INFO: CPU: calc-server INFO: Crux version: 3.1-4438655b INFO: Sat Jun 9 17:10:19 MSK 2018 COMMAND LINE: crux q-ranker /home/mark/overfit_test/mzxml/20100609_Velos1_TaGe_SA_293_4.mzXML /home/mark/overfit_test/comet/20100609_Velos1_TaGe_SA_293_4_8.comet.target.txt --decoy-prefix DECOY_ --output-dir /home/mark/overfit_test/qranker --fileroot 20100609_Velos1_TaGe_SA_293_4_8 INFO: Beginning q-ranker. INFO: delmited source: /home/mark/overfit_test/comet/20100609_Velos1_TaGe_SA_293_4_8.comet.target.txt INFO: ms2 source: /home/mark/overfit_test/mzxml/20100609_Velos1_TaGe_SA_293_4.mzXML INFO: output_directory: /home/mark/overfit_test/qranker INFO: enzyme: trypsin INFO: decoy prefix: DECOY_ INFO: parsing files: INFO: reading file /home/mark/overfit_test/mzxml/20100609_Velos1_TaGe_SA_293_4.mzXML INFO: parsing file /home/mark/overfit_test/comet/20100609_Velos1_TaGe_SA_293_4_8.comet.target.txt INFO: PSM number 0 INFO: PSM number 5000 INFO: PSM number 10000 INFO: PSM number 15000 INFO: Number of spectra: 19424 INFO: Number of PSMs: total 19424 positives 16655 negatives 2769 INFO: Number of peptides: total 15694 positives 13120 negatives 2574 INFO: Number of proteins: total 8709 positives 6030 negatives 2679 INFO: reading data INFO: Before Iterating INFO: trainset 0.00:7795 0.00:8110 0.01:8464 0.01:8838 0.01:9041 0.02:9339 0.03:9518 0.04:9671 0.05:9759 0.06:9865 0.07:9989 0.08:10062 0.09:10155 0.10:10246 INFO: trainset 0.00:2632 0.00:2671 0.01:2708 0.01:2724 0.01:2835 0.02:2933 0.03:3091 0.04:3157 0.05:3199 0.06:3240 0.07:3274 0.08:3324 0.09:3344 0.10:3367 INFO: Iteration 0 : INFO: trainset 0.00:7731 0.00:8759 0.01:9009 0.01:9197 0.01:9369 0.02:9696 0.03:9930 0.04:10062 0.05:10218 0.06:10273 0.07:10323 0.08:10353 0.09:10399 0.10:10466 INFO: testset 0.00:2646 0.00:2646 0.01:2882 0.01:2991 0.01:3153 0.02:3296 0.03:3351 0.04:3386 0.05:3406 0.06:3436 0.07:3460 0.08:3467 0.09:3477 0.10:3493 INFO: Iteration 10 : INFO: trainset 0.00:8093 0.00:9476 0.01:9508 0.01:9591 0.01:9786 0.02:10003 0.03:10139 0.04:10257 0.05:10299 0.06:10351 0.07:10404 0.08:10477 0.09:10512 0.10:10553 INFO: testset 0.00:2807 0.00:2903 0.01:3000 0.01:3062 0.01:3151 0.02:3358 0.03:3389 0.04:3428 0.05:3432 0.06:3441 0.07:3451 0.08:3456 0.09:3465 0.10:3479 INFO: Iteration 20 : INFO: trainset 0.00:8240 0.00:9424 0.01:9507 0.01:9618 0.01:9807 0.02:10037 0.03:10179 0.04:10254 0.05:10323 0.06:10372 0.07:10411 0.08:10467 0.09:10517 0.10:10560 INFO: testset 0.00:2746 0.00:2924 0.01:3040 0.01:3063 0.01:3128 0.02:3352 0.03:3400 0.04:3410 0.05:3425 0.06:3451 0.07:3458 0.08:3465 0.09:3470 0.10:3477 INFO: training threshold 13 INFO: Iteration 30 : INFO: trainset 0.00:8071 0.00:9350 0.01:9478 0.01:9684 0.01:9859 0.02:10052 0.03:10193 0.04:10262 0.05:10302 0.06:10352 0.07:10388 0.08:10434 0.09:10469 0.10:10521 INFO: testset 0.00:2755 0.00:2775 0.01:3011 0.01:3104 0.01:3210 0.02:3336 0.03:3374 0.04:3388 0.05:3414 0.06:3428 0.07:3451 0.08:3474 0.09:3477 0.10:3497 INFO: Iteration 33 : INFO: trainset 0.00:8448 0.00:9367 0.01:9602 0.01:9716 0.01:9893 0.02:10098 0.03:10228 0.04:10282 0.05:10321 0.06:10398 0.07:10430 0.08:10486 0.09:10510 0.10:10553 INFO: testset 0.00:2769 0.00:2778 0.01:3065 0.01:3119 0.01:3213 0.02:3330 0.03:3391 0.04:3423 0.05:3433 0.06:3455 0.07:3459 0.08:3465 0.09:3469 0.10:3485 INFO: Iteration 36 : INFO: trainset 0.00:8454 0.00:9495 0.01:9631 0.01:9845 0.01:9900 0.02:10133 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INFO: Return Code:0