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 07-Jul-2021 21:49:05 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/2_msa/P58107_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107 --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/P58107/2_msa/P58107_trimmed_msa.fasta
[00:00:00] Loaded alignment with 469 taxa and 3732 sites

WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PT23_A0A2D0PT23_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PT29_A0A2D0PT29_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PUI9_A0A2D0PUI9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PUJ2_A0A2D0PUJ2_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PUJ7_A0A2D0PUJ7_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PUK2_A0A2D0PUK2_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PUM4_A0A2D0PUM4_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PWA1_A0A2D0PWA1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PWA6_A0A2D0PWA6_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PWB1_A0A2D0PWB1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PT18_A0A2D0PT18_ICTPU_7998 and tr_A0A2D0PX51_A0A2D0PX51_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RPP3_A0A2D0RPP3_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RPW9_A0A2D0RPW9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RQ32_A0A2D0RQ32_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RQN1_A0A2D0RQN1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RQP1_A0A2D0RQP1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RQW3_A0A2D0RQW3_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RQX2_A0A2D0RQX2_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RRF7_A0A2D0RRF7_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RRG7_A0A2D0RRG7_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RRK2_A0A2D0RRK2_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPN8_A0A2D0RPN8_ICTPU_7998 and tr_A0A2D0RRL2_A0A2D0RRL2_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPT8_A0A2D0RPT8_ICTPU_7998 and tr_A0A2D0RPT9_A0A2D0RPT9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPT8_A0A2D0RPT8_ICTPU_7998 and tr_A0A2D0RQ29_A0A2D0RQ29_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RPT8_A0A2D0RPT8_ICTPU_7998 and tr_A0A2D0RRC2_A0A2D0RRC2_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 25

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/P58107/3_mltree/P58107.raxml.reduced.phy

Alignment comprises 1 partitions and 3731 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 3732 / 3731
Gaps: 41.77 %
Invariant sites: 0.80 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 8 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 469 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 467 / 37360
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1799365.856826] Initial branch length optimization
[00:00:05 -1457532.611246] Model parameter optimization (eps = 10.000000)
[00:01:03 -1451035.444097] AUTODETECT spr round 1 (radius: 5)
[00:02:14 -896733.022115] AUTODETECT spr round 2 (radius: 10)
[00:03:40 -663311.789508] AUTODETECT spr round 3 (radius: 15)
[00:05:21 -530863.108929] AUTODETECT spr round 4 (radius: 20)
[00:07:13 -512120.149385] AUTODETECT spr round 5 (radius: 25)
[00:09:33 -502499.337846] SPR radius for FAST iterations: 25 (autodetect)
[00:09:33 -502499.337846] Model parameter optimization (eps = 3.000000)
[00:09:54 -501488.076123] FAST spr round 1 (radius: 25)
[00:11:46 -451808.572084] FAST spr round 2 (radius: 25)
[00:13:10 -450186.793161] FAST spr round 3 (radius: 25)
[00:14:08 -450157.712645] FAST spr round 4 (radius: 25)
[00:14:58 -450157.710301] Model parameter optimization (eps = 1.000000)
[00:15:10 -450136.703533] SLOW spr round 1 (radius: 5)
[00:16:48 -450031.376062] SLOW spr round 2 (radius: 5)
[00:18:15 -450025.160564] SLOW spr round 3 (radius: 5)
[00:19:39 -450025.157926] SLOW spr round 4 (radius: 10)
[00:21:09 -450025.157426] SLOW spr round 5 (radius: 15)
[00:24:36 -450025.157143] SLOW spr round 6 (radius: 20)
[00:29:12 -450025.156981] SLOW spr round 7 (radius: 25)
[00:35:09 -450025.156887] Model parameter optimization (eps = 0.100000)

[00:35:17] ML tree search #1, logLikelihood: -450024.848795

[00:35:17 -1800099.588128] Initial branch length optimization
[00:35:23 -1449970.488796] Model parameter optimization (eps = 10.000000)
[00:36:15 -1443525.828879] AUTODETECT spr round 1 (radius: 5)
[00:37:25 -898645.503733] AUTODETECT spr round 2 (radius: 10)
[00:38:50 -637845.629666] AUTODETECT spr round 3 (radius: 15)
[00:40:37 -523270.823146] AUTODETECT spr round 4 (radius: 20)
[00:42:42 -500079.065175] AUTODETECT spr round 5 (radius: 25)
[00:45:29 -499298.147176] SPR radius for FAST iterations: 25 (autodetect)
[00:45:29 -499298.147176] Model parameter optimization (eps = 3.000000)
[00:45:56 -498305.383318] FAST spr round 1 (radius: 25)
[00:47:44 -451915.793684] FAST spr round 2 (radius: 25)
[00:49:04 -450267.486285] FAST spr round 3 (radius: 25)
[00:50:07 -450190.619048] FAST spr round 4 (radius: 25)
[00:50:59 -450186.636776] FAST spr round 5 (radius: 25)
[00:51:50 -450176.797154] FAST spr round 6 (radius: 25)
[00:52:43 -450155.895820] FAST spr round 7 (radius: 25)
[00:53:32 -450132.325515] FAST spr round 8 (radius: 25)
[00:54:19 -450132.325290] Model parameter optimization (eps = 1.000000)
[00:54:34 -450113.202555] SLOW spr round 1 (radius: 5)
[00:56:09 -450038.961083] SLOW spr round 2 (radius: 5)
[00:57:38 -450022.694482] SLOW spr round 3 (radius: 5)
[00:59:04 -450022.236985] SLOW spr round 4 (radius: 5)
[01:00:28 -450022.234829] SLOW spr round 5 (radius: 10)
[01:02:00 -450022.234042] SLOW spr round 6 (radius: 15)
[01:05:22 -450022.233681] SLOW spr round 7 (radius: 20)
[01:09:48 -450022.233441] SLOW spr round 8 (radius: 25)
[01:15:44 -450022.233232] Model parameter optimization (eps = 0.100000)

[01:15:53] ML tree search #2, logLikelihood: -450021.910465

[01:15:53 -1821666.451401] Initial branch length optimization
[01:16:00 -1489568.247568] Model parameter optimization (eps = 10.000000)
[01:16:52 -1482986.505681] AUTODETECT spr round 1 (radius: 5)
[01:18:01 -870205.129386] AUTODETECT spr round 2 (radius: 10)
[01:19:28 -595601.120128] AUTODETECT spr round 3 (radius: 15)
[01:21:17 -504773.202522] AUTODETECT spr round 4 (radius: 20)
[01:23:12 -495555.434916] AUTODETECT spr round 5 (radius: 25)
[01:25:51 -494912.991283] SPR radius for FAST iterations: 25 (autodetect)
[01:25:51 -494912.991283] Model parameter optimization (eps = 3.000000)
[01:26:19 -493646.580173] FAST spr round 1 (radius: 25)
[01:28:28 -451787.537859] FAST spr round 2 (radius: 25)
[01:29:59 -450267.798981] FAST spr round 3 (radius: 25)
[01:31:00 -450250.280891] FAST spr round 4 (radius: 25)
[01:31:51 -450248.210415] FAST spr round 5 (radius: 25)
[01:32:39 -450248.209216] Model parameter optimization (eps = 1.000000)
[01:32:52 -450233.557108] SLOW spr round 1 (radius: 5)
[01:34:29 -450147.313951] SLOW spr round 2 (radius: 5)
[01:35:53 -450146.621883] SLOW spr round 3 (radius: 5)
[01:37:17 -450146.618979] SLOW spr round 4 (radius: 10)
[01:38:51 -450146.617864] SLOW spr round 5 (radius: 15)
[01:42:55 -450133.764552] SLOW spr round 6 (radius: 5)
[01:45:14 -450089.607458] SLOW spr round 7 (radius: 5)
[01:47:08 -450089.136671] SLOW spr round 8 (radius: 5)
[01:48:45 -450089.135298] SLOW spr round 9 (radius: 10)
[01:50:29 -450044.262810] SLOW spr round 10 (radius: 5)
[01:52:39 -450038.317557] SLOW spr round 11 (radius: 5)
[01:54:25 -450038.287998] SLOW spr round 12 (radius: 10)
[01:56:06 -450038.283743] SLOW spr round 13 (radius: 15)
[01:59:29 -450022.840410] SLOW spr round 14 (radius: 5)
[02:01:48 -450022.195475] SLOW spr round 15 (radius: 5)
[02:03:40 -450022.194002] SLOW spr round 16 (radius: 10)
[02:05:25 -450022.193556] SLOW spr round 17 (radius: 15)
[02:08:43 -450022.193476] SLOW spr round 18 (radius: 20)
[02:13:12 -450022.193411] SLOW spr round 19 (radius: 25)
[02:19:10 -450022.193352] Model parameter optimization (eps = 0.100000)

[02:19:18] ML tree search #3, logLikelihood: -450021.911762

[02:19:18 -1828187.398199] Initial branch length optimization
[02:19:25 -1490609.546589] Model parameter optimization (eps = 10.000000)
[02:20:21 -1483835.198362] AUTODETECT spr round 1 (radius: 5)
[02:21:32 -865713.250993] AUTODETECT spr round 2 (radius: 10)
[02:22:55 -636155.149580] AUTODETECT spr round 3 (radius: 15)
[02:24:39 -514876.675323] AUTODETECT spr round 4 (radius: 20)
[02:26:30 -503687.985314] AUTODETECT spr round 5 (radius: 25)
[02:28:23 -500452.280067] SPR radius for FAST iterations: 25 (autodetect)
[02:28:23 -500452.280067] Model parameter optimization (eps = 3.000000)
[02:28:47 -499147.568263] FAST spr round 1 (radius: 25)
[02:30:39 -452182.345607] FAST spr round 2 (radius: 25)
[02:32:12 -450210.601002] FAST spr round 3 (radius: 25)
[02:33:21 -450109.023064] FAST spr round 4 (radius: 25)
[02:34:10 -450109.006489] Model parameter optimization (eps = 1.000000)
[02:34:23 -450094.444507] SLOW spr round 1 (radius: 5)
[02:36:01 -450039.074960] SLOW spr round 2 (radius: 5)
[02:37:27 -450038.655029] SLOW spr round 3 (radius: 5)
[02:38:51 -450038.653819] SLOW spr round 4 (radius: 10)
[02:40:22 -450038.653390] SLOW spr round 5 (radius: 15)
[02:43:48 -450038.653059] SLOW spr round 6 (radius: 20)
[02:48:41 -450038.652779] SLOW spr round 7 (radius: 25)
[02:55:21 -450038.652525] Model parameter optimization (eps = 0.100000)

[02:55:27] ML tree search #4, logLikelihood: -450038.630802

[02:55:27 -1791053.964505] Initial branch length optimization
[02:55:33 -1442110.750787] Model parameter optimization (eps = 10.000000)
[02:56:23 -1435765.679953] AUTODETECT spr round 1 (radius: 5)
[02:57:42 -863023.793555] AUTODETECT spr round 2 (radius: 10)
[02:59:17 -637608.063773] AUTODETECT spr round 3 (radius: 15)
[03:01:07 -517380.078166] AUTODETECT spr round 4 (radius: 20)
[03:03:58 -499942.344744] AUTODETECT spr round 5 (radius: 25)
[03:07:51 -498314.115276] SPR radius for FAST iterations: 25 (autodetect)
[03:07:51 -498314.115276] Model parameter optimization (eps = 3.000000)
[03:08:17 -497173.635342] FAST spr round 1 (radius: 25)
[03:10:25 -453053.385222] FAST spr round 2 (radius: 25)
[03:11:57 -450329.619508] FAST spr round 3 (radius: 25)
[03:13:16 -450195.256035] FAST spr round 4 (radius: 25)
[03:14:18 -450167.044656] FAST spr round 5 (radius: 25)
[03:15:12 -450167.044320] Model parameter optimization (eps = 1.000000)
[03:15:29 -450137.490302] SLOW spr round 1 (radius: 5)
[03:17:16 -450042.361383] SLOW spr round 2 (radius: 5)
[03:18:53 -450041.372962] SLOW spr round 3 (radius: 5)
[03:20:27 -450041.372383] SLOW spr round 4 (radius: 10)
[03:22:09 -450041.372058] SLOW spr round 5 (radius: 15)
[03:25:56 -450041.371842] SLOW spr round 6 (radius: 20)
[03:31:18 -450041.371687] SLOW spr round 7 (radius: 25)
[03:38:15 -450041.371569] Model parameter optimization (eps = 0.100000)

[03:38:20] ML tree search #5, logLikelihood: -450041.283691

[03:38:20 -1791706.312006] Initial branch length optimization
[03:38:27 -1448721.484075] Model parameter optimization (eps = 10.000000)
[03:39:23 -1442447.455836] AUTODETECT spr round 1 (radius: 5)
[03:40:41 -878753.271720] AUTODETECT spr round 2 (radius: 10)
[03:42:21 -594118.792775] AUTODETECT spr round 3 (radius: 15)
[03:44:14 -511224.442670] AUTODETECT spr round 4 (radius: 20)
[03:47:18 -499576.393460] AUTODETECT spr round 5 (radius: 25)
[03:50:20 -499433.014911] SPR radius for FAST iterations: 25 (autodetect)
[03:50:20 -499433.014911] Model parameter optimization (eps = 3.000000)
[03:50:43 -498343.497281] FAST spr round 1 (radius: 25)
[03:52:53 -451840.969724] FAST spr round 2 (radius: 25)
[03:54:24 -450325.261797] FAST spr round 3 (radius: 25)
[03:55:34 -450258.062743] FAST spr round 4 (radius: 25)
[03:56:31 -450257.757672] FAST spr round 5 (radius: 25)
[03:57:25 -450257.756817] Model parameter optimization (eps = 1.000000)
[03:57:41 -450247.632772] SLOW spr round 1 (radius: 5)
[03:59:26 -450163.279039] SLOW spr round 2 (radius: 5)
[04:01:10 -450147.376465] SLOW spr round 3 (radius: 5)
[04:02:44 -450147.371512] SLOW spr round 4 (radius: 10)
[04:04:31 -450145.346840] SLOW spr round 5 (radius: 5)
[04:06:54 -450142.967640] SLOW spr round 6 (radius: 5)
[04:08:51 -450142.967334] SLOW spr round 7 (radius: 10)
[04:10:50 -450142.967102] SLOW spr round 8 (radius: 15)
[04:15:19 -450142.966894] SLOW spr round 9 (radius: 20)
[04:21:46 -450142.966693] SLOW spr round 10 (radius: 25)
[04:29:09 -450142.966493] Model parameter optimization (eps = 0.100000)

[04:29:22] ML tree search #6, logLikelihood: -450142.363064

[04:29:22 -1829463.566735] Initial branch length optimization
[04:29:30 -1490968.197662] Model parameter optimization (eps = 10.000000)
[04:30:37 -1484102.074721] AUTODETECT spr round 1 (radius: 5)
[04:31:56 -855544.227014] AUTODETECT spr round 2 (radius: 10)
[04:33:26 -622422.723978] AUTODETECT spr round 3 (radius: 15)
[04:35:08 -521428.105235] AUTODETECT spr round 4 (radius: 20)
[04:37:17 -500125.869283] AUTODETECT spr round 5 (radius: 25)
[04:39:56 -499050.510358] SPR radius for FAST iterations: 25 (autodetect)
[04:39:56 -499050.510358] Model parameter optimization (eps = 3.000000)
[04:40:20 -497935.710928] FAST spr round 1 (radius: 25)
[04:42:36 -451207.798896] FAST spr round 2 (radius: 25)
[04:44:08 -450199.846301] FAST spr round 3 (radius: 25)
[04:45:19 -450125.672687] FAST spr round 4 (radius: 25)
[04:46:14 -450125.671736] Model parameter optimization (eps = 1.000000)
[04:46:28 -450107.181529] SLOW spr round 1 (radius: 5)
[04:48:15 -450045.659759] SLOW spr round 2 (radius: 5)
[04:49:51 -450043.325354] SLOW spr round 3 (radius: 5)
[04:51:24 -450043.323309] SLOW spr round 4 (radius: 10)
[04:53:05 -450043.322586] SLOW spr round 5 (radius: 15)
[04:56:49 -450028.791718] SLOW spr round 6 (radius: 5)
[04:59:21 -450028.166906] SLOW spr round 7 (radius: 5)
[05:01:24 -450028.166872] SLOW spr round 8 (radius: 10)
[05:03:19 -450028.166847] SLOW spr round 9 (radius: 15)
[05:06:52 -450028.166826] SLOW spr round 10 (radius: 20)
[05:11:48 -450028.166808] SLOW spr round 11 (radius: 25)
[05:18:23 -450028.166791] Model parameter optimization (eps = 0.100000)

[05:18:33] ML tree search #7, logLikelihood: -450026.805097

[05:18:33 -1828031.534004] Initial branch length optimization
[05:18:40 -1493065.567507] Model parameter optimization (eps = 10.000000)
[05:19:31 -1486646.095907] AUTODETECT spr round 1 (radius: 5)
[05:20:48 -879658.277061] AUTODETECT spr round 2 (radius: 10)
[05:22:17 -634855.196880] AUTODETECT spr round 3 (radius: 15)
[05:24:20 -554845.216983] AUTODETECT spr round 4 (radius: 20)
[05:27:36 -504317.047556] AUTODETECT spr round 5 (radius: 25)
[05:31:04 -503044.487778] SPR radius for FAST iterations: 25 (autodetect)
[05:31:04 -503044.487778] Model parameter optimization (eps = 3.000000)
[05:31:29 -501934.595697] FAST spr round 1 (radius: 25)
[05:33:31 -453524.228383] FAST spr round 2 (radius: 25)
[05:35:04 -450203.982856] FAST spr round 3 (radius: 25)
[05:36:17 -450108.561817] FAST spr round 4 (radius: 25)
[05:37:11 -450108.560645] Model parameter optimization (eps = 1.000000)
[05:37:27 -450089.455217] SLOW spr round 1 (radius: 5)
[05:39:15 -450032.299772] SLOW spr round 2 (radius: 5)
[05:40:51 -450026.811990] SLOW spr round 3 (radius: 5)
[05:42:24 -450026.811700] SLOW spr round 4 (radius: 10)
[05:44:05 -450026.811541] SLOW spr round 5 (radius: 15)
[05:47:53 -450026.811451] SLOW spr round 6 (radius: 20)
[05:53:05 -450026.811400] SLOW spr round 7 (radius: 25)
[05:59:53 -450026.811370] Model parameter optimization (eps = 0.100000)

[06:00:01] ML tree search #8, logLikelihood: -450026.590540

[06:00:02 -1826539.667071] Initial branch length optimization
[06:00:09 -1480900.846165] Model parameter optimization (eps = 10.000000)
[06:01:08 -1474173.075894] AUTODETECT spr round 1 (radius: 5)
[06:02:25 -853701.417451] AUTODETECT spr round 2 (radius: 10)
[06:04:00 -593387.493878] AUTODETECT spr round 3 (radius: 15)
[06:05:52 -539984.837585] AUTODETECT spr round 4 (radius: 20)
[06:08:13 -506231.664250] AUTODETECT spr round 5 (radius: 25)
[06:10:43 -505940.911806] SPR radius for FAST iterations: 25 (autodetect)
[06:10:43 -505940.911806] Model parameter optimization (eps = 3.000000)
[06:11:09 -504836.423868] FAST spr round 1 (radius: 25)
[06:13:06 -453050.256520] FAST spr round 2 (radius: 25)
[06:14:54 -450259.243539] FAST spr round 3 (radius: 25)
[06:16:09 -450129.403523] FAST spr round 4 (radius: 25)
[06:17:11 -450115.124949] FAST spr round 5 (radius: 25)
[06:18:05 -450114.118930] FAST spr round 6 (radius: 25)
[06:18:58 -450114.118917] Model parameter optimization (eps = 1.000000)
[06:19:11 -450099.690473] SLOW spr round 1 (radius: 5)
[06:20:57 -450050.624901] SLOW spr round 2 (radius: 5)
[06:22:36 -450045.834833] SLOW spr round 3 (radius: 5)
[06:24:18 -450041.183783] SLOW spr round 4 (radius: 5)
[06:25:59 -450035.627051] SLOW spr round 5 (radius: 5)
[06:27:34 -450035.627023] SLOW spr round 6 (radius: 10)
[06:29:17 -450032.988422] SLOW spr round 7 (radius: 5)
[06:31:42 -450029.916269] SLOW spr round 8 (radius: 5)
[06:33:45 -450018.778368] SLOW spr round 9 (radius: 5)
[06:35:29 -450018.777740] SLOW spr round 10 (radius: 10)
[06:37:14 -450018.777731] SLOW spr round 11 (radius: 15)
[06:40:58 -450018.777728] SLOW spr round 12 (radius: 20)
[06:45:55 -450018.777727] SLOW spr round 13 (radius: 25)
[06:52:33 -450018.777727] Model parameter optimization (eps = 0.100000)

[06:52:42] ML tree search #9, logLikelihood: -450018.588140

[06:52:43 -1800529.903145] Initial branch length optimization
[06:52:50 -1481629.939295] Model parameter optimization (eps = 10.000000)
[06:53:53 -1474972.630912] AUTODETECT spr round 1 (radius: 5)
[06:55:09 -887469.752052] AUTODETECT spr round 2 (radius: 10)
[06:56:43 -633903.854475] AUTODETECT spr round 3 (radius: 15)
[06:58:33 -559000.691791] AUTODETECT spr round 4 (radius: 20)
[07:00:50 -516609.107073] AUTODETECT spr round 5 (radius: 25)
[07:03:20 -506404.709207] SPR radius for FAST iterations: 25 (autodetect)
[07:03:20 -506404.709207] Model parameter optimization (eps = 3.000000)
[07:03:46 -505526.065179] FAST spr round 1 (radius: 25)
[07:06:09 -452456.949329] FAST spr round 2 (radius: 25)
[07:07:57 -450157.467409] FAST spr round 3 (radius: 25)
[07:09:11 -450118.183681] FAST spr round 4 (radius: 25)
[07:10:15 -450110.692887] FAST spr round 5 (radius: 25)
[07:11:10 -450110.691848] Model parameter optimization (eps = 1.000000)
[07:11:26 -450077.158026] SLOW spr round 1 (radius: 5)
[07:13:10 -450053.477878] SLOW spr round 2 (radius: 5)
[07:14:47 -450045.567346] SLOW spr round 3 (radius: 5)
[07:16:23 -450040.068429] SLOW spr round 4 (radius: 5)
[07:17:58 -450040.068094] SLOW spr round 5 (radius: 10)
[07:19:40 -450040.067893] SLOW spr round 6 (radius: 15)
[07:23:34 -450040.067726] SLOW spr round 7 (radius: 20)
[07:28:53 -450040.067567] SLOW spr round 8 (radius: 25)
[07:35:54 -450040.067409] Model parameter optimization (eps = 0.100000)

[07:36:00] ML tree search #10, logLikelihood: -450040.016907

[07:36:00 -1825611.070759] Initial branch length optimization
[07:36:07 -1489731.997247] Model parameter optimization (eps = 10.000000)
[07:37:05 -1483035.058710] AUTODETECT spr round 1 (radius: 5)
[07:38:24 -890415.848460] AUTODETECT spr round 2 (radius: 10)
[07:39:54 -621752.639150] AUTODETECT spr round 3 (radius: 15)
[07:41:42 -557330.615582] AUTODETECT spr round 4 (radius: 20)
[07:43:43 -514516.528710] AUTODETECT spr round 5 (radius: 25)
[07:46:20 -510014.314549] SPR radius for FAST iterations: 25 (autodetect)
[07:46:20 -510014.314549] Model parameter optimization (eps = 3.000000)
[07:46:44 -508954.985486] FAST spr round 1 (radius: 25)
[07:48:50 -451809.669948] FAST spr round 2 (radius: 25)
[07:50:17 -450170.406086] FAST spr round 3 (radius: 25)
[07:51:20 -450158.222992] FAST spr round 4 (radius: 25)
[07:52:15 -450158.222281] Model parameter optimization (eps = 1.000000)
[07:52:28 -450143.253002] SLOW spr round 1 (radius: 5)
[07:54:16 -450039.356404] SLOW spr round 2 (radius: 5)
[07:55:50 -450039.349637] SLOW spr round 3 (radius: 10)
[07:57:33 -450037.089611] SLOW spr round 4 (radius: 5)
[07:59:54 -450034.902111] SLOW spr round 5 (radius: 5)
[08:01:50 -450034.901790] SLOW spr round 6 (radius: 10)
[08:03:42 -450034.901535] SLOW spr round 7 (radius: 15)
[08:07:23 -450034.901305] SLOW spr round 8 (radius: 20)
[08:12:40 -450034.901087] SLOW spr round 9 (radius: 25)
[08:19:35 -450034.900874] Model parameter optimization (eps = 0.100000)

[08:19:42] ML tree search #11, logLikelihood: -450034.755731

[08:19:42 -1842468.601413] Initial branch length optimization
[08:19:49 -1500856.726859] Model parameter optimization (eps = 10.000000)
[08:20:53 -1494052.767331] AUTODETECT spr round 1 (radius: 5)
[08:22:11 -885868.270350] AUTODETECT spr round 2 (radius: 10)
[08:23:48 -585489.132793] AUTODETECT spr round 3 (radius: 15)
[08:25:42 -508227.565828] AUTODETECT spr round 4 (radius: 20)
[08:27:57 -494318.586998] AUTODETECT spr round 5 (radius: 25)
[08:30:23 -494002.637125] SPR radius for FAST iterations: 25 (autodetect)
[08:30:23 -494002.637125] Model parameter optimization (eps = 3.000000)
[08:30:51 -492827.310616] FAST spr round 1 (radius: 25)
[08:32:49 -451553.482658] FAST spr round 2 (radius: 25)
[08:34:17 -450182.971519] FAST spr round 3 (radius: 25)
[08:35:27 -450109.707492] FAST spr round 4 (radius: 25)
[08:36:23 -450109.069659] FAST spr round 5 (radius: 25)
[08:37:16 -450109.069068] Model parameter optimization (eps = 1.000000)
[08:37:33 -450092.948640] SLOW spr round 1 (radius: 5)
[08:39:16 -450025.682155] SLOW spr round 2 (radius: 5)
[08:40:49 -450025.678544] SLOW spr round 3 (radius: 10)
[08:42:31 -450025.677715] SLOW spr round 4 (radius: 15)
[08:46:24 -450025.677343] SLOW spr round 5 (radius: 20)
[08:51:39 -450025.677146] SLOW spr round 6 (radius: 25)
[08:58:33 -450025.677036] Model parameter optimization (eps = 0.100000)

[08:58:40] ML tree search #12, logLikelihood: -450025.593468

[08:58:40 -1834881.926833] Initial branch length optimization
[08:58:46 -1485783.528271] Model parameter optimization (eps = 10.000000)
[08:59:47 -1479575.106411] AUTODETECT spr round 1 (radius: 5)
[09:01:05 -875189.618432] AUTODETECT spr round 2 (radius: 10)
[09:02:37 -602384.317695] AUTODETECT spr round 3 (radius: 15)
[09:04:32 -516637.476153] AUTODETECT spr round 4 (radius: 20)
[09:06:39 -494051.795590] AUTODETECT spr round 5 (radius: 25)
[09:09:04 -493589.341713] SPR radius for FAST iterations: 25 (autodetect)
[09:09:04 -493589.341713] Model parameter optimization (eps = 3.000000)
[09:09:31 -492372.348899] FAST spr round 1 (radius: 25)
[09:11:27 -451223.603149] FAST spr round 2 (radius: 25)
[09:12:49 -450117.739401] FAST spr round 3 (radius: 25)
[09:13:50 -450114.637679] FAST spr round 4 (radius: 25)
[09:14:44 -450114.626307] Model parameter optimization (eps = 1.000000)
[09:14:58 -450103.277116] SLOW spr round 1 (radius: 5)
[09:16:46 -450053.131489] SLOW spr round 2 (radius: 5)
[09:18:24 -450042.671598] SLOW spr round 3 (radius: 5)
[09:20:00 -450037.205198] SLOW spr round 4 (radius: 5)
[09:21:34 -450037.205020] SLOW spr round 5 (radius: 10)
[09:23:16 -450037.204858] SLOW spr round 6 (radius: 15)
[09:27:10 -450037.204701] SLOW spr round 7 (radius: 20)
[09:32:29 -450037.204549] SLOW spr round 8 (radius: 25)
[09:39:29 -450037.204400] Model parameter optimization (eps = 0.100000)

[09:39:37] ML tree search #13, logLikelihood: -450037.096672

[09:39:37 -1804500.070921] Initial branch length optimization
[09:39:43 -1448998.868046] Model parameter optimization (eps = 10.000000)
[09:40:30 -1442393.781996] AUTODETECT spr round 1 (radius: 5)
[09:41:48 -909483.630181] AUTODETECT spr round 2 (radius: 10)
[09:43:27 -623301.956938] AUTODETECT spr round 3 (radius: 15)
[09:45:15 -532151.355829] AUTODETECT spr round 4 (radius: 20)
[09:47:30 -508919.714529] AUTODETECT spr round 5 (radius: 25)
[09:49:48 -505574.854449] SPR radius for FAST iterations: 25 (autodetect)
[09:49:48 -505574.854449] Model parameter optimization (eps = 3.000000)
[09:50:11 -504497.865297] FAST spr round 1 (radius: 25)
[09:52:13 -454046.408382] FAST spr round 2 (radius: 25)
[09:53:45 -450401.940081] FAST spr round 3 (radius: 25)
[09:54:57 -450186.262448] FAST spr round 4 (radius: 25)
[09:55:57 -450163.132455] FAST spr round 5 (radius: 25)
[09:56:51 -450162.903903] FAST spr round 6 (radius: 25)
[09:57:43 -450162.902876] Model parameter optimization (eps = 1.000000)
[09:57:57 -450135.241054] SLOW spr round 1 (radius: 5)
[09:59:46 -450032.548166] SLOW spr round 2 (radius: 5)
[10:01:20 -450032.152497] SLOW spr round 3 (radius: 5)
[10:02:53 -450032.150784] SLOW spr round 4 (radius: 10)
[10:04:37 -450030.020029] SLOW spr round 5 (radius: 5)
[10:06:59 -450027.823460] SLOW spr round 6 (radius: 5)
[10:08:56 -450027.823030] SLOW spr round 7 (radius: 10)
[10:10:49 -450027.822723] SLOW spr round 8 (radius: 15)
[10:14:39 -450027.822714] SLOW spr round 9 (radius: 20)
[10:19:58 -450027.822709] SLOW spr round 10 (radius: 25)
[10:26:55 -450027.822705] Model parameter optimization (eps = 0.100000)

[10:27:05] ML tree search #14, logLikelihood: -450027.509734

[10:27:05 -1814811.876338] Initial branch length optimization
[10:27:11 -1476299.235646] Model parameter optimization (eps = 10.000000)
[10:27:55 -1469921.477188] AUTODETECT spr round 1 (radius: 5)
[10:29:17 -872419.946138] AUTODETECT spr round 2 (radius: 10)
[10:30:55 -649824.605986] AUTODETECT spr round 3 (radius: 15)
[10:33:02 -589719.246027] AUTODETECT spr round 4 (radius: 20)
[10:35:33 -568875.237696] AUTODETECT spr round 5 (radius: 25)
[10:38:41 -525493.757019] SPR radius for FAST iterations: 25 (autodetect)
[10:38:41 -525493.757019] Model parameter optimization (eps = 3.000000)
[10:39:08 -524422.737566] FAST spr round 1 (radius: 25)
[10:41:39 -452530.589025] FAST spr round 2 (radius: 25)
[10:43:26 -450305.115737] FAST spr round 3 (radius: 25)
[10:44:57 -450140.374995] FAST spr round 4 (radius: 25)
[10:45:57 -450135.198938] FAST spr round 5 (radius: 25)
[10:46:54 -450135.197803] Model parameter optimization (eps = 1.000000)
[10:47:08 -450111.590179] SLOW spr round 1 (radius: 5)
[10:48:58 -450042.392405] SLOW spr round 2 (radius: 5)
[10:50:33 -450042.386470] SLOW spr round 3 (radius: 10)
[10:52:15 -450042.385409] SLOW spr round 4 (radius: 15)
[10:56:09 -450042.385065] SLOW spr round 5 (radius: 20)
[11:01:30 -450042.384867] SLOW spr round 6 (radius: 25)
[11:08:28 -450042.384717] Model parameter optimization (eps = 0.100000)

[11:08:34] ML tree search #15, logLikelihood: -450042.284807

[11:08:34 -1815064.854969] Initial branch length optimization
[11:08:41 -1478554.158695] Model parameter optimization (eps = 10.000000)
[11:09:33 -1471987.679997] AUTODETECT spr round 1 (radius: 5)
[11:10:52 -885986.901333] AUTODETECT spr round 2 (radius: 10)
[11:12:28 -622138.085715] AUTODETECT spr round 3 (radius: 15)
[11:14:26 -515331.166626] AUTODETECT spr round 4 (radius: 20)
[11:16:40 -508096.885663] AUTODETECT spr round 5 (radius: 25)
[11:19:27 -502054.986749] SPR radius for FAST iterations: 25 (autodetect)
[11:19:27 -502054.986749] Model parameter optimization (eps = 3.000000)
[11:19:54 -501076.973668] FAST spr round 1 (radius: 25)
[11:21:58 -451988.186808] FAST spr round 2 (radius: 25)
[11:23:28 -450180.717728] FAST spr round 3 (radius: 25)
[11:24:36 -450105.915458] FAST spr round 4 (radius: 25)
[11:25:31 -450105.914583] Model parameter optimization (eps = 1.000000)
[11:25:47 -450082.934456] SLOW spr round 1 (radius: 5)
[11:27:30 -450039.835012] SLOW spr round 2 (radius: 5)
[11:29:03 -450039.832743] SLOW spr round 3 (radius: 10)
[11:30:44 -450039.832088] SLOW spr round 4 (radius: 15)
[11:34:31 -450039.831756] SLOW spr round 5 (radius: 20)
[11:39:25 -450039.831524] SLOW spr round 6 (radius: 25)
[11:45:54 -450039.831339] Model parameter optimization (eps = 0.100000)

[11:46:01] ML tree search #16, logLikelihood: -450039.780610

[11:46:02 -1811221.170199] Initial branch length optimization
[11:46:07 -1486832.078121] Model parameter optimization (eps = 10.000000)
[11:47:03 -1480514.017390] AUTODETECT spr round 1 (radius: 5)
[11:48:18 -889637.067004] AUTODETECT spr round 2 (radius: 10)
[11:49:55 -642048.195194] AUTODETECT spr round 3 (radius: 15)
[11:51:47 -542502.480131] AUTODETECT spr round 4 (radius: 20)
[11:54:02 -511608.170406] AUTODETECT spr round 5 (radius: 25)
[11:56:43 -510838.370775] SPR radius for FAST iterations: 25 (autodetect)
[11:56:43 -510838.370775] Model parameter optimization (eps = 3.000000)
[11:57:09 -509873.637249] FAST spr round 1 (radius: 25)
[11:59:16 -453096.723084] FAST spr round 2 (radius: 25)
[12:00:47 -450236.291463] FAST spr round 3 (radius: 25)
[12:01:56 -450124.941272] FAST spr round 4 (radius: 25)
[12:02:53 -450124.939466] Model parameter optimization (eps = 1.000000)
[12:03:09 -450107.958956] SLOW spr round 1 (radius: 5)
[12:04:59 -450049.250712] SLOW spr round 2 (radius: 5)
[12:06:35 -450049.247854] SLOW spr round 3 (radius: 10)
[12:08:20 -450046.737817] SLOW spr round 4 (radius: 5)
[12:10:46 -450044.536426] SLOW spr round 5 (radius: 5)
[12:12:47 -450044.535975] SLOW spr round 6 (radius: 10)
[12:14:48 -450044.535690] SLOW spr round 7 (radius: 15)
[12:18:49 -450044.535446] SLOW spr round 8 (radius: 20)
[12:24:35 -450044.535232] SLOW spr round 9 (radius: 25)
[12:32:03 -450044.535044] Model parameter optimization (eps = 0.100000)

[12:32:11] ML tree search #17, logLikelihood: -450044.375443

[12:32:11 -1813940.782019] Initial branch length optimization
[12:32:17 -1464409.849460] Model parameter optimization (eps = 10.000000)
[12:33:09 -1458023.492688] AUTODETECT spr round 1 (radius: 5)
[12:34:31 -910098.976955] AUTODETECT spr round 2 (radius: 10)
[12:36:07 -651399.312497] AUTODETECT spr round 3 (radius: 15)
[12:38:10 -553774.864303] AUTODETECT spr round 4 (radius: 20)
[12:40:38 -524371.024878] AUTODETECT spr round 5 (radius: 25)
[12:43:12 -508921.930904] SPR radius for FAST iterations: 25 (autodetect)
[12:43:12 -508921.930904] Model parameter optimization (eps = 3.000000)
[12:43:42 -507918.573808] FAST spr round 1 (radius: 25)
[12:46:01 -453807.167282] FAST spr round 2 (radius: 25)
[12:47:52 -450251.990313] FAST spr round 3 (radius: 25)
[12:49:06 -450105.154249] FAST spr round 4 (radius: 25)
[12:50:04 -450104.982588] FAST spr round 5 (radius: 25)
[12:51:01 -450104.968918] Model parameter optimization (eps = 1.000000)
[12:51:17 -450072.656786] SLOW spr round 1 (radius: 5)
[12:53:11 -450045.968293] SLOW spr round 2 (radius: 5)
[12:54:53 -450039.345359] SLOW spr round 3 (radius: 5)
[12:56:33 -450039.344369] SLOW spr round 4 (radius: 10)
[12:58:21 -450039.344184] SLOW spr round 5 (radius: 15)
[13:02:24 -450039.344087] SLOW spr round 6 (radius: 20)
[13:07:40 -450039.344024] SLOW spr round 7 (radius: 25)
[13:14:38 -450039.343980] Model parameter optimization (eps = 0.100000)

[13:14:44] ML tree search #18, logLikelihood: -450039.304877

[13:14:44 -1796872.281487] Initial branch length optimization
[13:14:50 -1451597.534435] Model parameter optimization (eps = 10.000000)
[13:15:49 -1445130.884825] AUTODETECT spr round 1 (radius: 5)
[13:17:10 -914187.935733] AUTODETECT spr round 2 (radius: 10)
[13:18:56 -634342.524304] AUTODETECT spr round 3 (radius: 15)
[13:21:05 -509039.953860] AUTODETECT spr round 4 (radius: 20)
[13:23:21 -493914.961438] AUTODETECT spr round 5 (radius: 25)
[13:26:19 -490959.981526] SPR radius for FAST iterations: 25 (autodetect)
[13:26:19 -490959.981526] Model parameter optimization (eps = 3.000000)
[13:26:45 -489935.201741] FAST spr round 1 (radius: 25)
[13:28:54 -451287.646860] FAST spr round 2 (radius: 25)
[13:30:35 -450345.704323] FAST spr round 3 (radius: 25)
[13:31:51 -450281.372738] FAST spr round 4 (radius: 25)
[13:32:46 -450275.489460] FAST spr round 5 (radius: 25)
[13:33:39 -450275.451512] Model parameter optimization (eps = 1.000000)
[13:33:55 -450258.389272] SLOW spr round 1 (radius: 5)
[13:35:45 -450162.590156] SLOW spr round 2 (radius: 5)
[13:37:20 -450157.865001] SLOW spr round 3 (radius: 5)
[13:38:52 -450157.864559] SLOW spr round 4 (radius: 10)
[13:40:36 -450157.864349] SLOW spr round 5 (radius: 15)
[13:45:07 -450157.864173] SLOW spr round 6 (radius: 20)
[13:51:18 -450157.864004] SLOW spr round 7 (radius: 25)
[13:58:35 -450157.863836] Model parameter optimization (eps = 0.100000)

[13:58:45] ML tree search #19, logLikelihood: -450157.318040

[13:58:45 -1809577.847900] Initial branch length optimization
[13:58:51 -1476122.028358] Model parameter optimization (eps = 10.000000)
[13:59:53 -1469612.751548] AUTODETECT spr round 1 (radius: 5)
[14:01:09 -869218.862219] AUTODETECT spr round 2 (radius: 10)
[14:02:44 -617069.877548] AUTODETECT spr round 3 (radius: 15)
[14:04:39 -531152.572236] AUTODETECT spr round 4 (radius: 20)
[14:07:10 -509826.476963] AUTODETECT spr round 5 (radius: 25)
[14:10:12 -509045.263916] SPR radius for FAST iterations: 25 (autodetect)
[14:10:12 -509045.263916] Model parameter optimization (eps = 3.000000)
[14:10:36 -508140.022067] FAST spr round 1 (radius: 25)
[14:12:32 -451595.219666] FAST spr round 2 (radius: 25)
[14:13:57 -450169.811779] FAST spr round 3 (radius: 25)
[14:15:05 -450117.097050] FAST spr round 4 (radius: 25)
[14:16:00 -450117.095842] Model parameter optimization (eps = 1.000000)
[14:16:14 -450095.234476] SLOW spr round 1 (radius: 5)
[14:18:01 -450032.767093] SLOW spr round 2 (radius: 5)
[14:19:41 -450026.801765] SLOW spr round 3 (radius: 5)
[14:21:17 -450021.305205] SLOW spr round 4 (radius: 5)
[14:22:51 -450021.304572] SLOW spr round 5 (radius: 10)
[14:24:31 -450021.304151] SLOW spr round 6 (radius: 15)
[14:28:22 -450021.303849] SLOW spr round 7 (radius: 20)
[14:33:30 -450021.303613] SLOW spr round 8 (radius: 25)
[14:40:12 -450021.303415] Model parameter optimization (eps = 0.100000)

[14:40:20] ML tree search #20, logLikelihood: -450021.159943


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.179638,0.585829) (0.114238,0.611380) (0.431320,0.879949) (0.274804,1.620720) 
   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: -450018.588140

AIC score: 901919.176280 / AICc score: 902554.604237 / BIC score: 907776.618568
Free parameters (model + branch lengths): 941

Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P58107/3_mltree/P58107.raxml.log

Analysis started: 07-Jul-2021 21:49:05 / finished: 08-Jul-2021 12:29:26

Elapsed time: 52820.909 seconds

Consumed energy: 3800.632 Wh (= 19 km in an electric car, or 95 km with an e-scooter!)