RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab.
Developed by: Alexey M. Kozlov and Alexandros Stamatakis.
Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth.
Latest version: https://github.com/amkozlov/raxml-ng
Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml

System: Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 40 cores, 376 GB RAM

RAxML-NG was called at 02-Jul-2021 11:37:56 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/2_msa/O43548_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548 --seed 2 --threads 8 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/2_msa/O43548_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 668 sites

WARNING: Sequences tr_A0A2J8QED7_A0A2J8QED7_PANTR_9598 and tr_A0A2R8Z5W5_A0A2R8Z5W5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QJU1_H2QJU1_PANTR_9598 and tr_A0A2R9AJY8_A0A2R9AJY8_PANPA_9597 are exactly identical!
WARNING: Sequences sp_P21980_TGM2_HUMAN_9606 and tr_A0A2R9A118_A0A2R9A118_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6VWS4_F6VWS4_MACMU_9544 and tr_A0A2K6BMD2_A0A2K6BMD2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7D3L5_F7D3L5_MACMU_9544 and tr_G7P4C8_G7P4C8_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A140T892_A0A140T892_BOVIN_9913 and sp_P51176_TGM2_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_A0A0V1CED8_A0A0V1CED8_TRIBR_45882 and tr_A0A0V0V6H8_A0A0V0V6H8_9BILA_181606 are exactly identical!
WARNING: Sequences tr_A0A0V1CED8_A0A0V1CED8_TRIBR_45882 and tr_A0A0V1NLG7_A0A0V1NLG7_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V1MKU3_A0A0V1MKU3_9BILA_268474 and tr_A0A0V1GZH4_A0A0V1GZH4_9BILA_268475 are exactly identical!
WARNING: Sequences tr_A0A2K5LPD1_A0A2K5LPD1_CERAT_9531 and tr_A0A2K5Z9Y8_A0A2K5Z9Y8_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K5NYW7_A0A2K5NYW7_CERAT_9531 and tr_A0A2K5YKZ0_A0A2K5YKZ0_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 11

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.reduced.phy

Alignment comprises 1 partitions and 668 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 668 / 668
Gaps: 6.47 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s)

Parallel reduction/worker buffer size: 1 KB  / 0 KB

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 167 / 13360
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1270012.307669] Initial branch length optimization
[00:00:07 -1095732.239818] Model parameter optimization (eps = 10.000000)
[00:01:20 -1092726.193905] AUTODETECT spr round 1 (radius: 5)
[00:04:36 -786655.190019] AUTODETECT spr round 2 (radius: 10)
[00:08:16 -573252.129013] AUTODETECT spr round 3 (radius: 15)
[00:12:06 -483834.080160] AUTODETECT spr round 4 (radius: 20)
[00:16:31 -463863.242130] AUTODETECT spr round 5 (radius: 25)
[00:22:43 -442798.297549] SPR radius for FAST iterations: 25 (autodetect)
[00:22:43 -442798.297549] Model parameter optimization (eps = 3.000000)
[00:23:11 -442604.243474] FAST spr round 1 (radius: 25)
[00:27:25 -388301.993228] FAST spr round 2 (radius: 25)
[00:30:36 -386992.115228] FAST spr round 3 (radius: 25)
[00:33:24 -386891.434955] FAST spr round 4 (radius: 25)
[00:35:48 -386874.536799] FAST spr round 5 (radius: 25)
[00:38:06 -386869.851614] FAST spr round 6 (radius: 25)
[00:40:16 -386869.851486] Model parameter optimization (eps = 1.000000)
[00:40:36 -386855.412513] SLOW spr round 1 (radius: 5)
[00:43:43 -386758.518965] SLOW spr round 2 (radius: 5)
[00:46:43 -386748.442462] SLOW spr round 3 (radius: 5)
[00:49:34 -386747.265191] SLOW spr round 4 (radius: 5)
[00:52:24 -386747.265158] SLOW spr round 5 (radius: 10)
[00:55:18 -386747.253454] SLOW spr round 6 (radius: 15)
[01:00:33 -386747.253419] SLOW spr round 7 (radius: 20)
[01:09:05 -386747.253418] SLOW spr round 8 (radius: 25)
[01:21:49 -386747.253418] Model parameter optimization (eps = 0.100000)

[01:21:58] [worker #0] ML tree search #1, logLikelihood: -386747.242622

[01:21:59 -1266709.862397] Initial branch length optimization
[01:22:05 -1095719.898439] Model parameter optimization (eps = 10.000000)
[01:23:14 -1092616.729861] AUTODETECT spr round 1 (radius: 5)
[01:26:28 -784281.216523] AUTODETECT spr round 2 (radius: 10)
[01:28:50] [worker #1] ML tree search #2, logLikelihood: -386727.272779
[01:30:08 -552548.435977] AUTODETECT spr round 3 (radius: 15)
[01:34:03 -473722.260337] AUTODETECT spr round 4 (radius: 20)
[01:38:49 -442141.109467] AUTODETECT spr round 5 (radius: 25)
[01:44:50 -437808.983161] SPR radius for FAST iterations: 25 (autodetect)
[01:44:50 -437808.983161] Model parameter optimization (eps = 3.000000)
[01:45:13 -437542.181259] FAST spr round 1 (radius: 25)
[01:49:15 -389024.714589] FAST spr round 2 (radius: 25)
[01:52:23 -386994.545202] FAST spr round 3 (radius: 25)
[01:55:11 -386875.633942] FAST spr round 4 (radius: 25)
[01:57:36 -386872.898814] FAST spr round 5 (radius: 25)
[01:59:59 -386868.970413] FAST spr round 6 (radius: 25)
[02:02:20 -386868.970389] Model parameter optimization (eps = 1.000000)
[02:02:44 -386860.940060] SLOW spr round 1 (radius: 5)
[02:06:08 -386777.288927] SLOW spr round 2 (radius: 5)
[02:09:24 -386751.878055] SLOW spr round 3 (radius: 5)
[02:12:29 -386748.442455] SLOW spr round 4 (radius: 5)
[02:15:29 -386748.442379] SLOW spr round 5 (radius: 10)
[02:18:31 -386748.442378] SLOW spr round 6 (radius: 15)
[02:23:51 -386748.442378] SLOW spr round 7 (radius: 20)
[02:32:38 -386748.442377] SLOW spr round 8 (radius: 25)
[02:45:12 -386748.442377] Model parameter optimization (eps = 0.100000)

[02:45:22] [worker #0] ML tree search #3, logLikelihood: -386748.409495

[02:45:22 -1265997.774343] Initial branch length optimization
[02:45:28 -1090173.238806] Model parameter optimization (eps = 10.000000)
[02:46:16 -1087085.079298] AUTODETECT spr round 1 (radius: 5)
[02:49:34 -778442.831427] AUTODETECT spr round 2 (radius: 10)
[02:53:16 -596973.774251] AUTODETECT spr round 3 (radius: 15)
[02:57:19 -513377.340770] AUTODETECT spr round 4 (radius: 20)
[03:01:34 -457430.650949] AUTODETECT spr round 5 (radius: 25)
[03:02:46] [worker #1] ML tree search #4, logLikelihood: -386719.314430
[03:06:28 -448442.628994] SPR radius for FAST iterations: 25 (autodetect)
[03:06:28 -448442.628994] Model parameter optimization (eps = 3.000000)
[03:06:55 -448180.627171] FAST spr round 1 (radius: 25)
[03:11:04 -389516.373783] FAST spr round 2 (radius: 25)
[03:14:19 -386987.562467] FAST spr round 3 (radius: 25)
[03:17:11 -386884.397870] FAST spr round 4 (radius: 25)
[03:19:45 -386863.539922] FAST spr round 5 (radius: 25)
[03:22:06 -386862.432904] FAST spr round 6 (radius: 25)
[03:24:26 -386862.432887] Model parameter optimization (eps = 1.000000)
[03:24:53 -386853.968260] SLOW spr round 1 (radius: 5)
[03:28:15 -386772.867626] SLOW spr round 2 (radius: 5)
[03:31:29 -386759.753534] SLOW spr round 3 (radius: 5)
[03:34:37 -386750.915122] SLOW spr round 4 (radius: 5)
[03:37:44 -386750.181829] SLOW spr round 5 (radius: 5)
[03:40:48 -386748.812371] SLOW spr round 6 (radius: 5)
[03:43:51 -386748.812194] SLOW spr round 7 (radius: 10)
[03:46:56 -386748.066418] SLOW spr round 8 (radius: 5)
[03:50:41 -386748.066373] SLOW spr round 9 (radius: 10)
[03:54:03 -386748.066362] SLOW spr round 10 (radius: 15)
[03:59:02 -386748.066352] SLOW spr round 11 (radius: 20)
[04:08:49 -386748.066342] SLOW spr round 12 (radius: 25)
[04:22:00 -386748.066332] Model parameter optimization (eps = 0.100000)

[04:22:06] [worker #0] ML tree search #5, logLikelihood: -386747.981136

[04:22:07 -1273190.225480] Initial branch length optimization
[04:22:13 -1096780.222533] Model parameter optimization (eps = 10.000000)
[04:23:10 -1093669.404146] AUTODETECT spr round 1 (radius: 5)
[04:26:29 -797737.145901] AUTODETECT spr round 2 (radius: 10)
[04:30:16 -559096.969798] AUTODETECT spr round 3 (radius: 15)
[04:32:19] [worker #1] ML tree search #6, logLikelihood: -386738.875141
[04:34:09 -485200.807018] AUTODETECT spr round 4 (radius: 20)
[04:39:11 -453024.528760] AUTODETECT spr round 5 (radius: 25)
[04:46:22 -441379.621996] SPR radius for FAST iterations: 25 (autodetect)
[04:46:22 -441379.621996] Model parameter optimization (eps = 3.000000)
[04:46:48 -441082.288989] FAST spr round 1 (radius: 25)
[04:50:46 -389883.630183] FAST spr round 2 (radius: 25)
[04:54:03 -387067.409864] FAST spr round 3 (radius: 25)
[04:56:52 -386902.646341] FAST spr round 4 (radius: 25)
[04:59:24 -386857.073444] FAST spr round 5 (radius: 25)
[05:01:46 -386857.073134] Model parameter optimization (eps = 1.000000)
[05:02:03 -386852.506193] SLOW spr round 1 (radius: 5)
[05:05:29 -386737.615450] SLOW spr round 2 (radius: 5)
[05:08:46 -386732.256380] SLOW spr round 3 (radius: 5)
[05:11:52 -386732.256366] SLOW spr round 4 (radius: 10)
[05:15:00 -386732.256366] SLOW spr round 5 (radius: 15)
[05:20:27 -386732.256366] SLOW spr round 6 (radius: 20)
[05:29:18 -386732.256366] SLOW spr round 7 (radius: 25)
[05:42:02 -386732.256366] Model parameter optimization (eps = 0.100000)

[05:42:20] [worker #0] ML tree search #7, logLikelihood: -386731.120628

[05:42:21 -1266008.269198] Initial branch length optimization
[05:42:27 -1091523.982573] Model parameter optimization (eps = 10.000000)
[05:43:15 -1088401.301346] AUTODETECT spr round 1 (radius: 5)
[05:46:30 -795084.801368] AUTODETECT spr round 2 (radius: 10)
[05:50:09 -593610.557255] AUTODETECT spr round 3 (radius: 15)
[05:54:19 -498082.354289] AUTODETECT spr round 4 (radius: 20)
[05:56:46] [worker #1] ML tree search #8, logLikelihood: -386756.943009
[05:59:06 -444507.205140] AUTODETECT spr round 5 (radius: 25)
[06:05:10 -438727.639316] SPR radius for FAST iterations: 25 (autodetect)
[06:05:10 -438727.639316] Model parameter optimization (eps = 3.000000)
[06:05:37 -438501.800640] FAST spr round 1 (radius: 25)
[06:09:56 -388520.335960] FAST spr round 2 (radius: 25)
[06:13:10 -387071.971943] FAST spr round 3 (radius: 25)
[06:16:04 -386890.781236] FAST spr round 4 (radius: 25)
[06:18:38 -386863.784087] FAST spr round 5 (radius: 25)
[06:21:02 -386863.331401] FAST spr round 6 (radius: 25)
[06:23:23 -386863.331342] Model parameter optimization (eps = 1.000000)
[06:23:44 -386851.675841] SLOW spr round 1 (radius: 5)
[06:27:05 -386749.476672] SLOW spr round 2 (radius: 5)
[06:30:11 -386738.724957] SLOW spr round 3 (radius: 5)
[06:33:09 -386732.563058] SLOW spr round 4 (radius: 5)
[06:36:07 -386732.134022] SLOW spr round 5 (radius: 5)
[06:39:07 -386732.133995] SLOW spr round 6 (radius: 10)
[06:42:10 -386731.388322] SLOW spr round 7 (radius: 5)
[06:45:56 -386731.388298] SLOW spr round 8 (radius: 10)
[06:49:19 -386731.388297] SLOW spr round 9 (radius: 15)
[06:54:23 -386731.388297] SLOW spr round 10 (radius: 20)
[07:04:17 -386731.388297] SLOW spr round 11 (radius: 25)
[07:17:29 -386731.388296] Model parameter optimization (eps = 0.100000)

[07:17:37] [worker #0] ML tree search #9, logLikelihood: -386731.307885

[07:17:37 -1272669.907539] Initial branch length optimization
[07:17:43 -1093420.066779] Model parameter optimization (eps = 10.000000)
[07:18:44 -1090376.049071] AUTODETECT spr round 1 (radius: 5)
[07:22:07 -779866.601183] AUTODETECT spr round 2 (radius: 10)
[07:25:48 -559244.252357] AUTODETECT spr round 3 (radius: 15)
[07:27:43] [worker #1] ML tree search #10, logLikelihood: -386736.130790
[07:29:50 -452387.064820] AUTODETECT spr round 4 (radius: 20)
[07:34:55 -433701.818628] AUTODETECT spr round 5 (radius: 25)
[07:41:50 -431188.358709] SPR radius for FAST iterations: 25 (autodetect)
[07:41:50 -431188.358709] Model parameter optimization (eps = 3.000000)
[07:42:16 -430945.989596] FAST spr round 1 (radius: 25)
[07:46:18 -388585.016590] FAST spr round 2 (radius: 25)
[07:49:26 -386966.768415] FAST spr round 3 (radius: 25)
[07:52:10 -386918.559287] FAST spr round 4 (radius: 25)
[07:54:42 -386885.235043] FAST spr round 5 (radius: 25)
[07:57:06 -386882.580483] FAST spr round 6 (radius: 25)
[07:59:28 -386882.580462] Model parameter optimization (eps = 1.000000)
[07:59:50 -386879.059287] SLOW spr round 1 (radius: 5)
[08:03:19 -386770.824467] SLOW spr round 2 (radius: 5)
[08:06:30 -386765.171190] SLOW spr round 3 (radius: 5)
[08:09:36 -386764.707412] SLOW spr round 4 (radius: 5)
[08:12:39 -386764.707365] SLOW spr round 5 (radius: 10)
[08:15:44 -386763.949016] SLOW spr round 6 (radius: 5)
[08:19:33 -386763.948975] SLOW spr round 7 (radius: 10)
[08:22:59 -386763.948975] SLOW spr round 8 (radius: 15)
[08:28:12 -386763.948975] SLOW spr round 9 (radius: 20)
[08:38:19 -386763.948975] SLOW spr round 10 (radius: 25)
[08:51:23] [worker #1] ML tree search #12, logLikelihood: -386739.326950
[08:51:44 -386763.948975] Model parameter optimization (eps = 0.100000)

[08:52:02] [worker #0] ML tree search #11, logLikelihood: -386762.829687

[08:52:02 -1274771.994407] Initial branch length optimization
[08:52:08 -1094730.434489] Model parameter optimization (eps = 10.000000)
[08:52:53 -1091472.677523] AUTODETECT spr round 1 (radius: 5)
[08:56:10 -785733.826149] AUTODETECT spr round 2 (radius: 10)
[08:59:50 -550718.005064] AUTODETECT spr round 3 (radius: 15)
[09:03:48 -480249.060517] AUTODETECT spr round 4 (radius: 20)
[09:09:01 -448763.149961] AUTODETECT spr round 5 (radius: 25)
[09:14:58 -439151.771005] SPR radius for FAST iterations: 25 (autodetect)
[09:14:58 -439151.771005] Model parameter optimization (eps = 3.000000)
[09:15:23 -438864.715569] FAST spr round 1 (radius: 25)
[09:19:36 -389863.909141] FAST spr round 2 (radius: 25)
[09:22:52 -387162.705514] FAST spr round 3 (radius: 25)
[09:25:48 -386865.671366] FAST spr round 4 (radius: 25)
[09:28:28 -386808.972520] FAST spr round 5 (radius: 25)
[09:30:52 -386808.972450] Model parameter optimization (eps = 1.000000)
[09:31:10 -386807.263020] SLOW spr round 1 (radius: 5)
[09:34:38 -386743.777068] SLOW spr round 2 (radius: 5)
[09:37:54 -386735.329730] SLOW spr round 3 (radius: 5)
[09:40:59 -386735.329646] SLOW spr round 4 (radius: 10)
[09:44:07 -386735.329631] SLOW spr round 5 (radius: 15)
[09:49:31 -386735.329620] SLOW spr round 6 (radius: 20)
[09:58:16 -386735.329609] SLOW spr round 7 (radius: 25)
[10:10:36] [worker #1] ML tree search #14, logLikelihood: -386748.114249
[10:11:02 -386735.329598] Model parameter optimization (eps = 0.100000)

[10:11:18] [worker #0] ML tree search #13, logLikelihood: -386734.779425

[10:11:18 -1270450.737375] Initial branch length optimization
[10:11:26 -1097499.572732] Model parameter optimization (eps = 10.000000)
[10:12:17 -1094344.218096] AUTODETECT spr round 1 (radius: 5)
[10:15:39 -782423.155748] AUTODETECT spr round 2 (radius: 10)
[10:19:21 -563070.674050] AUTODETECT spr round 3 (radius: 15)
[10:23:21 -484443.621500] AUTODETECT spr round 4 (radius: 20)
[10:28:00 -452237.710749] AUTODETECT spr round 5 (radius: 25)
[10:33:15 -437810.320279] SPR radius for FAST iterations: 25 (autodetect)
[10:33:15 -437810.320279] Model parameter optimization (eps = 3.000000)
[10:33:46 -437618.235742] FAST spr round 1 (radius: 25)
[10:38:04 -388656.169302] FAST spr round 2 (radius: 25)
[10:41:16 -387113.032665] FAST spr round 3 (radius: 25)
[10:44:05 -386884.867639] FAST spr round 4 (radius: 25)
[10:46:41 -386838.511390] FAST spr round 5 (radius: 25)
[10:49:08 -386836.080486] FAST spr round 6 (radius: 25)
[10:51:31 -386836.041654] Model parameter optimization (eps = 1.000000)
[10:51:51 -386832.953278] SLOW spr round 1 (radius: 5)
[10:55:12 -386748.387705] SLOW spr round 2 (radius: 5)
[10:58:22 -386739.808000] SLOW spr round 3 (radius: 5)
[11:01:29 -386738.544790] SLOW spr round 4 (radius: 5)
[11:04:34 -386738.544476] SLOW spr round 5 (radius: 10)
[11:07:38 -386738.172985] SLOW spr round 6 (radius: 5)
[11:11:25 -386736.705015] SLOW spr round 7 (radius: 5)
[11:14:44 -386736.704904] SLOW spr round 8 (radius: 10)
[11:17:49 -386736.704904] SLOW spr round 9 (radius: 15)
[11:22:55 -386736.704904] SLOW spr round 10 (radius: 20)
[11:31:52 -386736.704904] SLOW spr round 11 (radius: 25)
[11:31:55] [worker #1] ML tree search #16, logLikelihood: -386726.091962
[11:44:54 -386736.704904] Model parameter optimization (eps = 0.100000)

[11:45:13] [worker #0] ML tree search #15, logLikelihood: -386734.572131

[11:45:13 -1270122.894633] Initial branch length optimization
[11:45:23 -1094892.460695] Model parameter optimization (eps = 10.000000)
[11:46:16 -1091865.347199] AUTODETECT spr round 1 (radius: 5)
[11:49:33 -778780.145819] AUTODETECT spr round 2 (radius: 10)
[11:53:17 -567566.800837] AUTODETECT spr round 3 (radius: 15)
[11:57:08 -495560.270777] AUTODETECT spr round 4 (radius: 20)
[12:01:27 -448789.789691] AUTODETECT spr round 5 (radius: 25)
[12:06:43 -443407.388450] SPR radius for FAST iterations: 25 (autodetect)
[12:06:43 -443407.388450] Model parameter optimization (eps = 3.000000)
[12:07:08 -443137.871120] FAST spr round 1 (radius: 25)
[12:11:16 -389248.582062] FAST spr round 2 (radius: 25)
[12:14:23 -387029.173926] FAST spr round 3 (radius: 25)
[12:17:14 -386873.415204] FAST spr round 4 (radius: 25)
[12:19:41 -386866.469072] FAST spr round 5 (radius: 25)
[12:22:01 -386866.469055] Model parameter optimization (eps = 1.000000)
[12:22:27 -386857.585269] SLOW spr round 1 (radius: 5)
[12:25:51 -386748.479722] SLOW spr round 2 (radius: 5)
[12:28:56 -386746.184966] SLOW spr round 3 (radius: 5)
[12:31:56 -386746.184624] SLOW spr round 4 (radius: 10)
[12:34:57 -386745.030463] SLOW spr round 5 (radius: 5)
[12:38:40 -386742.751212] SLOW spr round 6 (radius: 5)
[12:41:59 -386738.785987] SLOW spr round 7 (radius: 5)
[12:45:05 -386738.302267] SLOW spr round 8 (radius: 5)
[12:48:05 -386737.896178] SLOW spr round 9 (radius: 5)
[12:51:02 -386732.064807] SLOW spr round 10 (radius: 5)
[12:53:55 -386732.064745] SLOW spr round 11 (radius: 10)
[12:56:46 -386732.064744] SLOW spr round 12 (radius: 15)
[13:01:52 -386732.064744] SLOW spr round 13 (radius: 20)
[13:03:05] [worker #1] ML tree search #18, logLikelihood: -386719.146453
[13:10:24 -386732.064744] SLOW spr round 14 (radius: 25)
[13:22:59 -386732.064744] Model parameter optimization (eps = 0.100000)

[13:23:19] [worker #0] ML tree search #17, logLikelihood: -386731.883397

[13:23:19 -1272799.543280] Initial branch length optimization
[13:23:24 -1097677.020008] Model parameter optimization (eps = 10.000000)
[13:24:15 -1094672.542948] AUTODETECT spr round 1 (radius: 5)
[13:27:36 -795612.781175] AUTODETECT spr round 2 (radius: 10)
[13:31:19 -554530.843937] AUTODETECT spr round 3 (radius: 15)
[13:35:03 -477490.570202] AUTODETECT spr round 4 (radius: 20)
[13:39:47 -451551.910623] AUTODETECT spr round 5 (radius: 25)
[13:45:01 -439976.226808] SPR radius for FAST iterations: 25 (autodetect)
[13:45:01 -439976.226808] Model parameter optimization (eps = 3.000000)
[13:45:25 -439757.024497] FAST spr round 1 (radius: 25)
[13:49:43 -388440.160053] FAST spr round 2 (radius: 25)
[13:52:57 -387076.175178] FAST spr round 3 (radius: 25)
[13:55:49 -386870.197393] FAST spr round 4 (radius: 25)
[13:58:21 -386854.267481] FAST spr round 5 (radius: 25)
[14:00:41 -386849.990420] FAST spr round 6 (radius: 25)
[14:02:59 -386846.333694] FAST spr round 7 (radius: 25)
[14:05:16 -386846.333677] Model parameter optimization (eps = 1.000000)
[14:05:30 -386843.767882] SLOW spr round 1 (radius: 5)
[14:08:53 -386751.297418] SLOW spr round 2 (radius: 5)
[14:12:00 -386734.520287] SLOW spr round 3 (radius: 5)
[14:15:00 -386732.466677] SLOW spr round 4 (radius: 5)
[14:17:58 -386732.466614] SLOW spr round 5 (radius: 10)
[14:21:01 -386728.514862] SLOW spr round 6 (radius: 5)
[14:24:46 -386724.112257] SLOW spr round 7 (radius: 5)
[14:28:05 -386724.112196] SLOW spr round 8 (radius: 10)
[14:31:11 -386723.348919] SLOW spr round 9 (radius: 5)
[14:32:29] [worker #1] ML tree search #20, logLikelihood: -386727.664604
[14:34:50 -386723.348904] SLOW spr round 10 (radius: 10)
[14:38:04 -386723.348895] SLOW spr round 11 (radius: 15)
[14:42:56 -386723.348885] SLOW spr round 12 (radius: 20)
[14:52:00 -386723.348875] SLOW spr round 13 (radius: 25)
[15:04:38 -386723.348865] Model parameter optimization (eps = 0.100000)

[15:04:52] [worker #0] ML tree search #19, logLikelihood: -386722.642399


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.137437,0.325189) (0.238300,0.458412) (0.317203,0.942213) (0.307060,1.782046) 
   Base frequencies (model): 
M0: 0.147383 0.017579 0.058208 0.017707 0.026331 0.041582 0.017494 0.027859 0.011849 0.076971 0.147823 0.019535 0.037132 0.029940 0.008059 0.088179 0.089653 0.006477 0.032308 0.097931 
M1: 0.063139 0.066357 0.011586 0.066571 0.010800 0.009276 0.053984 0.146986 0.034214 0.088822 0.098196 0.032390 0.021263 0.072697 0.016761 0.020711 0.020797 0.025463 0.045615 0.094372 
M2: 0.062457 0.066826 0.049332 0.065270 0.006513 0.041231 0.058965 0.080852 0.028024 0.037024 0.075925 0.064131 0.019620 0.028710 0.104579 0.056388 0.062027 0.008241 0.033124 0.050760 
M3: 0.106471 0.074171 0.044513 0.096390 0.002148 0.066733 0.158908 0.037625 0.020691 0.014608 0.028797 0.105352 0.007864 0.007477 0.083595 0.055726 0.047711 0.003975 0.010088 0.027159 
   Substitution rates (model): 
M 0: 0.295719 0.067388 0.253712 1.029289 0.107964 0.514644 10.868848 0.380498 0.084223 0.086976 0.188789 0.286389 0.155567 1.671061 2.132922 0.529591 0.115551 0.102453 0.916683 0.448317 0.457483 0.576016 1.741924 0.736017 0.704334 5.658311 0.123387 0.221777 93.433377 0.382175 0.235965 6.535048 0.525521 0.303537 0.641259 0.289466 0.102065 2.358429 0.251987 0.216561 0.503084 0.435271 4.873453 0.090748 0.033310 0.746537 0.128905 0.127321 0.904011 0.939733 0.435450 0.046646 0.262076 0.043986 0.189008 0.599450 109.901504 1.070052 5.229858 0.052764 0.021407 0.621146 0.081091 0.205164 5.164456 0.747330 0.308078 0.260889 0.185083 0.080708 0.029955 0.084794 1.862626 0.553477 0.151733 0.230320 0.096955 0.352526 0.590018 0.386853 1.559564 0.606648 0.587531 0.592318 0.885230 4.117654 0.246260 6.508329 0.054187 0.195703 1.669092 0.810168 0.066081 2.437439 0.165666 0.106333 0.093417 0.035149 0.072549 1.202023 1.634845 0.060194 0.069359 2.448827 0.232297 0.064822 3.537387 0.435384 0.290413 0.280695 0.105999 0.206603 0.404968 0.048984 0.069963 0.256662 0.228519 0.241077 4.320442 3.656545 0.290216 0.307466 0.096556 0.306067 0.204296 0.504221 1.991533 0.655465 6.799829 11.291065 0.961142 0.448965 6.227274 20.304886 0.205944 1.495537 0.091940 1.994320 0.754940 0.170343 0.050315 0.372166 0.206332 0.097050 5.381403 0.122332 3.256485 2.261319 0.848067 0.064441 0.102493 0.459041 0.133091 0.561215 0.457430 0.163849 5.260446 0.360946 0.389413 0.033291 0.115301 0.112593 1.559944 0.426508 0.132547 0.498634 0.559069 0.264728 0.693307 0.438856 0.306683 0.109129 18.392863 66.647302 0.400021 4.586081 2.099355 0.411347 0.476350 0.584622 3.634276 0.101797 0.148995 0.089177 0.034710 0.063603 0.755865 20.561407 0.133790 0.154902 
M 1: 0.066142 0.590377 0.069930 9.850951 1.101363 0.150375 0.568586 0.051668 0.127170 0.292429 0.071458 1.218562 0.075144 7.169085 30.139501 13.461692 0.021372 0.045779 4.270235 0.468325 0.013688 0.302287 1.353957 0.028386 0.037750 0.262130 0.016923 0.064289 0.855973 0.079621 0.011169 0.161937 0.276530 0.161053 0.081472 0.036742 0.030342 2.851667 3.932151 8.159169 0.219934 0.421974 2.468752 0.344765 0.210724 1.172204 0.763553 0.082464 0.726566 11.149790 4.782635 0.058046 0.498072 0.258487 0.146882 0.249672 0.560142 0.046719 0.106259 0.003656 0.004200 0.014189 0.009876 0.002656 0.040244 0.267322 0.053740 0.006597 0.027639 0.012745 0.582670 0.005035 0.275844 0.098208 0.445038 1.217010 0.033969 1.988516 0.681161 0.825960 18.762977 11.949233 0.286794 0.534219 4.336817 3.054085 0.129551 4.210126 0.165753 1.088704 1.889645 3.344809 0.111063 2.067758 3.547017 2.466507 0.188236 0.203493 0.281953 0.037250 0.029788 0.008541 0.014768 0.125869 0.056702 0.004186 0.110993 0.201148 0.139705 0.009201 0.012095 0.043812 0.013513 0.002533 0.005848 0.031390 0.021612 0.004854 0.129497 0.976631 0.053397 0.019475 0.004964 0.015539 0.031779 0.064558 0.065585 0.079927 0.095591 0.196886 0.408834 0.126088 0.037226 0.452302 0.016212 7.278994 0.029917 7.918203 0.450964 0.169797 0.104288 1.578530 0.015909 0.094365 16.179952 0.042762 14.799537 1.506485 0.637893 0.123793 0.641351 0.154810 0.140750 3.416059 0.259400 0.009457 0.090576 0.292108 0.297913 0.017172 0.021976 0.032578 1.375871 0.457399 0.598048 4.418398 0.239749 0.168432 2.950318 0.143327 0.328689 0.125011 0.562720 1.414883 0.227807 3.478333 2.984862 0.061299 0.077470 1.050562 13.974326 0.154326 0.224675 0.112000 0.060703 0.123480 5.294490 0.447011 0.033381 0.045528 
M 2: 0.733336 0.558955 0.503360 4.149599 1.415369 1.367574 1.263002 0.994098 0.517204 0.775054 0.763094 1.890137 0.540460 0.200122 4.972745 1.825593 0.450842 0.526135 3.839269 0.597671 0.058964 2.863355 2.872594 0.258365 0.366868 2.578946 0.358350 0.672023 5.349861 0.691594 0.063347 0.032875 0.821562 0.580847 0.661866 0.265730 0.395134 5.581680 1.279881 1.335650 0.397108 1.840061 5.739035 0.284730 0.109781 1.612642 0.466979 0.141582 0.019509 4.670980 1.967383 0.088064 0.581928 0.145401 0.225860 0.434096 2.292917 1.024707 0.821921 0.027824 0.021443 0.088850 0.060820 0.018288 0.042687 1.199607 0.420710 0.037642 0.141233 0.090101 1.043232 0.209978 0.823594 3.039380 1.463390 1.983693 0.397640 2.831098 4.102068 0.059723 5.901348 2.034980 2.600668 5.413080 4.193725 4.534772 0.377181 4.877840 0.370939 1.298542 3.509873 2.646440 0.087872 0.072299 1.139018 0.864479 0.390688 0.322761 0.625409 0.496780 0.532488 0.232460 0.169219 0.755219 0.379926 0.020447 0.023282 0.503875 0.577513 0.109318 0.153776 0.696533 0.398817 0.008940 0.043707 0.436013 0.087640 0.064863 0.036426 1.673207 0.124068 0.218118 0.039217 0.104335 0.349195 0.838324 0.888693 0.488389 1.385133 0.050226 0.962470 0.502294 1.065585 8.351808 0.377304 5.102837 0.561690 7.010411 3.054968 0.039318 0.204155 2.653232 0.564368 0.854294 15.559906 0.401070 8.929538 5.525874 0.067505 0.273372 0.437116 1.927515 0.940458 2.508169 1.357738 0.043394 0.023126 0.567639 1.048288 0.120994 0.180650 0.449074 3.135353 0.012695 0.570771 2.319555 1.856122 0.975427 3.404087 0.015631 0.458799 0.151684 4.154750 11.429924 1.457957 0.233109 0.077004 0.011074 0.026268 0.052132 8.113282 0.377578 0.429221 0.260296 0.222293 0.273138 2.903836 4.731579 0.564762 0.681215 
M 3: 0.658412 0.566269 0.854111 0.884454 1.309554 1.272639 1.874713 0.552007 0.227683 0.581512 0.695190 0.967985 0.344015 0.978992 3.427163 2.333253 0.154701 0.221089 2.088785 0.540749 0.058015 5.851132 2.294145 0.182966 0.684164 3.192521 0.528161 1.128882 3.010922 1.012866 0.227296 0.156635 0.878405 0.802754 0.830884 0.431617 0.456530 3.060574 1.279257 1.438430 0.431464 2.075952 4.840271 0.644656 0.266076 2.084975 0.720060 0.291854 0.028961 4.071574 2.258357 0.073037 1.238426 0.199728 0.160296 0.482619 2.992763 1.296206 0.841829 0.031467 0.048542 0.132774 0.133055 0.056045 0.209188 0.925172 0.360522 0.094591 0.313945 0.118104 0.992259 0.086318 2.149634 5.103188 3.775817 3.954021 0.190734 1.776095 4.495841 0.264277 7.063879 2.221150 3.017954 8.558815 4.310199 2.130054 0.571406 4.137385 0.437589 2.071689 2.498630 1.763546 0.116381 0.296578 1.033710 1.283423 0.312579 0.305772 0.681277 0.507160 0.351381 0.189152 0.217780 0.767361 0.278392 0.092075 0.177263 0.451893 0.653836 0.074620 0.181992 0.752277 0.679853 0.025780 0.082005 0.326441 0.343977 0.195877 0.217424 3.057583 0.377558 0.401252 0.072258 0.241015 0.665865 1.266791 0.680174 0.717301 4.001286 0.362942 1.189259 0.964545 1.350568 12.869737 0.531100 8.904999 0.652629 10.091413 2.671718 0.086367 0.359932 4.797423 0.336801 1.021885 23.029406 0.440178 14.013035 5.069337 0.539010 0.742569 0.780580 1.331875 1.531589 4.414850 1.082703 0.091278 0.172734 0.693405 1.422571 0.068958 0.163829 0.481711 4.643214 0.121821 0.584083 4.216178 1.677263 1.575754 5.046403 0.161015 1.531223 0.599244 5.832025 33.873091 1.914768 1.287474 0.444362 0.076328 0.079916 0.466823 5.231362 0.548763 0.831890 0.382271 0.208791 0.307846 3.717971 5.910440 0.282540 0.964421 


Final LogLikelihood: -386719.146453

AIC score: 777448.292905 / AICc score: 8821508.292905 / BIC score: 786479.390693
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=668).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O43548/3_mltree/O43548.raxml.log

Analysis started: 02-Jul-2021 11:37:56 / finished: 03-Jul-2021 02:42:49

Elapsed time: 54292.805 seconds

Consumed energy: 4619.829 Wh (= 23 km in an electric car, or 115 km with an e-scooter!)