Reduction started at: 20050703-024958 Reading data from rxh3-20050701-015154.fits Reduction ID: default Read keywords into global array holo_keys Read binary table data into global array holo_data Finished reading data Converted positions to arcsec, times to elapsed seconds, and reversed x-axis Pattern extent: min = 2401.8 max = 7789867270.2 arcsec Nominal defocus setting was 31. mm Using actual defocus setting of 34.200 mm ----------------- Data Summary --------------------- Number of samples: 1466025 This is a 160 GHz map Number of frequencies: 16 Frequencies (GHz): 160.676000 160.680000 160.684000 160.688000 160.692000 160.696000 160.700000 160.704000 160.708000 160.712000 160.716000 160.720000 160.724000 160.728000 160.732000 160.736000 item min max mean loreal -3.04199 2.99561 -0.00417 loimag -3.22998 3.13965 -0.00964 hireal -5.00000 4.99756 -0.00321 hiimag -5.00000 4.99756 0.02149 xpos -7789867270.18290 2407.96774 -7943097.78082 ypos -19419252.55745 2401.83184 -19613.33732 plock160 0.34424 1.75293 1.10488 lorefpwr 0.94482 2.77344 2.20433 losigpwr -4.51904 -0.04883 -4.33708 hirefpwr 1.03516 2.75146 2.22486 hisigpwr -4.43604 4.99756 -1.78788 encltemp 31.59180 32.86133 32.15830 flags 0.00000 256.00000 2.44471 phi-lock -1.87012 -0.49316 -1.23836 sindex 0.00000 254.00000 126.60925 time 0.00000 19441326.98524 22755.46102 zeropt -0.00732 -0.00244 -0.00609 !!!Warning!!! philock max less than 0.2 !!!Warning!!! philock min less than -1.5 ---------------------------------------------------- Subtracting zeropt channel Data contains a total of 255 rows There are 241 data rows and 14 calibrator rows Calibrator rows: 0 21 42 63 84 105 126 147 168 189 210 231 252 254 Checking pointing along rasters... This map is more horizontally scanned than vertically Mean row spacing = 20.00262 arcsec Mean row spacing = 20.00263 arcsec (alternate estimator) Mean tracking incline = -0.11140 arcsec Mean pointing range = 0.77446 arcsec Mean pointing rms = 0.17312 arcsec This map *probably* has non-inclined rows !!!Warning!!! Bad tracking on row 2: range = 12.1758 > 4.0 !!!Warning!!! Bad tracking on row 2: rms = 4.60337 > 2.0 !!!Warning!!! Bad tracking on row 54: range = 11.7641 > 4.0 !!!Warning!!! Bad tracking on row 54: rms = 4.47542 > 2.0 !!!Warning!!! Bad tracking on row 70: range = 11.7251 > 4.0 !!!Warning!!! Bad tracking on row 70: rms = 4.4921 > 2.0 Applying pointing shifts: (-58.2, 7.3 ) arcsec Applying pointing lags: (0, 0 ) arcsec Deciphering frequencies... Selecting hi/lo channels using method 2 Inverting the phase on this 160 GHz map Doing geometric phase correction Status bits counts: bit: 0 1 2 3 4 5 6 7 8 set: 0 0 0 0 0 0 0 0 14000 Extracting frequencies Selecting all rows from the map (row = -1) Extracted frequency 0: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 1: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 2: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 3: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 4: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 5: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 6: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 7: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 8: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 9: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 10: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 11: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 12: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 13: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 14: 90359 data points Selecting all rows from the map (row = -1) Extracted frequency 15: 90359 data points No calibration requested... Creating template maps for gridding Using a grid cellsize of 20.0 arcseconds Using a grid of 256 points Grid has even number of points Maximum data offset = 7.78987e+09 arcsec Grid extent = 2550 arcsec lambda_min = 0.00186512 scale = 0.00259937 Diffraction scale lambda/D = 25.6569 arcsec Gridding function extent = 153.941 arcsec Using Gaussian * Airy regridding function Gaussian FWHM = 76.9706 arcsec Airy first null at 31.2929 arcsec Gridding frequency index 0 lambda = 0.00186582 metres, scale = 0.0025984 radians per metre Gridding real part of frequency 0... Gridding imag part of frequency 0... Pattern is holo(res.pattern0) Weights in holo(obs.real,wt0) and holo(obs.imag,wt0) Maximum amplitude = 2.84986 at (0.0, 0.0) arcsec Real: mean = -5.7368e-05 sum of squares = 1877.95 Imag: mean = 0.000362708 sum of squares = 1790.49 Gridding frequency index 1 lambda = 0.00186577 metres, scale = 0.00259846 radians per metre Gridding real part of frequency 1... Gridding imag part of frequency 1... Pattern is holo(res.pattern1) Weights in holo(obs.real,wt1) and holo(obs.imag,wt1) Maximum amplitude = 2.85918 at (0.0, 0.0) arcsec Real: mean = -0.000209838 sum of squares = 1878.24 Imag: mean = 0.000347263 sum of squares = 1812.52 Gridding frequency index 2 lambda = 0.00186573 metres, scale = 0.00259852 radians per metre Gridding real part of frequency 2... Gridding imag part of frequency 2... Pattern is holo(res.pattern2) Weights in holo(obs.real,wt2) and holo(obs.imag,wt2) Maximum amplitude = 2.85337 at (0.0, 0.0) arcsec Real: mean = -0.000178111 sum of squares = 1799.53 Imag: mean = 0.00023428 sum of squares = 1916.64 Gridding frequency index 3 lambda = 0.00186568 metres, scale = 0.00259859 radians per metre Gridding real part of frequency 3... Gridding imag part of frequency 3... Pattern is holo(res.pattern3) Weights in holo(obs.real,wt3) and holo(obs.imag,wt3) Maximum amplitude = 2.83202 at (0.0, 0.0) arcsec Real: mean = -0.000150051 sum of squares = 1852.58 Imag: mean = 0.000224206 sum of squares = 1894.77 Gridding frequency index 4 lambda = 0.00186563 metres, scale = 0.00259865 radians per metre Gridding real part of frequency 4... Gridding imag part of frequency 4... Pattern is holo(res.pattern4) Weights in holo(obs.real,wt4) and holo(obs.imag,wt4) Maximum amplitude = 2.81601 at (0.0, 0.0) arcsec Real: mean = -0.00014369 sum of squares = 1950.49 Imag: mean = 0.000239907 sum of squares = 1829.36 Gridding frequency index 5 lambda = 0.00186559 metres, scale = 0.00259872 radians per metre Gridding real part of frequency 5... Gridding imag part of frequency 5... Pattern is holo(res.pattern5) Weights in holo(obs.real,wt5) and holo(obs.imag,wt5) Maximum amplitude = 2.82179 at (0.0, 0.0) arcsec Real: mean = -6.59318e-05 sum of squares = 1908.16 Imag: mean = 0.000253997 sum of squares = 1905.75 Gridding frequency index 6 lambda = 0.00186554 metres, scale = 0.00259878 radians per metre Gridding real part of frequency 6... Gridding imag part of frequency 6... Pattern is holo(res.pattern6) Weights in holo(obs.real,wt6) and holo(obs.imag,wt6) Maximum amplitude = 2.84827 at (0.0, 0.0) arcsec Real: mean = -4.6859e-05 sum of squares = 1856.22 Imag: mean = 0.000349393 sum of squares = 1993.05 Gridding frequency index 7 lambda = 0.00186549 metres, scale = 0.00259885 radians per metre Gridding real part of frequency 7... Gridding imag part of frequency 7... Pattern is holo(res.pattern7) Weights in holo(obs.real,wt7) and holo(obs.imag,wt7) Maximum amplitude = 2.88879 at (0.0, 0.0) arcsec Real: mean = -0.000144986 sum of squares = 1959.83 Imag: mean = 0.000440128 sum of squares = 1924.21 Gridding frequency index 8 lambda = 0.00186545 metres, scale = 0.00259891 radians per metre Gridding real part of frequency 8... Gridding imag part of frequency 8... Pattern is holo(res.pattern8) Weights in holo(obs.real,wt8) and holo(obs.imag,wt8) Maximum amplitude = 2.93284 at (0.0, 0.0) arcsec Real: mean = -0.000227351 sum of squares = 2019.18 Imag: mean = 0.000315004 sum of squares = 1906.11 Gridding frequency index 9 lambda = 0.0018654 metres, scale = 0.00259898 radians per metre Gridding real part of frequency 9... Gridding imag part of frequency 9... Pattern is holo(res.pattern9) Weights in holo(obs.real,wt9) and holo(obs.imag,wt9) Maximum amplitude = 2.93679 at (0.0, 0.0) arcsec Real: mean = -0.000127472 sum of squares = 1944.51 Imag: mean = 0.000269343 sum of squares = 2027.87 Gridding frequency index 10 lambda = 0.00186536 metres, scale = 0.00259904 radians per metre Gridding real part of frequency 10... Gridding imag part of frequency 10... Pattern is holo(res.pattern10) Weights in holo(obs.real,wt10) and holo(obs.imag,wt10) Maximum amplitude = 2.90942 at (0.0, 0.0) arcsec Real: mean = -0.000156548 sum of squares = 1956.92 Imag: mean = 0.000252977 sum of squares = 2058.67 Gridding frequency index 11 lambda = 0.00186531 metres, scale = 0.00259911 radians per metre Gridding real part of frequency 11... Gridding imag part of frequency 11... Pattern is holo(res.pattern11) Weights in holo(obs.real,wt11) and holo(obs.imag,wt11) Maximum amplitude = 2.89061 at (0.0, 0.0) arcsec Real: mean = -8.82712e-05 sum of squares = 2081.98 Imag: mean = 0.000213794 sum of squares = 1978.53 Gridding frequency index 12 lambda = 0.00186526 metres, scale = 0.00259917 radians per metre Gridding real part of frequency 12... Gridding imag part of frequency 12... Pattern is holo(res.pattern12) Weights in holo(obs.real,wt12) and holo(obs.imag,wt12) Maximum amplitude = 2.90504 at (0.0, 0.0) arcsec Real: mean = -6.05732e-05 sum of squares = 2087.88 Imag: mean = 0.000345679 sum of squares = 2022.65 Gridding frequency index 13 lambda = 0.00186522 metres, scale = 0.00259924 radians per metre Gridding real part of frequency 13... Gridding imag part of frequency 13... Pattern is holo(res.pattern13) Weights in holo(obs.real,wt13) and holo(obs.imag,wt13) Maximum amplitude = 2.95172 at (0.0, 0.0) arcsec Real: mean = -0.000155398 sum of squares = 2010.11 Imag: mean = 0.000391531 sum of squares = 2152.3 Gridding frequency index 14 lambda = 0.00186517 metres, scale = 0.0025993 radians per metre Gridding real part of frequency 14... Gridding imag part of frequency 14... Pattern is holo(res.pattern14) Weights in holo(obs.real,wt14) and holo(obs.imag,wt14) Maximum amplitude = 2.9822 at (0.0, 0.0) arcsec Real: mean = -0.000152755 sum of squares = 2097.58 Imag: mean = 0.000350959 sum of squares = 2120.37 Gridding frequency index 15 lambda = 0.00186512 metres, scale = 0.00259937 radians per metre Gridding real part of frequency 15... Gridding imag part of frequency 15... Pattern is holo(res.pattern15) Weights in holo(obs.real,wt15) and holo(obs.imag,wt15) Maximum amplitude = 3.02307 at (0.0, 0.0) arcsec Real: mean = -0.00017899 sum of squares = 2203.97 Imag: mean = 0.000372705 sum of squares = 2064.91 Masking frequency index 0 Mask scale size = 6.11609 Masking frequency index 1 Mask scale size = 6.11624 Masking frequency index 2 Mask scale size = 6.11639 Masking frequency index 3 Mask scale size = 6.11655 Masking frequency index 4 Mask scale size = 6.1167 Masking frequency index 5 Mask scale size = 6.11685 Masking frequency index 6 Mask scale size = 6.117 Masking frequency index 7 Mask scale size = 6.11716 Masking frequency index 8 Mask scale size = 6.11731 Masking frequency index 9 Mask scale size = 6.11746 Masking frequency index 10 Mask scale size = 6.11761 Masking frequency index 11 Mask scale size = 6.11776 Masking frequency index 12 Mask scale size = 6.11792 Masking frequency index 13 Mask scale size = 6.11807 Masking frequency index 14 Mask scale size = 6.11822 Masking frequency index 15 Mask scale size = 6.11837 Checking phase lock voltage for frequency 0... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 1... Max point-to-point PLL voltage change: 0.195312 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 2... Max point-to-point PLL voltage change: 0.239258 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 3... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 4... Max point-to-point PLL voltage change: 0.219727 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 5... Max point-to-point PLL voltage change: 0.222168 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 6... Max point-to-point PLL voltage change: 0.200195 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 7... Max point-to-point PLL voltage change: 0.212402 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 8... Max point-to-point PLL voltage change: 0.209961 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 9... Max point-to-point PLL voltage change: 0.214844 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 10... Max point-to-point PLL voltage change: 0.217285 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 11... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 12... Max point-to-point PLL voltage change: 0.20752 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 13... Max point-to-point PLL voltage change: 0.214844 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 14... Max point-to-point PLL voltage change: 0.214844 Median point-to-point PLL voltage change: 0.00976562 Checking phase lock voltage for frequency 15... Max point-to-point PLL voltage change: 0.229492 Median point-to-point PLL voltage change: 0.00976562 Doing FFT of patterns... Normalising FFT patterns... Freq 0: Shift, scale = 0.87608 115.43 Freq 1: Shift, scale = 0.012261 115.36 Freq 2: Shift, scale = -0.85236 116.38 Freq 3: Shift, scale = -1.7176 117.33 Freq 4: Shift, scale = -2.5841 116.65 Freq 5: Shift, scale = 2.842 115.94 Freq 6: Shift, scale = 1.9886 117.53 Freq 7: Shift, scale = 1.1271 119.14 Freq 8: Shift, scale = 0.25728 119.53 Freq 9: Shift, scale = -0.61902 120.16 Freq 10: Shift, scale = -1.4836 120.02 Freq 11: Shift, scale = -2.3336 120.45 Freq 12: Shift, scale = 3.0865 121.58 Freq 13: Shift, scale = 2.2159 122.46 Freq 14: Shift, scale = 1.3455 123.96 Freq 15: Shift, scale = 0.47353 124.11 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: -0.258 radians x offset: 0.0211 arcsec y offset: 0.0364 arcsec defocus: 0.00966 mm Estimated x pointing error is -58.18 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.336 arcsec (used 7.3 arcsec) Estimated defocus error is 3.21 mm (used 3.2 mm) Fitting frequency 1 Minimiser fit code = 3 piston: -0.259 radians x offset: 0.0189 arcsec y offset: 0.0492 arcsec defocus: 0.0089 mm Estimated x pointing error is -58.18 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.349 arcsec (used 7.3 arcsec) Estimated defocus error is 3.209 mm (used 3.2 mm) Fitting frequency 2 Minimiser fit code = 3 piston: -0.259 radians x offset: 0.00663 arcsec y offset: 0.051 arcsec defocus: 0.0097 mm Estimated x pointing error is -58.19 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.351 arcsec (used 7.3 arcsec) Estimated defocus error is 3.21 mm (used 3.2 mm) Fitting frequency 3 Minimiser fit code = 1 piston: -0.261 radians x offset: -0.00712 arcsec y offset: 0.0529 arcsec defocus: 0.0101 mm Estimated x pointing error is -58.21 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.353 arcsec (used 7.3 arcsec) Estimated defocus error is 3.21 mm (used 3.2 mm) Fitting frequency 4 Minimiser fit code = 3 piston: -0.265 radians x offset: -0.0116 arcsec y offset: 0.0501 arcsec defocus: 0.00917 mm Estimated x pointing error is -58.21 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.35 arcsec (used 7.3 arcsec) Estimated defocus error is 3.209 mm (used 3.2 mm) Fitting frequency 5 Minimiser fit code = 3 piston: -0.261 radians x offset: -0.0165 arcsec y offset: 0.0344 arcsec defocus: 0.00693 mm Estimated x pointing error is -58.22 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.334 arcsec (used 7.3 arcsec) Estimated defocus error is 3.207 mm (used 3.2 mm) Fitting frequency 6 Minimiser fit code = 1 piston: -0.251 radians x offset: -0.0183 arcsec y offset: 0.031 arcsec defocus: 0.00658 mm Estimated x pointing error is -58.22 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.331 arcsec (used 7.3 arcsec) Estimated defocus error is 3.207 mm (used 3.2 mm) Fitting frequency 7 Minimiser fit code = 3 piston: -0.248 radians x offset: -0.0277 arcsec y offset: 0.025 arcsec defocus: 0.00706 mm Estimated x pointing error is -58.23 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.325 arcsec (used 7.3 arcsec) Estimated defocus error is 3.207 mm (used 3.2 mm) Fitting frequency 8 Minimiser fit code = 3 piston: -0.254 radians x offset: -0.0407 arcsec y offset: 0.0262 arcsec defocus: 0.00724 mm Estimated x pointing error is -58.24 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.326 arcsec (used 7.3 arcsec) Estimated defocus error is 3.207 mm (used 3.2 mm) Fitting frequency 9 Minimiser fit code = 1 piston: -0.268 radians x offset: -0.0424 arcsec y offset: 0.0132 arcsec defocus: 0.00545 mm Estimated x pointing error is -58.24 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.313 arcsec (used 7.3 arcsec) Estimated defocus error is 3.205 mm (used 3.2 mm) Fitting frequency 10 Minimiser fit code = 3 piston: -0.269 radians x offset: -0.0411 arcsec y offset: -0.00982 arcsec defocus: 0.00447 mm Estimated x pointing error is -58.24 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.29 arcsec (used 7.3 arcsec) Estimated defocus error is 3.204 mm (used 3.2 mm) Fitting frequency 11 Minimiser fit code = 3 piston: -0.256 radians x offset: -0.0467 arcsec y offset: -0.0236 arcsec defocus: 0.00255 mm Estimated x pointing error is -58.25 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.276 arcsec (used 7.3 arcsec) Estimated defocus error is 3.203 mm (used 3.2 mm) Fitting frequency 12 Minimiser fit code = 3 piston: -0.253 radians x offset: -0.0606 arcsec y offset: -0.0206 arcsec defocus: 0.00309 mm Estimated x pointing error is -58.26 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.279 arcsec (used 7.3 arcsec) Estimated defocus error is 3.203 mm (used 3.2 mm) Fitting frequency 13 Minimiser fit code = 1 piston: -0.256 radians x offset: -0.0726 arcsec y offset: -0.0246 arcsec defocus: 0.00393 mm Estimated x pointing error is -58.27 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.275 arcsec (used 7.3 arcsec) Estimated defocus error is 3.204 mm (used 3.2 mm) Fitting frequency 14 Minimiser fit code = 1 piston: -0.261 radians x offset: -0.0749 arcsec y offset: -0.0224 arcsec defocus: 0.0029 mm Estimated x pointing error is -58.27 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.278 arcsec (used 7.3 arcsec) Estimated defocus error is 3.203 mm (used 3.2 mm) Fitting frequency 15 Minimiser fit code = 3 piston: -0.267 radians x offset: -0.0732 arcsec y offset: -0.0428 arcsec defocus: 0.00223 mm Estimated x pointing error is -58.27 arcsec (used -58.2 arcsec) Estimated y pointing error is 7.257 arcsec (used 7.3 arcsec) Estimated defocus error is 3.202 mm (used 3.2 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 0.00061 piston 1 1 -0.02026 tilt_x 1 -1 0.04348 tilt_y 2 2 0.02614 astigmatism_0 2 0 -0.00602 curvature 2 -2 0.00763 astigmatism45 3 3 -0.05178 trefoil_0 3 1 -0.05398 coma_x 3 -1 0.15522 coma_y 3 -3 -0.04815 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 0.00054 piston 1 1 -0.02043 tilt_x 1 -1 0.04306 tilt_y 2 2 0.02723 astigmatism_0 2 0 -0.00622 curvature 2 -2 0.00768 astigmatism45 3 3 -0.05300 trefoil_0 3 1 -0.05459 coma_x 3 -1 0.15363 coma_y 3 -3 -0.04984 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 0.00052 piston 1 1 -0.01987 tilt_x 1 -1 0.04429 tilt_y 2 2 0.02904 astigmatism_0 2 0 -0.00634 curvature 2 -2 0.00734 astigmatism45 3 3 -0.05396 trefoil_0 3 1 -0.05281 coma_x 3 -1 0.15711 coma_y 3 -3 -0.05014 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 0.00070 piston 1 1 -0.02008 tilt_x 1 -1 0.04451 tilt_y 2 2 0.02928 astigmatism_0 2 0 -0.00623 curvature 2 -2 0.00770 astigmatism45 3 3 -0.05335 trefoil_0 3 1 -0.05304 coma_x 3 -1 0.15894 coma_y 3 -3 -0.05216 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 0.00078 piston 1 1 -0.01927 tilt_x 1 -1 0.04396 tilt_y 2 2 0.02819 astigmatism_0 2 0 -0.00609 curvature 2 -2 0.00780 astigmatism45 3 3 -0.05255 trefoil_0 3 1 -0.05040 coma_x 3 -1 0.15776 coma_y 3 -3 -0.05027 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 0.00073 piston 1 1 -0.01979 tilt_x 1 -1 0.04289 tilt_y 2 2 0.02568 astigmatism_0 2 0 -0.00612 curvature 2 -2 0.00911 astigmatism45 3 3 -0.05156 trefoil_0 3 1 -0.05221 coma_x 3 -1 0.15422 coma_y 3 -3 -0.04972 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 0.00067 piston 1 1 -0.01933 tilt_x 1 -1 0.04263 tilt_y 2 2 0.02682 astigmatism_0 2 0 -0.00617 curvature 2 -2 0.00881 astigmatism45 3 3 -0.05136 trefoil_0 3 1 -0.05180 coma_x 3 -1 0.15302 coma_y 3 -3 -0.04944 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 0.00064 piston 1 1 -0.01887 tilt_x 1 -1 0.04316 tilt_y 2 2 0.02888 astigmatism_0 2 0 -0.00636 curvature 2 -2 0.00806 astigmatism45 3 3 -0.05252 trefoil_0 3 1 -0.05027 coma_x 3 -1 0.15460 coma_y 3 -3 -0.05012 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 0.00061 piston 1 1 -0.01880 tilt_x 1 -1 0.04293 tilt_y 2 2 0.02793 astigmatism_0 2 0 -0.00651 curvature 2 -2 0.00659 astigmatism45 3 3 -0.05028 trefoil_0 3 1 -0.05050 coma_x 3 -1 0.15485 coma_y 3 -3 -0.05062 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 0.00070 piston 1 1 -0.01845 tilt_x 1 -1 0.04256 tilt_y 2 2 0.02768 astigmatism_0 2 0 -0.00628 curvature 2 -2 0.00753 astigmatism45 3 3 -0.04930 trefoil_0 3 1 -0.04954 coma_x 3 -1 0.15433 coma_y 3 -3 -0.05147 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 0.00066 piston 1 1 -0.01863 tilt_x 1 -1 0.04248 tilt_y 2 2 0.02586 astigmatism_0 2 0 -0.00627 curvature 2 -2 0.00816 astigmatism45 3 3 -0.04981 trefoil_0 3 1 -0.05015 coma_x 3 -1 0.15379 coma_y 3 -3 -0.04925 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 0.00055 piston 1 1 -0.01920 tilt_x 1 -1 0.04271 tilt_y 2 2 0.02584 astigmatism_0 2 0 -0.00656 curvature 2 -2 0.00876 astigmatism45 3 3 -0.04973 trefoil_0 3 1 -0.05200 coma_x 3 -1 0.15441 coma_y 3 -3 -0.05038 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 0.00055 piston 1 1 -0.01861 tilt_x 1 -1 0.04297 tilt_y 2 2 0.02641 astigmatism_0 2 0 -0.00665 curvature 2 -2 0.00779 astigmatism45 3 3 -0.04993 trefoil_0 3 1 -0.05023 coma_x 3 -1 0.15513 coma_y 3 -3 -0.05234 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 0.00069 piston 1 1 -0.01840 tilt_x 1 -1 0.04317 tilt_y 2 2 0.02709 astigmatism_0 2 0 -0.00655 curvature 2 -2 0.00889 astigmatism45 3 3 -0.04879 trefoil_0 3 1 -0.04965 coma_x 3 -1 0.15643 coma_y 3 -3 -0.05378 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 0.00075 piston 1 1 -0.01847 tilt_x 1 -1 0.04216 tilt_y 2 2 0.02769 astigmatism_0 2 0 -0.00646 curvature 2 -2 0.00770 astigmatism45 3 3 -0.04713 trefoil_0 3 1 -0.05025 coma_x 3 -1 0.15344 coma_y 3 -3 -0.05114 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 0.00058 piston 1 1 -0.01836 tilt_x 1 -1 0.04275 tilt_y 2 2 0.02518 astigmatism_0 2 0 -0.00676 curvature 2 -2 0.00781 astigmatism45 3 3 -0.04616 trefoil_0 3 1 -0.05069 coma_x 3 -1 0.15566 coma_y 3 -3 -0.04790 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: 26.5 29.3 23.7 29.3 28.2 32.8 38.8 32.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.4 27.2 22.4 27.5 27.3 31.6 38.4 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.02 8.67 10.6 10.3 7.37 5.21 13.3 9.65 Unweighted rms analysis, frequency 1 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 28.8 23.3 29.2 27.9 32.8 39.2 32.1 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.7 26.5 21.9 27.3 27 31.5 38.9 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.98 8.6 10.6 10.2 7.35 5.33 13.4 9.64 Unweighted rms analysis, frequency 2 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 28.7 23.6 28.5 28 32.8 38.4 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.6 26.4 22.2 26.6 27.1 31.5 38.1 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.07 8.75 10.7 10.4 7.48 5.43 13.6 9.81 Unweighted rms analysis, frequency 3 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.5 28.6 23.8 28.4 28.2 32.9 38.1 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.3 26.3 22.3 26.5 27.4 31.6 37.8 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.12 8.84 10.9 10.5 7.57 5.5 13.8 9.92 Unweighted rms analysis, frequency 4 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 28.8 23.7 28 28.3 33 38.1 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 26.5 22.3 26.2 27.4 31.8 37.8 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.06 8.74 10.7 10.4 7.46 5.37 13.5 9.77 Unweighted rms analysis, frequency 5 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 29 23.9 28.4 28 32.6 38.4 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 26.7 22.4 26.7 27.2 31.4 38 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.98 8.59 10.5 10.2 7.32 5.24 13.3 9.59 Unweighted rms analysis, frequency 6 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.9 29.1 23.5 29 27.9 33 38.7 32 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.8 26.9 22.1 27.3 27 31.7 38.4 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.94 8.52 10.5 10.1 7.28 5.24 13.2 9.54 Unweighted rms analysis, frequency 7 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27.2 28.9 23.7 29.2 27.7 32.7 38.4 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 25 26.7 22.3 27.4 26.8 31.4 38.3 30.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.97 8.58 10.5 10.2 7.35 5.36 13.4 9.63 Unweighted rms analysis, frequency 8 Total errors: ring: 1 2 3 4 5 6 7 total rms: 27 28.4 23.9 28.7 27.9 32.9 38.2 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.9 26.1 22.5 26.9 27.1 31.6 38 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.98 8.59 10.5 10.2 7.33 5.27 13.3 9.61 Unweighted rms analysis, frequency 9 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 29 23.6 28 28 32.9 38.2 31.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.6 26.7 22.2 26.2 27.2 31.7 37.9 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.95 8.55 10.5 10.1 7.3 5.26 13.3 9.57 Unweighted rms analysis, frequency 10 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.5 30 23.4 28.4 28 32.6 38.3 31.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.4 27.8 22 26.7 27.1 31.4 37.8 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.94 8.53 10.5 10.1 7.26 5.16 13.2 9.51 Unweighted rms analysis, frequency 11 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.8 28.9 23.4 28.4 27.8 33.1 38.3 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.6 26.7 21.9 26.7 26.9 31.8 38 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.98 8.6 10.6 10.2 7.31 5.21 13.3 9.58 Unweighted rms analysis, frequency 12 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.7 28.5 23.8 28.4 27.8 33.1 38.2 31.7 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.6 26.3 22.5 26.6 27 31.8 37.9 30.6 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.98 8.6 10.6 10.2 7.34 5.29 13.3 9.62 Unweighted rms analysis, frequency 13 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.6 28.4 23.7 28.8 28.1 32.9 38.3 31.8 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 26.1 22.3 27 27.2 31.5 38 30.7 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5.01 8.66 10.6 10.3 7.39 5.33 13.4 9.69 Unweighted rms analysis, frequency 14 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.6 28.5 23.7 29 28.1 33 38.3 31.9 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 24.5 26.3 22.3 27.3 27.3 31.7 38 30.8 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 4.93 8.52 10.5 10.1 7.26 5.18 13.1 9.5 Unweighted rms analysis, frequency 15 Total errors: ring: 1 2 3 4 5 6 7 total rms: 26.1 29.1 23.4 29 28.1 32.9 38.8 32 Small-scale errors: ring: 1 2 3 4 5 6 7 total rms: 23.9 26.9 21.9 27.2 27.3 31.7 38.4 30.9 Large-scale errors: ring: 1 2 3 4 5 6 7 total rms: 5 8.64 10.6 10.2 7.28 4.99 13.1 9.52 Total errors on mean aperture: ring: 1 2 3 4 5 6 7 total rms: 25.7 28 22.9 27 27 31.4 36.9 30.6 Mean deviation is -1.4126528587778202 microns Taper = 10 dB, Ruze illumination-weighted rms = 29.9 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 = 27.4 micron Centre pixel: 128.0 128.0 Value = 11883 (estimate), 15687.6 (perfect) Strehl = 0.573767 Strehl ratio estimate = 0.5738 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 = 26.7 micron Centre pixel: 128.0 128.0 Value = 9446.4 (estimate), 15687.6 (perfect) Strehl = 0.362592 Strehl ratio estimate = 0.3626 Fitting panels... No Zernike terms to subtract before panel fitting edge scale = 0.07514 metres panel scale = 3.00000 metres mean frequency = 160.70600 GHz min edge weight = 0.1 # rng pan adj1 adj2 adj3 qsum 1 1 1 20.1 8.9 8.7 23.6 2 1 2 11.0 29.1 23.1 38.8 3 1 3 16.2 4.5 14.0 21.9 4 1 4 16.3 19.6 3.9 25.8 5 1 5 -23.0 -6.1 -1.0 23.8 6 1 6 -1.6 -16.2 -25.4 30.2 7 1 7 -19.6 -15.8 -12.8 28.2 8 1 8 -22.4 -7.1 -2.3 23.7 9 1 9 -44.6 0.8 8.6 45.4 10 1 10 16.2 22.2 7.2 28.4 11 1 11 13.1 21.2 21.9 33.2 12 1 12 43.7 11.6 14.6 47.5 13 2 1 10.8 0.2 3.1 11.2 14 2 2 14.2 4.9 -5.8 16.1 15 2 3 3.5 -2.7 -15.1 15.7 16 2 4 13.5 -6.4 -2.6 15.2 17 2 5 12.6 7.1 2.5 14.6 18 2 6 17.1 7.0 32.7 37.5 19 2 7 -2.4 10.7 13.4 17.3 20 2 8 9.7 21.0 13.4 26.7 21 2 9 6.7 12.1 2.4 14.0 22 2 10 12.4 -11.1 -30.7 34.9 23 2 11 -3.0 -39.5 -52.0 65.4 24 2 12 -28.9 -44.3 -65.9 84.5 25 2 13 -30.1 -46.0 -56.5 78.9 26 2 14 -30.4 -67.8 -42.7 85.7 27 2 15 -2.8 -50.1 -42.8 66.0 28 2 16 9.8 -29.2 -14.2 33.9 29 2 17 8.6 2.2 7.5 11.6 30 2 18 2.3 20.5 -9.7 22.8 31 2 19 13.4 11.6 2.9 18.0 32 2 20 21.1 16.6 -1.5 26.9 33 2 21 14.0 2.3 7.7 16.1 34 2 22 13.3 -13.3 -23.4 30.0 35 2 23 22.3 -19.9 -7.5 30.9 36 2 24 15.4 -17.0 -0.2 23.0 37 3 1 -10.0 6.7 15.8 19.9 38 3 2 -9.8 8.2 14.5 19.4 39 3 3 -3.0 7.8 7.0 10.9 40 3 4 2.9 7.2 24.2 25.4 41 3 5 -8.9 7.2 -5.4 12.7 42 3 6 -3.1 -1.2 9.1 9.7 43 3 7 1.9 -0.7 -6.1 6.5 44 3 8 1.5 7.9 -0.4 8.0 45 3 9 20.1 9.6 2.4 22.4 46 3 10 17.3 6.1 3.9 18.7 47 3 11 25.2 17.5 8.5 31.9 48 3 12 17.6 19.7 23.5 35.4 49 3 13 -2.7 4.6 15.6 16.5 50 3 14 16.0 20.8 9.4 27.9 51 3 15 22.3 24.3 -4.7 33.3 52 3 16 22.4 -4.2 -7.3 23.9 53 3 17 -1.0 -1.7 -38.9 38.9 54 3 18 -13.4 -20.1 -14.1 28.0 55 3 19 -28.9 -24.2 -11.6 39.4 56 3 20 -42.5 -14.8 -3.2 45.1 57 3 21 -44.5 -19.0 -5.9 48.7 58 3 22 -33.2 -16.5 -3.6 37.3 59 3 23 -41.7 -13.6 -3.7 44.0 60 3 24 -30.0 -13.0 8.6 33.8 61 3 25 -40.1 -7.1 5.8 41.1 62 3 26 -46.3 -24.8 2.6 52.6 63 3 27 -46.3 -28.5 -12.9 55.9 64 3 28 -40.3 -24.5 -8.8 48.0 65 3 29 -43.7 -19.2 1.6 47.8 66 3 30 -36.0 -44.1 -4.7 57.1 67 3 31 -28.9 -24.0 -25.0 45.2 68 3 32 -16.9 -13.5 -37.6 43.4 69 3 33 14.9 -9.1 -6.6 18.6 70 3 34 24.7 24.0 9.6 35.8 71 3 35 1.2 23.9 14.7 28.1 72 3 36 15.8 13.1 19.4 28.2 73 3 37 -0.8 17.4 -13.8 22.2 74 3 38 15.2 13.6 9.2 22.4 75 3 39 5.7 0.1 1.8 6.0 76 3 40 9.9 15.0 7.7 19.5 77 3 41 4.1 11.7 -7.8 14.6 78 3 42 5.9 -1.7 0.2 6.1 79 3 43 -3.3 -3.6 -3.6 6.0 80 3 44 -3.3 -3.1 -4.6 6.5 81 3 45 -16.7 -3.8 0.3 17.1 82 3 46 -4.7 -1.7 3.0 5.8 83 3 47 -20.0 -1.3 7.1 21.3 84 3 48 -12.2 6.5 -0.6 13.9 85 4 1 37.9 14.1 26.1 48.1 86 4 2 28.6 28.3 30.8 50.7 87 4 3 34.2 24.5 35.1 54.7 88 4 4 25.7 31.6 16.1 43.8 89 4 5 18.5 34.0 27.1 47.2 90 4 6 15.1 20.6 27.2 37.3 91 4 7 -2.8 19.3 25.5 32.0 92 4 8 -0.8 8.8 14.8 17.3 93 4 9 11.1 9.3 5.6 15.5 94 4 10 -11.7 -3.5 10.0 15.8 95 4 11 26.3 -1.8 -2.0 26.4 96 4 12 17.2 7.7 16.5 25.0 97 4 13 16.8 12.6 27.9 34.9 98 4 14 28.2 2.2 -2.4 28.4 99 4 15 -12.6 -0.8 -37.3 39.4 100 4 16 -26.5 -6.6 -8.3 28.6 101 4 17 -15.1 -9.2 4.2 18.1 102 4 18 -15.1 7.5 13.8 21.7 103 4 19 -10.7 9.9 26.0 29.8 104 4 20 22.0 12.6 -1.6 25.4 105 4 21 31.7 14.4 -16.9 38.7 106 4 22 -8.0 -13.0 -22.9 27.6 107 4 23 -0.2 -13.6 -7.1 15.3 108 4 24 12.4 -17.3 -23.4 31.6 109 4 25 -6.3 -12.8 -5.0 15.1 110 4 26 -6.3 -29.9 -37.9 48.6 111 4 27 -1.1 -31.9 -32.0 45.2 112 4 28 0.2 -0.6 -31.0 31.0 113 4 29 8.3 -1.7 -84.3 84.7 114 4 30 -2.3 3.3 4.1 5.7 115 4 31 -15.4 0.9 -7.1 17.0 116 4 32 -20.1 -10.7 5.5 23.5 117 4 33 -37.4 -5.7 -17.3 41.6 118 4 34 -8.8 9.8 -42.3 44.3 119 4 35 31.7 15.6 21.0 41.1 120 4 36 19.7 12.4 35.0 42.1 121 4 37 5.6 12.9 13.2 19.3 122 4 38 13.6 5.7 4.9 15.5 123 4 39 8.8 5.9 22.3 24.7 124 4 40 23.5 0.1 0.9 23.5 125 4 41 -10.6 8.2 2.6 13.6 126 4 42 -15.0 8.8 -0.4 17.4 127 4 43 -5.1 2.7 11.2 12.6 128 4 44 8.1 19.2 6.4 21.8 129 4 45 15.0 16.3 7.9 23.5 130 4 46 23.0 0.1 1.7 23.0 131 4 47 16.1 2.4 27.1 31.6 132 4 48 24.2 17.2 6.3 30.3 133 5 1 27.8 -1.2 -24.5 37.1 134 5 2 26.3 4.0 -25.4 36.8 135 5 3 37.8 16.7 -4.7 41.6 136 5 4 40.3 18.1 -6.7 44.7 137 5 5 41.5 20.8 9.4 47.4 138 5 6 35.5 30.6 19.4 50.7 139 5 7 25.0 40.9 31.2 57.2 140 5 8 24.5 29.5 22.9 44.7 141 5 9 7.3 23.5 16.5 29.6 142 5 10 11.4 8.3 14.7 20.4 143 5 11 5.3 7.0 9.5 13.0 144 5 12 11.7 19.4 -1.7 22.7 145 5 13 10.8 21.2 7.9 25.1 146 5 14 12.2 -12.6 -8.8 19.6 147 5 15 -10.7 -22.7 2.9 25.2 148 5 16 -11.7 22.6 -6.0 26.1 149 5 17 15.5 21.9 47.3 54.4 150 5 18 45.3 -10.3 246.3 250.6 151 5 19 -19.5 -4.9 -11.0 23.0 152 5 20 -29.0 -6.0 10.3 31.4 153 5 21 4.8 14.0 23.5 27.7 154 5 22 5.1 8.9 23.5 25.7 155 5 23 15.4 16.2 1.6 22.4 156 5 24 32.7 2.8 -13.5 35.5 157 5 25 21.7 6.3 -13.0 26.0 158 5 26 7.3 4.2 -10.7 13.6 159 5 27 -10.3 -2.6 17.6 20.6 160 5 28 -18.8 3.0 21.1 28.5 161 5 29 -15.2 -9.5 4.0 18.4 162 5 30 -12.5 -20.3 7.4 25.0 163 5 31 4.2 -16.0 -29.9 34.1 164 5 32 -6.9 2.3 -25.2 26.2 165 5 33 2.4 22.2 8.3 23.8 166 5 34 -7.8 -30.8 9.9 33.3 167 5 35 32.2 3.4 17.9 37.0 168 5 36 26.5 23.2 21.9 41.5 169 5 37 18.5 23.7 -12.1 32.4 170 5 38 3.1 19.7 6.9 21.1 171 5 39 10.7 32.2 -5.8 34.4 172 5 40 -8.2 21.5 10.4 25.2 173 5 41 25.4 20.6 34.8 47.8 174 5 42 22.6 18.7 1.4 29.4 175 5 43 10.3 15.0 1.6 18.3 176 5 44 15.3 12.7 -0.1 19.9 177 5 45 31.2 13.4 -17.1 38.0 178 5 46 9.8 7.3 -18.2 22.0 179 5 47 11.2 -5.4 -37.6 39.6 180 5 48 8.8 2.4 -36.2 37.3 181 6 1 -18.0 -24.1 -38.8 49.1 182 6 2 -32.9 -19.9 -27.5 47.3 183 6 3 -14.7 -24.0 -19.1 34.0 184 6 4 -20.0 -13.9 -18.5 30.6 185 6 5 -10.2 -24.8 -38.7 47.1 186 6 6 6.8 -4.3 -38.5 39.4 187 6 7 37.3 -5.6 -15.8 40.9 188 6 8 34.1 22.9 18.7 45.1 189 6 9 24.4 10.6 -2.5 26.8 190 6 10 15.4 4.8 17.6 23.9 191 6 11 -0.7 -5.6 -12.5 13.7 192 6 12 -1.7 4.0 -24.8 25.2 193 6 13 3.9 8.8 -32.2 33.7 194 6 14 -17.9 -21.7 -54.2 61.0 195 6 15 -0.8 -23.1 -6.2 24.0 196 6 16 39.3 -0.4 4.6 39.6 197 6 17 -24.2 -13.2 -23.0 35.9 198 6 18 -6.2 13.7 -50.5 52.7 199 6 19 19.1 20.1 -0.7 27.8 200 6 20 -2.5 -1.5 36.5 36.6 201 6 21 -28.0 -4.2 46.3 54.3 202 6 22 -48.1 19.8 50.3 72.4 203 6 23 -12.6 19.7 93.6 96.4 204 6 24 -14.3 34.1 59.9 70.4 205 6 25 -31.4 30.2 34.6 55.6 206 6 26 -49.5 -0.2 76.6 91.2 207 6 27 -77.2 3.0 45.5 89.6 208 6 28 -41.5 -2.4 58.1 71.5 209 6 29 -5.0 28.9 20.8 36.0 210 6 30 5.4 16.2 76.0 77.9 211 6 31 -22.6 10.4 -3.4 25.1 212 6 32 -20.2 -38.0 3.0 43.1 213 6 33 23.2 -19.0 -13.5 32.9 214 6 34 25.0 8.0 20.5 33.2 215 6 35 11.8 -20.7 0.1 23.8 216 6 36 20.5 47.1 9.2 52.1 217 6 37 0.8 13.0 -0.4 13.0 218 6 38 18.3 -3.9 5.8 19.6 219 6 39 16.8 6.8 15.7 23.9 220 6 40 24.9 20.4 14.5 35.4 221 6 41 17.2 21.7 -1.5 27.7 222 6 42 38.0 -0.4 -9.8 39.2 223 6 43 2.5 -10.7 -31.5 33.4 224 6 44 -7.1 -27.0 -27.7 39.3 225 6 45 -17.2 -10.4 -14.5 24.7 226 6 46 -26.9 -19.0 -19.2 38.1 227 6 47 -37.2 -35.1 -26.3 57.6 228 6 48 -29.6 -24.4 -26.1 46.4 229 7 1 -16.6 -12.6 -26.5 33.7 230 7 2 -39.4 -19.7 -31.4 54.1 231 7 3 -44.1 -23.5 -37.5 62.5 232 7 4 -44.8 -13.5 -35.2 58.5 233 7 5 -45.8 -26.7 -56.4 77.4 234 7 6 -31.9 -30.1 -41.3 60.3 235 7 7 -29.7 -35.2 -49.9 67.9 236 7 8 -15.8 -12.5 -66.3 69.3 237 7 9 9.6 -11.0 -20.9 25.5 238 7 10 7.2 -11.3 -31.9 34.6 239 7 11 -4.8 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0 12 4 -7 12 5 -7 12 6 -9 12 7 -6 12 8 -6 12 9 -12 12 10 -8 12 11 -10 12 12 -11 12 13 -8 12 14 -7 12 15 -7 12 16 -5 12 17 -5 12 18 -8 12 19 -5 12 20 0 12 21 -10 12 22 -4 12 23 -3 12 24 -5 12 25 -11 12 26 0 12 27 2 12 28 1 12 29 5 12 30 7 12 31 -11 12 32 -1 12 33 3 12 34 8 12 35 0 12 36 4 12 37 -5 12 38 2 12 39 3 12 40 0 12 41 0 12 42 7 12 43 -5 12 44 4 12 45 9 12 46 2 12 47 4 12 48 4 12 49 2 12 50 0 12 51 -6 12 52 0 12 53 -5 12 54 4 12 55 0 12 56 0 12 57 -1 12 58 3 12 59 13 12 60 4 12 61 0 12 62 -1 12 63 -5 12 64 0 12 65 6 12 66 -2 12 67 0 12 68 1 12 69 -3 Adjuster movements: rms = 26.9 micron Looking for bad motors No bad motor file specified Finished panel fit Evaluating simulated dish from adjuster moves Reduction ended at: 20050703-031122 Creating HTML output file of plots Plotting summary text Saving results to disk - level = 1