Saturday, November 9, 2013
Found bugs in calfiles and aipy. Restarting cal of yy pols. xx should still be good and fine.
starting point was tau_ew = 2.232084 for all the commands following....
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 41_49,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.24042460526
Score: 0.631938926099 (99.99% of 0.631992)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_19,41_49,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.24028150467
Score: 0.728974710762 (99.99% of 0.729023)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.27530398689
Score: 0.72641753719 (99.62% of 0.729153)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.28560861569
Score: 0.725256931038 (99.22% of 0.730995)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.24796288741
Score: 0.778859653 (99.89% of 0.779711)
Note that this is xx pol.
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.22040827268
Score: 0.71422251739 (99.92% of 0.714768)
Note that this is xx,yy
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456248.*49*.uvcRREcAzx tau_ew 2.23367312702
Score: 0.748045993491 (100.00% of 0.748055)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.21090148196
crab
jys 138.78195542 # it is ok that this is low. crab is probably low in the beam. The other 2 seem good.
# Note that the gain is .0054 (change to 0.00505 doesnt change mush. pic - > 388)
for
jys 852.149337521
pic
jys 339.807280482
Score: 0.728038539606 (93.37% of 0.779711)
========================================================================================
GAIN CAL :
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 41_49 -s pic,for,crab -c 50_150_10 -x 20 -P "aa=gain" *49*.uvcRREcAzx gain 0.00542092979193
Score: 0.657149620702 (100.00% of 0.657175)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a "(49)_(41,47,19,29,28,34,51)" -s pic,for,crab -c 50_150_10 -x 20 -P "aa=gain" *49*.uvcRREcAzx gain 0.00505113018036
Score: 0.707598775297 (99.00% of 0.714768)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -P "aa=gain" *49*.uvcRREcAzx
gain 0.0049389653635
Score: 0.736276075596 (99.91% of 0.736919)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a cross -s pic,for,crab -c 50_150_10 -x 20 -P "aa=gain" *49*.uvcRREcAzx
gain 0.00500928205848
Score: 0.78741752438 (99.99% of 0.787482)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -P "aa=gain" *49*.uvcRREcAzx
gain 0.00493412065268
Score: 0.799825814938 (99.94% of 0.800334)
==========================================================================================
with gain = 0.004934
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.2055258857
crab
jys 204.255327636
for
jys 1001.40292946
pic
jys 420.590007336
Score: 0.707840976059 (96.13% of 0.7363 11)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.2385479798
crab
jys 913.172829664
for
jys 883.384644132
pic
jys 426.617074502
Score: 0.792162095915 (99.02% of 0.799991)
Note new Day!
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" zen.2456278.*{41,45}*.uvcRREcAzx
tau_ew 2.2365445099
Score: 0.772742556379 (100.00% of 0.772753)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(pic/for/crab)=jys" zen.2456278.*{41,45}*.uvcRREcAzx
tau_ew 2.20443305591
crab
jys 197.095695927
for
jys 891.258850664
pic
jys 429.902202063
Score: 0.750500083862 (97.12% of 0.772753)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(pic/for/crab)=jys" zen.2456278.*{41,45}*.uvcRREcAzx
tau_ew 2.20486334935
crab
jys 66.0079799233
for
jys 954.221697449
pic
jys 420.441220818
Score: 0.773870742787 (95.52% of 0.810149)
(similar with -p xx,yy)
[zakiali@node04 psa6294]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456294.*37*.uvcRREcAzx
aa
tau_ew 2.21831273428
crab
jys 117.428560061
for
jys 944.941500769
pic
jys 423.163176316
Score: 0.707291640189 (95.42% of 0.741252)
[zakiali@node04 psa6316]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456316.*33*.uvcRREcAzx
aa
tau_ew 2.18145433175
crab
jys -108.950814207 # note that crab is below the horizon. Dont worry about it.
for
jys 906.416058294
pic
jys 420.821146975
Score: 0.733504022698 (93.53% of 0.784241)
[zakiali@node04 psa6345]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456345.*25*.uvcRREcAzx
aa
tau_ew 2.20756070318
crab
jys 267.467062925
for
jys 986.972670116
pic
jys 422.755275091
Score: 0.727902574833 (96.24% of 0.756313)
[zakiali@node04 psa6370]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew)" -P "(for/crab/pic)=jys" zen.2456370.*17*.uvcRREcAzx
aa
tau_ew 2.16848000409
crab
jys -129.393732629
for
jys 890.719408713
pic
jys 302.422919733
Score: 0.978078618803 (99.27% of 0.985317)
This is bad... but the sun is also up when pic and crab are. This corrupts the data.
CALIBRATING YY POL
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.20704611848
tau_ns 0.772841762634
crab
jys 835.949586433
for
jys 987.969722631
pic
jys 444.870901259
Score: 0.678101190526 (97.76% of 0.693668)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.20935239745
tau_ns 0.922886493171
crab
jys 942.757951802
for
jys 958.855611524
pic
jys 461.553136025
Score: 0.666100575646 (97.94% of 0.680124)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61,49_63,49_2,49_21,49_45 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.21648661121
tau_ns 0.890497942791
crab
jys 1160.89272592
for
jys 963.763218886
pic
jys 452.464841474
Score: 0.664603294777 (98.59% of 0.674102)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61,49_63,49_2,49_21,49_45,49_33,49_32,49_46 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.21793019409
tau_ns 0.889020116186
crab
jys 988.14538299
for
jys 964.894256111
pic
jys 451.313804193
Score: 0.664042573042 (98.34% of 0.675221)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61,49_63,49_2,49_21,49_45,49_33,49_32,49_46 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ew 2.23355053693
tau_ns 0.883658250738
crab
jys 822.647563339
for
jys 1010.88273902
pic
jys 418.345897185
Score: 0.690334541722 (97.85% of 0.705485)
[zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ns 0.87060313138
crab
jys 998.777636638
for
jys 892.807703405
pic
jys 408.967891428
Score: 0.804649807207 (99.17% of 0.811360)
zakiali@node04 psa6248]$ fitmdl.py -C psa6240_v003 -p xx,yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ns)" -P "(for/crab/pic)=jys" zen.2456248.*49*.uvcRREcAzx
aa
tau_ns 0.875550278086
crab
jys 911.923086971
for
jys 883.800367381
pic
jys 426.522298675
Score: 0.792120207587 (99.08% of 0.799479)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61,49_63,49_2,49_21,49_45,49_33,49_32,49_46 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456278.*41*.uvcRREcAzx
aa
tau_ew 2.23617670648
tau_ns 0.879231945776
crab
jys 828.989351624
for
jys 957.768808656
pic
jys 407.436883231
Score: 0.69168187379 (97.88% of 0.706640)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p xx,yy -a 49_34,49_51,49_28,49_19,41_49,49_47,49_29,49_3,49_25,49_48,49_24,49_55,49_58,49_61,49_63,49_2,49_21,49_45,49_33,49_32,49_46 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ew/tau_ns)" -P "(for/crab/pic)=jys" zen.2456278.*41*.uvcRREcAzx
aa
tau_ew 2.22699108802
tau_ns 0.88096723485
crab
jys 866.929402899
for
jys 944.863663621
pic
jys 418.127618002
Score: 0.680036814234 (98.37% of 0.691272)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v003 -p xx,yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ns)" -P "(for/crab/pic)=jys" zen.2456278.*41*.uvcRREcAzx
aa
tau_ns 0.882103895884
crab
jys 844.49941077
for
jys 839.0918705
pic
jys 404.344329204
Score: 0.795459261209 (98.99% of 0.803597)
[zakiali@node04 psa6294]$ fitmdl.py -C psa6240_v003 -p xx,yy -a cross -s pic,for,crab -c 50_150_10 -x 20 -S "aa=(tau_ns)" -P "(for/crab/pic)=jys" zen.2456294.*37*.uvcRREcAzx
aa
tau_ns 0.886105486656
crab
jys 731.374185569
for
jys 836.429354892
pic
jys 409.361952505
Score: 0.805238350612 (98.75% of 0.815430)
FINAL : tau_ew = 2.23
tau_ns = 0.88
6294,6316,6345,6370
originial fluxes for crab,for, and pic
crab jys 1838.0
for
jys 907.09
pic
jys 381.999680788
Get yy calibrated asap…
Note that the calfile was modified from the previous runs with the dly_xx_to_yy from redcal.
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v001 -p xx -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/2.3" -P "(for/crab)=jys" *{37,41,45}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew 2.18942749261
crab
jys 2204.64964343
for
jys 1715.4811407
Score: 0.916110476391 (98.16% of 0.933305)
------------------------------------------------------------
(off a little bit from the previous value, however the it was a different day)
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v001 -p xx -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/2.3" -P "(for/crab)=jys" *{37,41,45}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew -0.0665818528798
crab
jys -76.4234201128
for
jys 149.6196526
Score: 1.00209206053 (98.09% of 1.021554)
------------------------------------------------------------
[zakiali@node04 psa6278]$ fitmdl.py -C psa6240_v001 -p xx -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/2.3" -P "(for/crab)=jys" *{37,41,45}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew 2.64568763435
crab
jys 323.210411318
for
jys 97.5017062731
Score: 1.003079055 (97.45% of 1.029351)
------------------------------------------------------------
Thursday, November 7, 2013
Got the dly coefficients (xx_to_yy).... just seeing if they make any sense now.
[zakiali@node04 psa6240]$ fitmdl.py -C psa6240_v001 -p yy -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/2.2" -P "(for/crab)=jys" *{48,52}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew 0.607325790907
crab
jys 186225.457783
for
jys 42109.5328223
Score: 0.997490669453 (99.76% of 0.999930)
[zakiali@node04 psa6240]$ fitmdl.py -C psa6240_v001 -p yy -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/0" -P "(for/crab)=jys" *{48,52}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew 5.72764148927
crab
jys -87676.3731156
for
jys 40547.0175286
Score: 0.998241865674 (99.82% of 1.000058)
[zakiali@node04 psa6240]$ fitmdl.py -C psa6240_v001 -p yy -a 10_3,22_35,10_42,43_33,52_15,31_8,1_9,49_47 -s pic,for,crab -c 50_150_10 -x 20 -S "aa=tau_ew/3" -P "(for/crab)=jys" *{48,52}*.uvcRREcAzx
----------------------------------------------------------------------
aa
tau_ew 0.607325816215
crab
jys 186225.524616
for
jys 42109.5140519
{'aa': {'tau_ew': 0.60732581621479442}, 'crab': {'jys': 186225.52461571048}, 'for': {'jys': 42109.514051882812}}
Score: 0.997490669453 (99.75% of 0.999977)
Get similar results for psa6240_v002, which is the calfile with the new delays. That is the one from all the data.
off by ~.01 in either case.
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