INFO : AT.py : Setting {'basename': 'x', 'file': 'NGC5194_90911_91112.nfs.fits'} for Ingest_AT
INFO : AT.py : Setting 'ppp' = True for CubeStats_AT
INFO : AT.py : Setting 'numsigma' = 4.0 for CubeSum_AT
INFO : AT.py : Setting 'sigma' = 99.0 for CubeSum_AT
INFO : AT.py : Setting 'numsigma' = 4.0 for SFind2D_AT
INFO : Admit.py : ADMIT run() called [flowcount 1]
INFO : 
INFO : 
INFO :    Executing Ingest_AT - '' (V1.2.13)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     box :  []
INFO :     file :  NGC5194_90911_91112.nfs.fits
INFO :     smooth :  []
INFO :     basename :  x
INFO :     mask :  True
INFO :     pb :  
INFO :     edge :  []
INFO :     restfreq :  -1.0
INFO :     vlsr :  -999999.9
INFO :     usepb :  True
INFO : 
TIMING : Ingest ADMIT [  2.25231700e+00   1.64394465e+09]
TIMING : Ingest BEGIN [ 0.  0.]
INFO : Ingest_AT.py : OBJECT: NGC5194   SHAPE: [153 219 590]
INFO : Ingest_AT.py : basename=x
INFO : utils.py : OSTYPE: linux
TIMING : Ingest start  [  3.55873000e-01   3.62476110e-01   1.41090234e+03   2.17226562e+02]
TIMING : Ingest importfits  [  2.60942000e-01   3.28392982e-01   1.41107031e+03   2.18714844e+02]
WARNING : Ingest_AT.py : Adding dummy STOKES-I axis
TIMING : Ingest adddegaxes  [  1.07814000e-01   3.08888912e-01   1.41226172e+03   2.20843750e+02]
TIMING : Ingest summary-0  [  1.81420000e-02   1.82759762e-02   1.41226172e+03   2.20843750e+02]
TIMING : Ingest mask  [  1.09429000e-01   1.46773100e-01   1.41226172e+03   2.20843750e+02]
TIMING : Ingest summary-1  [  1.83630000e-02   3.27129364e-02   1.41226172e+03   2.20843750e+02]
TIMING : Ingest statistics  [  1.42029000e-01   1.42364979e-01   1.41254688e+03   2.22164062e+02]
INFO : Ingest_AT.py : COMMONBEAM[3] {'major': {'value': 12.6500004, 'unit': 'arcsec'}, 'pa': {'value': 0.0, 'unit': 'deg'}, 'minor': {'value': 12.6500004, 'unit': 'arcsec'}}
INFO : Ingest_AT.py : BASICS: [shape] npts min max: [153 219 590   1] 9514930 -0.071791 0.613950
INFO : Ingest_AT.py : S/N (all data): 26.604922
INFO : Ingest_AT.py : GOOD PIXELS: 9514930/19769130 (48.130241% good or 51.869759% bad)
WARNING : Ingest_AT.py : MASKS: ['mask0']
REGRESSION : CUBE: -0.0717913 0.61395 0.0230765  153 219 590  51.869759
INFO : Ingest_AT.py : TELESCOPE: LMT
INFO : Ingest_AT.py : OBJECT: NGC5194
INFO : Ingest_AT.py : REFFREQTYPE: LSRK
INFO : Ingest_AT.py : RA   Axis 1: 202.469600 -5.500001 109.000000
INFO : Ingest_AT.py : DEC  Axis 2: 47.195170 5.500001 76.000000
INFO : Ingest_AT.py : VLSRv = 0.000000 (from source catalog)
INFO : Ingest_AT.py : VLSRz = 0.000000 +/- 0.000000   1 values: [ 0.]
INFO : Ingest_AT.py : Freq Orig Axis 3: 114.964 0.000390625 0
INFO : Ingest_AT.py : Cube Orig Axis 3: type=Frequency  velocity increment=-1.015921 km/s @ fc=115.078726 fw=0.230469 GHz
INFO : Ingest_AT.py : RESTFREQ: 115.271 115.271 -1
INFO : Ingest_AT.py : VLSRc= 500.589066  VLSRf= 0.000000  VLSRv= 0.000000 VLSRz= 0.000000 WIDTH= -599.393390
INFO : Ingest_AT.py : VLSR = 500.589066 errs = 0.000000 0.000000 0.000000 width = -1.015921
TIMING : Ingest done  [  6.52896000e-01   6.72649145e-01   1.41554688e+03   2.25515625e+02]
TIMING : Ingest END [ 1.677601    2.02467895]
INFO : AT.py : BDP_OUT[0] = SpwCube_BDP x.im
INFO : 
INFO : 
INFO :    Executing CubeStats_AT - '' (V1.2.3)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     ppp :  True
INFO :     psample :  -1
INFO :     robust :  []
INFO :     maxvrms :  2.0
INFO : 
TIMING : CubeStats ADMIT [  3.99067600e+00   1.64394465e+09]
TIMING : CubeStats BEGIN [ 0.  0.]
TIMING : CubeStats imval  [  5.19750000e-02   5.21888733e-02   1.41467578e+03   2.25039062e+02]
TIMING : CubeStats start  [  1.28790000e-02   1.29210949e-02   1.41467578e+03   2.25039062e+02]
TIMING : CubeStats imstat0  [  6.27666000e-01   6.29194975e-01   1.44626953e+03   2.57332031e+02]
TIMING : CubeStats imstat1  [  6.94958000e-01   6.96583033e-01   1.46189062e+03   2.73082031e+02]
INFO : CubeStats_AT.py : sigma varies from 0.005265 to 0.017665; 590/590 channels ok
WARNING : CubeStats_AT.py : sigma varies too much, going to clip to 0.0105305 (3.3551 > 2)
INFO : CubeStats_AT.py : Computing MaxPos for PeakPointPlot
TIMING : CubeStats ppp  [  1.02512000e+00   1.02868390e+00   1.42509375e+03   2.36343750e+02]
INFO : CubeStats_AT.py : CubeMax: 0.613950 @ [ 48  73 300   0]
INFO : CubeStats_AT.py : CubeMin: -0.071791 @ [ 11  29 322   0]
INFO : CubeStats_AT.py : CubeRMS: 0.012897
INFO : CubeStats_AT.py : RMS Sanity check 1.789236
WARNING : CubeStats_AT.py : RMS sanity check = 1.789236.  Either bad sidelobes, lotsa signal, or both
REGRESSION : CST: 0.012897 1.789236
INFO : CubeStats_AT.py : mean,rms,S/N=-0.004176 0.012897 47.602483
INFO : CubeStats_AT.py : RMS BAD VARIATION RATIO: 2.977430 3.940852
TIMING : CubeStats plotting  [    2.371305       2.54661012  1455.890625     265.36328125]
TIMING : CubeStats done  [  1.34410000e-02   1.34789944e-02   1.45589062e+03   2.65363281e+02]
TIMING : CubeStats summary  [  1.22490000e-02   1.22959614e-02   1.45589062e+03   2.65363281e+02]
TIMING : CubeStats END [ 4.821784    5.00418901]
INFO : AT.py : BDP_OUT[0] = CubeStats_BDP x.cst
INFO : 
INFO : 
INFO :    Executing CubeSum_AT - '' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     linesum :  True
INFO :     numsigma :  4.0
INFO :     zoom :  1
INFO :     pad :  5
INFO :     sigma :  99.0
INFO : 
TIMING : CubeSum ADMIT [  8.87244300e+00   1.64394465e+09]
TIMING : CubeSum BEGIN [ 0.  0.]
INFO : CubeSum_AT.py : Using constant sigma = 0.012897
TIMING : CubeSum start  [  5.17850000e-02   5.19330502e-02   1.45589062e+03   2.65363281e+02]
TIMING : CubeSum immoments  [  2.44717000e-01   2.72033930e-01   1.46339844e+03   2.73347656e+02]
TIMING : CubeSum statistics  [  2.01410000e-02   2.02100277e-02   1.46339844e+03   2.73347656e+02]
INFO : CubeSum_AT.py : Total flux: 432972.084548 (sum=14313.122598)
REGRESSION : CSM: [432972.08454820589, 14313.122598106376]
TIMING : CubeSum implot  [  1.65660000e-01   6.16575789e+00   1.53540234e+03   2.73386719e+02]
TIMING : CubeSum getdata  [  2.69350000e-02   2.70171165e-02   1.53540234e+03   2.73386719e+02]
TIMING : CubeSum done  [  2.67774000e-01   2.86773920e-01   1.53540234e+03   2.73449219e+02]
TIMING : CubeSum END [ 0.791085    6.83783388]
INFO : AT.py : BDP_OUT[0] = Moment_BDP x.csm
INFO : 
INFO : 
INFO :    Executing SFind2D_AT - 'csm' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     nmax :  30
INFO :     numsigma :  4.0
INFO :     snmax :  35.0
INFO :     region :  
INFO :     zoom :  1
INFO :     robust :  ['hin', 1.5]
INFO :     sigma :  -1.0
INFO : 
TIMING : SFind2D ADMIT [  9.72396300e+00   1.64394466e+09]
TIMING : SFind2D BEGIN [ 0.  0.]
TIMING : SFind2D start  [  3.45290000e-02   3.46369743e-02   1.53540234e+03   2.73449219e+02]
TIMING : SFind2D imstat  [  4.31140000e-02   4.32989597e-02   1.53540234e+03   2.73449219e+02]
INFO : AT.py : Setting 'sigma' = 2.34048685306 for SFind2D_AT
INFO : SFind2D_AT.py : sigma, dmin, dmax, snmax, cutoff 2.34049 -0.79739 34.2636 35 0.273233
WARNING : SFind2D_AT.py : Temporarely patching your K.km/s units to Jy/beam for ia.findsources()
TIMING : SFind2D findsources  [  2.59480000e-01   2.67296076e-01   1.53540234e+03   2.73449219e+02]
INFO : SFind2D_AT.py : Right Ascen.  Declination   X(pix)   Y(pix)      Peak       Flux    Major   Minor    PA    SNR
INFO : SFind2D_AT.py :                                                K.km/s       Jy    arcsec   arcsec   deg
INFO : SFind2D_AT.py : 13:30:27.010 +47.11.34.59    45.42    74.60       28.9   1.03e+03  96.508  52.540  179.9   12.3
INFO : SFind2D_AT.py : 13:30:14.917 +47.10.33.62    67.82    63.48          0   9.02e+03 270.874  82.385   60.8    0.0
INFO : SFind2D_AT.py : 13:30:30.305 +47.10.49.14    39.30    66.35       18.5       88.5  27.500  27.500    0.1    7.9
INFO : SFind2D_AT.py : 13:30:30.073 +47.09.50.69    39.71    55.72       1.37   7.72e+03 232.419  94.428  170.3    0.6
INFO : SFind2D_AT.py : 13:30:35.937 +47.13.04.67    28.91    91.01       10.4        231  96.325  35.572  148.1    4.4
INFO : SFind2D_AT.py : 13:30:20.486 +47.10.18.18    57.49    60.69       8.54        202  72.990  46.833  149.4    3.6
INFO : SFind2D_AT.py : Wrote ds9.reg
TIMING : SFind2D table  [  2.70315000e-01   2.74994135e-01   1.53540234e+03   2.74210938e+02]
REGRESSION : CONTFLUX: 6 18286.3
INFO : SFind2D_AT.py :  Fitted Gaussian size; NOT deconvolved source size.
INFO : SFind2D_AT.py :  Restoring Beam: Major axis:       12.7 arcsec , Minor axis:       12.7 arcsec , PA:   0.0 deg
TIMING : SFind2D done  [  2.87347000e-01   3.05895805e-01   1.53540234e+03   2.74210938e+02]
TIMING : SFind2D END [ 0.908174    0.93955302]
INFO : AT.py : BDP_OUT[0] = SourceList_BDP x-csm.sl
TIMING : ADMITrun END [  8.801665    15.47172189]
INFO : Admit.py : ADMIT run() finished [flowcount 1] [cpu 8.80166 15.4717 ]
INFO : AT.py : Setting 'csub' = [0, 0] for LineSegment_AT
INFO : Admit.py : ADMIT run() called [flowcount 1]
INFO : 
INFO : 
INFO :    Executing CubeSpectrum_AT - '' (V1.2.5)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     xaxis :  
INFO :     sources :  [0]
INFO :     pos :  []
INFO : 
TIMING : CubeSpectrum ADMIT [  1.08443470e+01   1.64394466e+09]
TIMING : CubeSpectrum BEGIN [ 0.  0.]
INFO : CubeSpectrum_AT.py : CubeStats::maxpos,val=[48, 73, 300],0.613950
TIMING : CubeSpectrum CubeStats-pos  [  4.83800000e-02   4.85031605e-02   1.53540234e+03   2.74210938e+02]
INFO : CubeSpectrum_AT.py : CubeSum::maxpos,val=[47, 74],34.263611
TIMING : CubeSpectrum Moment-pos  [  4.37460000e-02   4.38718796e-02   1.53540234e+03   2.74210938e+02]
INFO : CubeSpectrum_AT.py : SourceList::maxpos,val=('13h30m27.010s', '+47d11m34.59s'),28.883375
TIMING : CubeSpectrum SourceList-pos  [  3.59700000e-02   3.60641479e-02   1.53540234e+03   2.74210938e+02]
TIMING : CubeSpectrum open  [  1.21860000e-02   1.22208595e-02   1.53540234e+03   2.74210938e+02]
TIMING : CubeSpectrum imval  [  4.36600000e-02   4.38420773e-02   1.53540234e+03   2.74683594e+02]
TIMING : CubeSpectrum imhead  [  4.17920000e-02   4.19170856e-02   1.53540234e+03   2.74683594e+02]
TIMING : CubeSpectrum imval  [  2.48539000e-01   2.66919851e-01   1.53540234e+03   2.74785156e+02]
TIMING : CubeSpectrum imval  [  2.63555000e-01   2.82161951e-01   1.53540234e+03   2.74785156e+02]
REGRESSION : CSP: [0.61394959688186646, 0.59777951240539551, 0.36016166210174561]
INFO : CubeSpectrum_AT.py : Writing 3 testCubeSpectrum tables
TIMING : CubeSpectrum done  [  2.66725000e-01   2.85752058e-01   1.53540234e+03   2.74785156e+02]
TIMING : CubeSpectrum summary  [  1.24810000e-02   1.25110149e-02   1.53540234e+03   2.74785156e+02]
TIMING : CubeSpectrum END [ 1.02924     1.08600307]
INFO : AT.py : BDP_OUT[0] = CubeSpectrum_BDP x.csp
INFO : 
INFO : 
INFO :    Executing LineSegment_AT - '' (V1.2.3)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     numsigma :  5.0
INFO :     minchan :  4
INFO :     edgechannels :  0
INFO :     smooth :  []
INFO :     recalcnoise :  False
INFO :     maxgap :  3
INFO :     csub :  [0, 0]
INFO :     iterate :  True
INFO :     segment :  ADMIT
INFO : 
TIMING : LineSegment ADMIT [  1.19340030e+01   1.64394466e+09]
TIMING : LineSegment BEGIN [ 0.  0.]
TIMING : LineSegment start  [  2.43310000e-02   2.43968964e-02   1.53540234e+03   2.74785156e+02]
INFO : LineSegment_AT.py : Attempting Continuum Subtraction for Input Spectra
INFO : LineSegment_AT.py : Attempting Continuum Subtraction for Input CubeStats Spectra
TIMING : LineSegment getspectrum  [   23.173768      23.23115301  1535.40234375   275.25390625]
INFO : LineSegment_AT.py : Detecting segments in CubeSpectrum based data
WARNING : specutil.py : 0 [26, 33]
WARNING : specutil.py : 1 [53, 65]
WARNING : specutil.py : 2 [246, 350]
WARNING : specutil.py : 3 [410, 413]
WARNING : specutil.py : 4 [426, 431]
WARNING : specutil.py : 0 [19, 22]
WARNING : specutil.py : 1 [27, 43]
WARNING : specutil.py : 2 [53, 65]
WARNING : specutil.py : 3 [246, 365]
WARNING : specutil.py : 4 [404, 417]
WARNING : specutil.py : 5 [427, 431]
WARNING : specutil.py : 0 [7, 13]
WARNING : specutil.py : 1 [19, 44]
WARNING : specutil.py : 2 [54, 66]
WARNING : specutil.py : 3 [235, 397]
WARNING : specutil.py : 4 [410, 420]
WARNING : specutil.py : 5 [431, 434]
INFO : LineSegment_AT.py : Detecting segments in CubeStats based data
WARNING : specutil.py : 0 [123, 130]
WARNING : specutil.py : 1 [137, 163]
WARNING : specutil.py : 2 [188, 198]
WARNING : specutil.py : 3 [202, 207]
WARNING : specutil.py : 4 [223, 417]
WARNING : specutil.py : 0 [2, 26]
WARNING : specutil.py : 1 [30, 42]
WARNING : specutil.py : 2 [53, 81]
WARNING : specutil.py : 3 [135, 139]
WARNING : specutil.py : 4 [301, 385]
WARNING : specutil.py : 5 [390, 393]
WARNING : specutil.py : 6 [398, 423]
TIMING : LineSegment segment finder  [    5.510325       5.5309732   1535.40234375   275.25390625]
INFO : LineSegment_AT.py :  Segment Coverage 236 / 590 = 0.4
REGRESSION : LINESEG: [[115.01173363598141, 115.01446801116663], [115.01720238635185, 115.02735863703982], [115.03712426270134, 115.04103051296595], [115.04259301307178, 115.04454613820408], [115.05079613862746, 115.12657739376077], [114.9644680077797, 114.97384300841475], [114.97540550852058, 114.98009300883813], [114.98438988412919, 114.99532738487007], [115.01642113629893, 115.01798363640476], [115.08126489069136, 115.11407739291403], [115.11603051804634, 115.11720239312572], [115.11915551825803, 115.12892114391954], [114.97384300841475, 114.97657738359997], [114.98438988412919, 114.9890773844467], [115.05978051423604, 115.10040551698793], [115.12384301857554, 115.12501489365492], [115.13009301899892, 115.13204614413121], [114.97110863322952, 114.9722805083089], [114.9742336334412, 114.98048363386458], [114.98438988412919, 114.9890773844467], [115.05978051423604, 115.10626489238483], [115.12149926841678, 115.12657739376077], [115.13048364402538, 115.13204614413121], [114.966421132912, 114.96876488307076], [114.97110863322952, 114.98087425889103], [114.98478050915564, 114.98946800947316], [115.05548363894498, 115.11876489323157], [115.12384301857554, 115.12774926884015], [115.13204614413121, 115.1332180192106]]
TIMING : LineSegment done  [    2.288865       2.418962    1556.05078125   295.67578125]
TIMING : LineSegment END [ 31.009711  31.217942]
INFO : AT.py : BDP_OUT[0] = LineSegment_BDP x.lseg
TIMING : ADMITrun END [ 41.121848    48.11435795]
INFO : Admit.py : ADMIT run() finished [flowcount 1] [cpu 41.1218 48.1144 ]
INFO : Admit.py : ADMIT run() called [flowcount 1]
TIMING : ADMITrun END [ 41.222165    48.29479694]
INFO : Admit.py : ADMIT run() finished [flowcount 1] [cpu 41.2222 48.2948 ]
INFO : AT.py : Setting 'csub' = [0, 0] for LineID_AT
INFO : AT.py : Setting 'references' = etc/tier1_lines.list for LineID_AT
INFO : Admit.py : ADMIT run() called [flowcount 1]
INFO : 
INFO : 
INFO :    Executing LineID_AT - '' (V1.2.7)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     numsigma :  5.0
INFO :     force :  []
INFO :     tier1width :  0.0
INFO :     online :  False
INFO :     recomblevel :  shallow
INFO :     references :  etc/tier1_lines.list
INFO :     csub :  [0, 0]
INFO :     identifylines :  True
INFO :     iterate :  True
INFO :     segment :  ADMIT
INFO :     allowexotics :  False
INFO :     minchan :  4
INFO :     pattern :  AUTO
INFO :     edgechannels :  0
INFO :     smooth :  []
INFO :     recalcnoise :  False
INFO :     vlsr :  -999999.99
INFO :     maxgap :  3
INFO :     reject :  []
INFO :     method :  {'PeakFinder': {'thresh': 0.0}}
INFO :     mode :  ONE
INFO : 
TIMING : LineID ADMIT [  4.32885450e+01   1.64394469e+09]
TIMING : LineID BEGIN [ 0.  0.]
INFO : LineID_AT.py : Set vlsr = 500.59 for line identification.
INFO : LineID_AT.py : Identifylines = True
INFO : LineID_AT.py : Using vlsr = 500.589
INFO : LineID_AT.py : Attempting Continuum Subtraction for Input Spectra
TIMING : LineID getspectrum-cubespecs  [   15.056401      15.09721708  1556.05078125   295.87109375]
INFO : LineID_AT.py : Attempting Continuum Subtraction for Input CubeStats Spectra
TIMING : LineID getspectrum-cubestats  [    8.359593       8.37999392  1556.05078125   295.87109375]
TIMING : LineID segment finder  [  1.41790000e-02   1.42269135e-02   1.55605078e+03   2.95871094e+02]
INFO : LineID_AT.py : Detecting segments in CubeSpectrum based data
WARNING : specutil.py : 0 [26, 33]
WARNING : specutil.py : 1 [53, 65]
WARNING : specutil.py : 2 [246, 350]
WARNING : specutil.py : 3 [410, 413]
WARNING : specutil.py : 4 [426, 431]
WARNING : specutil.py : 0 [19, 22]
WARNING : specutil.py : 1 [27, 43]
WARNING : specutil.py : 2 [53, 65]
WARNING : specutil.py : 3 [246, 365]
WARNING : specutil.py : 4 [404, 417]
WARNING : specutil.py : 5 [427, 431]
WARNING : specutil.py : 0 [7, 13]
WARNING : specutil.py : 1 [19, 44]
WARNING : specutil.py : 2 [54, 66]
WARNING : specutil.py : 3 [235, 397]
WARNING : specutil.py : 4 [410, 420]
WARNING : specutil.py : 5 [431, 434]
INFO : LineID_AT.py : Detecting segments in CubeStats based data
WARNING : specutil.py : 0 [123, 130]
WARNING : specutil.py : 1 [137, 163]
WARNING : specutil.py : 2 [188, 198]
WARNING : specutil.py : 3 [202, 207]
WARNING : specutil.py : 4 [223, 417]
WARNING : specutil.py : 0 [2, 26]
WARNING : specutil.py : 1 [30, 42]
WARNING : specutil.py : 2 [53, 81]
WARNING : specutil.py : 3 [135, 139]
WARNING : specutil.py : 4 [301, 385]
WARNING : specutil.py : 5 [390, 393]
WARNING : specutil.py : 6 [398, 423]
INFO : LineID_AT.py : Searching for spectral peaks with method: PeakFinder
INFO : LineID_AT.py : Found 1 potential pattern(s) with separation(s) of 71.2 km/s
INFO : LineID_AT.py : Found 1 potential pattern(s) with separation(s) of 59.0 km/s
INFO : LineID_AT.py :  Found line: NS J=5/2-3/2,&Omega=1/2,F=7/2-5/2,l=e @ 115.15394GHz, channels 44 - 44
REGRESSION : LINEID: NS 115.15394  44 44
INFO : LineID_AT.py :  Found line: CO 1-0 @ 115.2712GHz, channels 2 - 434
REGRESSION : LINEID: CO 115.27120  2 434
INFO : LineID_AT.py :  Line Coverage 433 / 590 = 0.733898
TIMING : LineID done  [   19.173904      19.96034217  1657.0234375    397.8203125 ]
TIMING : LineID END [ 42.618262    43.46599793]
INFO : AT.py : BDP_OUT[0] = LineList_BDP x.ll
TIMING : ADMITrun END [ 84.164564    92.19555187]
INFO : Admit.py : ADMIT run() finished [flowcount 1] [cpu 84.1646 92.1956 ]
INFO : Admit.py : ADMIT run() called [flowcount 1]
INFO : 
INFO : 
INFO :    Executing LineCube_AT - '' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     equalize :  False
INFO :     pad :  5
INFO :     fpad :  -1.0
INFO : 
TIMING : LineCube ADMIT [  8.61834730e+01   1.64394474e+09]
TIMING : LineCube BEGIN [ 0.  0.]
TIMING : LineCube start  [  1.61378000e-01   1.61865950e-01   1.60758594e+03   3.48761719e+02]
TIMING : LineCube pad  [  1.35770000e-02   1.36208534e-02   1.60758594e+03   3.48761719e+02]
TIMING : LineCube trans-x.NS_115.15394  [  7.79310000e-02   1.86072111e-01   1.60758594e+03   3.48824219e+02]
WARNING : LineCube_AT.py : pad=5 too large, start=-3 resetting to 0
TIMING : LineCube trans-x.CO_115.27120  [  1.72654000e-01   2.74518013e-01   1.60758594e+03   3.48824219e+02]
REGRESSION : LC: [39, 49, 0, 439]
TIMING : LineCube done  [  2.49650000e-02   2.50399113e-02   1.60758594e+03   3.48824219e+02]
TIMING : LineCube END [ 0.462954    0.67360687]
INFO : AT.py : BDP_OUT[0] = LineCube_BDP x.NS_115.15394/lc.im
INFO : AT.py : BDP_OUT[1] = LineCube_BDP x.CO_115.27120/lc.im
TIMING : ADMITrun END [ 84.826111    93.12617207]
INFO : Admit.py : ADMIT run() finished [flowcount 1] [cpu 84.8261 93.1262 ]
INFO : AT.py : Setting 'moments' = [0, 1, 2] for Moment_AT
INFO : AT.py : Setting 'mom0clip' = 2.0 for Moment_AT
INFO : AT.py : Setting 'moments' = [0, 1, 2] for Moment_AT
INFO : AT.py : Setting 'mom0clip' = 2.0 for Moment_AT
INFO : AT.py : Setting 'numsigma' = [3.0] for Moment_AT
INFO : AT.py : Setting 'mom0clip' = 2.0 for Moment_AT
INFO : Admit.py : ADMIT run() called [flowcount 1]
INFO : 
INFO : 
INFO :    Executing Moment_AT - '@2' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     numsigma :  [3.0]
INFO :     moments :  [0]
INFO :     mom0clip :  2.0
INFO :     zoom :  1
INFO :     chans :  
INFO :     sigma :  -1.0
INFO : 
TIMING : Moment ADMIT [  8.69903370e+01   1.64394474e+09]
TIMING : Moment BEGIN [ 0.  0.]
TIMING : Moment open  [  4.92720000e-02   4.94039059e-02   1.60758594e+03   3.48824219e+02]
TIMING : Moment immoments-0  [  2.34417000e-01   3.17876101e-01   1.62652344e+03   3.67636719e+02]
TIMING : Moment mom0clip  [  7.06970000e-02   1.27964020e-01   1.62652344e+03   3.67789062e+02]
TIMING : Moment implot  [  9.61730000e-02   4.04346943e-01   1.62652344e+03   3.67789062e+02]
TIMING : Moment getdata  [  2.14980000e-02   2.15790272e-02   1.62652344e+03   3.67789062e+02]
TIMING : Moment ren+mask_0  [  3.21047000e-01   3.26206923e-01   1.63201172e+03   3.73339844e+02]
TIMING : Moment done  [  1.51620000e-02   1.52029991e-02   1.63201172e+03   3.73339844e+02]
TIMING : Moment END [ 0.820675    1.27505803]
INFO : AT.py : BDP_OUT[0] = Moment_BDP x-@2.mom_0
INFO : 
INFO : 
INFO :    Executing Moment_AT - '' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     numsigma :  [2.0]
INFO :     moments :  [0, 1, 2]
INFO :     mom0clip :  2.0
INFO :     zoom :  1
INFO :     chans :  
INFO :     sigma :  -1.0
INFO : 
TIMING : Moment ADMIT [  8.78720470e+01   1.64394474e+09]
TIMING : Moment BEGIN [ 0.  0.]
TIMING : Moment open  [  4.86780000e-02   4.87999916e-02   1.63201172e+03   3.73339844e+02]
TIMING : Moment immoments-all  [  8.52900000e-02   2.96682119e-01   1.63201172e+03   3.73339844e+02]
TIMING : Moment mom0clip  [  6.97440000e-02   1.57192945e-01   1.63201172e+03   3.73339844e+02]
TIMING : Moment implot  [  9.30270000e-02   3.94670010e-01   1.63201172e+03   3.73339844e+02]
TIMING : Moment getdata  [  2.10770000e-02   2.11589336e-02   1.63201172e+03   3.73339844e+02]
TIMING : Moment ren+mask_0  [  2.57748000e-01   2.62533188e-01   1.63201172e+03   3.73339844e+02]
TIMING : Moment makemask  [  1.53543000e-01   4.61951017e-01   1.63201172e+03   3.73496094e+02]
TIMING : Moment implot  [  7.62360000e-02   3.43512774e-01   1.63201172e+03   3.73496094e+02]
TIMING : Moment getdata  [  2.08550000e-02   2.09300518e-02   1.63201172e+03   3.73496094e+02]
TIMING : Moment ren+mask_1  [  2.49057000e-01   2.54147053e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment makemask  [  1.52778000e-01   7.54456997e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment implot  [  7.66120000e-02   3.36884022e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment getdata  [  2.08020000e-02   2.08768845e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment ren+mask_2  [  2.49188000e-01   2.53977060e-01   1.63201172e+03   3.74070312e+02]
REGRESSION : MOM0FLUX: x.NS_115.15394 -722.166 0.164963 0.0330578 448.975 448.975 0
TIMING : Moment mom0flux  [  5.27800000e-02   5.29551506e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment flux-spectrum  [  2.62318000e-01   2.67252922e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment done  [  1.48440000e-02   1.48859024e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment END [ 1.916919    3.97526717]
INFO : AT.py : BDP_OUT[0] = Moment_BDP x.NS_115.15394/lc.mom_0
INFO : AT.py : BDP_OUT[1] = Moment_BDP x.NS_115.15394/lc.mom_1
INFO : AT.py : BDP_OUT[2] = Moment_BDP x.NS_115.15394/lc.mom_2
INFO : 
INFO : 
INFO :    Executing Moment_AT - '@1' (V1.2.2)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     numsigma :  [2.0]
INFO :     moments :  [0, 1, 2]
INFO :     mom0clip :  2.0
INFO :     zoom :  1
INFO :     chans :  
INFO :     sigma :  -1.0
INFO : 
TIMING : Moment ADMIT [  8.98977540e+01   1.64394474e+09]
TIMING : Moment BEGIN [ 0.  0.]
TIMING : Moment open  [  4.87320000e-02   4.88581657e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment immoments-all  [  2.21084000e-01   4.07202005e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment mom0clip  [  6.92130000e-02   1.35409832e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment implot  [  9.30320000e-02   4.00663137e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment getdata  [  2.09730000e-02   2.10449696e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment ren+mask_0  [  2.53246000e-01   2.58024931e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment makemask  [  1.52414000e-01   5.67255974e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment implot  [  7.66210000e-02   3.37581158e-01   1.63201172e+03   3.74070312e+02]
TIMING : Moment getdata  [  2.06580000e-02   2.07269192e-02   1.63201172e+03   3.74070312e+02]
TIMING : Moment ren+mask_1  [  2.49103000e-01   2.53901958e-01   1.63201172e+03   3.74074219e+02]
TIMING : Moment makemask  [  1.52836000e-01   4.44516897e-01   1.63201172e+03   3.74074219e+02]
TIMING : Moment implot  [  7.62260000e-02   3.31980228e-01   1.63201172e+03   3.74074219e+02]
TIMING : Moment getdata  [  2.07250000e-02   2.07967758e-02   1.63201172e+03   3.74074219e+02]
TIMING : Moment ren+mask_2  [  2.59819000e-01   2.64536142e-01   1.63201172e+03   3.74074219e+02]
REGRESSION : MOM0FLUX: x.CO_115.27120 -9343.24 7159.62 0.0330578 459.449 459.449 51.1695
TIMING : Moment mom0flux  [  5.26160000e-02   5.27708530e-02   1.63201172e+03   3.74074219e+02]
TIMING : Moment flux-spectrum  [  7.40899000e-01   7.47032166e-01   1.63201172e+03   3.74074219e+02]
TIMING : Moment done  [  1.48400000e-02   1.48789883e-02   1.63201172e+03   3.74074219e+02]
TIMING : Moment END [ 2.535438    4.33963799]
INFO : AT.py : BDP_OUT[0] = Moment_BDP x.CO_115.27120/lc-@1.mom_0
INFO : AT.py : BDP_OUT[1] = Moment_BDP x.CO_115.27120/lc-@1.mom_1
INFO : AT.py : BDP_OUT[2] = Moment_BDP x.CO_115.27120/lc-@1.mom_2
INFO : 
INFO : 
INFO :    Executing CubeSpectrum_AT - '@1' (V1.2.5)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     xaxis :  
INFO :     sources :  [0]
INFO :     pos :  []
INFO : 
TIMING : CubeSpectrum ADMIT [  9.25423480e+01   1.64394475e+09]
TIMING : CubeSpectrum BEGIN [ 0.  0.]
INFO : CubeSpectrum_AT.py : CubeSum::maxpos,val=[95, 98],0.164963
TIMING : CubeSpectrum Moment-pos  [  5.51320000e-02   5.52909374e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum open  [  1.23490000e-02   1.23829842e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum imval  [  3.61000000e-02   3.62870693e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum imhead  [  4.24020000e-02   4.25598621e-02   1.63201172e+03   3.74074219e+02]
REGRESSION : CSP: [0.028777245432138443]
INFO : CubeSpectrum_AT.py : Writing 1 testCubeSpectrum tables
TIMING : CubeSpectrum done  [  2.50446000e-01   2.55548000e-01   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum summary  [  1.25000000e-02   1.25410557e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum END [ 0.421264    0.42697883]
INFO : AT.py : BDP_OUT[0] = CubeSpectrum_BDP x.NS_115.15394/lc-@1.csp
INFO : 
INFO : 
INFO :    Executing CubeSpectrum_AT - '@2' (V1.2.5)
INFO : 
INFO : 
INFO :   Run using the following settings:
INFO :     xaxis :  
INFO :     sources :  [0]
INFO :     pos :  []
INFO : 
TIMING : CubeSpectrum ADMIT [  9.30243590e+01   1.64394475e+09]
TIMING : CubeSpectrum BEGIN [ 0.  0.]
INFO : CubeSpectrum_AT.py : CubeSum::maxpos,val=[47, 73],33.723354
TIMING : CubeSpectrum Moment-pos  [  5.52050000e-02   5.53560257e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum open  [  1.24070000e-02   1.24440193e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum imval  [  3.92470000e-02   3.94439697e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum imhead  [  4.27120000e-02   4.28769588e-02   1.63201172e+03   3.74074219e+02]
REGRESSION : CSP: [0.60351389646530151]
INFO : CubeSpectrum_AT.py : Writing 1 testCubeSpectrum tables
TIMING : CubeSpectrum done  [  2.59789000e-01   2.64760971e-01   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum summary  [  1.25930000e-02   1.26290321e-02   1.63201172e+03   3.74074219e+02]
TIMING : CubeSpectrum END [ 0.43438     0.43997097]
INFO : AT.py : BDP_OUT[0] = CubeSpectrum_BDP x.CO_115.27120/lc-@2.csp