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) CPU E5-2690 v4 @ 2.60GHz, 28 cores, 251 GB RAM

RAxML-NG was called at 30-Jun-2021 17:28:44 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/2_msa/Q9NR50_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/3_mltree/Q9NR50 --seed 2 --threads 7 --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 (7 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/2_msa/Q9NR50_trimmed_msa.fasta
[00:00:00] Loaded alignment with 350 taxa and 477 sites

WARNING: Sequences tr_B4QGW1_B4QGW1_DROSI_7240 and tr_B4HS55_B4HS55_DROSE_7238 are exactly identical!
WARNING: Sequences tr_A0A0E0GPR9_A0A0E0GPR9_ORYNI_4536 and tr_I1Q257_I1Q257_ORYGL_4538 are exactly identical!
WARNING: Sequences tr_A0A0E0GPR9_A0A0E0GPR9_ORYNI_4536 and tr_A0A0E0E1R0_A0A0E0E1R0_9ORYZ_40149 are exactly identical!
WARNING: Sequences tr_A0A0E0GPR9_A0A0E0GPR9_ORYNI_4536 and tr_A0A0D3GG65_A0A0D3GG65_9ORYZ_65489 are exactly identical!
WARNING: Sequences tr_B3S2F9_B3S2F9_TRIAD_10228 and tr_A0A369SN84_A0A369SN84_9METZ_287889 are exactly identical!
WARNING: Sequences tr_A0A015L0U2_A0A015L0U2_9GLOM_1432141 and tr_A0A2I1G677_A0A2I1G677_9GLOM_588596 are exactly identical!
WARNING: Sequences tr_A0A015L0U2_A0A015L0U2_9GLOM_1432141 and tr_U9SQ12_U9SQ12_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A0W8C7Y2_A0A0W8C7Y2_PHYNI_4790 and tr_W2FN73_W2FN73_PHYPR_4792 are exactly identical!
WARNING: Sequences tr_A0A1S3Y0N2_A0A1S3Y0N2_TOBAC_4097 and tr_A0A1U7YB97_A0A1U7YB97_NICSY_4096 are exactly identical!
WARNING: Duplicate sequences found: 9

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/Q9NR50/3_mltree/Q9NR50.raxml.reduced.phy

Alignment comprises 1 partitions and 477 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 477 / 477
Gaps: 19.64 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/3_mltree/Q9NR50.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 7 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 350 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 69 / 5520
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -274850.712765] Initial branch length optimization
[00:00:00 -225031.261274] Model parameter optimization (eps = 10.000000)
[00:00:12 -223898.232186] AUTODETECT spr round 1 (radius: 5)
[00:00:26 -159100.106654] AUTODETECT spr round 2 (radius: 10)
[00:00:44 -117788.457058] AUTODETECT spr round 3 (radius: 15)
[00:01:04 -107909.574302] AUTODETECT spr round 4 (radius: 20)
[00:01:31 -107156.802993] AUTODETECT spr round 5 (radius: 25)
[00:02:01 -106707.935738] SPR radius for FAST iterations: 25 (autodetect)
[00:02:01 -106707.935738] Model parameter optimization (eps = 3.000000)
[00:02:09 -106426.331285] FAST spr round 1 (radius: 25)
[00:02:33 -98577.764574] FAST spr round 2 (radius: 25)
[00:02:52 -98215.163949] FAST spr round 3 (radius: 25)
[00:03:07 -98190.525536] FAST spr round 4 (radius: 25)
[00:03:21 -98189.845460] FAST spr round 5 (radius: 25)
[00:03:35 -98189.843214] Model parameter optimization (eps = 1.000000)
[00:03:39 -98186.133685] SLOW spr round 1 (radius: 5)
[00:04:01 -98165.153456] SLOW spr round 2 (radius: 5)
[00:04:23 -98162.825802] SLOW spr round 3 (radius: 5)
[00:04:44 -98162.822833] SLOW spr round 4 (radius: 10)
[00:05:07 -98161.614637] SLOW spr round 5 (radius: 5)
[00:05:35 -98161.614209] SLOW spr round 6 (radius: 10)
[00:06:02 -98161.614039] SLOW spr round 7 (radius: 15)
[00:06:38 -98161.613964] SLOW spr round 8 (radius: 20)
[00:07:26 -98161.613929] SLOW spr round 9 (radius: 25)
[00:08:17 -98161.613910] Model parameter optimization (eps = 0.100000)

[00:08:20] ML tree search #1, logLikelihood: -98161.358939

[00:08:20 -271595.209183] Initial branch length optimization
[00:08:21 -222587.523705] Model parameter optimization (eps = 10.000000)
[00:08:33 -221437.625870] AUTODETECT spr round 1 (radius: 5)
[00:08:48 -162694.315848] AUTODETECT spr round 2 (radius: 10)
[00:09:05 -132321.174105] AUTODETECT spr round 3 (radius: 15)
[00:09:26 -109650.549529] AUTODETECT spr round 4 (radius: 20)
[00:09:51 -108547.825495] AUTODETECT spr round 5 (radius: 25)
[00:10:16 -108475.705789] SPR radius for FAST iterations: 25 (autodetect)
[00:10:16 -108475.705789] Model parameter optimization (eps = 3.000000)
[00:10:26 -108313.790303] FAST spr round 1 (radius: 25)
[00:10:47 -98975.089654] FAST spr round 2 (radius: 25)
[00:11:05 -98306.288419] FAST spr round 3 (radius: 25)
[00:11:22 -98226.746724] FAST spr round 4 (radius: 25)
[00:11:36 -98223.718292] FAST spr round 5 (radius: 25)
[00:11:49 -98223.717042] Model parameter optimization (eps = 1.000000)
[00:11:54 -98217.561799] SLOW spr round 1 (radius: 5)
[00:12:16 -98176.580095] SLOW spr round 2 (radius: 5)
[00:12:39 -98165.901967] SLOW spr round 3 (radius: 5)
[00:13:00 -98165.900079] SLOW spr round 4 (radius: 10)
[00:13:23 -98164.914961] SLOW spr round 5 (radius: 5)
[00:13:51 -98164.914685] SLOW spr round 6 (radius: 10)
[00:14:18 -98164.914576] SLOW spr round 7 (radius: 15)
[00:14:55 -98164.914524] SLOW spr round 8 (radius: 20)
[00:15:44 -98164.914495] SLOW spr round 9 (radius: 25)
[00:16:36 -98164.914476] Model parameter optimization (eps = 0.100000)

[00:16:39] ML tree search #2, logLikelihood: -98164.758877

[00:16:39 -271279.290102] Initial branch length optimization
[00:16:39 -220747.126680] Model parameter optimization (eps = 10.000000)
[00:16:50 -219622.584417] AUTODETECT spr round 1 (radius: 5)
[00:17:05 -158896.665862] AUTODETECT spr round 2 (radius: 10)
[00:17:22 -123707.145980] AUTODETECT spr round 3 (radius: 15)
[00:17:43 -108728.114971] AUTODETECT spr round 4 (radius: 20)
[00:18:04 -106103.730131] AUTODETECT spr round 5 (radius: 25)
[00:18:27 -106084.529154] SPR radius for FAST iterations: 25 (autodetect)
[00:18:27 -106084.529154] Model parameter optimization (eps = 3.000000)
[00:18:35 -105874.892632] FAST spr round 1 (radius: 25)
[00:18:56 -98530.934669] FAST spr round 2 (radius: 25)
[00:19:13 -98233.906595] FAST spr round 3 (radius: 25)
[00:19:28 -98215.235536] FAST spr round 4 (radius: 25)
[00:19:42 -98200.739853] FAST spr round 5 (radius: 25)
[00:19:56 -98200.738105] Model parameter optimization (eps = 1.000000)
[00:20:01 -98196.230794] SLOW spr round 1 (radius: 5)
[00:20:24 -98173.933590] SLOW spr round 2 (radius: 5)
[00:20:45 -98173.642439] SLOW spr round 3 (radius: 5)
[00:21:07 -98173.535289] SLOW spr round 4 (radius: 5)
[00:21:28 -98172.664961] SLOW spr round 5 (radius: 5)
[00:21:50 -98172.590871] SLOW spr round 6 (radius: 10)
[00:22:13 -98172.590697] SLOW spr round 7 (radius: 15)
[00:22:53 -98172.590682] SLOW spr round 8 (radius: 20)
[00:23:39 -98172.590672] SLOW spr round 9 (radius: 25)
[00:24:30 -98172.590664] Model parameter optimization (eps = 0.100000)

[00:24:33] ML tree search #3, logLikelihood: -98172.389347

[00:24:33 -274399.126235] Initial branch length optimization
[00:24:33 -222124.281678] Model parameter optimization (eps = 10.000000)
[00:24:44 -220942.849837] AUTODETECT spr round 1 (radius: 5)
[00:24:59 -166160.482781] AUTODETECT spr round 2 (radius: 10)
[00:25:16 -126801.939271] AUTODETECT spr round 3 (radius: 15)
[00:25:36 -109914.917660] AUTODETECT spr round 4 (radius: 20)
[00:25:59 -106943.744023] AUTODETECT spr round 5 (radius: 25)
[00:26:25 -106485.848330] SPR radius for FAST iterations: 25 (autodetect)
[00:26:25 -106485.848330] Model parameter optimization (eps = 3.000000)
[00:26:34 -106203.467562] FAST spr round 1 (radius: 25)
[00:26:58 -98579.911883] FAST spr round 2 (radius: 25)
[00:27:17 -98235.982073] FAST spr round 3 (radius: 25)
[00:27:34 -98193.037549] FAST spr round 4 (radius: 25)
[00:27:49 -98180.221631] FAST spr round 5 (radius: 25)
[00:28:02 -98178.248690] FAST spr round 6 (radius: 25)
[00:28:16 -98178.246884] Model parameter optimization (eps = 1.000000)
[00:28:20 -98176.366031] SLOW spr round 1 (radius: 5)
[00:28:42 -98166.581111] SLOW spr round 2 (radius: 5)
[00:29:03 -98166.562910] SLOW spr round 3 (radius: 10)
[00:29:26 -98165.372261] SLOW spr round 4 (radius: 5)
[00:29:54 -98165.371770] SLOW spr round 5 (radius: 10)
[00:30:20 -98165.371491] SLOW spr round 6 (radius: 15)
[00:30:58 -98165.371313] SLOW spr round 7 (radius: 20)
[00:31:47 -98165.371196] SLOW spr round 8 (radius: 25)
[00:32:38 -98164.163770] SLOW spr round 9 (radius: 5)
[00:33:09 -98164.162817] SLOW spr round 10 (radius: 10)
[00:33:40 -98164.162334] SLOW spr round 11 (radius: 15)
[00:34:17 -98164.162071] SLOW spr round 12 (radius: 20)
[00:35:07 -98164.161923] SLOW spr round 13 (radius: 25)
[00:35:58 -98164.161836] Model parameter optimization (eps = 0.100000)

[00:36:00] ML tree search #4, logLikelihood: -98164.140903

[00:36:00 -271510.728514] Initial branch length optimization
[00:36:00 -220360.862636] Model parameter optimization (eps = 10.000000)
[00:36:12 -219279.327099] AUTODETECT spr round 1 (radius: 5)
[00:36:26 -163657.822708] AUTODETECT spr round 2 (radius: 10)
[00:36:43 -133067.498278] AUTODETECT spr round 3 (radius: 15)
[00:37:06 -108271.438881] AUTODETECT spr round 4 (radius: 20)
[00:37:30 -106166.879762] AUTODETECT spr round 5 (radius: 25)
[00:37:54 -106090.640946] SPR radius for FAST iterations: 25 (autodetect)
[00:37:54 -106090.640946] Model parameter optimization (eps = 3.000000)
[00:38:04 -105880.328821] FAST spr round 1 (radius: 25)
[00:38:28 -98665.518900] FAST spr round 2 (radius: 25)
[00:38:47 -98222.380986] FAST spr round 3 (radius: 25)
[00:39:03 -98186.907866] FAST spr round 4 (radius: 25)
[00:39:17 -98186.556151] FAST spr round 5 (radius: 25)
[00:39:31 -98186.556009] Model parameter optimization (eps = 1.000000)
[00:39:35 -98184.752259] SLOW spr round 1 (radius: 5)
[00:39:58 -98165.795865] SLOW spr round 2 (radius: 5)
[00:40:20 -98164.987568] SLOW spr round 3 (radius: 5)
[00:40:41 -98164.986355] SLOW spr round 4 (radius: 10)
[00:41:04 -98164.985998] SLOW spr round 5 (radius: 15)
[00:41:42 -98164.985847] SLOW spr round 6 (radius: 20)
[00:42:30 -98164.985775] SLOW spr round 7 (radius: 25)
[00:43:22 -98164.985737] Model parameter optimization (eps = 0.100000)

[00:43:23] ML tree search #5, logLikelihood: -98164.950302

[00:43:24 -270904.065769] Initial branch length optimization
[00:43:24 -220767.516518] Model parameter optimization (eps = 10.000000)
[00:43:38 -219646.402118] AUTODETECT spr round 1 (radius: 5)
[00:43:53 -162298.514799] AUTODETECT spr round 2 (radius: 10)
[00:44:10 -119699.021579] AUTODETECT spr round 3 (radius: 15)
[00:44:30 -108918.862095] AUTODETECT spr round 4 (radius: 20)
[00:44:55 -106416.175552] AUTODETECT spr round 5 (radius: 25)
[00:45:24 -106368.917805] SPR radius for FAST iterations: 25 (autodetect)
[00:45:24 -106368.917805] Model parameter optimization (eps = 3.000000)
[00:45:34 -106173.411003] FAST spr round 1 (radius: 25)
[00:45:57 -98462.473379] FAST spr round 2 (radius: 25)
[00:46:16 -98199.065299] FAST spr round 3 (radius: 25)
[00:46:32 -98187.943531] FAST spr round 4 (radius: 25)
[00:46:45 -98187.907466] Model parameter optimization (eps = 1.000000)
[00:46:50 -98185.549432] SLOW spr round 1 (radius: 5)
[00:47:13 -98164.591234] SLOW spr round 2 (radius: 5)
[00:47:35 -98164.588077] SLOW spr round 3 (radius: 10)
[00:47:58 -98164.406551] SLOW spr round 4 (radius: 5)
[00:48:26 -98164.383952] SLOW spr round 5 (radius: 10)
[00:48:53 -98164.382779] SLOW spr round 6 (radius: 15)
[00:49:31 -98160.807394] SLOW spr round 7 (radius: 5)
[00:50:00 -98160.804277] SLOW spr round 8 (radius: 10)
[00:50:30 -98160.804000] SLOW spr round 9 (radius: 15)
[00:51:07 -98160.803966] SLOW spr round 10 (radius: 20)
[00:51:53 -98160.803954] SLOW spr round 11 (radius: 25)
[00:52:43 -98160.803945] Model parameter optimization (eps = 0.100000)

[00:52:46] ML tree search #6, logLikelihood: -98160.721810

[00:52:46 -269372.875899] Initial branch length optimization
[00:52:46 -218637.965029] Model parameter optimization (eps = 10.000000)
[00:53:01 -217556.918525] AUTODETECT spr round 1 (radius: 5)
[00:53:15 -159917.763552] AUTODETECT spr round 2 (radius: 10)
[00:53:32 -128604.930234] AUTODETECT spr round 3 (radius: 15)
[00:53:54 -115786.070386] AUTODETECT spr round 4 (radius: 20)
[00:54:18 -109479.977433] AUTODETECT spr round 5 (radius: 25)
[00:54:44 -109470.510809] SPR radius for FAST iterations: 25 (autodetect)
[00:54:44 -109470.510809] Model parameter optimization (eps = 3.000000)
[00:54:53 -109352.971959] FAST spr round 1 (radius: 25)
[00:55:17 -98787.633784] FAST spr round 2 (radius: 25)
[00:55:35 -98213.781697] FAST spr round 3 (radius: 25)
[00:55:50 -98192.347231] FAST spr round 4 (radius: 25)
[00:56:04 -98188.764313] FAST spr round 5 (radius: 25)
[00:56:17 -98188.762107] Model parameter optimization (eps = 1.000000)
[00:56:21 -98187.207894] SLOW spr round 1 (radius: 5)
[00:56:43 -98164.931874] SLOW spr round 2 (radius: 5)
[00:57:05 -98164.931605] SLOW spr round 3 (radius: 10)
[00:57:28 -98163.751640] SLOW spr round 4 (radius: 5)
[00:57:56 -98163.751532] SLOW spr round 5 (radius: 10)
[00:58:23 -98163.751492] SLOW spr round 6 (radius: 15)
[00:59:01 -98163.751464] SLOW spr round 7 (radius: 20)
[00:59:49 -98163.751442] SLOW spr round 8 (radius: 25)
[01:00:40 -98163.751425] Model parameter optimization (eps = 0.100000)

[01:00:42] ML tree search #7, logLikelihood: -98163.737426

[01:00:42 -274698.563428] Initial branch length optimization
[01:00:43 -221192.494142] Model parameter optimization (eps = 10.000000)
[01:00:56 -220109.694523] AUTODETECT spr round 1 (radius: 5)
[01:01:10 -164191.637827] AUTODETECT spr round 2 (radius: 10)
[01:01:28 -126941.083135] AUTODETECT spr round 3 (radius: 15)
[01:01:49 -111574.681179] AUTODETECT spr round 4 (radius: 20)
[01:02:14 -106960.348195] AUTODETECT spr round 5 (radius: 25)
[01:02:43 -106640.529496] SPR radius for FAST iterations: 25 (autodetect)
[01:02:43 -106640.529496] Model parameter optimization (eps = 3.000000)
[01:02:53 -106338.687376] FAST spr round 1 (radius: 25)
[01:03:17 -98522.641234] FAST spr round 2 (radius: 25)
[01:03:38 -98215.024318] FAST spr round 3 (radius: 25)
[01:03:54 -98202.687012] FAST spr round 4 (radius: 25)
[01:04:07 -98201.976639] FAST spr round 5 (radius: 25)
[01:04:21 -98201.975775] Model parameter optimization (eps = 1.000000)
[01:04:26 -98196.585572] SLOW spr round 1 (radius: 5)
[01:04:48 -98168.544183] SLOW spr round 2 (radius: 5)
[01:05:10 -98166.531566] SLOW spr round 3 (radius: 5)
[01:05:31 -98166.531030] SLOW spr round 4 (radius: 10)
[01:05:54 -98166.530970] SLOW spr round 5 (radius: 15)
[01:06:36 -98166.530953] SLOW spr round 6 (radius: 20)
[01:07:23 -98166.530942] SLOW spr round 7 (radius: 25)
[01:08:14 -98166.530933] Model parameter optimization (eps = 0.100000)

[01:08:18] ML tree search #8, logLikelihood: -98166.244564

[01:08:18 -272971.830629] Initial branch length optimization
[01:08:19 -221684.521256] Model parameter optimization (eps = 10.000000)
[01:08:33 -220527.727641] AUTODETECT spr round 1 (radius: 5)
[01:08:47 -162567.275215] AUTODETECT spr round 2 (radius: 10)
[01:09:04 -130138.084345] AUTODETECT spr round 3 (radius: 15)
[01:09:25 -108750.404180] AUTODETECT spr round 4 (radius: 20)
[01:09:55 -106448.080157] AUTODETECT spr round 5 (radius: 25)
[01:10:30 -106357.307683] SPR radius for FAST iterations: 25 (autodetect)
[01:10:30 -106357.307683] Model parameter optimization (eps = 3.000000)
[01:10:39 -106226.845042] FAST spr round 1 (radius: 25)
[01:11:05 -98661.359194] FAST spr round 2 (radius: 25)
[01:11:25 -98280.480649] FAST spr round 3 (radius: 25)
[01:11:42 -98258.649689] FAST spr round 4 (radius: 25)
[01:11:57 -98253.658888] FAST spr round 5 (radius: 25)
[01:12:10 -98253.596348] Model parameter optimization (eps = 1.000000)
[01:12:15 -98250.283418] SLOW spr round 1 (radius: 5)
[01:12:37 -98230.513196] SLOW spr round 2 (radius: 5)
[01:12:59 -98227.832289] SLOW spr round 3 (radius: 5)
[01:13:20 -98227.831091] SLOW spr round 4 (radius: 10)
[01:13:43 -98227.831025] SLOW spr round 5 (radius: 15)
[01:14:23 -98227.352346] SLOW spr round 6 (radius: 5)
[01:14:53 -98227.308767] SLOW spr round 7 (radius: 10)
[01:15:22 -98227.307342] SLOW spr round 8 (radius: 15)
[01:15:58 -98227.307126] SLOW spr round 9 (radius: 20)
[01:16:46 -98227.307086] SLOW spr round 10 (radius: 25)
[01:17:36 -98220.636896] SLOW spr round 11 (radius: 5)
[01:18:08 -98169.323434] SLOW spr round 12 (radius: 5)
[01:18:35 -98164.336139] SLOW spr round 13 (radius: 5)
[01:18:59 -98163.547285] SLOW spr round 14 (radius: 5)
[01:19:20 -98163.544265] SLOW spr round 15 (radius: 10)
[01:19:44 -98162.539145] SLOW spr round 16 (radius: 5)
[01:20:12 -98162.501929] SLOW spr round 17 (radius: 10)
[01:20:39 -98162.490632] SLOW spr round 18 (radius: 15)
[01:21:18 -98162.488212] SLOW spr round 19 (radius: 20)
[01:22:06 -98162.487734] SLOW spr round 20 (radius: 25)
[01:22:58 -98162.487639] Model parameter optimization (eps = 0.100000)

[01:23:03] ML tree search #9, logLikelihood: -98160.383927

[01:23:03 -274567.132071] Initial branch length optimization
[01:23:04 -220796.745696] Model parameter optimization (eps = 10.000000)
[01:23:17 -219702.871650] AUTODETECT spr round 1 (radius: 5)
[01:23:32 -156635.157021] AUTODETECT spr round 2 (radius: 10)
[01:23:49 -122795.697633] AUTODETECT spr round 3 (radius: 15)
[01:24:11 -107777.725567] AUTODETECT spr round 4 (radius: 20)
[01:24:35 -106898.893987] AUTODETECT spr round 5 (radius: 25)
[01:25:00 -106816.752474] SPR radius for FAST iterations: 25 (autodetect)
[01:25:00 -106816.752474] Model parameter optimization (eps = 3.000000)
[01:25:09 -106646.251093] FAST spr round 1 (radius: 25)
[01:25:31 -98465.107102] FAST spr round 2 (radius: 25)
[01:25:50 -98283.233658] FAST spr round 3 (radius: 25)
[01:26:05 -98263.922089] FAST spr round 4 (radius: 25)
[01:26:19 -98200.969185] FAST spr round 5 (radius: 25)
[01:26:33 -98200.967804] Model parameter optimization (eps = 1.000000)
[01:26:38 -98196.396497] SLOW spr round 1 (radius: 5)
[01:27:00 -98177.862515] SLOW spr round 2 (radius: 5)
[01:27:22 -98177.585350] SLOW spr round 3 (radius: 5)
[01:27:43 -98177.584784] SLOW spr round 4 (radius: 10)
[01:28:06 -98177.154013] SLOW spr round 5 (radius: 5)
[01:28:34 -98176.416018] SLOW spr round 6 (radius: 5)
[01:28:58 -98176.412947] SLOW spr round 7 (radius: 10)
[01:29:22 -98176.410663] SLOW spr round 8 (radius: 15)
[01:30:00 -98176.408962] SLOW spr round 9 (radius: 20)
[01:30:46 -98176.407695] SLOW spr round 10 (radius: 25)
[01:31:36 -98176.406754] Model parameter optimization (eps = 0.100000)

[01:31:41] ML tree search #10, logLikelihood: -98175.860178

[01:31:41 -272805.720404] Initial branch length optimization
[01:31:41 -221528.141520] Model parameter optimization (eps = 10.000000)
[01:31:56 -220476.676007] AUTODETECT spr round 1 (radius: 5)
[01:32:11 -165066.124660] AUTODETECT spr round 2 (radius: 10)
[01:32:29 -123268.308067] AUTODETECT spr round 3 (radius: 15)
[01:32:49 -111006.009599] AUTODETECT spr round 4 (radius: 20)
[01:33:18 -108011.746267] AUTODETECT spr round 5 (radius: 25)
[01:33:48 -107907.774369] SPR radius for FAST iterations: 25 (autodetect)
[01:33:48 -107907.774369] Model parameter optimization (eps = 3.000000)
[01:33:58 -107698.606740] FAST spr round 1 (radius: 25)
[01:34:23 -98576.584943] FAST spr round 2 (radius: 25)
[01:34:43 -98222.273093] FAST spr round 3 (radius: 25)
[01:35:00 -98197.619058] FAST spr round 4 (radius: 25)
[01:35:15 -98192.320780] FAST spr round 5 (radius: 25)
[01:35:28 -98190.340997] FAST spr round 6 (radius: 25)
[01:35:41 -98190.340027] Model parameter optimization (eps = 1.000000)
[01:35:46 -98188.666746] SLOW spr round 1 (radius: 5)
[01:36:09 -98162.577164] SLOW spr round 2 (radius: 5)
[01:36:30 -98160.754639] SLOW spr round 3 (radius: 5)
[01:36:51 -98160.754143] SLOW spr round 4 (radius: 10)
[01:37:15 -98160.754097] SLOW spr round 5 (radius: 15)
[01:37:55 -98160.754086] SLOW spr round 6 (radius: 20)
[01:38:42 -98160.754078] SLOW spr round 7 (radius: 25)
[01:39:34 -98160.754072] Model parameter optimization (eps = 0.100000)

[01:39:38] ML tree search #11, logLikelihood: -98159.592879

[01:39:38 -273741.807682] Initial branch length optimization
[01:39:39 -222392.588737] Model parameter optimization (eps = 10.000000)
[01:39:50 -221307.498218] AUTODETECT spr round 1 (radius: 5)
[01:40:05 -158640.430918] AUTODETECT spr round 2 (radius: 10)
[01:40:22 -126918.300536] AUTODETECT spr round 3 (radius: 15)
[01:40:43 -114153.859765] AUTODETECT spr round 4 (radius: 20)
[01:41:10 -109944.207327] AUTODETECT spr round 5 (radius: 25)
[01:41:42 -108607.208158] SPR radius for FAST iterations: 25 (autodetect)
[01:41:42 -108607.208158] Model parameter optimization (eps = 3.000000)
[01:41:50 -108316.150771] FAST spr round 1 (radius: 25)
[01:42:15 -98917.783893] FAST spr round 2 (radius: 25)
[01:42:34 -98232.857266] FAST spr round 3 (radius: 25)
[01:42:51 -98196.050206] FAST spr round 4 (radius: 25)
[01:43:06 -98189.081618] FAST spr round 5 (radius: 25)
[01:43:19 -98189.080635] Model parameter optimization (eps = 1.000000)
[01:43:23 -98186.905537] SLOW spr round 1 (radius: 5)
[01:43:46 -98170.956320] SLOW spr round 2 (radius: 5)
[01:44:08 -98169.231683] SLOW spr round 3 (radius: 5)
[01:44:29 -98169.231465] SLOW spr round 4 (radius: 10)
[01:44:52 -98169.135620] SLOW spr round 5 (radius: 15)
[01:45:32 -98169.123773] SLOW spr round 6 (radius: 20)
[01:46:21 -98169.119514] SLOW spr round 7 (radius: 25)
[01:47:13 -98169.118010] Model parameter optimization (eps = 0.100000)

[01:47:17] ML tree search #12, logLikelihood: -98169.004966

[01:47:17 -270200.170533] Initial branch length optimization
[01:47:17 -221924.016071] Model parameter optimization (eps = 10.000000)
[01:47:28 -220796.715902] AUTODETECT spr round 1 (radius: 5)
[01:47:43 -161595.792907] AUTODETECT spr round 2 (radius: 10)
[01:48:00 -127114.655562] AUTODETECT spr round 3 (radius: 15)
[01:48:21 -110086.807044] AUTODETECT spr round 4 (radius: 20)
[01:48:46 -106474.770175] AUTODETECT spr round 5 (radius: 25)
[01:49:16 -106320.519650] SPR radius for FAST iterations: 25 (autodetect)
[01:49:16 -106320.519650] Model parameter optimization (eps = 3.000000)
[01:49:23 -106126.836718] FAST spr round 1 (radius: 25)
[01:49:48 -98529.885031] FAST spr round 2 (radius: 25)
[01:50:08 -98217.122551] FAST spr round 3 (radius: 25)
[01:50:23 -98196.807636] FAST spr round 4 (radius: 25)
[01:50:37 -98190.362339] FAST spr round 5 (radius: 25)
[01:50:51 -98189.490517] FAST spr round 6 (radius: 25)
[01:51:04 -98189.488849] Model parameter optimization (eps = 1.000000)
[01:51:06 -98188.942397] SLOW spr round 1 (radius: 5)
[01:51:30 -98171.360614] SLOW spr round 2 (radius: 5)
[01:51:52 -98169.876261] SLOW spr round 3 (radius: 5)
[01:52:13 -98169.875644] SLOW spr round 4 (radius: 10)
[01:52:35 -98169.875242] SLOW spr round 5 (radius: 15)
[01:53:16 -98169.874960] SLOW spr round 6 (radius: 20)
[01:54:05 -98169.874756] SLOW spr round 7 (radius: 25)
[01:54:58 -98169.874606] Model parameter optimization (eps = 0.100000)

[01:54:59] ML tree search #13, logLikelihood: -98169.839197

[01:54:59 -272576.502660] Initial branch length optimization
[01:55:00 -221301.392081] Model parameter optimization (eps = 10.000000)
[01:55:12 -220220.108794] AUTODETECT spr round 1 (radius: 5)
[01:55:26 -164079.476640] AUTODETECT spr round 2 (radius: 10)
[01:55:44 -132057.954476] AUTODETECT spr round 3 (radius: 15)
[01:56:05 -112934.270524] AUTODETECT spr round 4 (radius: 20)
[01:56:26 -108339.702022] AUTODETECT spr round 5 (radius: 25)
[01:56:53 -107921.916985] SPR radius for FAST iterations: 25 (autodetect)
[01:56:53 -107921.916985] Model parameter optimization (eps = 3.000000)
[01:57:02 -107693.912915] FAST spr round 1 (radius: 25)
[01:57:26 -98662.735274] FAST spr round 2 (radius: 25)
[01:57:43 -98234.518021] FAST spr round 3 (radius: 25)
[01:57:58 -98224.767248] FAST spr round 4 (radius: 25)
[01:58:12 -98221.173784] FAST spr round 5 (radius: 25)
[01:58:26 -98221.133944] Model parameter optimization (eps = 1.000000)
[01:58:31 -98217.551524] SLOW spr round 1 (radius: 5)
[01:58:53 -98186.768332] SLOW spr round 2 (radius: 5)
[01:59:15 -98175.314266] SLOW spr round 3 (radius: 5)
[01:59:36 -98173.415800] SLOW spr round 4 (radius: 5)
[01:59:58 -98173.222857] SLOW spr round 5 (radius: 5)
[02:00:18 -98173.221740] SLOW spr round 6 (radius: 10)
[02:00:42 -98172.465380] SLOW spr round 7 (radius: 5)
[02:01:10 -98172.463810] SLOW spr round 8 (radius: 10)
[02:01:37 -98172.463577] SLOW spr round 9 (radius: 15)
[02:02:17 -98172.463515] SLOW spr round 10 (radius: 20)
[02:03:05 -98172.463491] SLOW spr round 11 (radius: 25)
[02:03:56 -98172.463478] Model parameter optimization (eps = 0.100000)

[02:04:00] ML tree search #14, logLikelihood: -98171.589343

[02:04:00 -276905.612539] Initial branch length optimization
[02:04:01 -223335.445478] Model parameter optimization (eps = 10.000000)
[02:04:13 -222196.358539] AUTODETECT spr round 1 (radius: 5)
[02:04:27 -165848.816448] AUTODETECT spr round 2 (radius: 10)
[02:04:45 -127217.546968] AUTODETECT spr round 3 (radius: 15)
[02:05:05 -108912.563792] AUTODETECT spr round 4 (radius: 20)
[02:05:28 -105908.361643] AUTODETECT spr round 5 (radius: 25)
[02:05:53 -104967.861828] SPR radius for FAST iterations: 25 (autodetect)
[02:05:53 -104967.861828] Model parameter optimization (eps = 3.000000)
[02:06:05 -104731.208845] FAST spr round 1 (radius: 25)
[02:06:28 -98370.687282] FAST spr round 2 (radius: 25)
[02:06:47 -98210.122124] FAST spr round 3 (radius: 25)
[02:07:03 -98195.479852] FAST spr round 4 (radius: 25)
[02:07:18 -98190.550826] FAST spr round 5 (radius: 25)
[02:07:32 -98190.541528] Model parameter optimization (eps = 1.000000)
[02:07:35 -98188.954543] SLOW spr round 1 (radius: 5)
[02:07:58 -98167.880574] SLOW spr round 2 (radius: 5)
[02:08:20 -98167.832651] SLOW spr round 3 (radius: 10)
[02:08:43 -98167.831322] SLOW spr round 4 (radius: 15)
[02:09:23 -98166.637349] SLOW spr round 5 (radius: 5)
[02:09:53 -98166.636457] SLOW spr round 6 (radius: 10)
[02:10:22 -98166.636386] SLOW spr round 7 (radius: 15)
[02:11:00 -98166.636365] SLOW spr round 8 (radius: 20)
[02:11:48 -98166.636352] SLOW spr round 9 (radius: 25)
[02:12:40 -98166.636340] Model parameter optimization (eps = 0.100000)

[02:12:42] ML tree search #15, logLikelihood: -98166.603245

[02:12:42 -273262.458089] Initial branch length optimization
[02:12:42 -221858.514130] Model parameter optimization (eps = 10.000000)
[02:12:53 -220730.728479] AUTODETECT spr round 1 (radius: 5)
[02:13:08 -168244.720142] AUTODETECT spr round 2 (radius: 10)
[02:13:25 -124824.659144] AUTODETECT spr round 3 (radius: 15)
[02:13:46 -109272.854635] AUTODETECT spr round 4 (radius: 20)
[02:14:09 -104975.422771] AUTODETECT spr round 5 (radius: 25)
[02:14:32 -104006.407074] SPR radius for FAST iterations: 25 (autodetect)
[02:14:32 -104006.407074] Model parameter optimization (eps = 3.000000)
[02:14:41 -103713.990084] FAST spr round 1 (radius: 25)
[02:15:03 -98577.413117] FAST spr round 2 (radius: 25)
[02:15:23 -98257.005038] FAST spr round 3 (radius: 25)
[02:15:39 -98223.558599] FAST spr round 4 (radius: 25)
[02:15:53 -98208.470065] FAST spr round 5 (radius: 25)
[02:16:07 -98200.997781] FAST spr round 6 (radius: 25)
[02:16:20 -98200.997508] Model parameter optimization (eps = 1.000000)
[02:16:25 -98198.065593] SLOW spr round 1 (radius: 5)
[02:16:48 -98170.588189] SLOW spr round 2 (radius: 5)
[02:17:10 -98165.723597] SLOW spr round 3 (radius: 5)
[02:17:31 -98165.722680] SLOW spr round 4 (radius: 10)
[02:17:55 -98165.239770] SLOW spr round 5 (radius: 5)
[02:18:23 -98165.114531] SLOW spr round 6 (radius: 5)
[02:18:47 -98165.114122] SLOW spr round 7 (radius: 10)
[02:19:12 -98165.114024] SLOW spr round 8 (radius: 15)
[02:19:52 -98165.113985] SLOW spr round 9 (radius: 20)
[02:20:40 -98165.113963] SLOW spr round 10 (radius: 25)
[02:21:31 -98165.113947] Model parameter optimization (eps = 0.100000)

[02:21:35] ML tree search #16, logLikelihood: -98163.817350

[02:21:35 -273031.157609] Initial branch length optimization
[02:21:36 -219908.667395] Model parameter optimization (eps = 10.000000)
[02:21:47 -218849.465576] AUTODETECT spr round 1 (radius: 5)
[02:22:01 -163583.842020] AUTODETECT spr round 2 (radius: 10)
[02:22:20 -125320.980222] AUTODETECT spr round 3 (radius: 15)
[02:22:40 -109273.629151] AUTODETECT spr round 4 (radius: 20)
[02:23:05 -106757.429930] AUTODETECT spr round 5 (radius: 25)
[02:23:32 -106661.737693] SPR radius for FAST iterations: 25 (autodetect)
[02:23:32 -106661.737693] Model parameter optimization (eps = 3.000000)
[02:23:42 -106406.136523] FAST spr round 1 (radius: 25)
[02:24:04 -98500.564440] FAST spr round 2 (radius: 25)
[02:24:21 -98263.987940] FAST spr round 3 (radius: 25)
[02:24:37 -98216.326794] FAST spr round 4 (radius: 25)
[02:24:52 -98199.160591] FAST spr round 5 (radius: 25)
[02:25:06 -98193.949012] FAST spr round 6 (radius: 25)
[02:25:19 -98192.031311] FAST spr round 7 (radius: 25)
[02:25:32 -98192.028388] Model parameter optimization (eps = 1.000000)
[02:25:37 -98189.457049] SLOW spr round 1 (radius: 5)
[02:25:59 -98172.463055] SLOW spr round 2 (radius: 5)
[02:26:20 -98172.462947] SLOW spr round 3 (radius: 10)
[02:26:43 -98172.462935] SLOW spr round 4 (radius: 15)
[02:27:25 -98169.729268] SLOW spr round 5 (radius: 5)
[02:27:54 -98169.727887] SLOW spr round 6 (radius: 10)
[02:28:23 -98169.727746] SLOW spr round 7 (radius: 15)
[02:29:02 -98169.727709] SLOW spr round 8 (radius: 20)
[02:29:51 -98169.727690] SLOW spr round 9 (radius: 25)
[02:30:43 -98169.727677] Model parameter optimization (eps = 0.100000)

[02:30:45] ML tree search #17, logLikelihood: -98169.654649

[02:30:45 -269717.376147] Initial branch length optimization
[02:30:46 -220072.081615] Model parameter optimization (eps = 10.000000)
[02:31:02 -218973.801417] AUTODETECT spr round 1 (radius: 5)
[02:31:17 -162538.255958] AUTODETECT spr round 2 (radius: 10)
[02:31:35 -124811.940048] AUTODETECT spr round 3 (radius: 15)
[02:31:56 -109637.458035] AUTODETECT spr round 4 (radius: 20)
[02:32:22 -107293.992575] AUTODETECT spr round 5 (radius: 25)
[02:32:51 -107104.566792] SPR radius for FAST iterations: 25 (autodetect)
[02:32:51 -107104.566792] Model parameter optimization (eps = 3.000000)
[02:33:00 -106975.854991] FAST spr round 1 (radius: 25)
[02:33:25 -98602.815311] FAST spr round 2 (radius: 25)
[02:33:42 -98222.290568] FAST spr round 3 (radius: 25)
[02:33:58 -98195.377023] FAST spr round 4 (radius: 25)
[02:34:12 -98193.666072] FAST spr round 5 (radius: 25)
[02:34:25 -98188.930816] FAST spr round 6 (radius: 25)
[02:34:39 -98187.822423] FAST spr round 7 (radius: 25)
[02:34:52 -98187.821149] Model parameter optimization (eps = 1.000000)
[02:34:57 -98183.872207] SLOW spr round 1 (radius: 5)
[02:35:19 -98171.663239] SLOW spr round 2 (radius: 5)
[02:35:42 -98170.701743] SLOW spr round 3 (radius: 5)
[02:36:03 -98170.699009] SLOW spr round 4 (radius: 10)
[02:36:25 -98170.697695] SLOW spr round 5 (radius: 15)
[02:37:03 -98170.467824] SLOW spr round 6 (radius: 5)
[02:37:33 -98170.467464] SLOW spr round 7 (radius: 10)
[02:38:01 -98170.467310] SLOW spr round 8 (radius: 15)
[02:38:37 -98170.467230] SLOW spr round 9 (radius: 20)
[02:39:22 -98170.467186] SLOW spr round 10 (radius: 25)
[02:40:13 -98170.467156] Model parameter optimization (eps = 0.100000)

[02:40:14] ML tree search #18, logLikelihood: -98170.444661

[02:40:14 -276527.016894] Initial branch length optimization
[02:40:15 -224016.332363] Model parameter optimization (eps = 10.000000)
[02:40:27 -222886.072878] AUTODETECT spr round 1 (radius: 5)
[02:40:41 -164447.271256] AUTODETECT spr round 2 (radius: 10)
[02:40:58 -128467.841947] AUTODETECT spr round 3 (radius: 15)
[02:41:19 -116049.478932] AUTODETECT spr round 4 (radius: 20)
[02:41:42 -108013.402144] AUTODETECT spr round 5 (radius: 25)
[02:42:08 -107804.847951] SPR radius for FAST iterations: 25 (autodetect)
[02:42:08 -107804.847951] Model parameter optimization (eps = 3.000000)
[02:42:17 -107546.529443] FAST spr round 1 (radius: 25)
[02:42:42 -98629.323616] FAST spr round 2 (radius: 25)
[02:43:01 -98216.389595] FAST spr round 3 (radius: 25)
[02:43:19 -98189.891443] FAST spr round 4 (radius: 25)
[02:43:32 -98189.891046] Model parameter optimization (eps = 1.000000)
[02:43:35 -98188.460991] SLOW spr round 1 (radius: 5)
[02:43:59 -98170.431360] SLOW spr round 2 (radius: 5)
[02:44:20 -98169.887707] SLOW spr round 3 (radius: 5)
[02:44:42 -98169.424725] SLOW spr round 4 (radius: 5)
[02:45:03 -98169.421902] SLOW spr round 5 (radius: 10)
[02:45:26 -98168.678439] SLOW spr round 6 (radius: 5)
[02:45:54 -98168.677742] SLOW spr round 7 (radius: 10)
[02:46:21 -98168.620357] SLOW spr round 8 (radius: 15)
[02:47:00 -98168.615704] SLOW spr round 9 (radius: 20)
[02:47:50 -98168.615074] SLOW spr round 10 (radius: 25)
[02:48:41 -98168.614976] Model parameter optimization (eps = 0.100000)

[02:48:46] ML tree search #19, logLikelihood: -98167.965987

[02:48:46 -275334.350412] Initial branch length optimization
[02:48:47 -223488.781265] Model parameter optimization (eps = 10.000000)
[02:48:57 -222440.721392] AUTODETECT spr round 1 (radius: 5)
[02:49:12 -160442.401523] AUTODETECT spr round 2 (radius: 10)
[02:49:29 -133272.442483] AUTODETECT spr round 3 (radius: 15)
[02:49:50 -109737.566033] AUTODETECT spr round 4 (radius: 20)
[02:50:13 -106508.245321] AUTODETECT spr round 5 (radius: 25)
[02:50:38 -105777.052958] SPR radius for FAST iterations: 25 (autodetect)
[02:50:38 -105777.052958] Model parameter optimization (eps = 3.000000)
[02:50:47 -105502.565398] FAST spr round 1 (radius: 25)
[02:51:11 -98652.228093] FAST spr round 2 (radius: 25)
[02:51:31 -98282.592576] FAST spr round 3 (radius: 25)
[02:51:47 -98197.591560] FAST spr round 4 (radius: 25)
[02:52:02 -98195.081043] FAST spr round 5 (radius: 25)
[02:52:16 -98193.906338] FAST spr round 6 (radius: 25)
[02:52:29 -98193.905691] Model parameter optimization (eps = 1.000000)
[02:52:36 -98190.279026] SLOW spr round 1 (radius: 5)
[02:52:59 -98173.945845] SLOW spr round 2 (radius: 5)
[02:53:20 -98173.801876] SLOW spr round 3 (radius: 5)
[02:53:41 -98173.801343] SLOW spr round 4 (radius: 10)
[02:54:05 -98171.693728] SLOW spr round 5 (radius: 5)
[02:54:34 -98170.201816] SLOW spr round 6 (radius: 5)
[02:54:58 -98169.080126] SLOW spr round 7 (radius: 5)
[02:55:21 -98169.072806] SLOW spr round 8 (radius: 10)
[02:55:44 -98169.069464] SLOW spr round 9 (radius: 15)
[02:56:23 -98168.550953] SLOW spr round 10 (radius: 5)
[02:56:52 -98168.550266] SLOW spr round 11 (radius: 10)
[02:57:22 -98168.549956] SLOW spr round 12 (radius: 15)
[02:57:58 -98168.549798] SLOW spr round 13 (radius: 20)
[02:58:45 -98168.549716] SLOW spr round 14 (radius: 25)
[02:59:36 -98168.549670] Model parameter optimization (eps = 0.100000)

[02:59:38] ML tree search #20, logLikelihood: -98168.491701


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.130876,0.525383) (0.183045,0.498776) (0.400174,0.873303) (0.285905,1.715495) 
   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: -98159.592879

AIC score: 197725.185757 / AICc score: 1187549.185757 / BIC score: 200654.949850
Free parameters (model + branch lengths): 703

WARNING: Number of free parameters (K=703) is larger than alignment size (n=477).
         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/Q9NR50/3_mltree/Q9NR50.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/3_mltree/Q9NR50.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/3_mltree/Q9NR50.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9NR50/3_mltree/Q9NR50.raxml.log

Analysis started: 30-Jun-2021 17:28:44 / finished: 30-Jun-2021 20:28:23

Elapsed time: 10779.024 seconds

Consumed energy: 661.614 Wh (= 3 km in an electric car, or 17 km with an e-scooter!)