Copying data files and other necessary files
Changing to reduced data directory
Generating file lists...
Setting dispaxis...
add 120827.0001.fits,dispaxis = 1
120827.0001.fits updated
add 120827.0002.fits,dispaxis = 1
120827.0002.fits updated
add 120827.0003.fits,dispaxis = 1
120827.0003.fits updated
add 120827.0004.fits,dispaxis = 1
120827.0004.fits updated
add 120827.0005.fits,dispaxis = 1
120827.0005.fits updated
add 120827.0006.fits,dispaxis = 1
120827.0006.fits updated
add 120827.0007.fits,dispaxis = 1
120827.0007.fits updated
add 120827.0008.fits,dispaxis = 1
120827.0008.fits updated
add 120827.0009.fits,dispaxis = 1
120827.0009.fits updated
add 120827.0010.fits,dispaxis = 1
120827.0010.fits updated
add 120827.0011.fits,dispaxis = 1
120827.0011.fits updated
add 120827.0012.fits,dispaxis = 1
120827.0012.fits updated
add 120827.0013.fits,dispaxis = 1
120827.0013.fits updated
add 120827.0014.fits,dispaxis = 1
120827.0014.fits updated
add 120827.0015.fits,dispaxis = 1
120827.0015.fits updated
add 120827.0016.fits,dispaxis = 1
120827.0016.fits updated
add 120827.0017.fits,dispaxis = 1
120827.0017.fits updated
add 120827.0018.fits,dispaxis = 1
120827.0018.fits updated
add 120827.0019.fits,dispaxis = 1
120827.0019.fits updated
add 120827.0020.fits,dispaxis = 1
120827.0020.fits updated
add 120827.0021.fits,dispaxis = 1
120827.0021.fits updated
add 120827.0022.fits,dispaxis = 1
120827.0022.fits updated
add 120827.0023.fits,dispaxis = 1
120827.0023.fits updated
add 120827.0024.fits,dispaxis = 1
120827.0024.fits updated
add 120827.0025.fits,dispaxis = 1
120827.0025.fits updated
add 120827.0026.fits,dispaxis = 1
120827.0026.fits updated
add 120827.0027.fits,dispaxis = 1
120827.0027.fits updated
add 120827.0028.fits,dispaxis = 1
120827.0028.fits updated
add 120827.0029.fits,dispaxis = 1
120827.0029.fits updated
add 120827.0030.fits,dispaxis = 1
120827.0030.fits updated
FIXPIX: image 120827.0005.fits with mask echmask.pl
FIXPIX: image 120827.0006.fits with mask echmask.pl
FIXPIX: image 120827.0007.fits with mask echmask.pl
FIXPIX: image 120827.0008.fits with mask echmask.pl
FIXPIX: image 120827.0009.fits with mask echmask.pl
FIXPIX: image 120827.0010.fits with mask echmask.pl
FIXPIX: image 120827.0021.fits with mask echmask.pl
FIXPIX: image 120827.0022.fits with mask echmask.pl
FIXPIX: image 120827.0023.fits with mask echmask.pl
FIXPIX: image 120827.0024.fits with mask echmask.pl
FIXPIX: image 120827.0025.fits with mask echmask.pl
FIXPIX: image 120827.0026.fits with mask echmask.pl
FIXPIX: image 120827.0027.fits with mask echmask.pl
FIXPIX: image 120827.0028.fits with mask echmask.pl
FIXPIX: image 120827.0029.fits with mask echmask.pl
FIXPIX: image 120827.0030.fits with mask echmask.pl
FIXPIX: image 120827.0001.fits with mask echmask.pl
FIXPIX: image 120827.0002.fits with mask echmask.pl
FIXPIX: image 120827.0003.fits with mask echmask.pl
FIXPIX: image 120827.0004.fits with mask echmask.pl

Dec 10 12:56: IMCOMBINE
  combine = median, scale = none, zero = none, weight = none
  blank = 0.
                Images     Exp
       120827.0011.fits    0.0
       120827.0012.fits    0.0
       120827.0013.fits    0.9
       120827.0014.fits    0.0
       120827.0015.fits    0.9
       120827.0016.fits    0.0
       120827.0017.fits    0.9
       120827.0018.fits    0.0
       120827.0019.fits    0.9
       120827.0020.fits    0.0

  Output image = bias_fid, ncombine = 10
Calibrating object images and flats (bias, and trimming)...
120827.0021.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
bias_fid: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0021.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0022.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0022.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0023.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0023.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0024.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0024.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0025.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0025.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0026.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0026.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0027.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0027.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0028.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0028.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0029.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0029.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0030.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0030.fits: Dec 10 12:56 Zero level correction image is bias_fid
Calibrating object images and flats (bias, and trimming)...
120827.0005.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0005.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0006.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0006.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0007.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0007.fits: Dec 10 12:56 Zero level correction image is bias_fid
Calibrating object images and flats (bias, and trimming)...
120827.0008.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0008.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0009.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0009.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0010.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0010.fits: Dec 10 12:56 Zero level correction image is bias_fid
Calibrating ThAr arcs...
120827.0001.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0001.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0002.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0002.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0003.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0003.fits: Dec 10 12:56 Zero level correction image is bias_fid
120827.0004.fits: Dec 10 12:56 Trim data section is [200:1850,1:2048]
120827.0004.fits: Dec 10 12:56 Zero level correction image is bias_fid
Combining red and blue flats into separate fiducial flats...

Dec 10 12:57: IMCOMBINE
  combine = median, scale = none, zero = none, weight = none
  reject = avsigclip, mclip = yes, nkeep = 1
  lsigma = 3., hsigma = 3.
  blank = 1.
                Images     Exp
       120827.0008.fits  200.0
       120827.0009.fits  200.0
       120827.0010.fits  200.0

  Output image = flat_blue_mean.fits, ncombine = 3

Dec 10 12:57: IMCOMBINE
  combine = median, scale = none, zero = none, weight = none
  reject = avsigclip, mclip = yes, nkeep = 1
  lsigma = 3., hsigma = 3.
  blank = 1.
                Images     Exp
       120827.0005.fits    7.0
       120827.0006.fits    7.0
       120827.0007.fits    7.0

  Output image = flat_red_mean.fits, ncombine = 3
Combining average red and blue flats into a superflat...
IMARITH:
  Operation = *
  Operand1 = flat_red_mean.fits
  Operand2 = filter_redflat.fit
  Result = flat_red_mean_filt.fits
  Result pixel type = double
  Calculation type = double
IMARITH:
  Operation = +
  Operand1 = flat_blue_mean.fits
  Operand2 = flat_red_mean_filt.fits
  Result = junk
  Result pixel type = double
  Calculation type = double
IMARITH:
  Operation = /
  Operand1 = junk
  Operand2 = 2.0
  Result = flat_fid
  Result pixel type = double
  Calculation type = double
  Replacement value for division by zero  = 0.
Resample the superflat in the y direction...

flat_fid_mag.fits
  Magnify image flat_fid.fits to image flat_fid_mag.fits.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
flat_fid_mag.fits,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
flat_fid_mag.fits updated
Modeling and extracting the superflat...
Dec 10 12:57: TRACE - Trace of aperture 100 in flat_fid_mag lost at column 1614.
Dec 10 12:57: TRACE - Trace of aperture 100 in flat_fid_mag recovered at column 1615.
Dec 10 12:57: TRACE - Trace of aperture 100 in flat_fid_mag lost at column 1641.
Dec 10 12:57: TRACE - Trace of aperture 100 in flat_fid_mag lost at column 1642.
Dec 10 12:57: TRACE - Trace of aperture 100 in flat_fid_mag lost at column 1643.
Dec 10 12:57: TRACE - Trace of aperture 103 in flat_fid_mag lost at column 1624.
Dec 10 12:57: TRACE - Trace of aperture 103 in flat_fid_mag lost at column 1625.
Dec 10 12:57: TRACE - Trace of aperture 103 in flat_fid_mag lost at column 1626.
Dec 10 12:57: TRACE - Trace of aperture 103 in flat_fid_mag lost at column 141.
Dec 10 12:57: TRACE - Trace of aperture 103 in flat_fid_mag recovered at column 140.
Dec 10 12:57: TRACE - Trace of aperture 104 in flat_fid_mag lost at column 181.
Dec 10 12:57: TRACE - Trace of aperture 104 in flat_fid_mag lost at column 180.
Dec 10 12:57: TRACE - Trace of aperture 104 in flat_fid_mag lost at column 179.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 1575.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag recovered at column 1576.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 1600.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 1601.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 1602.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 180.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 179.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag recovered at column 178.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag lost at column 144.
Dec 10 12:57: TRACE - Trace of aperture 105 in flat_fid_mag recovered at column 143.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1475.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 1476.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1478.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 1479.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1585.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1586.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 1587.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1611.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 1612.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1614.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1615.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 1616.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 169.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 168.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 155.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 154.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 136.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag lost at column 135.
Dec 10 12:57: TRACE - Trace of aperture 106 in flat_fid_mag recovered at column 134.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 1542.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 1543.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 1607.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 1608.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 1609.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 204.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 203.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 202.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 187.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 186.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 185.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 158.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 157.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 146.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 145.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 144.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag lost at column 89.
Dec 10 12:57: TRACE - Trace of aperture 107 in flat_fid_mag recovered at column 88.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 1453.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 1454.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 1455.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 1464.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 1465.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 1466.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 226.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 225.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 192.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 191.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 149.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 148.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 135.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 134.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 128.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 127.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 126.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag recovered at column 125.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 116.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 115.
Dec 10 12:57: TRACE - Trace of aperture 108 in flat_fid_mag lost at column 114.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 1414.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 1415.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 1416.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 293.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag recovered at column 292.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 212.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 211.
Dec 10 12:57: TRACE - Trace of aperture 109 in flat_fid_mag lost at column 210.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1411.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag recovered at column 1412.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1458.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag recovered at column 1459.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1491.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag recovered at column 1492.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1495.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1496.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 1497.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 198.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 197.
Dec 10 12:57: TRACE - Trace of aperture 110 in flat_fid_mag lost at column 196.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1373.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 1374.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1375.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 1376.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1377.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 1378.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1379.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 1380.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1390.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1391.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 1392.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 262.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 261.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 260.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 259.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 213.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 212.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 211.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 206.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag recovered at column 205.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 199.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 198.
Dec 10 12:57: TRACE - Trace of aperture 111 in flat_fid_mag lost at column 197.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 1342.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag recovered at column 1343.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 1350.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 1351.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 1352.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 317.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag recovered at column 316.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 296.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag recovered at column 295.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 289.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag recovered at column 288.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 213.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 212.
Dec 10 12:57: TRACE - Trace of aperture 112 in flat_fid_mag lost at column 211.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1287.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag recovered at column 1288.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1371.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag recovered at column 1372.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1399.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag recovered at column 1400.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1407.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1408.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 1409.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 382.
Dec 10 12:57: TRACE - Trace of aperture 113 in flat_fid_mag recovered at column 381.
Dec 10 12:58: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 300.
Dec 10 12:58: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 299.
Dec 10 12:58: TRACE - Trace of aperture 113 in flat_fid_mag lost at column 298.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 1248.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 1249.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 1250.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 348.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 347.
Dec 10 12:58: TRACE - Trace of aperture 114 in flat_fid_mag lost at column 346.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 1052.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag recovered at column 1053.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 1120.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 1121.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 1122.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 558.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag recovered at column 557.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 423.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag recovered at column 422.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 406.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag recovered at column 405.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 391.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 390.
Dec 10 12:58: TRACE - Trace of aperture 115 in flat_fid_mag lost at column 389.
Normalizing the superflat...
flat_fid_mag.ec.fits -> nonorm_flat_fid_mag.ec.fits
IMARITH:
  Operation = +
  Operand1 = nonorm_flat_fid_mag.ec.fits
  Operand2 = 25.56
  Result = nonorm_flat_fid_mag_bias.fits
  Result pixel type = real
  Calculation type = real
Resampling the arc by a factor of 4 in the y direction...

120827.0001.fits
  Magnify image 120827.0001.fits to image 120827.0001.fits.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0001.fits,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0001.fits updated
Applying model apertures to the arc and extracting spectra...
Resampling the arc by a factor of 4 in the y direction...

120827.0002.fits
  Magnify image 120827.0002.fits to image 120827.0002.fits.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0002.fits,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0002.fits updated
Applying model apertures to the arc and extracting spectra...
Resampling the arc by a factor of 4 in the y direction...

120827.0003.fits
  Magnify image 120827.0003.fits to image 120827.0003.fits.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0003.fits,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0003.fits updated
Applying model apertures to the arc and extracting spectra...
Resampling the arc by a factor of 4 in the y direction...

120827.0004.fits
  Magnify image 120827.0004.fits to image 120827.0004.fits.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0004.fits,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0004.fits updated
Applying model apertures to the arc and extracting spectra...
Resampling the object by a factor of 4 in the y direction...

120827.0021
  Magnify image 120827.0021 to image 120827.0021.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0021,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0021 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0021 -> noscat120827.0021
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 12:59: EXTRACT: WARNING - Aperture 100:
Dec 10 12:59:    Total variance weighted spectrum flux is 12027.23
Dec 10 12:59:    Total unweighted spectrum flux is 3392.826
Dec 10 12:59: EXTRACT: Aperture 100 variance spectrum bias factor is 0.2820954
Dec 10 13:00: EXTRACT: WARNING - Aperture 107:
Dec 10 13:00:    Total variance weighted spectrum flux is 10771.01
Dec 10 13:00:    Total unweighted spectrum flux is 5125.778
Dec 10 13:00: EXTRACT: Aperture 107 variance spectrum bias factor is 0.4758866
Dec 10 13:00: EXTRACT: WARNING - Aperture 108:
Dec 10 13:00:    Total variance weighted spectrum flux is 5353.992
Dec 10 13:00:    Total unweighted spectrum flux is 1724.133
Dec 10 13:00: EXTRACT: Aperture 108 variance spectrum bias factor is 0.3220275
Dec 10 13:00: EXTRACT: WARNING - Aperture 109:
Dec 10 13:00:    Total variance weighted spectrum flux is 9413.031
Dec 10 13:00:    Total unweighted spectrum flux is 3554.204
Dec 10 13:00: EXTRACT: Aperture 109 variance spectrum bias factor is 0.3775833
Dec 10 13:00: EXTRACT: WARNING - Aperture 110:
Dec 10 13:00:    Total variance weighted spectrum flux is 8065.499
Dec 10 13:00:    Total unweighted spectrum flux is 3092.864
Dec 10 13:00: EXTRACT: Aperture 110 variance spectrum bias factor is 0.3834683
Dec 10 13:00: EXTRACT: WARNING - Aperture 111:
Dec 10 13:00:    Total variance weighted spectrum flux is 5001.512
Dec 10 13:00:    Total unweighted spectrum flux is 1872.047
Dec 10 13:00: EXTRACT: Aperture 111 variance spectrum bias factor is 0.3742962
Dec 10 13:00: EXTRACT: WARNING - Aperture 112:
Dec 10 13:00:    Total variance weighted spectrum flux is 2795.043
Dec 10 13:00:    Total unweighted spectrum flux is 837.7713
Dec 10 13:00: EXTRACT: Aperture 112 variance spectrum bias factor is 0.2997347
Dec 10 13:00: EXTRACT: WARNING - Aperture 113:
Dec 10 13:00:    Total variance weighted spectrum flux is 12729.65
Dec 10 13:00:    Total unweighted spectrum flux is 5139.645
Dec 10 13:00: EXTRACT: Aperture 113 variance spectrum bias factor is 0.4037539
Dec 10 13:00: EXTRACT: WARNING - Aperture 114:
Dec 10 13:00:    Total variance weighted spectrum flux is 6965.528
Dec 10 13:00:    Total unweighted spectrum flux is 602.5969
Dec 10 13:00: EXTRACT: Aperture 114 variance spectrum bias factor is 0.08651129
Dec 10 13:00: EXTRACT: WARNING - Aperture 115:
Dec 10 13:00:    Total variance weighted spectrum flux is 7251.118
Dec 10 13:00:    Total unweighted spectrum flux is 2507.199
Dec 10 13:00: EXTRACT: Aperture 115 variance spectrum bias factor is 0.3457673
Resampling the object by a factor of 4 in the y direction...

120827.0022
  Magnify image 120827.0022 to image 120827.0022.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0022,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0022 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0022 -> noscat120827.0022
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:02: EXTRACT: WARNING - Aperture 107:
Dec 10 13:02:    Total variance weighted spectrum flux is 10119.85
Dec 10 13:02:    Total unweighted spectrum flux is 4911.48
Dec 10 13:02: EXTRACT: Aperture 107 variance spectrum bias factor is 0.4853312
Dec 10 13:02: EXTRACT: WARNING - Aperture 108:
Dec 10 13:02:    Total variance weighted spectrum flux is 8785.217
Dec 10 13:02:    Total unweighted spectrum flux is 4319.627
Dec 10 13:02: EXTRACT: Aperture 108 variance spectrum bias factor is 0.4916927
Dec 10 13:02: EXTRACT: WARNING - Aperture 110:
Dec 10 13:02:    Total variance weighted spectrum flux is 3873.061
Dec 10 13:02:    Total unweighted spectrum flux is 1548.19
Dec 10 13:02: EXTRACT: Aperture 110 variance spectrum bias factor is 0.399733
Dec 10 13:02: EXTRACT: WARNING - Aperture 111:
Dec 10 13:02:    Total variance weighted spectrum flux is 12214.13
Dec 10 13:02:    Total unweighted spectrum flux is 3721.775
Dec 10 13:02: EXTRACT: Aperture 111 variance spectrum bias factor is 0.3047106
Dec 10 13:02: EXTRACT: WARNING - Aperture 112:
Dec 10 13:02:    Total variance weighted spectrum flux is 7891.972
Dec 10 13:02:    Total unweighted spectrum flux is 304.8907
Dec 10 13:02: EXTRACT: Aperture 112 variance spectrum bias factor is 0.03863301
Dec 10 13:02: EXTRACT: WARNING - Aperture 113:
Dec 10 13:02:    Total variance weighted spectrum flux is 7465.627
Dec 10 13:02:    Total unweighted spectrum flux is 2804.906
Dec 10 13:02: EXTRACT: Aperture 113 variance spectrum bias factor is 0.3757094
Dec 10 13:02: EXTRACT: WARNING - Aperture 114:
Dec 10 13:02:    Total variance weighted spectrum flux is 3465.764
Dec 10 13:02:    Total unweighted spectrum flux is 1079.319
Dec 10 13:02: EXTRACT: Aperture 114 variance spectrum bias factor is 0.3114232
Dec 10 13:02: EXTRACT: WARNING - Aperture 115:
Dec 10 13:02:    Total variance weighted spectrum flux is 5808.615
Dec 10 13:02:    Total unweighted spectrum flux is 2289.986
Dec 10 13:02: EXTRACT: Aperture 115 variance spectrum bias factor is 0.3942396
Resampling the object by a factor of 4 in the y direction...

120827.0023
  Magnify image 120827.0023 to image 120827.0023.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0023,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0023 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0023 -> noscat120827.0023
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:03: EXTRACT: WARNING - Aperture 106:
Dec 10 13:03:    Total variance weighted spectrum flux is 9636.787
Dec 10 13:03:    Total unweighted spectrum flux is 2605.661
Dec 10 13:03: EXTRACT: Aperture 106 variance spectrum bias factor is 0.2703869
Dec 10 13:03: EXTRACT: WARNING - Aperture 110:
Dec 10 13:03:    Total variance weighted spectrum flux is 4060.686
Dec 10 13:03:    Total unweighted spectrum flux is 1166.988
Dec 10 13:03: EXTRACT: Aperture 110 variance spectrum bias factor is 0.2873868
Dec 10 13:04: EXTRACT: WARNING - Aperture 113:
Dec 10 13:04:    Total variance weighted spectrum flux is 9884.045
Dec 10 13:04:    Total unweighted spectrum flux is 3572.281
Dec 10 13:04: EXTRACT: Aperture 113 variance spectrum bias factor is 0.3614189
Dec 10 13:04: EXTRACT: WARNING - Aperture 114:
Dec 10 13:04:    Total variance weighted spectrum flux is 4018.076
Dec 10 13:04:    Total unweighted spectrum flux is -2709.122
Dec 10 13:04:    Variance spectrum bias factor ignored
Dec 10 13:04: EXTRACT: WARNING - Aperture 115:
Dec 10 13:04:    Total variance weighted spectrum flux is 2965.779
Dec 10 13:04:    Total unweighted spectrum flux is -496.9026
Dec 10 13:04:    Variance spectrum bias factor ignored
Resampling the object by a factor of 4 in the y direction...

120827.0024
  Magnify image 120827.0024 to image 120827.0024.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0024,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0024 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0024 -> noscat120827.0024
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:05: EXTRACT: WARNING - Aperture 95:
Dec 10 13:05:    Total variance weighted spectrum flux is 12615.62
Dec 10 13:05:    Total unweighted spectrum flux is 5557.786
Dec 10 13:05: EXTRACT: Aperture 95 variance spectrum bias factor is 0.440548
Dec 10 13:05: EXTRACT: WARNING - Aperture 96:
Dec 10 13:05:    Total variance weighted spectrum flux is 4541.702
Dec 10 13:05:    Total unweighted spectrum flux is -1350.671
Dec 10 13:05:    Variance spectrum bias factor ignored
Dec 10 13:05: EXTRACT: WARNING - Aperture 97:
Dec 10 13:05:    Total variance weighted spectrum flux is 11714.73
Dec 10 13:05:    Total unweighted spectrum flux is 5703.407
Dec 10 13:05: EXTRACT: Aperture 97 variance spectrum bias factor is 0.4868579
Dec 10 13:05: EXTRACT: WARNING - Aperture 98:
Dec 10 13:05:    Total variance weighted spectrum flux is 5325.804
Dec 10 13:05:    Total unweighted spectrum flux is 2610.633
Dec 10 13:05: EXTRACT: Aperture 98 variance spectrum bias factor is 0.4901857
Dec 10 13:05: EXTRACT: WARNING - Aperture 99:
Dec 10 13:05:    Total variance weighted spectrum flux is 5351.057
Dec 10 13:05:    Total unweighted spectrum flux is 2605.199
Dec 10 13:05: EXTRACT: Aperture 99 variance spectrum bias factor is 0.486857
Dec 10 13:05: EXTRACT: WARNING - Aperture 100:
Dec 10 13:05:    Total variance weighted spectrum flux is 7666.28
Dec 10 13:05:    Total unweighted spectrum flux is 2570.654
Dec 10 13:05: EXTRACT: Aperture 100 variance spectrum bias factor is 0.3353195
Dec 10 13:05: EXTRACT: WARNING - Aperture 101:
Dec 10 13:05:    Total variance weighted spectrum flux is 15974.37
Dec 10 13:05:    Total unweighted spectrum flux is 5760.394
Dec 10 13:05: EXTRACT: Aperture 101 variance spectrum bias factor is 0.3606022
Dec 10 13:05: EXTRACT: WARNING - Aperture 102:
Dec 10 13:05:    Total variance weighted spectrum flux is 9453.618
Dec 10 13:05:    Total unweighted spectrum flux is 4158.72
Dec 10 13:05: EXTRACT: Aperture 102 variance spectrum bias factor is 0.4399077
Dec 10 13:05: EXTRACT: WARNING - Aperture 103:
Dec 10 13:05:    Total variance weighted spectrum flux is 3880.236
Dec 10 13:05:    Total unweighted spectrum flux is 627.2947
Dec 10 13:05: EXTRACT: Aperture 103 variance spectrum bias factor is 0.1616641
Dec 10 13:05: EXTRACT: WARNING - Aperture 104:
Dec 10 13:05:    Total variance weighted spectrum flux is 5644.128
Dec 10 13:05:    Total unweighted spectrum flux is 236.8742
Dec 10 13:05: EXTRACT: Aperture 104 variance spectrum bias factor is 0.04196825
Dec 10 13:05: EXTRACT: WARNING - Aperture 105:
Dec 10 13:05:    Total variance weighted spectrum flux is 4577.208
Dec 10 13:05:    Total unweighted spectrum flux is 771.7144
Dec 10 13:05: EXTRACT: Aperture 105 variance spectrum bias factor is 0.1685994
Dec 10 13:05: EXTRACT: WARNING - Aperture 106:
Dec 10 13:05:    Total variance weighted spectrum flux is 3740.059
Dec 10 13:05:    Total unweighted spectrum flux is 166.0161
Dec 10 13:05: EXTRACT: Aperture 106 variance spectrum bias factor is 0.04438863
Dec 10 13:05: EXTRACT: WARNING - Aperture 107:
Dec 10 13:05:    Total variance weighted spectrum flux is 9289.544
Dec 10 13:05:    Total unweighted spectrum flux is 983.511
Dec 10 13:05: EXTRACT: Aperture 107 variance spectrum bias factor is 0.1058729
Dec 10 13:05: EXTRACT: WARNING - Aperture 108:
Dec 10 13:05:    Total variance weighted spectrum flux is 1955.578
Dec 10 13:05:    Total unweighted spectrum flux is -1114.062
Dec 10 13:05:    Variance spectrum bias factor ignored
Dec 10 13:05: EXTRACT: WARNING - Aperture 109:
Dec 10 13:05:    Total variance weighted spectrum flux is 8555.945
Dec 10 13:05:    Total unweighted spectrum flux is 352.8538
Dec 10 13:05: EXTRACT: Aperture 109 variance spectrum bias factor is 0.04124077
Dec 10 13:05: EXTRACT: WARNING - Aperture 110:
Dec 10 13:05:    Total variance weighted spectrum flux is 3291.4
Dec 10 13:05:    Total unweighted spectrum flux is 161.3917
Dec 10 13:05: EXTRACT: Aperture 110 variance spectrum bias factor is 0.04903436
Dec 10 13:05: EXTRACT: WARNING - Aperture 111:
Dec 10 13:05:    Total variance weighted spectrum flux is 2395.65
Dec 10 13:05:    Total unweighted spectrum flux is 145.4334
Dec 10 13:05: EXTRACT: Aperture 111 variance spectrum bias factor is 0.06070727
Dec 10 13:05: EXTRACT: WARNING - Aperture 112:
Dec 10 13:05:    Total variance weighted spectrum flux is 2235.533
Dec 10 13:05:    Total unweighted spectrum flux is -253.3103
Dec 10 13:05:    Variance spectrum bias factor ignored
Dec 10 13:05: EXTRACT: WARNING - Aperture 113:
Dec 10 13:05:    Total variance weighted spectrum flux is 7272.625
Dec 10 13:05:    Total unweighted spectrum flux is 476.2386
Dec 10 13:05: EXTRACT: Aperture 113 variance spectrum bias factor is 0.06548372
Dec 10 13:05: EXTRACT: WARNING - Aperture 114:
Dec 10 13:05:    Total variance weighted spectrum flux is 7238.2
Dec 10 13:05:    Total unweighted spectrum flux is -1064.633
Dec 10 13:05:    Variance spectrum bias factor ignored
Dec 10 13:05: EXTRACT: WARNING - Aperture 115:
Dec 10 13:05:    Total variance weighted spectrum flux is 4773.969
Dec 10 13:05:    Total unweighted spectrum flux is -682.499
Dec 10 13:05:    Variance spectrum bias factor ignored
Resampling the object by a factor of 4 in the y direction...

120827.0025
  Magnify image 120827.0025 to image 120827.0025.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0025,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0025 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0025 -> noscat120827.0025
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:07: EXTRACT: WARNING - Aperture 95:
Dec 10 13:07:    Total variance weighted spectrum flux is 14403.
Dec 10 13:07:    Total unweighted spectrum flux is 5693.172
Dec 10 13:07: EXTRACT: Aperture 95 variance spectrum bias factor is 0.395277
Dec 10 13:07: EXTRACT: WARNING - Aperture 96:
Dec 10 13:07:    Total variance weighted spectrum flux is 4368.571
Dec 10 13:07:    Total unweighted spectrum flux is 998.1801
Dec 10 13:07: EXTRACT: Aperture 96 variance spectrum bias factor is 0.2284912
Dec 10 13:07: EXTRACT: WARNING - Aperture 98:
Dec 10 13:07:    Total variance weighted spectrum flux is 18382.44
Dec 10 13:07:    Total unweighted spectrum flux is 8962.55
Dec 10 13:07: EXTRACT: Aperture 98 variance spectrum bias factor is 0.4875604
Dec 10 13:07: EXTRACT: WARNING - Aperture 99:
Dec 10 13:07:    Total variance weighted spectrum flux is 10666.05
Dec 10 13:07:    Total unweighted spectrum flux is 4442.162
Dec 10 13:07: EXTRACT: Aperture 99 variance spectrum bias factor is 0.4164769
Dec 10 13:07: EXTRACT: WARNING - Aperture 100:
Dec 10 13:07:    Total variance weighted spectrum flux is 5141.511
Dec 10 13:07:    Total unweighted spectrum flux is 1560.112
Dec 10 13:07: EXTRACT: Aperture 100 variance spectrum bias factor is 0.3034346
Dec 10 13:07: EXTRACT: WARNING - Aperture 101:
Dec 10 13:07:    Total variance weighted spectrum flux is 7996.908
Dec 10 13:07:    Total unweighted spectrum flux is 2950.884
Dec 10 13:07: EXTRACT: Aperture 101 variance spectrum bias factor is 0.3690031
Dec 10 13:07: EXTRACT: WARNING - Aperture 102:
Dec 10 13:07:    Total variance weighted spectrum flux is 7313.646
Dec 10 13:07:    Total unweighted spectrum flux is 1961.523
Dec 10 13:07: EXTRACT: Aperture 102 variance spectrum bias factor is 0.2682004
Dec 10 13:07: EXTRACT: WARNING - Aperture 103:
Dec 10 13:07:    Total variance weighted spectrum flux is 6997.874
Dec 10 13:07:    Total unweighted spectrum flux is 2088.064
Dec 10 13:07: EXTRACT: Aperture 103 variance spectrum bias factor is 0.2983855
Dec 10 13:07: EXTRACT: WARNING - Aperture 104:
Dec 10 13:07:    Total variance weighted spectrum flux is 9423.921
Dec 10 13:07:    Total unweighted spectrum flux is 2053.045
Dec 10 13:07: EXTRACT: Aperture 104 variance spectrum bias factor is 0.2178546
Dec 10 13:07: EXTRACT: WARNING - Aperture 105:
Dec 10 13:07:    Total variance weighted spectrum flux is 10801.37
Dec 10 13:07:    Total unweighted spectrum flux is -412.185
Dec 10 13:07:    Variance spectrum bias factor ignored
Dec 10 13:07: EXTRACT: WARNING - Aperture 106:
Dec 10 13:07:    Total variance weighted spectrum flux is 6633.127
Dec 10 13:07:    Total unweighted spectrum flux is 887.7761
Dec 10 13:07: EXTRACT: Aperture 106 variance spectrum bias factor is 0.1338398
Dec 10 13:07: EXTRACT: WARNING - Aperture 107:
Dec 10 13:07:    Total variance weighted spectrum flux is 7809.686
Dec 10 13:07:    Total unweighted spectrum flux is -827.9035
Dec 10 13:07:    Variance spectrum bias factor ignored
Dec 10 13:07: EXTRACT: WARNING - Aperture 108:
Dec 10 13:07:    Total variance weighted spectrum flux is 2246.596
Dec 10 13:07:    Total unweighted spectrum flux is -341.2432
Dec 10 13:07:    Variance spectrum bias factor ignored
Dec 10 13:07: EXTRACT: WARNING - Aperture 109:
Dec 10 13:07:    Total variance weighted spectrum flux is 5189.905
Dec 10 13:07:    Total unweighted spectrum flux is 1325.355
Dec 10 13:07: EXTRACT: Aperture 109 variance spectrum bias factor is 0.2553718
Dec 10 13:07: EXTRACT: WARNING - Aperture 110:
Dec 10 13:07:    Total variance weighted spectrum flux is 2894.734
Dec 10 13:07:    Total unweighted spectrum flux is 17.12389
Dec 10 13:07: EXTRACT: Aperture 110 variance spectrum bias factor is 0.00591553
Dec 10 13:07: EXTRACT: WARNING - Aperture 111:
Dec 10 13:07:    Total variance weighted spectrum flux is 6076.072
Dec 10 13:07:    Total unweighted spectrum flux is 273.9519
Dec 10 13:07: EXTRACT: Aperture 111 variance spectrum bias factor is 0.04508701
Dec 10 13:07: EXTRACT: WARNING - Aperture 112:
Dec 10 13:07:    Total variance weighted spectrum flux is 2480.648
Dec 10 13:07:    Total unweighted spectrum flux is 136.8066
Dec 10 13:07: EXTRACT: Aperture 112 variance spectrum bias factor is 0.05514955
Dec 10 13:07: EXTRACT: WARNING - Aperture 113:
Dec 10 13:07:    Total variance weighted spectrum flux is 7603.479
Dec 10 13:07:    Total unweighted spectrum flux is -11.88856
Dec 10 13:07:    Variance spectrum bias factor ignored
Dec 10 13:07: EXTRACT: WARNING - Aperture 114:
Dec 10 13:07:    Total variance weighted spectrum flux is 1499.305
Dec 10 13:07:    Total unweighted spectrum flux is -49.81398
Dec 10 13:07:    Variance spectrum bias factor ignored
Dec 10 13:07: EXTRACT: WARNING - Aperture 115:
Dec 10 13:07:    Total variance weighted spectrum flux is 1018.644
Dec 10 13:07:    Total unweighted spectrum flux is -322.8783
Dec 10 13:07:    Variance spectrum bias factor ignored
Resampling the object by a factor of 4 in the y direction...

120827.0026
  Magnify image 120827.0026 to image 120827.0026.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0026,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0026 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0026 -> noscat120827.0026
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:09: EXTRACT: WARNING - Aperture 91:
Dec 10 13:09:    Total variance weighted spectrum flux is 4334.961
Dec 10 13:09:    Total unweighted spectrum flux is 1502.578
Dec 10 13:09: EXTRACT: Aperture 91 variance spectrum bias factor is 0.3466187
Dec 10 13:09: EXTRACT: WARNING - Aperture 92:
Dec 10 13:09:    Total variance weighted spectrum flux is 9106.435
Dec 10 13:09:    Total unweighted spectrum flux is -448.8184
Dec 10 13:09:    Variance spectrum bias factor ignored
Dec 10 13:09: EXTRACT: WARNING - Aperture 93:
Dec 10 13:09:    Total variance weighted spectrum flux is 7197.545
Dec 10 13:09:    Total unweighted spectrum flux is 2323.319
Dec 10 13:09: EXTRACT: Aperture 93 variance spectrum bias factor is 0.3227933
Dec 10 13:09: EXTRACT: WARNING - Aperture 95:
Dec 10 13:09:    Total variance weighted spectrum flux is 4291.729
Dec 10 13:09:    Total unweighted spectrum flux is 949.9563
Dec 10 13:09: EXTRACT: Aperture 95 variance spectrum bias factor is 0.2213458
Dec 10 13:09: EXTRACT: WARNING - Aperture 96:
Dec 10 13:09:    Total variance weighted spectrum flux is 5292.559
Dec 10 13:09:    Total unweighted spectrum flux is -1115.516
Dec 10 13:09:    Variance spectrum bias factor ignored
Dec 10 13:09: EXTRACT: WARNING - Aperture 97:
Dec 10 13:09:    Total variance weighted spectrum flux is 8398.374
Dec 10 13:09:    Total unweighted spectrum flux is 728.8757
Dec 10 13:09: EXTRACT: Aperture 97 variance spectrum bias factor is 0.08678772
Dec 10 13:09: EXTRACT: WARNING - Aperture 98:
Dec 10 13:09:    Total variance weighted spectrum flux is 8643.44
Dec 10 13:09:    Total unweighted spectrum flux is 1683.887
Dec 10 13:09: EXTRACT: Aperture 98 variance spectrum bias factor is 0.1948168
Dec 10 13:09: EXTRACT: WARNING - Aperture 99:
Dec 10 13:09:    Total variance weighted spectrum flux is 5843.336
Dec 10 13:09:    Total unweighted spectrum flux is 672.0901
Dec 10 13:09: EXTRACT: Aperture 99 variance spectrum bias factor is 0.1150182
Dec 10 13:09: EXTRACT: WARNING - Aperture 100:
Dec 10 13:09:    Total variance weighted spectrum flux is 4660.228
Dec 10 13:09:    Total unweighted spectrum flux is 976.7914
Dec 10 13:09: EXTRACT: Aperture 100 variance spectrum bias factor is 0.2096016
Dec 10 13:09: EXTRACT: WARNING - Aperture 101:
Dec 10 13:09:    Total variance weighted spectrum flux is 4118.434
Dec 10 13:09:    Total unweighted spectrum flux is 779.7364
Dec 10 13:09: EXTRACT: Aperture 101 variance spectrum bias factor is 0.1893284
Dec 10 13:09: EXTRACT: WARNING - Aperture 102:
Dec 10 13:09:    Total variance weighted spectrum flux is 13345.44
Dec 10 13:09:    Total unweighted spectrum flux is 2793.636
Dec 10 13:09: EXTRACT: Aperture 102 variance spectrum bias factor is 0.2093327
Dec 10 13:09: EXTRACT: WARNING - Aperture 103:
Dec 10 13:09:    Total variance weighted spectrum flux is 4192.658
Dec 10 13:09:    Total unweighted spectrum flux is 771.0923
Dec 10 13:09: EXTRACT: Aperture 103 variance spectrum bias factor is 0.1839149
Dec 10 13:09: EXTRACT: WARNING - Aperture 104:
Dec 10 13:09:    Total variance weighted spectrum flux is 3939.176
Dec 10 13:09:    Total unweighted spectrum flux is 46.60307
Dec 10 13:09: EXTRACT: Aperture 104 variance spectrum bias factor is 0.01183067
Dec 10 13:09: EXTRACT: WARNING - Aperture 105:
Dec 10 13:09:    Total variance weighted spectrum flux is 7750.845
Dec 10 13:09:    Total unweighted spectrum flux is 142.8543
Dec 10 13:09: EXTRACT: Aperture 105 variance spectrum bias factor is 0.01843081
Dec 10 13:09: EXTRACT: WARNING - Aperture 106:
Dec 10 13:09:    Total variance weighted spectrum flux is 5802.58
Dec 10 13:09:    Total unweighted spectrum flux is 225.537
Dec 10 13:09: EXTRACT: Aperture 106 variance spectrum bias factor is 0.0388684
Dec 10 13:09: EXTRACT: WARNING - Aperture 107:
Dec 10 13:09:    Total variance weighted spectrum flux is 3789.718
Dec 10 13:09:    Total unweighted spectrum flux is -439.5107
Dec 10 13:09:    Variance spectrum bias factor ignored
Dec 10 13:09: EXTRACT: WARNING - Aperture 108:
Dec 10 13:09:    Total variance weighted spectrum flux is 3938.313
Dec 10 13:09:    Total unweighted spectrum flux is -1144.171
Dec 10 13:09:    Variance spectrum bias factor ignored
Dec 10 13:09: EXTRACT: WARNING - Aperture 109:
Dec 10 13:09:    Total variance weighted spectrum flux is 4350.954
Dec 10 13:09:    Total unweighted spectrum flux is 58.56638
Dec 10 13:09: EXTRACT: Aperture 109 variance spectrum bias factor is 0.01346058
Dec 10 13:09: EXTRACT: WARNING - Aperture 110:
Dec 10 13:09:    Total variance weighted spectrum flux is 6916.455
Dec 10 13:09:    Total unweighted spectrum flux is 670.1287
Dec 10 13:09: EXTRACT: Aperture 110 variance spectrum bias factor is 0.09688904
Dec 10 13:09: EXTRACT: WARNING - Aperture 111:
Dec 10 13:09:    Total variance weighted spectrum flux is 9299.107
Dec 10 13:09:    Total unweighted spectrum flux is 2181.71
Dec 10 13:09: EXTRACT: Aperture 111 variance spectrum bias factor is 0.234615
Dec 10 13:09: EXTRACT: WARNING - Aperture 112:
Dec 10 13:09:    Total variance weighted spectrum flux is 4017.063
Dec 10 13:09:    Total unweighted spectrum flux is 262.0523
Dec 10 13:09: EXTRACT: Aperture 112 variance spectrum bias factor is 0.0652348
Dec 10 13:09: EXTRACT: WARNING - Aperture 113:
Dec 10 13:09:    Total variance weighted spectrum flux is 2750.876
Dec 10 13:09:    Total unweighted spectrum flux is 442.3699
Dec 10 13:09: EXTRACT: Aperture 113 variance spectrum bias factor is 0.1608105
Dec 10 13:09: EXTRACT: WARNING - Aperture 114:
Dec 10 13:09:    Total variance weighted spectrum flux is 8144.568
Dec 10 13:09:    Total unweighted spectrum flux is -656.2133
Dec 10 13:09:    Variance spectrum bias factor ignored
Dec 10 13:09: EXTRACT: WARNING - Aperture 115:
Dec 10 13:09:    Total variance weighted spectrum flux is 913.3775
Dec 10 13:09:    Total unweighted spectrum flux is -534.7432
Dec 10 13:09:    Variance spectrum bias factor ignored
Resampling the object by a factor of 4 in the y direction...

120827.0027
  Magnify image 120827.0027 to image 120827.0027.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0027,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0027 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0027 -> noscat120827.0027
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:10: EXTRACT: WARNING - Aperture 1:
Dec 10 13:10:    Total variance weighted spectrum flux is 4589.007
Dec 10 13:10:    Total unweighted spectrum flux is 1139.38
Dec 10 13:10: EXTRACT: Aperture 1 variance spectrum bias factor is 0.2482847
Dec 10 13:11: EXTRACT: WARNING - Aperture 81:
Dec 10 13:11:    Total variance weighted spectrum flux is 6386.757
Dec 10 13:11:    Total unweighted spectrum flux is 2520.831
Dec 10 13:11: EXTRACT: Aperture 81 variance spectrum bias factor is 0.3946966
Dec 10 13:11: EXTRACT: WARNING - Aperture 82:
Dec 10 13:11:    Total variance weighted spectrum flux is 4625.601
Dec 10 13:11:    Total unweighted spectrum flux is 2018.348
Dec 10 13:11: EXTRACT: Aperture 82 variance spectrum bias factor is 0.4363427
Dec 10 13:11: EXTRACT: WARNING - Aperture 83:
Dec 10 13:11:    Total variance weighted spectrum flux is 4686.195
Dec 10 13:11:    Total unweighted spectrum flux is 2302.137
Dec 10 13:11: EXTRACT: Aperture 83 variance spectrum bias factor is 0.4912595
Dec 10 13:11: EXTRACT: WARNING - Aperture 84:
Dec 10 13:11:    Total variance weighted spectrum flux is 4903.738
Dec 10 13:11:    Total unweighted spectrum flux is 2415.195
Dec 10 13:11: EXTRACT: Aperture 84 variance spectrum bias factor is 0.4925211
Dec 10 13:11: EXTRACT: WARNING - Aperture 85:
Dec 10 13:11:    Total variance weighted spectrum flux is 5647.821
Dec 10 13:11:    Total unweighted spectrum flux is 1295.63
Dec 10 13:11: EXTRACT: Aperture 85 variance spectrum bias factor is 0.2294034
Dec 10 13:11: EXTRACT: WARNING - Aperture 86:
Dec 10 13:11:    Total variance weighted spectrum flux is 5652.898
Dec 10 13:11:    Total unweighted spectrum flux is 1052.421
Dec 10 13:11: EXTRACT: Aperture 86 variance spectrum bias factor is 0.1861738
Dec 10 13:11: EXTRACT: WARNING - Aperture 87:
Dec 10 13:11:    Total variance weighted spectrum flux is 10248.96
Dec 10 13:11:    Total unweighted spectrum flux is 2531.506
Dec 10 13:11: EXTRACT: Aperture 87 variance spectrum bias factor is 0.2470011
Warning: All pixels rejected
Resampling the object by a factor of 4 in the y direction...

120827.0028
  Magnify image 120827.0028 to image 120827.0028.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0028,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0028 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0028 -> noscat120827.0028
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:12: EXTRACT: WARNING - Aperture 90:
Dec 10 13:12:    Total variance weighted spectrum flux is 4538.86
Dec 10 13:12:    Total unweighted spectrum flux is 2143.898
Dec 10 13:12: EXTRACT: Aperture 90 variance spectrum bias factor is 0.4723429
Dec 10 13:12: EXTRACT: WARNING - Aperture 91:
Dec 10 13:12:    Total variance weighted spectrum flux is 7706.87
Dec 10 13:12:    Total unweighted spectrum flux is 1956.109
Dec 10 13:12: EXTRACT: Aperture 91 variance spectrum bias factor is 0.2538137
Dec 10 13:12: EXTRACT: WARNING - Aperture 92:
Dec 10 13:12:    Total variance weighted spectrum flux is 5955.893
Dec 10 13:12:    Total unweighted spectrum flux is 902.4458
Dec 10 13:12: EXTRACT: Aperture 92 variance spectrum bias factor is 0.1515215
Dec 10 13:12: EXTRACT: WARNING - Aperture 93:
Dec 10 13:12:    Total variance weighted spectrum flux is 4956.115
Dec 10 13:12:    Total unweighted spectrum flux is 1910.367
Dec 10 13:12: EXTRACT: Aperture 93 variance spectrum bias factor is 0.3854566
Dec 10 13:12: EXTRACT: WARNING - Aperture 94:
Dec 10 13:12:    Total variance weighted spectrum flux is 11969.39
Dec 10 13:12:    Total unweighted spectrum flux is 2810.77
Dec 10 13:12: EXTRACT: Aperture 94 variance spectrum bias factor is 0.2348298
Dec 10 13:12: EXTRACT: WARNING - Aperture 95:
Dec 10 13:12:    Total variance weighted spectrum flux is 9312.538
Dec 10 13:12:    Total unweighted spectrum flux is -432.679
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 96:
Dec 10 13:12:    Total variance weighted spectrum flux is 5958.111
Dec 10 13:12:    Total unweighted spectrum flux is 429.5832
Dec 10 13:12: EXTRACT: Aperture 96 variance spectrum bias factor is 0.07210057
Dec 10 13:12: EXTRACT: WARNING - Aperture 97:
Dec 10 13:12:    Total variance weighted spectrum flux is 7482.207
Dec 10 13:12:    Total unweighted spectrum flux is 1237.509
Dec 10 13:12: EXTRACT: Aperture 97 variance spectrum bias factor is 0.1653935
Dec 10 13:12: EXTRACT: WARNING - Aperture 98:
Dec 10 13:12:    Total variance weighted spectrum flux is 8258.028
Dec 10 13:12:    Total unweighted spectrum flux is 669.3142
Dec 10 13:12: EXTRACT: Aperture 98 variance spectrum bias factor is 0.08105012
Dec 10 13:12: EXTRACT: WARNING - Aperture 99:
Dec 10 13:12:    Total variance weighted spectrum flux is 7942.341
Dec 10 13:12:    Total unweighted spectrum flux is 321.577
Dec 10 13:12: EXTRACT: Aperture 99 variance spectrum bias factor is 0.04048895
Dec 10 13:12: EXTRACT: WARNING - Aperture 100:
Dec 10 13:12:    Total variance weighted spectrum flux is 9332.225
Dec 10 13:12:    Total unweighted spectrum flux is 1470.253
Dec 10 13:12: EXTRACT: Aperture 100 variance spectrum bias factor is 0.1575459
Dec 10 13:12: EXTRACT: WARNING - Aperture 101:
Dec 10 13:12:    Total variance weighted spectrum flux is 5707.778
Dec 10 13:12:    Total unweighted spectrum flux is -52.94738
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 102:
Dec 10 13:12:    Total variance weighted spectrum flux is 5258.729
Dec 10 13:12:    Total unweighted spectrum flux is -903.1233
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 103:
Dec 10 13:12:    Total variance weighted spectrum flux is 6058.143
Dec 10 13:12:    Total unweighted spectrum flux is 1393.481
Dec 10 13:12: EXTRACT: Aperture 103 variance spectrum bias factor is 0.2300179
Dec 10 13:12: EXTRACT: WARNING - Aperture 104:
Dec 10 13:12:    Total variance weighted spectrum flux is 4386.557
Dec 10 13:12:    Total unweighted spectrum flux is 648.5225
Dec 10 13:12: EXTRACT: Aperture 104 variance spectrum bias factor is 0.1478432
Dec 10 13:12: EXTRACT: WARNING - Aperture 105:
Dec 10 13:12:    Total variance weighted spectrum flux is 3774.91
Dec 10 13:12:    Total unweighted spectrum flux is 531.8492
Dec 10 13:12: EXTRACT: Aperture 105 variance spectrum bias factor is 0.1408905
Dec 10 13:12: EXTRACT: WARNING - Aperture 106:
Dec 10 13:12:    Total variance weighted spectrum flux is 7021.88
Dec 10 13:12:    Total unweighted spectrum flux is -45.02578
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 107:
Dec 10 13:12:    Total variance weighted spectrum flux is 5467.958
Dec 10 13:12:    Total unweighted spectrum flux is -225.3575
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 108:
Dec 10 13:12:    Total variance weighted spectrum flux is 2432.639
Dec 10 13:12:    Total unweighted spectrum flux is -417.0619
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 109:
Dec 10 13:12:    Total variance weighted spectrum flux is 3835.994
Dec 10 13:12:    Total unweighted spectrum flux is 61.3069
Dec 10 13:12: EXTRACT: Aperture 109 variance spectrum bias factor is 0.01598201
Dec 10 13:12: EXTRACT: WARNING - Aperture 110:
Dec 10 13:12:    Total variance weighted spectrum flux is 2698.248
Dec 10 13:12:    Total unweighted spectrum flux is -474.2545
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 111:
Dec 10 13:12:    Total variance weighted spectrum flux is 2954.526
Dec 10 13:12:    Total unweighted spectrum flux is 502.8476
Dec 10 13:12: EXTRACT: Aperture 111 variance spectrum bias factor is 0.1701957
Dec 10 13:12: EXTRACT: WARNING - Aperture 112:
Dec 10 13:12:    Total variance weighted spectrum flux is 2172.409
Dec 10 13:12:    Total unweighted spectrum flux is -646.566
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 113:
Dec 10 13:12:    Total variance weighted spectrum flux is 7387.385
Dec 10 13:12:    Total unweighted spectrum flux is -256.9229
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 114:
Dec 10 13:12:    Total variance weighted spectrum flux is 4610.777
Dec 10 13:12:    Total unweighted spectrum flux is -1417.442
Dec 10 13:12:    Variance spectrum bias factor ignored
Dec 10 13:12: EXTRACT: WARNING - Aperture 115:
Dec 10 13:12:    Total variance weighted spectrum flux is 3321.123
Dec 10 13:12:    Total unweighted spectrum flux is 1316.401
Dec 10 13:12: EXTRACT: Aperture 115 variance spectrum bias factor is 0.3963723
Resampling the object by a factor of 4 in the y direction...

120827.0029
  Magnify image 120827.0029 to image 120827.0029.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0029,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0029 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0029 -> noscat120827.0029
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Resampling the object by a factor of 4 in the y direction...

120827.0030
  Magnify image 120827.0030 to image 120827.0030.
  Interpolation is linear.
  Boundary extension is nearest.
  Output coordinates in terms of input coordinates:
    x1 =         1., x2 =      1651., dx =         1.
    y1 =         1., y2 =      2048., dy =       0.25
120827.0030,CCDSEC: [200:1850,1:2048] -> [200:1850,1:8189]
120827.0030 updated
Applying model apertures to the object...
Removing scattered inter-order light from the spectrum...
120827.0030 -> noscat120827.0030
Removing scattered light with apscatter...
Fine-tuning apertures and extracting spectra...
Dec 10 13:16: EXTRACT: WARNING - Aperture 114:
Dec 10 13:16:    Total variance weighted spectrum flux is 6513.962
Dec 10 13:16:    Total unweighted spectrum flux is 641.1355
Dec 10 13:16: EXTRACT: Aperture 114 variance spectrum bias factor is 0.09842481
Warning: FXF: EOF encountered while reading FITS file (120827.0027.ec.fits)
add 120827.0001.ec.fits,REFSPEC1 = 120827.0001.ec.fits
120827.0001.ec.fits updated
add 120827.0002.ec.fits,REFSPEC1 = 120827.0002.ec.fits
120827.0002.ec.fits updated
add 120827.0003.ec.fits,REFSPEC1 = 120827.0003.ec.fits
120827.0003.ec.fits updated
add 120827.0004.ec.fits,REFSPEC1 = 120827.0004.ec.fits
120827.0004.ec.fits updated
Flatfielding extracted arcs and object spectra...
parameter 120827.0001.ec.fits,UTMIDDLE already exists
120827.0001.ec.fits updated
120827.0001.ec.fits,UTMIDDLE: 06:32:33.343 -> 06:33:07.342992
120827.0001.ec.fits updated
parameter 120827.0002.ec.fits,UTMIDDLE already exists
120827.0002.ec.fits updated
120827.0002.ec.fits,UTMIDDLE: 06:35:24.512 -> 06:35:58.511740
120827.0002.ec.fits updated
parameter 120827.0003.ec.fits,UTMIDDLE already exists
120827.0003.ec.fits updated
120827.0003.ec.fits,UTMIDDLE: 06:38:26.670 -> 06:39:00.670180
120827.0003.ec.fits updated
parameter 120827.0004.ec.fits,UTMIDDLE already exists
120827.0004.ec.fits updated
120827.0004.ec.fits,UTMIDDLE: 06:41:29.322 -> 06:42:03.321783
120827.0004.ec.fits updated
parameter 120827.0021.ec.fits,UTMIDDLE already exists
120827.0021.ec.fits updated
120827.0021.ec.fits,UTMIDDLE: 08:48:29.545 -> 08:49:03.544806
120827.0021.ec.fits updated
parameter 120827.0022.ec.fits,UTMIDDLE already exists
120827.0022.ec.fits updated
120827.0022.ec.fits,UTMIDDLE: 09:02:55.041 -> 09:03:29.041161
120827.0022.ec.fits updated
parameter 120827.0023.ec.fits,UTMIDDLE already exists
120827.0023.ec.fits updated
120827.0023.ec.fits,UTMIDDLE: 09:16:05.487 -> 09:16:39.487108
120827.0023.ec.fits updated
parameter 120827.0024.ec.fits,UTMIDDLE already exists
120827.0024.ec.fits updated
120827.0024.ec.fits,UTMIDDLE: 09:31:13.174 -> 09:31:47.173991
120827.0024.ec.fits updated
parameter 120827.0025.ec.fits,UTMIDDLE already exists
120827.0025.ec.fits updated
120827.0025.ec.fits,UTMIDDLE: 09:47:48.803 -> 09:48:22.802829
120827.0025.ec.fits updated
parameter 120827.0026.ec.fits,UTMIDDLE already exists
120827.0026.ec.fits updated
120827.0026.ec.fits,UTMIDDLE: 10:04:10.730 -> 10:04:44.730594
120827.0026.ec.fits updated
parameter 120827.0028.ec.fits,UTMIDDLE already exists
120827.0028.ec.fits updated
120827.0028.ec.fits,UTMIDDLE: 10:48:07.535 -> 10:48:41.535755
120827.0028.ec.fits updated
parameter 120827.0029.ec.fits,UTMIDDLE already exists
120827.0029.ec.fits updated
120827.0029.ec.fits,UTMIDDLE: 11:16:23.300 -> 11:16:57.299726
120827.0029.ec.fits updated
parameter 120827.0030.ec.fits,UTMIDDLE already exists
120827.0030.ec.fits updated
120827.0030.ec.fits,UTMIDDLE: 11:38:12.625 -> 11:38:46.624399
120827.0030.ec.fits updated
Setting Julian Date Keywords
#              Image             jd            hjd       ljd
# SETJD: Observatory parameters for Apache Point Observatory
#	timezone = 7
 120827.0021.ec.fits  2456166.86740  2456166.86983   2456166
 120827.0022.ec.fits  2456166.87742  2456166.87963   2456166
 120827.0023.ec.fits  2456166.88657  2456166.88913   2456166
 120827.0024.ec.fits  2456166.89707  2456166.89877   2456166
 120827.0025.ec.fits  2456166.90860  2456166.91131   2456166
 120827.0026.ec.fits  2456166.91996  2456166.92239   2456166
 120827.0028.ec.fits  2456166.95048  2456166.95284   2456166
 120827.0029.ec.fits  2456166.97011  2456166.96768   2456166
 120827.0030.ec.fits  2456166.98526  2456166.98611   2456166

ECREIDENTIFY: NOAO/IRAF V2.16.1 jeanm12@tequila.nmsu.edu Tue 13:16:50 10-Dec-2013
  Reference image = arcnewref.ec, Refit = yes
               Image    Found     Fit Pix Shift  User Shift  Z Shift      RMS
      120827.0001.ec  1197/2055 1197/1197      3.15        -23.  -4.1E-5    0.013
      120827.0002.ec  2045/2055 2045/2045      3.13       -22.9  -4.0E-5  0.00777
      120827.0003.ec  2051/2055 2051/2051      3.13        -23.  -4.0E-5  0.00733
      120827.0004.ec  2050/2055 2050/2050      3.13       -22.9  -4.0E-5  0.00756
[120827.0021.ec] refspec1='120827.0004.ec'
[120827.0022.ec] refspec1='120827.0004.ec'
[120827.0023.ec] refspec1='120827.0004.ec'
[120827.0024.ec] refspec1='120827.0004.ec'
[120827.0025.ec] refspec1='120827.0004.ec'
[120827.0026.ec] refspec1='120827.0004.ec'
[120827.0028.ec] refspec1='120827.0004.ec'
[120827.0029.ec] refspec1='120827.0004.ec'
[120827.0030.ec] refspec1='120827.0004.ec'
[120827.0001.ec] refspec1='120827.0001.ec'
[120827.0002.ec] refspec1='120827.0002.ec'
[120827.0003.ec] refspec1='120827.0003.ec'
[120827.0004.ec] refspec1='120827.0004.ec'
120827.0021.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0021.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0021.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0021.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0021.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0021.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0021.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0021.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0021.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0021.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0021.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0021.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0021.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0021.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0021.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0021.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0021.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0021.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0021.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0021.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0021.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0021.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0021.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0021.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0021.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0021.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0021.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0021.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0021.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0021.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0021.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0021.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0021.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0021.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0021.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0021.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0021.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0021.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0021.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0021.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0021.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0021.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0021.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0021.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0021.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0021.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0021.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0021.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0021.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0021.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0021.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0021.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0021.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0021.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0021.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0021.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0021.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0021.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0021.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0021.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0021.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0021.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0021.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0021.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0021.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0021.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0021.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0021.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0021.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0021.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0021.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0021.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0021.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0021.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0021.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0021.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0021.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0021.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0021.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0021.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0021.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0021.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0021.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0021.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0021.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0021.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0021.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0021.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0021.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0021.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0021.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0021.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0021.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0021.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0021.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0021.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0021.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0021.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0021.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0021.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0021.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0021.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0021.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0021.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0021.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0021.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0021.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0021.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0021.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0021.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0021.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0021.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0021.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0021.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0021.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0021.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0022.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0022.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0022.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0022.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0022.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0022.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0022.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0022.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0022.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0022.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0022.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0022.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0022.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0022.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0022.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0022.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0022.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0022.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0022.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0022.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0022.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0022.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0022.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0022.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0022.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0022.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0022.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0022.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0022.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0022.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0022.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0022.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0022.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0022.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0022.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0022.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0022.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0022.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0022.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0022.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0022.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0022.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0022.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0022.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0022.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0022.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0022.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0022.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0022.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0022.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0022.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0022.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0022.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0022.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0022.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0022.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0022.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0022.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0022.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0022.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0022.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0022.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0022.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0022.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0022.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0022.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0022.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0022.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0022.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0022.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0022.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0022.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0022.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0022.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0022.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0022.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0022.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0022.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0022.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0022.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0022.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0022.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0022.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0022.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0022.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0022.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0022.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0022.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0022.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0022.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0022.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0022.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0022.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0022.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0022.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0022.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0022.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0022.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0022.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0022.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0022.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0022.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0022.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0022.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0022.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0022.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0022.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0022.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0022.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0022.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0022.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0022.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0022.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0022.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0022.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0022.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0023.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0023.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0023.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0023.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0023.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0023.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0023.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0023.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0023.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0023.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0023.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0023.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0023.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0023.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0023.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0023.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0023.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0023.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0023.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0023.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0023.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0023.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0023.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0023.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0023.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0023.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0023.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0023.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0023.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0023.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0023.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0023.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0023.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0023.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0023.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0023.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0023.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0023.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0023.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0023.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0023.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0023.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0023.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0023.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0023.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0023.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0023.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0023.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0023.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0023.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0023.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0023.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0023.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0023.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0023.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0023.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0023.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0023.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0023.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0023.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0023.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0023.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0023.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0023.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0023.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0023.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0023.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0023.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0023.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0023.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0023.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0023.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0023.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0023.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0023.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0023.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0023.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0023.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0023.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0023.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0023.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0023.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0023.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0023.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0023.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0023.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0023.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0023.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0023.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0023.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0023.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0023.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0023.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0023.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0023.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0023.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0023.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0023.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0023.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0023.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0023.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0023.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0023.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0023.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0023.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0023.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0023.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0023.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0023.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0023.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0023.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0023.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0023.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0023.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0023.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0023.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0024.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0024.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0024.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0024.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0024.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0024.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0024.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0024.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0024.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0024.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0024.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0024.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0024.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0024.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0024.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0024.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0024.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0024.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0024.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0024.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0024.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0024.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0024.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0024.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0024.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0024.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0024.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0024.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0024.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0024.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0024.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0024.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0024.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0024.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0024.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0024.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0024.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0024.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0024.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0024.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0024.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0024.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0024.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0024.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0024.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0024.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0024.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0024.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0024.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0024.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0024.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0024.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0024.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0024.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0024.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0024.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0024.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0024.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0024.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0024.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0024.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0024.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0024.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0024.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0024.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0024.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0024.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0024.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0024.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0024.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0024.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0024.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0024.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0024.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0024.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0024.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0024.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0024.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0024.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0024.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0024.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0024.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0024.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0024.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0024.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0024.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0024.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0024.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0024.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0024.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0024.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0024.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0024.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0024.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0024.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0024.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0024.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0024.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0024.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0024.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0024.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0024.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0024.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0024.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0024.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0024.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0024.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0024.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0024.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0024.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0024.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0024.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0024.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0024.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0024.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0024.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0025.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0025.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0025.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0025.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0025.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0025.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0025.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0025.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0025.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0025.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0025.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0025.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0025.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0025.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0025.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0025.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0025.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0025.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0025.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0025.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0025.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0025.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0025.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0025.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0025.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0025.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0025.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0025.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0025.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0025.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0025.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0025.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0025.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0025.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0025.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0025.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0025.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0025.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0025.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0025.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0025.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0025.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0025.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0025.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0025.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0025.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0025.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0025.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0025.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0025.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0025.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0025.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0025.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0025.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0025.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0025.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0025.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0025.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0025.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0025.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0025.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0025.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0025.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0025.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0025.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0025.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0025.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0025.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0025.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0025.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0025.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0025.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0025.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0025.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0025.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0025.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0025.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0025.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0025.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0025.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0025.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0025.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0025.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0025.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0025.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0025.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0025.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0025.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0025.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0025.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0025.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0025.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0025.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0025.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0025.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0025.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0025.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0025.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0025.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0025.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0025.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0025.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0025.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0025.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0025.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0025.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0025.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0025.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0025.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0025.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0025.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0025.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0025.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0025.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0025.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0025.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0026.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0026.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0026.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0026.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0026.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0026.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0026.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0026.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0026.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0026.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0026.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0026.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0026.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0026.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0026.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0026.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0026.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0026.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0026.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0026.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0026.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0026.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0026.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0026.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0026.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0026.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0026.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0026.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0026.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0026.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0026.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0026.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0026.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0026.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0026.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0026.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0026.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0026.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0026.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0026.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0026.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0026.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0026.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0026.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0026.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0026.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0026.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0026.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0026.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0026.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0026.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0026.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0026.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0026.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0026.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0026.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0026.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0026.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0026.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0026.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0026.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0026.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0026.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0026.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0026.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0026.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0026.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0026.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0026.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0026.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0026.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0026.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0026.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0026.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0026.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0026.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0026.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0026.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0026.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0026.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0026.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0026.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0026.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0026.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0026.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0026.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0026.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0026.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0026.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0026.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0026.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0026.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0026.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0026.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0026.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0026.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0026.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0026.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0026.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0026.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0026.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0026.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0026.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0026.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0026.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0026.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0026.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0026.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0026.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0026.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0026.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0026.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0026.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0026.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0026.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0026.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0028.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0028.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0028.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0028.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0028.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0028.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0028.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0028.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0028.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0028.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0028.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0028.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0028.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0028.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0028.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0028.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0028.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0028.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0028.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0028.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0028.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0028.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0028.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0028.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0028.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0028.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0028.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0028.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0028.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0028.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0028.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0028.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0028.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0028.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0028.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0028.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0028.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0028.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0028.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0028.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0028.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0028.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0028.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0028.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0028.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0028.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0028.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0028.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0028.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0028.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0028.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0028.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0028.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0028.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0028.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0028.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0028.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0028.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0028.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0028.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0028.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0028.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0028.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0028.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0028.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0028.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0028.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0028.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0028.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0028.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0028.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0028.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0028.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0028.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0028.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0028.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0028.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0028.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0028.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0028.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0028.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0028.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0028.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0028.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0028.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0028.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0028.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0028.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0028.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0028.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0028.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0028.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0028.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0028.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0028.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0028.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0028.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0028.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0028.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0028.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0028.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0028.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0028.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0028.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0028.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0028.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
120827.0028.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
120827.0028.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
120827.0028.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
120827.0028.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
120827.0028.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
120827.0028.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
120827.0028.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
120827.0028.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
120827.0028.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
120827.0028.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
120827.0029.ec.fits: REFSPEC1 = '120827.0004.ec 1.'
120827.0029.ec.fits: ap = 1, w1 = 10812.19, w2 = 10583.98, dw = -0.13831, nw = 1651
120827.0029.ec.fits: ap = 2, w1 = 10611.98, w2 =   10388., dw = -0.13575, nw = 1651
120827.0029.ec.fits: ap = 3, w1 = 10419.05, w2 = 10199.14, dw = -0.13328, nw = 1651
120827.0029.ec.fits: ap = 4, w1 = 10233.01, w2 = 10017.03, dw =  -0.1309, nw = 1651
120827.0029.ec.fits: ap = 5, w1 =  10053.5, w2 = 9841.309, dw =  -0.1286, nw = 1651
120827.0029.ec.fits: ap = 6, w1 = 9880.175, w2 = 9671.648, dw = -0.12638, nw = 1651
120827.0029.ec.fits: ap = 7, w1 = 9712.728, w2 = 9507.738, dw = -0.12424, nw = 1651
120827.0029.ec.fits: ap = 8, w1 = 9550.862, w2 = 9349.291, dw = -0.12216, nw = 1651
120827.0029.ec.fits: ap = 9, w1 = 9394.303, w2 = 9196.039, dw = -0.12016, nw = 1651
120827.0029.ec.fits: ap = 10, w1 = 9242.795, w2 = 9047.731, dw = -0.11822, nw = 1651
120827.0029.ec.fits: ap = 11, w1 = 9096.096, w2 = 8904.131, dw = -0.11634, nw = 1651
120827.0029.ec.fits: ap = 12, w1 = 8953.981, w2 = 8765.019, dw = -0.11452, nw = 1651
120827.0029.ec.fits: ap = 13, w1 = 8816.239, w2 = 8630.187, dw = -0.11276, nw = 1651
120827.0029.ec.fits: ap = 14, w1 = 8682.671, w2 =  8499.44, dw = -0.11105, nw = 1651
120827.0029.ec.fits: ap = 15, w1 =  8553.09, w2 = 8372.597, dw = -0.10939, nw = 1651
120827.0029.ec.fits: ap = 16, w1 = 8427.321, w2 = 8249.484, dw = -0.10778, nw = 1651
120827.0029.ec.fits: ap = 17, w1 = 8305.196, w2 =  8129.94, dw = -0.10622, nw = 1651
120827.0029.ec.fits: ap = 18, w1 = 8186.561, w2 = 8013.811, dw =  -0.1047, nw = 1651
120827.0029.ec.fits: ap = 19, w1 = 8071.268, w2 = 7900.953, dw = -0.10322, nw = 1651
120827.0029.ec.fits: ap = 20, w1 = 7959.177, w2 = 7791.231, dw = -0.10179, nw = 1651
120827.0029.ec.fits: ap = 21, w1 = 7850.157, w2 = 7684.514, dw = -0.10039, nw = 1651
120827.0029.ec.fits: ap = 22, w1 = 7744.084, w2 = 7580.682, dw = -0.09903, nw = 1651
120827.0029.ec.fits: ap = 23, w1 =  7640.84, w2 = 7479.618, dw = -0.09771, nw = 1651
120827.0029.ec.fits: ap = 24, w1 = 7540.312, w2 = 7381.215, dw = -0.09642, nw = 1651
120827.0029.ec.fits: ap = 25, w1 = 7442.395, w2 = 7285.367, dw = -0.09517, nw = 1651
120827.0029.ec.fits: ap = 26, w1 = 7346.989, w2 = 7191.976, dw = -0.09395, nw = 1651
120827.0029.ec.fits: ap = 27, w1 = 7253.999, w2 = 7100.951, dw = -0.09276, nw = 1651
120827.0029.ec.fits: ap = 28, w1 = 7163.333, w2 =   7012.2, dw =  -0.0916, nw = 1651
120827.0029.ec.fits: ap = 29, w1 = 7074.906, w2 = 6925.642, dw = -0.09046, nw = 1651
120827.0029.ec.fits: ap = 30, w1 = 6988.636, w2 = 6841.194, dw = -0.08936, nw = 1651
120827.0029.ec.fits: ap = 31, w1 = 6904.444, w2 = 6758.781, dw = -0.08828, nw = 1651
120827.0029.ec.fits: ap = 32, w1 = 6822.258, w2 = 6678.331, dw = -0.08723, nw = 1651
120827.0029.ec.fits: ap = 33, w1 = 6742.005, w2 = 6599.773, dw =  -0.0862, nw = 1651
120827.0029.ec.fits: ap = 34, w1 = 6663.618, w2 = 6523.043, dw =  -0.0852, nw = 1651
120827.0029.ec.fits: ap = 35, w1 = 6587.033, w2 = 6448.076, dw = -0.08422, nw = 1651
120827.0029.ec.fits: ap = 36, w1 = 6512.189, w2 = 6374.813, dw = -0.08326, nw = 1651
120827.0029.ec.fits: ap = 37, w1 = 6439.027, w2 = 6303.197, dw = -0.08232, nw = 1651
120827.0029.ec.fits: ap = 38, w1 = 6367.491, w2 = 6233.172, dw = -0.08141, nw = 1651
120827.0029.ec.fits: ap = 39, w1 = 6297.527, w2 = 6164.687, dw = -0.08051, nw = 1651
120827.0029.ec.fits: ap = 40, w1 = 6229.084, w2 =  6097.69, dw = -0.07963, nw = 1651
120827.0029.ec.fits: ap = 41, w1 = 6162.113, w2 = 6032.134, dw = -0.07878, nw = 1651
120827.0029.ec.fits: ap = 42, w1 = 6096.567, w2 = 5967.972, dw = -0.07794, nw = 1651
120827.0029.ec.fits: ap = 43, w1 = 6032.401, w2 = 5905.162, dw = -0.07711, nw = 1651
120827.0029.ec.fits: ap = 44, w1 = 5969.572, w2 =  5843.66, dw = -0.07631, nw = 1651
120827.0029.ec.fits: ap = 45, w1 = 5908.038, w2 = 5783.427, dw = -0.07552, nw = 1651
120827.0029.ec.fits: ap = 46, w1 =  5847.76, w2 = 5724.422, dw = -0.07475, nw = 1651
120827.0029.ec.fits: ap = 47, w1 =   5788.7, w2 =  5666.61, dw = -0.07399, nw = 1651
120827.0029.ec.fits: ap = 48, w1 = 5730.822, w2 = 5609.954, dw = -0.07325, nw = 1651
120827.0029.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
120827.0029.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
120827.0029.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
120827.0029.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
120827.0029.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
120827.0029.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
120827.0029.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
120827.0029.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
120827.0029.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
120827.0029.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
120827.0029.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
120827.0029.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
120827.0029.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
120827.0029.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
120827.0029.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
120827.0029.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
120827.0029.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
120827.0029.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
120827.0029.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
120827.0029.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
120827.0029.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
120827.0029.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
120827.0029.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
120827.0029.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
120827.0029.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
120827.0029.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
120827.0029.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
120827.0029.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
120827.0029.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
120827.0029.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
120827.0029.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
120827.0029.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
120827.0029.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
120827.0029.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
120827.0029.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
120827.0029.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
120827.0029.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
120827.0029.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
120827.0029.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
120827.0029.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
120827.0029.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
120827.0029.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
120827.0029.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
120827.0029.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
120827.0029.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
120827.0029.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
120827.0029.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
120827.0029.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
120827.0029.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
120827.0029.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
120827.0029.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
120827.0029.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
120827.0029.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
120827.0029.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
120827.0029.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
120827.0029.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
120827.0029.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
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z120827.0001.ec.fits: ap = 115, w1 = 3432.398, w2 = 3359.905, dw = -0.04394, nw = 1651
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z120827.0002.ec.fits: ap = 99, w1 = 3795.602, w2 = 3715.626, dw = -0.04847, nw = 1651
z120827.0002.ec.fits: ap = 100, w1 =  3770.64, w2 = 3691.192, dw = -0.04815, nw = 1651
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z120827.0002.ec.fits: ap = 102, w1 = 3721.689, w2 = 3643.276, dw = -0.04752, nw = 1651
z120827.0002.ec.fits: ap = 103, w1 = 3697.687, w2 = 3619.782, dw = -0.04721, nw = 1651
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z120827.0002.ec.fits: ap = 105, w1 = 3650.601, w2 = 3573.693, dw = -0.04661, nw = 1651
z120827.0002.ec.fits: ap = 106, w1 = 3627.505, w2 = 3551.086, dw = -0.04631, nw = 1651
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z120827.0004.ec.fits: ap = 49, w1 = 5674.089, w2 =  5554.42, dw = -0.07253, nw = 1651
z120827.0004.ec.fits: ap = 50, w1 = 5618.469, w2 = 5499.975, dw = -0.07181, nw = 1651
z120827.0004.ec.fits: ap = 51, w1 = 5563.929, w2 = 5446.587, dw = -0.07112, nw = 1651
z120827.0004.ec.fits: ap = 52, w1 = 5510.438, w2 = 5394.226, dw = -0.07043, nw = 1651
z120827.0004.ec.fits: ap = 53, w1 = 5457.966, w2 = 5342.863, dw = -0.06976, nw = 1651
z120827.0004.ec.fits: ap = 54, w1 = 5406.484, w2 = 5292.468, dw =  -0.0691, nw = 1651
z120827.0004.ec.fits: ap = 55, w1 = 5355.964, w2 = 5243.016, dw = -0.06845, nw = 1651
z120827.0004.ec.fits: ap = 56, w1 =  5306.38, w2 =  5194.48, dw = -0.06782, nw = 1651
z120827.0004.ec.fits: ap = 57, w1 = 5257.706, w2 = 5146.834, dw =  -0.0672, nw = 1651
z120827.0004.ec.fits: ap = 58, w1 = 5209.917, w2 = 5100.054, dw = -0.06658, nw = 1651
z120827.0004.ec.fits: ap = 59, w1 = 5162.989, w2 = 5054.118, dw = -0.06598, nw = 1651
z120827.0004.ec.fits: ap = 60, w1 = 5116.899, w2 = 5009.001, dw = -0.06539, nw = 1651
z120827.0004.ec.fits: ap = 61, w1 = 5071.625, w2 = 4964.684, dw = -0.06481, nw = 1651
z120827.0004.ec.fits: ap = 62, w1 = 5027.145, w2 = 4921.144, dw = -0.06424, nw = 1651
z120827.0004.ec.fits: ap = 63, w1 = 4983.439, w2 = 4878.361, dw = -0.06368, nw = 1651
z120827.0004.ec.fits: ap = 64, w1 = 4940.487, w2 = 4836.316, dw = -0.06313, nw = 1651
z120827.0004.ec.fits: ap = 65, w1 = 4898.269, w2 =  4794.99, dw = -0.06259, nw = 1651
z120827.0004.ec.fits: ap = 66, w1 = 4856.766, w2 = 4754.364, dw = -0.06206, nw = 1651
z120827.0004.ec.fits: ap = 67, w1 = 4815.961, w2 = 4714.421, dw = -0.06154, nw = 1651
z120827.0004.ec.fits: ap = 68, w1 = 4775.837, w2 = 4675.144, dw = -0.06103, nw = 1651
z120827.0004.ec.fits: ap = 69, w1 = 4736.375, w2 = 4636.516, dw = -0.06052, nw = 1651
z120827.0004.ec.fits: ap = 70, w1 = 4697.561, w2 = 4598.522, dw = -0.06002, nw = 1651
z120827.0004.ec.fits: ap = 71, w1 = 4659.378, w2 = 4561.145, dw = -0.05953, nw = 1651
z120827.0004.ec.fits: ap = 72, w1 = 4621.811, w2 = 4524.372, dw = -0.05905, nw = 1651
z120827.0004.ec.fits: ap = 73, w1 = 4584.845, w2 = 4488.186, dw = -0.05858, nw = 1651
z120827.0004.ec.fits: ap = 74, w1 = 4548.466, w2 = 4452.576, dw = -0.05812, nw = 1651
z120827.0004.ec.fits: ap = 75, w1 = 4512.659, w2 = 4417.526, dw = -0.05766, nw = 1651
z120827.0004.ec.fits: ap = 76, w1 = 4477.413, w2 = 4383.024, dw = -0.05721, nw = 1651
z120827.0004.ec.fits: ap = 77, w1 = 4442.713, w2 = 4349.057, dw = -0.05676, nw = 1651
z120827.0004.ec.fits: ap = 78, w1 = 4408.547, w2 = 4315.612, dw = -0.05632, nw = 1651
z120827.0004.ec.fits: ap = 79, w1 = 4374.902, w2 = 4282.678, dw = -0.05589, nw = 1651
z120827.0004.ec.fits: ap = 80, w1 = 4341.768, w2 = 4250.244, dw = -0.05547, nw = 1651
z120827.0004.ec.fits: ap = 81, w1 = 4309.132, w2 = 4218.297, dw = -0.05505, nw = 1651
z120827.0004.ec.fits: ap = 82, w1 = 4276.983, w2 = 4186.827, dw = -0.05464, nw = 1651
z120827.0004.ec.fits: ap = 83, w1 =  4245.31, w2 = 4155.823, dw = -0.05423, nw = 1651
z120827.0004.ec.fits: ap = 84, w1 = 4214.103, w2 = 4125.276, dw = -0.05383, nw = 1651
z120827.0004.ec.fits: ap = 85, w1 = 4183.352, w2 = 4095.174, dw = -0.05344, nw = 1651
z120827.0004.ec.fits: ap = 86, w1 = 4153.047, w2 = 4065.509, dw = -0.05305, nw = 1651
z120827.0004.ec.fits: ap = 87, w1 = 4123.178, w2 =  4036.27, dw = -0.05267, nw = 1651
z120827.0004.ec.fits: ap = 88, w1 = 4093.735, w2 =  4007.45, dw = -0.05229, nw = 1651
z120827.0004.ec.fits: ap = 89, w1 = 4064.711, w2 = 3979.038, dw = -0.05192, nw = 1651
z120827.0004.ec.fits: ap = 90, w1 = 4036.095, w2 = 3951.027, dw = -0.05156, nw = 1651
z120827.0004.ec.fits: ap = 91, w1 = 4007.879, w2 = 3923.407, dw =  -0.0512, nw = 1651
z120827.0004.ec.fits: ap = 92, w1 = 3980.056, w2 = 3896.171, dw = -0.05084, nw = 1651
z120827.0004.ec.fits: ap = 93, w1 = 3952.616, w2 = 3869.311, dw = -0.05049, nw = 1651
z120827.0004.ec.fits: ap = 94, w1 = 3925.553, w2 = 3842.819, dw = -0.05014, nw = 1651
z120827.0004.ec.fits: ap = 95, w1 = 3898.857, w2 = 3816.688, dw =  -0.0498, nw = 1651
z120827.0004.ec.fits: ap = 96, w1 = 3872.523, w2 = 3790.909, dw = -0.04946, nw = 1651
z120827.0004.ec.fits: ap = 97, w1 = 3846.542, w2 = 3765.477, dw = -0.04913, nw = 1651
z120827.0004.ec.fits: ap = 98, w1 = 3820.908, w2 = 3740.384, dw =  -0.0488, nw = 1651
z120827.0004.ec.fits: ap = 99, w1 = 3795.613, w2 = 3715.623, dw = -0.04848, nw = 1651
z120827.0004.ec.fits: ap = 100, w1 = 3770.651, w2 = 3691.189, dw = -0.04816, nw = 1651
z120827.0004.ec.fits: ap = 101, w1 = 3746.016, w2 = 3667.073, dw = -0.04784, nw = 1651
z120827.0004.ec.fits: ap = 102, w1 =   3721.7, w2 = 3643.271, dw = -0.04753, nw = 1651
z120827.0004.ec.fits: ap = 103, w1 = 3697.699, w2 = 3619.777, dw = -0.04723, nw = 1651
z120827.0004.ec.fits: ap = 104, w1 = 3674.005, w2 = 3596.583, dw = -0.04692, nw = 1651
z120827.0004.ec.fits: ap = 105, w1 = 3650.613, w2 = 3573.685, dw = -0.04662, nw = 1651
z120827.0004.ec.fits: ap = 106, w1 = 3627.517, w2 = 3551.077, dw = -0.04633, nw = 1651
z120827.0004.ec.fits: ap = 107, w1 = 3604.712, w2 = 3528.754, dw = -0.04604, nw = 1651
z120827.0004.ec.fits: ap = 108, w1 = 3582.192, w2 =  3506.71, dw = -0.04575, nw = 1651
z120827.0004.ec.fits: ap = 109, w1 = 3559.952, w2 = 3484.939, dw = -0.04546, nw = 1651
z120827.0004.ec.fits: ap = 110, w1 = 3537.987, w2 = 3463.438, dw = -0.04518, nw = 1651
z120827.0004.ec.fits: ap = 111, w1 = 3516.291, w2 =   3442.2, dw =  -0.0449, nw = 1651
z120827.0004.ec.fits: ap = 112, w1 =  3494.86, w2 = 3421.221, dw = -0.04463, nw = 1651
z120827.0004.ec.fits: ap = 113, w1 = 3473.689, w2 = 3400.497, dw = -0.04436, nw = 1651
z120827.0004.ec.fits: ap = 114, w1 = 3452.773, w2 = 3380.023, dw = -0.04409, nw = 1651
z120827.0004.ec.fits: ap = 115, w1 = 3432.107, w2 = 3359.793, dw = -0.04383, nw = 1651
Continuum fitting the spectra...
Singular solution
Singular solution
Singular solution
Singular solution
Singular solution
Singular solution
Singular solution
Singular solution
Singular solution
Combining spectra...

Dec 10 13:18: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0021.ec.fits[  1]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  2]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  3]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  4]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  5]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  6]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  7]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  8]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[  9]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 10]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 11]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 12]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 13]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 14]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 15]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 16]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 17]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 18]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 19]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 20]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 21]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 22]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 23]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 24]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 25]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 26]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 27]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 28]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 29]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 30]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 31]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 32]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 33]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 34]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 35]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 36]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 37]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 38]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 39]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 40]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 41]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 42]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 43]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 44]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 45]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 46]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 47]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 48]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 49]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 50]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 51]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 52]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 53]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 54]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 55]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 56]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 57]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 58]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 59]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 60]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 61]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 62]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 63]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 64]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 65]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 66]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 67]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 68]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 69]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 70]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 71]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 72]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 73]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 74]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 75]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 76]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 77]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 78]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 79]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 80]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 81]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 82]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 83]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 84]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 85]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 86]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 87]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 88]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 89]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 90]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 91]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 92]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 93]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 94]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 95]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 96]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 97]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 98]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[ 99]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[100]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[101]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[102]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[103]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[104]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[105]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[106]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[107]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[108]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[109]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[110]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[111]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[112]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[113]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[114]  720.0  1.000      0.  0.009
  120827.0021.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sum120827.0021.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:19: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0022.ec.fits[  1]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  2]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  3]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  4]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  5]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  6]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  7]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  8]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[  9]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 10]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 11]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 12]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 13]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 14]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 15]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 16]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 17]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 18]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 19]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 20]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 21]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 22]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 23]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 24]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 25]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 26]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 27]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 28]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 29]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 30]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 31]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 32]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 33]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 34]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 35]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 36]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 37]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 38]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 39]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 40]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 41]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 42]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 43]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 44]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 45]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 46]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 47]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 48]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 49]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 50]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 51]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 52]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 53]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 54]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 55]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 56]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 57]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 58]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 59]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 60]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 61]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 62]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 63]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 64]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 65]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 66]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 67]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 68]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 69]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 70]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 71]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 72]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 73]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 74]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 75]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 76]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 77]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 78]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 79]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 80]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 81]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 82]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 83]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 84]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 85]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 86]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 87]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 88]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 89]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 90]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 91]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 92]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 93]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 94]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 95]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 96]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 97]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 98]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[ 99]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[100]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[101]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[102]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[103]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[104]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[105]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[106]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[107]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[108]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[109]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[110]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[111]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[112]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[113]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[114]  600.0  1.000      0.  0.009
  120827.0022.ec.fits[115]  600.0  1.000      0.  0.009

  Output image = sum120827.0022.ec.fits, ncombine = 115, exptime = 69000.01
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:20: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0023.ec.fits[  1]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  2]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  3]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  4]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  5]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  6]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  7]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  8]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[  9]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 10]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 11]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 12]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 13]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 14]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 15]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 16]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 17]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 18]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 19]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 20]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 21]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 22]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 23]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 24]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 25]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 26]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 27]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 28]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 29]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 30]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 31]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 32]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 33]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 34]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 35]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 36]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 37]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 38]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 39]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 40]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 41]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 42]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 43]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 44]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 45]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 46]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 47]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 48]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 49]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 50]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 51]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 52]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 53]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 54]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 55]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 56]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 57]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 58]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 59]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 60]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 61]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 62]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 63]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 64]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 65]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 66]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 67]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 68]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 69]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 70]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 71]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 72]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 73]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 74]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 75]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 76]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 77]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 78]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 79]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 80]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 81]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 82]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 83]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 84]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 85]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 86]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 87]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 88]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 89]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 90]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 91]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 92]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 93]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 94]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 95]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 96]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 97]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 98]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[ 99]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[100]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[101]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[102]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[103]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[104]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[105]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[106]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[107]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[108]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[109]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[110]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[111]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[112]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[113]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[114]  600.0  1.000      0.  0.009
  120827.0023.ec.fits[115]  600.0  1.000      0.  0.009

  Output image = sum120827.0023.ec.fits, ncombine = 115, exptime = 69000.01
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:22: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0024.ec.fits[  1]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  2]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  3]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  4]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  5]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  6]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  7]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  8]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[  9]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 10]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 11]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 12]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 13]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 14]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 15]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 16]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 17]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 18]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 19]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 20]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 21]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 22]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 23]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 24]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 25]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 26]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 27]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 28]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 29]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 30]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 31]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 32]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 33]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 34]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 35]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 36]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 37]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 38]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 39]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 40]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 41]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 42]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 43]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 44]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 45]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 46]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 47]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 48]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 49]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 50]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 51]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 52]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 53]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 54]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 55]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 56]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 57]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 58]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 59]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 60]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 61]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 62]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 63]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 64]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 65]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 66]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 67]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 68]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 69]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 70]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 71]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 72]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 73]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 74]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 75]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 76]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 77]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 78]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 79]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 80]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 81]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 82]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 83]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 84]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 85]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 86]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 87]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 88]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 89]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 90]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 91]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 92]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 93]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 94]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 95]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 96]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 97]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 98]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[ 99]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[100]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[101]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[102]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[103]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[104]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[105]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[106]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[107]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[108]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[109]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[110]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[111]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[112]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[113]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[114]  900.0  1.000      0.  0.009
  120827.0024.ec.fits[115]  900.0  1.000      0.  0.009

  Output image = sum120827.0024.ec.fits, ncombine = 115, exptime = 103500.
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:23: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0025.ec.fits[  1]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  2]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  3]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  4]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  5]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  6]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  7]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  8]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[  9]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 10]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 11]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 12]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 13]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 14]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 15]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 16]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 17]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 18]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 19]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 20]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 21]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 22]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 23]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 24]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 25]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 26]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 27]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 28]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 29]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 30]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 31]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 32]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 33]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 34]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 35]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 36]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 37]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 38]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 39]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 40]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 41]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 42]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 43]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 44]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 45]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 46]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 47]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 48]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 49]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 50]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 51]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 52]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 53]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 54]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 55]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 56]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 57]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 58]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 59]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 60]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 61]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 62]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 63]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 64]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 65]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 66]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 67]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 68]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 69]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 70]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 71]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 72]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 73]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 74]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 75]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 76]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 77]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 78]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 79]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 80]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 81]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 82]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 83]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 84]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 85]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 86]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 87]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 88]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 89]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 90]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 91]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 92]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 93]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 94]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 95]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 96]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 97]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 98]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[ 99]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[100]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[101]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[102]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[103]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[104]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[105]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[106]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[107]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[108]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[109]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[110]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[111]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[112]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[113]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[114]  720.0  1.000      0.  0.009
  120827.0025.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sum120827.0025.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:24: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0026.ec.fits[  1]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  2]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  3]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  4]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  5]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  6]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  7]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  8]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[  9]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 10]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 11]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 12]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 13]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 14]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 15]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 16]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 17]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 18]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 19]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 20]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 21]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 22]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 23]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 24]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 25]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 26]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 27]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 28]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 29]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 30]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 31]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 32]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 33]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 34]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 35]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 36]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 37]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 38]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 39]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 40]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 41]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 42]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 43]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 44]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 45]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 46]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 47]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 48]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 49]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 50]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 51]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 52]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 53]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 54]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 55]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 56]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 57]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 58]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 59]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 60]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 61]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 62]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 63]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 64]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 65]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 66]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 67]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 68]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 69]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 70]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 71]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 72]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 73]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 74]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 75]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 76]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 77]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 78]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 79]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 80]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 81]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 82]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 83]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 84]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 85]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 86]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 87]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 88]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 89]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 90]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 91]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 92]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 93]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 94]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 95]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 96]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 97]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 98]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[ 99]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[100]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[101]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[102]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[103]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[104]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[105]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[106]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[107]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[108]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[109]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[110]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[111]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[112]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[113]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[114]  900.0  1.000      0.  0.009
  120827.0026.ec.fits[115]  900.0  1.000      0.  0.009

  Output image = sum120827.0026.ec.fits, ncombine = 115, exptime = 103500.1
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:25: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0028.ec.fits[  1]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  2]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  3]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  4]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  5]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  6]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  7]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  8]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[  9]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 10]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 11]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 12]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 13]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 14]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 15]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 16]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 17]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 18]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 19]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 20]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 21]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 22]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 23]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 24]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 25]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 26]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 27]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 28]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 29]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 30]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 31]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 32]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 33]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 34]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 35]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 36]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 37]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 38]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 39]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 40]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 41]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 42]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 43]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 44]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 45]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 46]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 47]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 48]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 49]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 50]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 51]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 52]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 53]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 54]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 55]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 56]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 57]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 58]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 59]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 60]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 61]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 62]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 63]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 64]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 65]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 66]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 67]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 68]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 69]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 70]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 71]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 72]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 73]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 74]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 75]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 76]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 77]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 78]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 79]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 80]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 81]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 82]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 83]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 84]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 85]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 86]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 87]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 88]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 89]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 90]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 91]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 92]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 93]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 94]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 95]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 96]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 97]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 98]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[ 99]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[100]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[101]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[102]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[103]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[104]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[105]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[106]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[107]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[108]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[109]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[110]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[111]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[112]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[113]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[114]  720.0  1.000      0.  0.009
  120827.0028.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sum120827.0028.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:26: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0029.ec.fits[  1] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  2] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  3] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  4] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  5] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  6] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  7] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  8] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[  9] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 10] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 11] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 12] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 13] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 14] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 15] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 16] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 17] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 18] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 19] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 20] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 21] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 22] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 23] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 24] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 25] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 26] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 27] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 28] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 29] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 30] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 31] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 32] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 33] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 34] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 35] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 36] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 37] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 38] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 39] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 40] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 41] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 42] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 43] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 44] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 45] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 46] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 47] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 48] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 49] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 50] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 51] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 52] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 53] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 54] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 55] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 56] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 57] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 58] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 59] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 60] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 61] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 62] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 63] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 64] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 65] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 66] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 67] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 68] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 69] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 70] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 71] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 72] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 73] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 74] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 75] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 76] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 77] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 78] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 79] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 80] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 81] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 82] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 83] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 84] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 85] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 86] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 87] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 88] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 89] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 90] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 91] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 92] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 93] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 94] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 95] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 96] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 97] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 98] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[ 99] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[100] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[101] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[102] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[103] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[104] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[105] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[106] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[107] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[108] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[109] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[110] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[111] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[112] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[113] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[114] 1800.0  1.000      0.  0.009
  120827.0029.ec.fits[115] 1800.0  1.000      0.  0.009

  Output image = sum120827.0029.ec.fits, ncombine = 115, exptime = 207000.
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:27: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  120827.0030.ec.fits[  1]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  2]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  3]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  4]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  5]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  6]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  7]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  8]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[  9]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 10]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 11]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 12]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 13]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 14]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 15]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 16]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 17]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 18]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 19]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 20]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 21]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 22]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 23]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 24]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 25]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 26]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 27]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 28]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 29]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 30]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 31]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 32]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 33]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 34]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 35]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 36]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 37]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 38]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 39]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 40]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 41]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 42]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 43]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 44]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 45]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 46]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 47]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 48]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 49]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 50]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 51]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 52]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 53]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 54]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 55]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 56]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 57]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 58]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 59]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 60]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 61]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 62]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 63]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 64]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 65]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 66]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 67]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 68]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 69]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 70]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 71]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 72]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 73]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 74]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 75]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 76]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 77]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 78]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 79]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 80]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 81]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 82]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 83]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 84]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 85]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 86]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 87]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 88]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 89]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 90]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 91]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 92]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 93]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 94]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 95]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 96]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 97]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 98]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[ 99]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[100]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[101]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[102]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[103]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[104]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[105]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[106]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[107]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[108]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[109]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[110]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[111]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[112]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[113]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[114]  300.6  1.000      0.  0.009
  120827.0030.ec.fits[115]  300.6  1.000      0.  0.009

  Output image = sum120827.0030.ec.fits, ncombine = 115, exptime = 34568.44
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:28: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0021.ec.fits[  1]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  2]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  3]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  4]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  5]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  6]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  7]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  8]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[  9]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 10]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 11]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 12]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 13]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 14]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 15]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 16]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 17]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 18]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 19]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 20]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 21]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 22]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 23]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 24]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 25]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 26]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 27]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 28]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 29]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 30]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 31]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 32]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 33]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 34]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 35]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 36]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 37]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 38]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 39]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 40]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 41]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 42]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 43]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 44]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 45]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 46]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 47]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 48]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 49]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 50]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 51]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 52]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 53]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 54]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 55]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 56]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 57]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 58]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 59]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 60]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 61]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 62]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 63]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 64]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 65]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 66]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 67]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 68]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 69]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 70]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 71]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 72]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 73]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 74]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 75]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 76]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 77]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 78]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 79]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 80]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 81]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 82]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 83]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 84]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 85]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 86]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 87]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 88]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 89]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 90]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 91]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 92]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 93]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 94]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 95]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 96]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 97]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 98]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[ 99]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[100]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[101]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[102]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[103]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[104]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[105]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[106]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[107]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[108]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[109]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[110]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[111]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[112]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[113]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[114]  720.0  1.000      0.  0.009
  fitcont120827.0021.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sumfitcont120827.0021.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:29: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0022.ec.fits[  1]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  2]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  3]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  4]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  5]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  6]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  7]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  8]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[  9]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 10]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 11]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 12]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 13]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 14]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 15]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 16]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 17]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 18]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 19]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 20]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 21]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 22]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 23]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 24]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 25]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 26]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 27]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 28]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 29]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 30]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 31]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 32]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 33]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 34]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 35]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 36]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 37]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 38]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 39]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 40]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 41]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 42]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 43]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 44]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 45]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 46]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 47]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 48]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 49]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 50]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 51]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 52]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 53]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 54]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 55]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 56]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 57]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 58]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 59]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 60]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 61]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 62]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 63]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 64]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 65]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 66]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 67]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 68]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 69]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 70]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 71]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 72]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 73]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 74]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 75]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 76]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 77]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 78]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 79]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 80]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 81]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 82]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 83]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 84]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 85]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 86]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 87]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 88]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 89]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 90]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 91]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 92]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 93]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 94]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 95]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 96]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 97]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 98]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[ 99]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[100]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[101]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[102]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[103]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[104]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[105]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[106]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[107]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[108]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[109]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[110]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[111]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[112]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[113]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[114]  600.0  1.000      0.  0.009
  fitcont120827.0022.ec.fits[115]  600.0  1.000      0.  0.009

  Output image = sumfitcont120827.0022.ec.fits, ncombine = 115, exptime = 69000.01
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:29: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0023.ec.fits[  1]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  2]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  3]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  4]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  5]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  6]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  7]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  8]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[  9]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 10]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 11]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 12]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 13]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 14]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 15]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 16]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 17]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 18]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 19]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 20]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 21]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 22]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 23]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 24]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 25]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 26]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 27]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 28]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 29]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 30]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 31]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 32]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 33]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 34]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 35]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 36]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 37]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 38]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 39]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 40]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 41]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 42]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 43]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 44]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 45]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 46]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 47]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 48]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 49]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 50]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 51]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 52]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 53]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 54]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 55]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 56]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 57]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 58]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 59]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 60]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 61]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 62]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 63]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 64]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 65]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 66]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 67]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 68]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 69]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 70]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 71]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 72]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 73]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 74]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 75]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 76]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 77]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 78]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 79]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 80]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 81]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 82]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 83]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 84]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 85]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 86]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 87]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 88]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 89]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 90]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 91]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 92]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 93]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 94]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 95]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 96]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 97]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 98]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[ 99]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[100]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[101]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[102]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[103]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[104]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[105]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[106]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[107]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[108]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[109]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[110]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[111]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[112]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[113]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[114]  600.0  1.000      0.  0.009
  fitcont120827.0023.ec.fits[115]  600.0  1.000      0.  0.009

  Output image = sumfitcont120827.0023.ec.fits, ncombine = 115, exptime = 69000.01
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:30: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0024.ec.fits[  1]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  2]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  3]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  4]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  5]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  6]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  7]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  8]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[  9]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 10]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 11]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 12]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 13]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 14]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 15]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 16]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 17]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 18]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 19]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 20]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 21]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 22]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 23]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 24]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 25]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 26]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 27]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 28]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 29]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 30]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 31]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 32]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 33]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 34]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 35]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 36]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 37]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 38]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 39]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 40]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 41]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 42]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 43]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 44]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 45]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 46]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 47]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 48]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 49]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 50]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 51]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 52]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 53]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 54]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 55]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 56]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 57]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 58]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 59]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 60]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 61]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 62]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 63]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 64]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 65]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 66]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 67]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 68]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 69]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 70]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 71]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 72]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 73]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 74]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 75]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 76]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 77]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 78]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 79]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 80]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 81]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 82]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 83]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 84]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 85]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 86]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 87]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 88]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 89]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 90]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 91]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 92]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 93]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 94]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 95]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 96]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 97]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 98]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[ 99]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[100]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[101]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[102]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[103]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[104]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[105]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[106]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[107]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[108]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[109]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[110]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[111]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[112]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[113]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[114]  900.0  1.000      0.  0.009
  fitcont120827.0024.ec.fits[115]  900.0  1.000      0.  0.009

  Output image = sumfitcont120827.0024.ec.fits, ncombine = 115, exptime = 103500.
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:31: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0025.ec.fits[  1]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  2]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  3]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  4]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  5]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  6]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  7]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  8]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[  9]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 10]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 11]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 12]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 13]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 14]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 15]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 16]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 17]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 18]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 19]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 20]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 21]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 22]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 23]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 24]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 25]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 26]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 27]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 28]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 29]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 30]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 31]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 32]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 33]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 34]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 35]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 36]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 37]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 38]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 39]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 40]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 41]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 42]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 43]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 44]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 45]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 46]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 47]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 48]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 49]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 50]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 51]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 52]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 53]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 54]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 55]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 56]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 57]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 58]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 59]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 60]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 61]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 62]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 63]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 64]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 65]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 66]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 67]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 68]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 69]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 70]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 71]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 72]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 73]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 74]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 75]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 76]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 77]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 78]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 79]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 80]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 81]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 82]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 83]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 84]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 85]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 86]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 87]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 88]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 89]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 90]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 91]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 92]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 93]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 94]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 95]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 96]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 97]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 98]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[ 99]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[100]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[101]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[102]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[103]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[104]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[105]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[106]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[107]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[108]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[109]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[110]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[111]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[112]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[113]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[114]  720.0  1.000      0.  0.009
  fitcont120827.0025.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sumfitcont120827.0025.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:32: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0026.ec.fits[  1]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  2]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  3]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  4]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  5]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  6]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  7]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  8]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[  9]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 10]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 11]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 12]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 13]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 14]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 15]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 16]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 17]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 18]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 19]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 20]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 21]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 22]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 23]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 24]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 25]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 26]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 27]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 28]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 29]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 30]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 31]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 32]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 33]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 34]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 35]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 36]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 37]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 38]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 39]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 40]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 41]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 42]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 43]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 44]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 45]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 46]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 47]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 48]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 49]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 50]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 51]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 52]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 53]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 54]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 55]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 56]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 57]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 58]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 59]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 60]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 61]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 62]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 63]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 64]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 65]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 66]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 67]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 68]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 69]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 70]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 71]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 72]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 73]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 74]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 75]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 76]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 77]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 78]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 79]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 80]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 81]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 82]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 83]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 84]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 85]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 86]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 87]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 88]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 89]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 90]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 91]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 92]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 93]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 94]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 95]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 96]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 97]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 98]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[ 99]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[100]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[101]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[102]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[103]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[104]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[105]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[106]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[107]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[108]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[109]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[110]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[111]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[112]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[113]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[114]  900.0  1.000      0.  0.009
  fitcont120827.0026.ec.fits[115]  900.0  1.000      0.  0.009

  Output image = sumfitcont120827.0026.ec.fits, ncombine = 115, exptime = 103500.1
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:33: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0028.ec.fits[  1]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  2]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  3]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  4]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  5]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  6]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  7]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  8]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[  9]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 10]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 11]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 12]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 13]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 14]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 15]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 16]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 17]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 18]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 19]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 20]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 21]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 22]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 23]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 24]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 25]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 26]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 27]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 28]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 29]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 30]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 31]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 32]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 33]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 34]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 35]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 36]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 37]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 38]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 39]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 40]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 41]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 42]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 43]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 44]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 45]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 46]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 47]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 48]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 49]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 50]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 51]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 52]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 53]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 54]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 55]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 56]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 57]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 58]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 59]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 60]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 61]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 62]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 63]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 64]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 65]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 66]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 67]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 68]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 69]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 70]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 71]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 72]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 73]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 74]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 75]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 76]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 77]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 78]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 79]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 80]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 81]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 82]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 83]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 84]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 85]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 86]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 87]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 88]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 89]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 90]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 91]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 92]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 93]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 94]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 95]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 96]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 97]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 98]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[ 99]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[100]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[101]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[102]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[103]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[104]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[105]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[106]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[107]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[108]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[109]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[110]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[111]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[112]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[113]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[114]  720.0  1.000      0.  0.009
  fitcont120827.0028.ec.fits[115]  720.0  1.000      0.  0.009

  Output image = sumfitcont120827.0028.ec.fits, ncombine = 115, exptime = 82799.99
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:34: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0029.ec.fits[  1] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  2] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  3] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  4] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  5] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  6] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  7] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  8] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[  9] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 10] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 11] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 12] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 13] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 14] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 15] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 16] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 17] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 18] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 19] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 20] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 21] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 22] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 23] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 24] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 25] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 26] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 27] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 28] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 29] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 30] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 31] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 32] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 33] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 34] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 35] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 36] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 37] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 38] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 39] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 40] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 41] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 42] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 43] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 44] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 45] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 46] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 47] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 48] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 49] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 50] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 51] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 52] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 53] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 54] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 55] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 56] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 57] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 58] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 59] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 60] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 61] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 62] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 63] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 64] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 65] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 66] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 67] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 68] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 69] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 70] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 71] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 72] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 73] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 74] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 75] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 76] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 77] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 78] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 79] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 80] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 81] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 82] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 83] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 84] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 85] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 86] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 87] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 88] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 89] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 90] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 91] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 92] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 93] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 94] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 95] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 96] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 97] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 98] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[ 99] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[100] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[101] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[102] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[103] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[104] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[105] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[106] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[107] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[108] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[109] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[110] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[111] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[112] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[113] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[114] 1800.0  1.000      0.  0.009
  fitcont120827.0029.ec.fits[115] 1800.0  1.000      0.  0.009

  Output image = sumfitcont120827.0029.ec.fits, ncombine = 115, exptime = 207000.
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0

Dec 10 13:34: SCOMBINE
  combine = sum
  blank = 0.
                Images     Exp  Scale    Zero Weight
  fitcont120827.0030.ec.fits[  1]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  2]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  3]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  4]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  5]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  6]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  7]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  8]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[  9]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 10]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 11]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 12]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 13]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 14]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 15]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 16]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 17]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 18]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 19]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 20]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 21]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 22]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 23]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 24]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 25]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 26]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 27]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 28]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 29]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 30]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 31]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 32]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 33]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 34]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 35]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 36]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 37]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 38]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 39]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 40]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 41]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 42]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 43]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 44]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 45]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 46]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 47]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 48]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 49]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 50]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 51]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 52]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 53]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 54]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 55]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 56]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 57]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 58]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 59]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 60]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 61]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 62]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 63]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 64]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 65]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 66]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 67]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 68]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 69]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 70]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 71]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 72]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 73]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 74]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 75]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 76]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 77]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 78]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 79]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 80]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 81]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 82]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 83]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 84]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 85]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 86]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 87]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 88]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 89]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 90]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 91]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 92]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 93]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 94]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 95]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 96]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 97]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 98]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[ 99]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[100]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[101]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[102]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[103]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[104]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[105]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[106]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[107]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[108]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[109]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[110]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[111]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[112]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[113]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[114]  300.6  1.000      0.  0.009
  fitcont120827.0030.ec.fits[115]  300.6  1.000      0.  0.009

  Output image = sumfitcont120827.0030.ec.fits, ncombine = 115, exptime = 34568.44
  w1 = 3359.793, w2 = 10812.19, dw = 0.04382655, nw = 170044., dtype = 0
82799.99
fullspec120827.0021.ec.fits,EXPTIME: 82799.99 -> 719.999913043
fullspec120827.0021.ec.fits updated
69000.01
fullspec120827.0022.ec.fits,EXPTIME: 69000.01 -> 600.000086957
fullspec120827.0022.ec.fits updated
69000.01
fullspec120827.0023.ec.fits,EXPTIME: 69000.01 -> 600.000086957
fullspec120827.0023.ec.fits updated
103500.
fullspec120827.0024.ec.fits,EXPTIME: 103500. -> 900.0
fullspec120827.0024.ec.fits updated
82799.99
fullspec120827.0025.ec.fits,EXPTIME: 82799.99 -> 719.999913043
fullspec120827.0025.ec.fits updated
103500.1
fullspec120827.0026.ec.fits,EXPTIME: 103500.1 -> 900.000869565
fullspec120827.0026.ec.fits updated
82799.99
fullspec120827.0028.ec.fits,EXPTIME: 82799.99 -> 719.999913043
fullspec120827.0028.ec.fits updated
207000.
fullspec120827.0029.ec.fits,EXPTIME: 207000. -> 1800.0
fullspec120827.0029.ec.fits updated
34568.44
fullspec120827.0030.ec.fits,EXPTIME: 34568.44 -> 300.595130435
fullspec120827.0030.ec.fits updated
ALL DONE! Yay! (=^.^=)