INFO: CPU: calc-server INFO: Crux version: 3.1-4438655b INFO: Sat Jun 9 17:07:21 MSK 2018 COMMAND LINE: crux q-ranker /home/mark/overfit_test/mzxml/olsen_100ng_30min_15k_01.mzXML /home/mark/overfit_test/comet/olsen_100ng_30min_15k_01_1.comet.target.txt --decoy-prefix DECOY_ --output-dir /home/mark/overfit_test/qranker --fileroot olsen_100ng_30min_15k_01_1 INFO: Beginning q-ranker. INFO: delmited source: /home/mark/overfit_test/comet/olsen_100ng_30min_15k_01_1.comet.target.txt INFO: ms2 source: /home/mark/overfit_test/mzxml/olsen_100ng_30min_15k_01.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/olsen_100ng_30min_15k_01.mzXML INFO: parsing file /home/mark/overfit_test/comet/olsen_100ng_30min_15k_01_1.comet.target.txt INFO: PSM number 0 INFO: PSM number 5000 INFO: PSM number 10000 INFO: PSM number 15000 INFO: PSM number 20000 INFO: PSM number 25000 INFO: Number of spectra: 26109 INFO: Number of PSMs: total 26109 positives 21329 negatives 4780 INFO: Number of peptides: total 23683 positives 18986 negatives 4697 INFO: Number of proteins: total 11156 positives 6969 negatives 4187 INFO: reading data INFO: Before Iterating INFO: trainset 0.00:1731 0.00:6963 0.01:7579 0.01:7931 0.01:8372 0.02:9261 0.03:9701 0.04:10077 0.05:10323 0.06:10521 0.07:10687 0.08:10871 0.09:11017 0.10:11119 INFO: trainset 0.00:2031 0.00:2306 0.01:2398 0.01:2654 0.01:2909 0.02:3127 0.03:3255 0.04:3333 0.05:3390 0.06:3470 0.07:3516 0.08:3547 0.09:3583 0.10:3632 INFO: Iteration 0 : INFO: trainset 0.00:5440 0.00:8191 0.01:8740 0.01:9236 0.01:9673 0.02:10335 0.03:10913 0.04:11335 0.05:11541 0.06:11725 0.07:11836 0.08:11943 0.09:12107 0.10:12218 INFO: testset 0.00:2317 0.00:2922 0.01:3285 0.01:3332 0.01:3425 0.02:3543 0.03:3674 0.04:3796 0.05:3881 0.06:3908 0.07:3925 0.08:3953 0.09:3989 0.10:4017 INFO: Iteration 10 : INFO: trainset 0.00:5628 0.00:8424 0.01:9017 0.01:9406 0.01:9635 0.02:10478 0.03:10951 0.04:11259 0.05:11496 0.06:11667 0.07:11803 0.08:11962 0.09:12103 0.10:12215 INFO: testset 0.00:2441 0.00:2971 0.01:3131 0.01:3353 0.01:3385 0.02:3538 0.03:3634 0.04:3717 0.05:3786 0.06:3854 0.07:3910 0.08:3947 0.09:3990 0.10:4025 INFO: Iteration 20 : INFO: trainset 0.00:5770 0.00:8265 0.01:8674 0.01:9107 0.01:9772 0.02:10723 0.03:11083 0.04:11298 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INFO: training threshold 7 INFO: Iteration 30 : INFO: trainset 0.00:5603 0.00:8476 0.01:9152 0.01:9528 0.01:9901 0.02:10476 0.03:10855 0.04:11192 0.05:11374 0.06:11606 0.07:11808 0.08:11918 0.09:12012 0.10:12119 INFO: testset 0.00:2530 0.00:2945 0.01:3107 0.01:3120 0.01:3335 0.02:3476 0.03:3595 0.04:3648 0.05:3769 0.06:3822 0.07:3867 0.08:3895 0.09:3918 0.10:3947 INFO: Iteration 33 : INFO: trainset 0.00:5486 0.00:8536 0.01:9199 0.01:9582 0.01:9997 0.02:10716 0.03:11216 0.04:11356 0.05:11532 0.06:11734 0.07:11897 0.08:11982 0.09:12044 0.10:12150 INFO: testset 0.00:2690 0.00:2874 0.01:2961 0.01:3194 0.01:3261 0.02:3540 0.03:3689 0.04:3723 0.05:3787 0.06:3828 0.07:3857 0.08:3928 0.09:3950 0.10:3961 INFO: Iteration 36 : INFO: trainset 0.00:5666 0.00:8744 0.01:9384 0.01:9744 0.01:10090 0.02:10737 0.03:11128 0.04:11334 0.05:11539 0.06:11699 0.07:11817 0.08:11947 0.09:12045 0.10:12126 INFO: testset 0.00:2636 0.00:2730 0.01:3090 0.01:3130 0.01:3380 0.02:3576 0.03:3630 0.04:3737 0.05:3795 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INFO: Return Code:0