0.26683 105.61 Freq 1: Shift, scale = -0.16642 104.75 Freq 2: Shift, scale = -0.595 103.45 Freq 3: Shift, scale = -1.0263 101.65 Freq 4: Shift, scale = -1.4632 100.61 Freq 5: Shift, scale = -1.9025 100.13 Freq 6: Shift, scale = -2.3545 100.34 Freq 7: Shift, scale = -2.8005 100.83 Freq 8: Shift, scale = 3.0323 101.38 Freq 9: Shift, scale = 2.5844 103.44 Freq 10: Shift, scale = 2.1445 104.96 Freq 11: Shift, scale = 1.7036 106.4 Freq 12: Shift, scale = 1.2722 107.6 Freq 13: Shift, scale = 0.84181 107.91 Freq 14: Shift, scale = 0.40755 107.37 Freq 15: Shift, scale = -0.022007 106.69 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: -0.245 radians x offset: -0.0442 arcsec y offset: -0.116 arcsec defocus: 0.00627 mm Estimated x pointing error is 0.5558 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.58 arcsec (used 13.7 arcsec) Estimated defocus error is 2.926 mm (used 2.92 mm) Fitting frequency 1 Minimiser fit code = 1 piston: -0.241 radians x offset: -0.0538 arcsec y offset: -0.121 arcsec defocus: 0.00557 mm Estimated x pointing error is 0.5462 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.58 arcsec (used 13.7 arcsec) Estimated defocus error is 2.926 mm (used 2.92 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.232 radians x offset: -0.0239 arcsec y offset: -0.107 arcsec defocus: 0.00554 mm Estimated x pointing error is 0.5761 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.59 arcsec (used 13.7 arcsec) Estimated defocus error is 2.926 mm (used 2.92 mm) Fitting frequency 3 Minimiser fit code = 3 piston: -0.227 radians x offset: -0.0169 arcsec y offset: -0.082 arcsec defocus: 0.00494 mm Estimated x pointing error is 0.5831 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.62 arcsec (used 13.7 arcsec) Estimated defocus error is 2.925 mm (used 2.92 mm) Fitting frequency 4 Minimiser fit code = 1 piston: -0.228 radians x offset: -0.011 arcsec y offset: -0.0489 arcsec defocus: 0.00251 mm Estimated x pointing error is 0.589 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.65 arcsec (used 13.7 arcsec) Estimated defocus error is 2.923 mm (used 2.92 mm) Fitting frequency 5 Minimiser fit code = 1 piston: -0.231 radians x offset: -0.0109 arcsec y offset: -0.037 arcsec defocus: 0.0015 mm Estimated x pointing error is 0.5891 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.66 arcsec (used 13.7 arcsec) Estimated defocus error is 2.921 mm (used 2.92 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.246 radians x offset: -0.0128 arcsec y offset: -0.0207 arcsec defocus: 0.000553 mm Estimated x pointing error is 0.5872 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.68 arcsec (used 13.7 arcsec) Estimated defocus error is 2.921 mm (used 2.92 mm) Fitting frequency 7 Minimiser fit code = 1 piston: -0.252 radians x offset: -0.0141 arcsec y offset: -0.0699 arcsec defocus: 0.00182 mm Estimated x pointing error is 0.5859 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.63 arcsec (used 13.7 arcsec) Estimated defocus error is 2.922 mm (used 2.92 mm) Fitting frequency 8 Minimiser fit code = 1 piston: -0.264 radians x offset: -0.0378 arcsec y offset: -0.0797 arcsec defocus: 0.00295 mm Estimated x pointing error is 0.5622 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.62 arcsec (used 13.7 arcsec) Estimated defocus error is 2.923 mm (used 2.92 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.272 radians x offset: -0.0459 arcsec y offset: -0.102 arcsec defocus: 0.00355 mm Estimated x pointing error is 0.5541 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.6 arcsec (used 13.7 arcsec) Estimated defocus error is 2.924 mm (used 2.92 mm) Fitting frequency 10 Minimiser fit code = 1 piston: -0.275 radians x offset: -0.0393 arcsec y offset: -0.143 arcsec defocus: 0.00251 mm Estimated x pointing error is 0.5607 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.56 arcsec (used 13.7 arcsec) Estimated defocus error is 2.923 mm (used 2.92 mm) Fitting frequency 11 Minimiser fit code = 1 piston: -0.277 radians x offset: -0.00128 arcsec y offset: -0.176 arcsec defocus: 0.00258 mm Estimated x pointing error is 0.5987 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.52 arcsec (used 13.7 arcsec) Estimated defocus error is 2.923 mm (used 2.92 mm) Fitting frequency 12 Minimiser fit code = 1 piston: -0.27 radians x offset: 0.0175 arcsec y offset: -0.21 arcsec defocus: 0.00142 mm Estimated x pointing error is 0.6175 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.49 arcsec (used 13.7 arcsec) Estimated defocus error is 2.921 mm (used 2.92 mm) Fitting frequency 13 Minimiser fit code = 3 piston: -0.263 radians x offset: 0.0525 arcsec y offset: -0.181 arcsec defocus: 0.000212 mm Estimated x pointing error is 0.6525 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.52 arcsec (used 13.7 arcsec) Estimated defocus error is 2.92 mm (used 2.92 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.26 radians x offset: 0.0657 arcsec y offset: -0.163 arcsec defocus: -0.0012 mm Estimated x pointing error is 0.6657 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.54 arcsec (used 13.7 arcsec) Estimated defocus error is 2.919 mm (used 2.92 mm) Fitting frequency 15 Minimiser fit code = 1 piston: -0.251 radians x offset: 0.0787 arcsec y offset: -0.136 arcsec defocus: -0.000653 mm Estimated x pointing error is 0.6787 arcsec (used 0.6 arcsec) Estimated y pointing error is 13.56 arcsec (used 13.7 arcsec) Estimated defocus error is 2.919 mm (used 2.92 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 0.00015 piston 1 1 0.00138 tilt_x 1 -1 -0.00913 tilt_y 2 2 -0.04178 astigmatism_0 2 0 -0.00009 curvature 2 -2 0.04218 astigmatism45 3 3 -0.04526 trefoil_0 3 1 0.00706 coma_x 3 -1 -0.03823 coma_y 3 -3 -0.04150 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 0.00024 piston 1 1 0.00090 tilt_x 1 -1 -0.00952 tilt_y 2 2 -0.04333 astigmatism_0 2 0 0.00011 curvature 2 -2 0.04179 astigmatism45 3 3 -0.04494 trefoil_0 3 1 0.00589 coma_x 3 -1 -0.03882 coma_y 3 -3 -0.03916 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 0.00029 piston 1 1 0.00153 tilt_x 1 -1 -0.00823 tilt_y 2 2 -0.04546 astigmatism_0 2 0 0.00045 curvature 2 -2 0.04226 astigmatism45 3 3 -0.04333 trefoil_0 3 1 0.00836 coma_x 3 -1 -0.03507 coma_y 3 -3 -0.03848 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 0.00029 piston 1 1 0.00233 tilt_x 1 -1 -0.00687 tilt_y 2 2 -0.04515 astigmatism_0 2 0 0.00075 curvature 2 -2 0.04404 astigmatism45 3 3 -0.04146 trefoil_0 3 1 0.01061 coma_x 3 -1 -0.03164 coma_y 3 -3 -0.04071 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 0.00023 piston 1 1 0.00301 tilt_x 1 -1 -0.00573 tilt_y 2 2 -0.04526 astigmatism_0 2 0 0.00080 curvature 2 -2 0.04474 astigmatism45 3 3 -0.03984 trefoil_0 3 1 0.01273 coma_x 3 -1 -0.02841 coma_y 3 -3 -0.04117 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 0.00015 piston 1 1 0.00412 tilt_x 1 -1 -0.00484 tilt_y 2 2 -0.04325 astigmatism_0 2 0 0.00082 curvature 2 -2 0.04691 astigmatism45 3 3 -0.04116 trefoil_0 3 1 0.01537 coma_x 3 -1 -0.02668 coma_y 3 -3 -0.04261 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 0.00014 piston 1 1 0.00468 tilt_x 1 -1 -0.00501 tilt_y 2 2 -0.04252 astigmatism_0 2 0 0.00077 curvature 2 -2 0.04577 astigmatism45 3 3 -0.04184 trefoil_0 3 1 0.01675 coma_x 3 -1 -0.02691 coma_y 3 -3 -0.04461 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 0.00008 piston 1 1 0.00427 tilt_x 1 -1 -0.00519 tilt_y 2 2 -0.04289 astigmatism_0 2 0 0.00048 curvature 2 -2 0.04594 astigmatism45 3 3 -0.04354 trefoil_0 3 1 0.01589 coma_x 3 -1 -0.02767 coma_y 3 -3 -0.04239 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 0.00009 piston 1 1 0.00426 tilt_x 1 -1 -0.00660 tilt_y 2 2 -0.04095 astigmatism_0 2 0 0.00027 curvature 2 -2 0.04377 astigmatism45 3 3 -0.04592 trefoil_0 3 1 0.01536 coma_x 3 -1 -0.03118 coma_y 3 -3 -0.04200 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 0.00007 piston 1 1 0.00361 tilt_x 1 -1 -0.00768 tilt_y 2 2 -0.04040 astigmatism_0 2 0 0.00001 curvature 2 -2 0.04172 astigmatism45 3 3 -0.04631 trefoil_0 3 1 0.01360 coma_x 3 -1 -0.03397 coma_y 3 -3 -0.04196 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 0.00003 piston 1 1 0.00283 tilt_x 1 -1 -0.00779 tilt_y 2 2 -0.04136 astigmatism_0 2 0 -0.00024 curvature 2 -2 0.04031 astigmatism45 3 3 -0.04702 trefoil_0 3 1 0.01173 coma_x 3 -1 -0.03387 coma_y 3 -3 -0.04028 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 0.00007 piston 1 1 0.00242 tilt_x 1 -1 -0.00800 tilt_y 2 2 -0.04104 astigmatism_0 2 0 -0.00023 curvature 2 -2 0.04012 astigmatism45 3 3 -0.04741 trefoil_0 3 1 0.01049 coma_x 3 -1 -0.03456 coma_y 3 -3 -0.03905 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 0.00011 piston 1 1 0.00175 tilt_x 1 -1 -0.00789 tilt_y 2 2 -0.04240 astigmatism_0 2 0 -0.00008 curvature 2 -2 0.04059 astigmatism45 3 3 -0.04670 trefoil_0 3 1 0.00867 coma_x 3 -1 -0.03429 coma_y 3 -3 -0.03758 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 0.00012 piston 1 1 0.00193 tilt_x 1 -1 -0.00802 tilt_y 2 2 -0.04150 astigmatism_0 2 0 0.00011 curvature 2 -2 0.04125 astigmatism45 3 3 -0.04403 trefoil_0 3 1 0.00925 coma_x 3 -1 -0.03468 coma_y 3 -3 -0.03708 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 0.00010 piston 1 1 0.00182 tilt_x 1 -1 -0.00702 tilt_y 2 2 -0.03954 astigmatism_0 2 0 0.00021 curvature 2 -2 0.04321 astigmatism45 3 3 -0.04382 trefoil_0 3 1 0.00826 coma_x 3 -1 -0.03222 coma_y 3 -3 -0.03886 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 0.00006 piston 1 1 0.00200 tilt_x 1 -1 -0.00601 tilt_y 2 2 -0.03838 astigmatism_0 2 0 0.00033 curvature 2 -2 0.04367 astigmatism45 3 3 -0.04304 trefoil_0 3 1 0.00851 coma_x 3 -1 -0.02912 coma_y 3 -3 -0.04083 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: 40.4 35.6 32.7 37.6 35.2 34.3 47.3 38.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 40.4 35.4 32.6 37.3 34.8 32.8 43.2 37.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.25 4.26 5.56 6.4 8 11 16.1 10.4 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41.2 35.4 33.1 37.3 35.3 34.4 47 38.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 41.2 35.2 33 37.1 34.8 32.9 42.9 37.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.27 4.31 5.61 6.45 8.01 11 16.1 10.4 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41.9 34.2 32.6 36.5 35.5 34.2 46.6 38.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 42 34.1 32.4 36.3 35 32.8 42.5 36.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.09 3.99 5.27 6.23 7.99 11.1 16 10.3 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41.6 33.2 31.7 36 35.5 34.3 45.9 37.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 41.7 33.1 31.6 35.8 35 32.7 41.9 36.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.94 3.73 4.99 6.06 8.01 11.2 16 10.3 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41.5 32.1 30.1 35.2 34.8 34.1 46.4 37.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 41.5 32.1 30 34.9 34.4 32.4 42.4 36 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.81 3.51 4.75 5.91 7.97 11.2 15.9 10.2 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41.6 31 29 34.3 34.4 34 45.9 37 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 41.6 31 28.9 34 34 32.3 42 35.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.8 3.47 4.73 5.94 8.05 11.3 16.1 10.3 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 41 31.1 28.4 34 34 33.7 46.4 36.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 41 31.1 28.3 33.6 33.6 31.9 42.4 35.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.85 3.56 4.8 5.96 8.03 11.3 16.2 10.4 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 39.9 30.9 28.7 34.1 33.8 33.3 47.2 37 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 39.9 31 28.6 33.7 33.4 31.6 43.2 35.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.86 3.58 4.83 5.99 8.06 11.4 16.2 10.4 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 38.4 31.8 29.4 34.3 34.1 33.1 47.1 37.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 38.5 31.7 29.2 34 33.8 31.5 43 35.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.02 3.85 5.09 6.09 7.95 11.2 16.1 10.3 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 37.4 32.4 30.2 35.9 34.3 32.9 47.9 37.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 37.5 32.3 30 35.6 34 31.3 44.1 36.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.12 4.03 5.27 6.16 7.87 11 16 10.2 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 36 32.9 30.8 36.9 34.8 33.1 47.9 38 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 36 32.7 30.7 36.8 34.4 31.6 44.2 36.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.08 3.95 5.18 6.07 7.8 10.9 15.9 10.2 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.4 34.5 30.5 37.6 35.2 33.2 48.1 38.2 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 34.4 34.3 30.4 37.5 34.8 31.7 44.4 36.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.09 3.97 5.2 6.08 7.76 10.8 15.8 10.1 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 34.9 35.6 30.9 38.2 35.7 33.4 48.2 38.6 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 35 35.5 30.9 38.1 35.2 31.9 44.4 37.2 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.05 3.9 5.14 6.06 7.78 10.9 15.8 10.1 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 36.3 36.1 32.2 38.4 36 33.7 47.7 38.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 36.4 36 32.1 38.3 35.5 32.2 43.9 37.4 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 2.08 3.95 5.19 6.07 7.7 10.7 15.5 9.95 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 38.5 36.2 32.4 38.1 35.5 34.3 47.4 38.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 38.6 36.1 32.4 37.9 35.1 32.7 43.7 37.5 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.93 3.69 4.9 5.89 7.68 10.7 15.5 9.92 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 40 35.1 31.8 37 35 34.6 46.7 38.4 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 40.1 35.1 31.8 36.9 34.7 32.9 43.2 37.1 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 1.76 3.39 4.58 5.66 7.6 10.7 15.4 9.82 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 36.4 32.7 29.1 33.7 33.7 32.4 45.6 36.3 Mean deviation is -0.24056043570762561 microns Taper = 10 dB, Ruze illumination-weighted rms = 35.7 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 = 34.1 micron Centre pixel: 64.0 64.0 Value = 2224.96 (estimate), 3426.12 (perfect) Strehl = 0.421735 Strehl ratio estimate = 0.4217 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 = 33.7 micron Centre pixel: 64.0 64.0 Value = 1525.23 (estimate), 3426.12 (perfect) Strehl = 0.198183 Strehl ratio estimate = 0.1982 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 1.7 -1.0 -56.0 56.1 2 1 2 22.6 -42.9 -3.4 48.6 3 1 3 48.1 -30.4 7.1 57.3 4 1 4 58.3 18.3 -30.3 68.3 5 1 5 -6.6 -15.3 36.8 40.4 6 1 6 37.0 -5.7 27.2 46.3 7 1 7 -24.1 26.9 -41.3 54.8 8 1 8 -33.4 13.1 29.1 46.2 9 1 9 -29.3 -39.9 30.1 57.9 10 1 10 44.5 39.4 -9.8 60.2 11 1 11 30.5 31.2 -6.2 44.0 12 1 12 29.8 -20.5 8.7 37.2 13 2 1 17.7 -51.8 -57.1 79.1 14 2 2 14.2 -80.0 -56.9 99.2 15 2 3 10.9 -26.9 -60.0 66.6 16 2 4 -64.6 -31.7 -33.4 79.4 17 2 5 17.9 -44.4 0.7 47.8 18 2 6 40.8 -35.7 -29.3 61.6 19 2 7 -6.9 -33.1 -22.0 40.3 20 2 8 61.0 -80.4 -63.1 119.1 21 2 9 17.0 -19.8 -28.2 38.4 22 2 10 -43.0 -16.1 -2.2 46.0 23 2 11 0.4 -32.5 -10.1 34.1 24 2 12 10.3 -50.8 -79.4 94.8 25 2 13 6.8 -6.6 -33.8 35.1 26 2 14 13.3 -90.1 -26.3 94.8 27 2 15 18.6 -17.5 -59.3 64.6 28 2 16 -38.0 -3.9 -13.6 40.5 29 2 17 3.4 -32.2 -16.4 36.3 30 2 18 44.8 -20.0 -64.2 80.8 31 2 19 -2.6 -36.0 -27.4 45.4 32 2 20 58.4 -67.6 -47.2 101.0 33 2 21 28.6 -5.1 -63.6 69.9 34 2 22 -52.7 -69.5 -74.4 114.6 35 2 23 52.9 -47.3 -32.3 78.0 36 2 24 34.2 -69.0 -97.9 124.5 37 3 1 3.9 28.1 -30.1 41.4 38 3 2 -25.6 39.7 -42.9 63.8 39 3 3 -3.6 37.7 -46.7 60.1 40 3 4 -23.0 36.6 -25.1 50.0 41 3 5 -41.4 26.5 -44.3 66.2 42 3 6 -34.5 29.9 -32.5 56.1 43 3 7 -19.5 27.8 -57.4 66.7 44 3 8 -23.8 16.7 -28.2 40.5 45 3 9 -18.0 18.0 -67.0 71.7 46 3 10 -0.8 35.1 -43.1 55.6 47 3 11 -38.4 35.9 -40.8 66.5 48 3 12 -0.2 37.3 -15.9 40.5 49 3 13 -10.0 23.4 -30.1 39.4 50 3 14 -42.3 28.2 -51.5 72.4 51 3 15 -17.0 33.9 -21.8 43.8 52 3 16 -18.2 39.9 -39.8 59.2 53 3 17 14.7 32.5 -39.7 53.4 54 3 18 0.7 51.7 -19.2 55.1 55 3 19 10.8 50.2 -55.5 75.6 56 3 20 -35.1 28.1 -24.5 51.2 57 3 21 -35.3 40.0 -54.5 76.3 58 3 22 -13.0 47.0 -16.3 51.4 59 3 23 -49.4 54.4 -30.8 79.7 60 3 24 13.2 22.5 -24.7 35.9 61 3 25 2.3 21.6 -8.5 23.3 62 3 26 -61.4 47.0 -6.6 77.7 63 3 27 -41.7 45.1 -30.4 68.5 64 3 28 -28.1 40.8 -58.4 76.6 65 3 29 -35.2 25.8 -14.0 45.9 66 3 30 -13.7 26.5 -38.0 48.3 67 3 31 -31.5 42.2 -26.5 59.0 68 3 32 -31.9 15.6 -46.6 58.6 69 3 33 -19.8 38.9 -27.5 51.6 70 3 34 10.4 44.8 -3.8 46.2 71 3 35 -28.0 48.3 -59.7 81.8 72 3 36 50.0 29.8 -19.5 61.4 73 3 37 4.3 28.4 -56.0 63.0 74 3 38 -34.6 51.7 -39.7 73.8 75 3 39 0.6 38.3 -54.7 66.8 76 3 40 -22.3 41.4 -69.0 83.6 77 3 41 -8.2 28.4 -26.8 39.9 78 3 42 2.2 44.3 -34.8 56.4 79 3 43 -20.0 42.4 -26.8 54.0 80 3 44 6.0 32.8 -7.9 34.3 81 3 45 -11.2 37.8 -47.5 61.8 82 3 46 -4.8 49.7 -44.4 66.8 83 3 47 -44.9 34.4 -41.0 69.9 84 3 48 20.9 27.3 -50.1 60.7 85 4 1 -3.3 -5.5 11.9 13.5 86 4 2 1.1 -7.2 -145.8 145.9 87 4 3 -36.1 4.2 -79.4 87.3 88 4 4 -21.3 21.1 -122.2 125.8 89 4 5 6.1 24.5 -72.0 76.3 90 4 6 -13.0 42.6 -64.4 78.3 91 4 7 -19.6 36.9 -27.5 50.0 92 4 8 -47.7 33.3 -68.0 89.4 93 4 9 -22.3 24.7 -34.8 48.1 94 4 10 -46.4 24.0 -55.4 76.2 95 4 11 -17.8 12.6 -80.9 83.8 96 4 12 -52.4 10.3 -20.0 57.0 97 4 13 -43.4 8.9 18.4 48.0 98 4 14 8.6 20.4 -55.8 60.0 99 4 15 -51.0 11.2 -56.3 76.8 100 4 16 -72.0 47.0 -54.5 101.8 101 4 17 -36.2 33.8 -54.5 73.6 102 4 18 -4.1 41.7 -39.9 57.9 103 4 19 -38.6 31.9 -49.7 70.5 104 4 20 -21.1 35.7 -60.5 73.4 105 4 21 -22.0 30.6 -39.3 54.5 106 4 22 -81.3 33.0 2.6 87.8 107 4 23 -22.2 12.7 -17.7 31.1 108 4 24 -97.1 33.4 12.4 103.4 109 4 25 -119.6 34.8 19.1 126.0 110 4 26 7.6 19.2 -33.5 39.4 111 4 27 -33.4 36.8 -27.2 56.7 112 4 28 -43.8 18.0 -27.9 55.0 113 4 29 -60.3 25.4 -103.6 122.5 114 4 30 -53.5 31.8 -41.1 74.6 115 4 31 -60.7 35.9 -51.8 87.5 116 4 32 -53.8 23.1 -43.2 72.7 117 4 33 -60.4 42.2 -32.1 80.4 118 4 34 -19.4 21.9 -70.8 76.6 119 4 35 -14.5 38.2 -86.0 95.2 120 4 36 -48.7 24.7 -45.0 70.8 121 4 37 -28.2 37.3 -31.6 56.5 122 4 38 12.5 6.7 -70.1 71.5 123 4 39 -27.0 36.9 -11.9 47.3 124 4 40 -3.2 27.6 -34.4 44.3 125 4 41 -30.0 65.3 -49.0 87.0 126 4 42 -19.2 43.8 -61.2 77.7 127 4 43 -30.9 39.8 -92.0 104.9 128 4 44 4.8 32.7 -57.2 66.0 129 4 45 -7.2 25.4 -87.8 91.7 130 4 46 -36.4 15.3 -77.6 87.1 131 4 47 0.7 -9.6 -197.3 197.6 132 4 48 -35.5 -9.0 -9.3 37.8 133 5 1 5.5 49.6 -15.4 52.2 134 5 2 10.8 52.5 -28.1 60.6 135 5 3 -32.9 84.4 -48.5 102.8 136 5 4 -27.2 25.5 -39.1 54.0 137 5 5 -36.2 16.3 -81.4 90.6 138 5 6 -29.8 30.0 -76.8 87.7 139 5 7 -6.1 55.2 -20.9 59.4 140 5 8 -9.4 50.3 -63.3 81.4 141 5 9 -16.3 38.5 -60.7 73.7 142 5 10 -19.7 78.0 -44.3 91.9 143 5 11 -38.8 19.2 -30.2 52.7 144 5 12 -45.5 44.6 -51.9 82.2 145 5 13 -40.0 25.8 -61.2 77.5 146 5 14 -46.9 34.0 -47.7 75.0 147 5 15 -29.3 70.4 -58.7 96.2 148 5 16 -40.0 57.1 -67.8 97.3 149 5 17 -29.5 54.9 -0.4 62.3 150 5 18 -33.2 27.1 152.3 158.2 151 5 19 -36.8 30.0 -70.9 85.3 152 5 20 -39.7 21.7 -63.1 77.7 153 5 21 -26.7 55.6 -25.9 66.9 154 5 22 -2.6 114.6 -42.5 122.3 155 5 23 -33.8 49.1 -2.1 59.6 156 5 24 24.0 55.3 -2.2 60.4 157 5 25 15.3 53.6 -20.1 59.2 158 5 26 -26.0 41.7 -7.8 49.8 159 5 27 4.5 113.5 -46.2 122.6 160 5 28 -21.6 28.4 -32.1 48.1 161 5 29 -18.2 30.9 -60.8 70.6 162 5 30 -32.4 14.0 -25.1 43.3 163 5 31 -37.0 21.8 -72.1 83.9 164 5 32 -49.5 10.4 -46.7 68.9 165 5 33 -31.9 42.9 -58.7 79.5 166 5 34 -48.5 48.2 -89.7 112.8 167 5 35 -16.2 33.7 -28.9 47.3 168 5 36 -23.9 18.9 -50.5 59.0 169 5 37 -8.5 48.3 -64.8 81.2 170 5 38 -30.0 19.9 -38.5 52.7 171 5 39 -12.5 148.5 -118.0 190.1 172 5 40 -27.2 43.4 -56.8 76.4 173 5 41 17.1 61.9 -30.7 71.1 174 5 42 -22.3 12.8 -80.7 84.7 175 5 43 -41.0 20.6 -76.9 89.5 176 5 44 -11.7 28.8 -73.0 79.4 177 5 45 -0.6 39.6 -52.6 65.9 178 5 46 -1.1 75.7 -3.9 75.8 179 5 47 -5.8 30.8 -41.3 51.8 180 5 48 -8.7 53.2 -39.3 66.7 181 6 1 0.2 20.4 -51.4 55.3 182 6 2 -12.4 18.9 -65.4 69.2 183 6 3 -30.5 11.3 -74.3 81.1 184 6 4 -48.1 17.2 -152.0 160.3 185 6 5 -15.0 8.8 -72.1 74.1 186 6 6 -13.1 24.3 -78.8 83.5 187 6 7 -12.3 11.6 -98.5 100.0 188 6 8 -22.9 16.8 -70.0 75.6 189 6 9 -36.8 -3.7 -175.3 179.2 190 6 10 -33.2 35.5 -52.9 71.9 191 6 11 -7.8 20.8 -73.6 76.9 192 6 12 -26.4 9.9 -71.9 77.3 193 6 13 -17.9 19.2 -95.0 98.6 194 6 14 -50.4 13.3 -65.6 83.8 195 6 15 -17.9 -1.6 -74.2 76.3 196 6 16 -49.7 16.4 -193.3 200.3 197 6 17 -40.0 -15.0 -74.3 85.7 198 6 18 -50.7 32.9 -138.5 151.1 199 6 19 3.8 15.9 -24.2 29.1 200 6 20 -15.0 47.7 24.3 55.6 201 6 21 -46.4 33.5 -213.0 220.5 202 6 22 14.0 63.5 -20.3 68.1 203 6 23 -1.3 51.7 46.9 69.8 204 6 24 -8.8 47.5 -7.4 48.9 205 6 25 -50.9 49.2 -74.1 102.5 206 6 26 -51.3 19.2 -44.7 70.7 207 6 27 -80.0 28.5 -80.4 117.0 208 6 28 -32.9 25.7 -70.5 81.9 209 6 29 -83.7 39.2 -83.5 124.6 210 6 30 -67.9 21.1 -29.5 77.0 211 6 31 -56.7 30.3 -61.9 89.2 212 6 32 -62.1 -47.9 -55.4 96.0 213 6 33 -39.1 10.0 -14.5 42.9 214 6 34 -0.6 4.5 -34.7 35.0 215 6 35 -27.3 6.7 -28.0 39.7 216 6 36 -27.3 33.4 -18.6 47.0 217 6 37 -10.6 34.0 -21.4 41.5 218 6 38 9.3 33.6 -37.6 51.2 219 6 39 15.1 51.1 -7.8 53.9 220 6 40 -16.6 37.3 -135.7 141.7 221 6 41 -25.1 27.6 -50.5 62.8 222 6 42 7.9 13.4 -1.7 15.6 223 6 43 -20.4 12.5 -6.2 24.7 224 6 44 -16.1 22.1 -27.2 38.6 225 6 45 -11.3 48.7 -46.4 68.2 226 6 46 5.8 41.5 -11.8 43.6 227 6 47 -11.3 14.6 -45.8 49.4 228 6 48 -8.0 27.6 -30.6 42.0 229 7 1 2.8 74.1 -0.0 74.2 230 7 2 -18.4 30.1 -34.7 49.5 231 7 3 -3.9 37.4 -22.0 43.5 232 7 4 18.3 -22.9 55.9 63.1 233 7 5 -14.1 -2.4 -25.3 29.0 234 7 6 -19.3 31.1 -25.1 44.4 235 7 7 -43.0 12.0 -67.2 80.7 236 7 8 -5.1 -15.3 -71.8 73.6 237 7 9 -2.7 -200.5 72.0 213.1 238 7 10 -13.2 45.3 -69.4 83.9 239 7 11 -10.0 9.5 -83.2 84.3 240 7 12 -14.7 24.1 -22.2 36.0 241 7 13 -71.5 27.8 -77.8 109.2 242 7 14 -36.8 21.4 -71.8 83.5 243 7 15 -41.9 -9.6 -77.2 88.4 244 7 16 15.9 -108.2 -32.7 114.2 245 7 17 -16.5 -47.4 -55.3 74.7 246 7 18 -33.2 44.4 -78.0 95.7 247 7 19 3.2 11.2 -2.9 12.0 248 7 20 10.4 -60.6 -19.4 64.5 249 7 21 49.3 -108.6 109.7 162.0 250 7 22 -3.9 58.8 4.7 59.1 251 7 23 47.6 60.9 -2.6 77.3 252 7 24 3.0 58.7 22.5 63.0 253 7 25 -54.6 48.1 -31.1 79.1 254 7 26 -8.7 44.6 -36.8 58.5 255 7 27 -36.1 36.2 -76.5 92.0 256 7 28 -76.2 -202.5 305.4 374.2 257 7 29 -17.9 -75.5 -149.3 168.3 258 7 30 -38.9 -35.3 -151.3 160.2 259 7 31 -84.5 -22.7 -165.4 187.1 260 7 32 -23.9 -50.7 -160.8 170.3 261 7 33 -67.4 -396.6 36.2 403.9 262 7 34 -14.4 -2.2 -131.7 132.5 263 7 35 -3.6 8.6 -88.1 88.6 264 7 36 13.1 24.5 -69.4 74.7 265 7 37 -3.6 46.5 -51.0 69.1 266 7 38 16.7 15.7 -60.4 64.6 267 7 39 60.6 67.5 -73.4 116.6 268 7 40 64.6 -34.9 10.0 74.1 269 7 41 34.4 -8.7 -29.9 46.4 270 7 42 22.5 -3.1 -60.7 64.9 271 7 43 -50.9 38.6 -83.4 105.0 272 7 44 21.4 2.6 -46.8 51.5 273 7 45 17.8 -82.0 67.1 107.4 274 7 46 37.0 47.7 -3.4 60.4 275 7 47 54.0 70.8 -46.6 100.5 276 7 48 54.7 190.8 9.5 198.7 Creating sector-motor-move file sector motor steps 1 1 17 1 2 -7 1 3 5 1 4 -46 1 5 5 1 6 -14 1 7 -6 1 8 11 1 9 -1 1 10 -22 1 11 3 1 12 -9 1 13 -10 1 14 9 1 15 -5 1 16 -20 1 17 5 1 18 -3 1 19 0 1 20 22 1 21 0 1 22 -15 1 23 6 1 24 0 1 25 -11 1 26 7 1 27 -8 1 28 -37 1 29 6 1 30 -6 1 31 -14 1 32 25 1 33 -10 1 34 -24 1 35 1 1 36 -11 1 37 -8 1 38 16 1 39 3 1 40 -44 1 41 -2 1 42 0 1 43 -4 1 44 15 1 45 1 1 46 3 1 47 -1 1 48 -1 1 49 -14 1 50 11 1 51 -1 1 52 -17 1 53 -24 1 54 4 1 55 -13 1 56 12 1 57 -7 1 58 0 1 59 0 1 60 -17 1 61 -9 1 62 8 1 63 1 1 64 -8 1 65 5 1 66 -17 1 67 -7 1 68 11 1 69 -7 2 1 -22 2 2 -4 2 3 -1 2 4 -21 2 5 5 2 6 -7 2 7 -20 2 8 3 2 9 -13 2 10 -30 2 11 3 2 12 -3 2 13 -7 2 14 9 2 15 -5 2 16 -24 2 17 7 2 18 -4 2 19 -7 2 20 0 2 21 -4 2 22 -22 2 23 2 2 24 -4 2 25 -19 2 26 15 2 27 -2 2 28 -20 2 29 10 2 30 -14 2 31 -6 2 32 16 2 33 -1 2 34 -8 2 35 11 2 36 -6 2 37 -23 2 38 9 2 39 -9 2 40 -19 2 41 13 2 42 -3 2 43 -24 2 44 5 2 45 -11 2 46 -22 2 47 7 2 48 1 2 49 -17 2 50 8 2 51 -5 2 52 -10 2 53 -9 2 54 -19 2 55 -9 2 56 9 2 57 -10 2 58 -13 2 59 6 2 60 -1 2 61 -13 2 62 8 2 63 -12 2 64 -13 2 65 3 2 66 -18 2 67 -8 2 68 5 2 69 -7 3 1 -6 3 2 7 3 3 -4 3 4 -22 3 5 3 3 6 -8 3 7 -25 3 8 2 3 9 -3 3 10 -22 3 11 6 3 12 -2 3 13 -21 3 14 13 3 15 -4 3 16 -16 3 17 10 3 18 -10 3 19 22 3 20 -61 3 21 0 3 22 -53 3 23 -1 3 24 -11 3 25 -15 3 26 13 3 27 -13 3 28 -6 3 29 3 3 30 -16 3 31 -9 3 32 5 3 33 -11 3 34 -24 3 35 3 3 36 -5 3 37 -13 3 38 23 3 39 -6 3 40 -17 3 41 7 3 42 -14 3 43 -18 3 44 11 3 45 -5 3 46 -10 3 47 7 3 48 -6 3 49 -12 3 50 11 3 51 -11 3 52 -8 3 53 -10 3 54 12 3 55 -13 3 56 10 3 57 0 3 58 -9 3 59 14 3 60 2 3 61 -20 3 62 5 3 63 -5 3 64 -10 3 65 5 3 66 0 3 67 -4 3 68 11 3 69 0 4 1 -10 4 2 -33 4 3 4 4 4 -59 4 5 5 4 6 -15 4 7 -23 4 8 -2 4 9 -12 4 10 -22 4 11 0 4 12 -5 4 13 -22 4 14 6 4 15 -11 4 16 -20 4 17 4 4 18 -15 4 19 -23 4 20 8 4 21 -21 4 22 -29 4 23 5 4 24 -5 4 25 -20 4 26 17 4 27 -12 4 28 -16 4 29 14 4 30 -22 4 31 -18 4 32 21 4 33 -8 4 34 -17 4 35 3 4 36 -15 4 37 -14 4 38 10 4 39 -14 4 40 -17 4 41 6 4 42 2 4 43 -18 4 44 7 4 45 -12 4 46 5 4 47 2 4 48 -13 4 49 -6 4 50 10 4 51 -5 4 52 -19 4 53 -24 4 54 18 4 55 -15 4 56 8 4 57 -12 4 58 5 4 59 17 4 60 -9 4 61 -9 4 62 7 4 63 -3 4 64 -6 4 65 -2 4 66 -6 4 67 -12 4 68 12 4 69 -5 5 1 -5 5 2 -18 5 3 3 5 4 7 5 5 14 5 6 -4 5 7 0 5 8 3 5 9 0 5 10 -7 5 11 4 5 12 1 5 13 -23 5 14 13 5 15 -10 5 16 -42 5 17 10 5 18 -15 5 19 -16 5 20 -14 5 21 -5 5 22 -22 5 23 -4 5 24 -12 5 25 -19 5 26 6 5 27 -12 5 28 -18 5 29 10 5 30 -6 5 31 -21 5 32 9 5 33 -11 5 34 -15 5 35 9 5 36 -11 5 37 46 5 38 8 5 39 -10 5 40 -12 5 41 12 5 42 -1 5 43 0 5 44 16 5 45 -9 5 46 -16 5 47 10 5 48 -11 5 49 -17 5 50 15 5 51 3 5 52 0 5 53 -4 5 54 -13 5 55 -5 5 56 15 5 57 0 5 58 -4 5 59 -2 5 60 11 5 61 -12 5 62 9 5 63 4 5 64 -9 5 65 5 5 66 -8 5 67 -7 5 68 8 5 69 -10 6 1 6 6 2 18 6 3 0 6 4 -2 6 5 14 6 6 -2 6 7 0 6 8 18 6 9 14 6 10 14 6 11 15 6 12 0 6 13 1 6 14 18 6 15 -1 6 16 -6 6 17 19 6 18 4 6 19 33 6 20 -33 6 21 15 6 22 -65 6 23 10 6 24 -14 6 25 0 6 26 16 6 27 7 6 28 3 6 29 10 6 30 -29 6 31 0 6 32 15 6 33 -10 6 34 -5 6 35 3 6 36 -6 6 37 -13 6 38 35 6 39 0 6 40 0 6 41 10 6 42 -24 6 43 -7 6 44 17 6 45 -8 6 46 -12 6 47 9 6 48 -6 6 49 -9 6 50 16 6 51 -15 6 52 -24 6 53 -15 6 54 3 6 55 -5 6 56 14 6 57 -3 6 58 -1 6 59 11 6 60 8 6 61 -16 6 62 12 6 63 -10 6 64 -2 6 65 0 6 66 -3 6 67 -7 6 68 6 6 69 4 7 1 93 7 2 -62 7 3 -23 7 4 -21 7 5 7 7 6 -10 7 7 -23 7 8 11 7 9 -11 7 10 -24 7 11 8 7 12 -24 7 13 -11 7 14 13 7 15 -2 7 16 -13 7 17 5 7 18 -15 7 19 -9 7 20 14 7 21 -16 7 22 -22 7 23 15 7 24 -15 7 25 -9 7 26 8 7 27 -6 7 28 -8 7 29 5 7 30 -13 7 31 -14 7 32 34 7 33 1 7 34 -8 7 35 11 7 36 -10 7 37 -2 7 38 12 7 39 -7 7 40 -10 7 41 5 7 42 2 7 43 -6 7 44 16 7 45 4 7 46 5 7 47 10 7 48 -36 7 49 -9 7 50 13 7 51 -12 7 52 -8 7 53 -27 7 54 4 7 55 -2 7 56 14 7 57 -18 7 58 8 7 59 -7 7 60 -12 7 61 -2 7 62 6 7 63 0 7 64 -5 7 65 2 7 66 -10 7 67 -17 7 68 12 7 69 -8 8 1 -49 8 2 -15 8 3 -7 8 4 -16 8 5 -14 8 6 -19 8 7 -50 8 8 -6 8 9 -25 8 10 -18 8 11 9 8 12 -17 8 13 -46 8 14 -10 8 15 -11 8 16 -9 8 17 6 8 18 -20 8 19 -45 8 20 -23 8 21 -5 8 22 -25 8 23 12 8 24 -25 8 25 -14 8 26 3 8 27 -15 8 28 -13 8 29 7 8 30 -16 8 31 -22 8 32 6 8 33 -11 8 34 -15 8 35 11 8 36 -18 8 37 -7 8 38 4 8 39 -9 8 40 -12 8 41 9 8 42 -16 8 43 -18 8 44 9 8 45 -5 8 46 -31 8 47 7 8 48 -18 8 49 -8 8 50 12 8 51 -9 8 52 -4 8 53 -1 8 54 -11 8 55 -11 8 56 8 8 57 -4 8 58 4 8 59 -10 8 60 8 8 61 -4 8 62 7 8 63 -10 8 64 -9 8 65 5 8 66 -18 8 67 -14 8 68 4 8 69 -9 9 1 -21 9 2 7 9 3 4 9 4 -5 9 5 10 9 6 -8 9 7 -27 9 8 2 9 9 -1 9 10 -8 9 11 2 9 12 -8 9 13 -40 9 14 0 9 15 -4 9 16 -10 9 17 1 9 18 0 9 19 11 9 20 -100 9 21 -20 9 22 -4 9 23 3 9 24 -12 9 25 -15 9 26 5 9 27 -7 9 28 -13 9 29 7 9 30 -14 9 31 -8 9 32 10 9 33 -4 9 34 -26 9 35 11 9 36 -4 9 37 -27 9 38 14 9 39 -14 9 40 -21 9 41 6 9 42 -5 9 43 -18 9 44 13 9 45 -9 9 46 -9 9 47 12 9 48 -18 9 49 -18 9 50 14 9 51 -8 9 52 -19 9 53 -6 9 54 13 9 55 -1 9 56 13 9 57 3 9 58 -12 9 59 -8 9 60 9 9 61 -8 9 62 11 9 63 -6 9 64 -11 9 65 1 9 66 -5 9 67 -5 9 68 9 9 69 15 10 1 3 10 2 -10 10 3 19 10 4 -41 10 5 11 10 6 -5 10 7 -22 10 8 20 10 9 18 10 10 -2 10 11 15 10 12 4 10 13 -18 10 14 4 10 15 5 10 16 -11 10 17 10 10 18 2 10 19 -15 10 20 14 10 21 -1 10 22 -6 10 23 10 10 24 -3 10 25 -17 10 26 13 10 27 -8 10 28 -10 10 29 8 10 30 0 10 31 -36 10 32 45 10 33 -3 10 34 -3 10 35 11 10 36 -8 10 37 -11 10 38 6 10 39 -9 10 40 -21 10 41 2 10 42 3 10 43 -19 10 44 14 10 45 -2 10 46 -9 10 47 11 10 48 -8 10 49 -16 10 50 11 10 51 0 10 52 -14 10 53 -20 10 54 17 10 55 -12 10 56 15 10 57 -10 10 58 12 10 59 13 10 60 -3 10 61 -17 10 62 8 10 63 1 10 64 -1 10 65 0 10 66 -8 10 67 -21 10 68 12 10 69 -6 11 1 -14 11 2 0 11 3 6 11 4 -8 11 5 6 11 6 -4 11 7 -25 11 8 11 11 9 -15 11 10 -1 11 11 3 11 12 -6 11 13 -18 11 14 0 11 15 6 11 16 0 11 17 4 11 18 2 11 19 -9 11 20 -2 11 21 10 11 22 -15 11 23 8 11 24 -7 11 25 -22 11 26 8 11 27 -3 11 28 -17 11 29 10 11 30 1 11 31 -23 11 32 6 11 33 -12 11 34 -28 11 35 12 11 36 -9 11 37 -24 11 38 3 11 39 -6 11 40 -18 11 41 13 11 42 -5 11 43 -9 11 44 18 11 45 5 11 46 -15 11 47 20 11 48 -9 11 49 -8 11 50 12 11 51 -6 11 52 -22 11 53 -21 11 54 -16 11 55 -10 11 56 13 11 57 0 11 58 9 11 59 9 11 60 -1 11 61 -8 11 62 8 11 63 -2 11 64 -14 11 65 8 11 66 -19 11 67 -2 11 68 10 11 69 1 12 1 2 12 2 58 12 3 16 12 4 -9 12 5 8 12 6 -2 12 7 -14 12 8 21 12 9 16 12 10 -14 12 11 4 12 12 -3 12 13 -1 12 14 14 12 15 11 12 16 -3 12 17 12 12 18 1 12 19 20 12 20 -25 12 21 5 12 22 -14 12 23 14 12 24 -3 12 25 -12 12 26 16 12 27 -2 12 28 -2 12 29 -2 12 30 -10 12 31 -12 12 32 9 12 33 -1 12 34 -60 12 35 -2 12 36 0 12 37 -1 12 38 23 12 39 0 12 40 -23 12 41 4 12 42 -11 12 43 -16 12 44 12 12 45 0 12 46 -26 12 47 7 12 48 -2 12 49 -12 12 50 10 12 51 -13 12 52 -30 12 53 -21 12 54 10 12 55 -13 12 56 15 12 57 -1 12 58 -6 12 59 9 12 60 2 12 61 -14 12 62 11 12 63 -3 12 64 -15 12 65 16 12 66 -9 12 67 -15 12 68 8 12 69 6 !!!Warning!!! Truncated 1 recommended moves exceeding 100 steps !!!Warning!!! sector 9 motor 20:: move = -121 Adjuster movements: rms = 49.4 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050421-225636 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1 Reducing ID = 20050420-172845 Data directory /net/moana/export/data/janw/rxh3 contains 151 data files Reading database file: /home/janw/rxh3/Rxh3red/rxh3db.dat Resolved file ID 20050420-172845 = rxh3-20050420-172845.fits Reducing file ID 20050420-172845 Found database entry for 20050420-172845 Setting data.pointing_offset_x = 1.7 Setting data.pointing_offset_y = 13.7 Setting data.secondary_defocus_offset = 2.84 Reducing data file rxh3-20050420-172845.fits at Thu Apr 21 23:00:42 HST 2005 Reduction code ID: 2.20 (created Apr 27 2004 at 15:09:15) (TDL_BIN = /.automount/moana/root/export/data/janw/install/tdl_2p21_test2) Comment: Deleting data and results from internal arrays Using output directory: /home/janw/rxh3/Rxh3red/20050420-172845/default Deleting all files in /home/janw/rxh3/Rxh3red/20050420-172845/default ... ... 206 files deleted.