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 14-Jul-2021 12:52:25 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/2_msa/P09619_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/3_mltree/P09619 --seed 2 --threads 9 --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 (9 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/2_msa/P09619_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 1087 sites

WARNING: Sequences tr_F1P382_F1P382_CHICK_9031 and sp_Q8QHL3_VGFR1_CHICK_9031 are exactly identical!
WARNING: Sequences tr_F1PE35_F1PE35_CANLF_9615 and sp_Q6QNF3_PGFRB_CANLF_9615 are exactly identical!
WARNING: Sequences tr_H2QPH5_H2QPH5_PANTR_9598 and tr_A0A2R9AUT4_A0A2R9AUT4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QPH6_H2QPH6_PANTR_9598 and tr_A0A2R9CED2_A0A2R9CED2_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F7E313_F7E313_MACMU_9544 and tr_A0A2K5L771_A0A2K5L771_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7E313_F7E313_MACMU_9544 and tr_A0A2K6DVH4_A0A2K6DVH4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7E313_F7E313_MACMU_9544 and tr_A0A2K5ZP61_A0A2K5ZP61_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G7MTB0_G7MTB0_MACMU_9544 and tr_A0A096N3T8_A0A096N3T8_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_A0A2D0Q0E5_A0A2D0Q0E5_ICTPU_7998 and tr_A0A2D0Q235_A0A2D0Q235_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0Q0E5_A0A2D0Q0E5_ICTPU_7998 and tr_W5UKQ9_W5UKQ9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0SCK0_A0A2D0SCK0_ICTPU_7998 and tr_A0A2D0SDA8_A0A2D0SDA8_ICTPU_7998 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/P09619/3_mltree/P09619.raxml.reduced.phy

Alignment comprises 1 partitions and 1087 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1087 / 1087
Gaps: 21.14 %
Invariant sites: 0.37 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/3_mltree/P09619.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 9 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 / 121 / 9680
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1830926.545367] Initial branch length optimization
[00:00:13 -1558506.191089] Model parameter optimization (eps = 10.000000)
[00:01:46 -1557670.566684] AUTODETECT spr round 1 (radius: 5)
[00:06:13 -1067154.891126] AUTODETECT spr round 2 (radius: 10)
[00:10:59 -788756.692192] AUTODETECT spr round 3 (radius: 15)
[00:16:33 -599558.224596] AUTODETECT spr round 4 (radius: 20)
[00:22:18 -565138.524674] AUTODETECT spr round 5 (radius: 25)
[00:29:14 -534662.671880] SPR radius for FAST iterations: 25 (autodetect)
[00:29:14 -534662.671880] Model parameter optimization (eps = 3.000000)
[00:29:42 -534403.764293] FAST spr round 1 (radius: 25)
[00:32:50 -463646.375437] FAST spr round 2 (radius: 25)
[00:35:18 -461319.875987] FAST spr round 3 (radius: 25)
[00:37:20 -461205.866846] FAST spr round 4 (radius: 25)
[00:39:14 -461180.892903] FAST spr round 5 (radius: 25)
[00:41:04 -461177.454868] FAST spr round 6 (radius: 25)
[00:42:50 -461177.453838] Model parameter optimization (eps = 1.000000)
[00:43:07 -461160.561669] SLOW spr round 1 (radius: 5)
[00:45:38 -461068.275808] SLOW spr round 2 (radius: 5)
[00:48:09 -461053.659313] SLOW spr round 3 (radius: 5)
[00:50:32 -461051.496036] SLOW spr round 4 (radius: 5)
[00:52:51 -461051.496020] SLOW spr round 5 (radius: 10)
[00:55:18 -461050.821167] SLOW spr round 6 (radius: 5)
[00:58:20 -461050.819307] SLOW spr round 7 (radius: 10)
[01:01:05 -461050.006146] SLOW spr round 8 (radius: 5)
[01:04:03 -461049.995038] SLOW spr round 9 (radius: 10)
[01:06:40 -461049.993928] SLOW spr round 10 (radius: 15)
[01:11:18 -461049.993886] SLOW spr round 11 (radius: 20)
[01:21:01 -461049.993874] SLOW spr round 12 (radius: 25)
[01:33:20 -461049.993867] Model parameter optimization (eps = 0.100000)

[01:33:32] ML tree search #1, logLikelihood: -461049.683540

[01:33:32 -1814076.975085] Initial branch length optimization
[01:33:40 -1539959.506678] Model parameter optimization (eps = 10.000000)
[01:34:19 -1539063.525223] AUTODETECT spr round 1 (radius: 5)
[01:36:57 -1055482.698330] AUTODETECT spr round 2 (radius: 10)
[01:39:45 -759867.559764] AUTODETECT spr round 3 (radius: 15)
[01:42:35 -641937.648627] AUTODETECT spr round 4 (radius: 20)
[01:45:49 -553318.650835] AUTODETECT spr round 5 (radius: 25)
[01:49:22 -538575.085348] SPR radius for FAST iterations: 25 (autodetect)
[01:49:22 -538575.085348] Model parameter optimization (eps = 3.000000)
[01:49:44 -538216.267802] FAST spr round 1 (radius: 25)
[01:52:46 -464318.226008] FAST spr round 2 (radius: 25)
[01:55:09 -461459.297669] FAST spr round 3 (radius: 25)
[01:57:17 -461208.100242] FAST spr round 4 (radius: 25)
[01:59:12 -461156.681938] FAST spr round 5 (radius: 25)
[02:00:55 -461156.681811] Model parameter optimization (eps = 1.000000)
[02:01:13 -461142.055697] SLOW spr round 1 (radius: 5)
[02:03:45 -461072.815388] SLOW spr round 2 (radius: 5)
[02:06:11 -461054.819923] SLOW spr round 3 (radius: 5)
[02:08:26 -461054.819238] SLOW spr round 4 (radius: 10)
[02:10:49 -461041.127638] SLOW spr round 5 (radius: 5)
[02:13:52 -461034.004292] SLOW spr round 6 (radius: 5)
[02:16:27 -461034.003744] SLOW spr round 7 (radius: 10)
[02:18:51 -461034.003735] SLOW spr round 8 (radius: 15)
[02:23:22 -461034.003735] SLOW spr round 9 (radius: 20)
[02:32:03 -461034.003734] SLOW spr round 10 (radius: 25)
[02:43:40 -461034.003734] Model parameter optimization (eps = 0.100000)

[02:43:49] ML tree search #2, logLikelihood: -461033.775460

[02:43:49 -1824386.840858] Initial branch length optimization
[02:43:57 -1543536.798981] Model parameter optimization (eps = 10.000000)
[02:44:47 -1542716.262523] AUTODETECT spr round 1 (radius: 5)
[02:47:22 -1077047.235251] AUTODETECT spr round 2 (radius: 10)
[02:50:14 -746707.486776] AUTODETECT spr round 3 (radius: 15)
[02:53:12 -603366.237822] AUTODETECT spr round 4 (radius: 20)
[02:56:39 -539192.325645] AUTODETECT spr round 5 (radius: 25)
[03:00:34 -534238.864857] SPR radius for FAST iterations: 25 (autodetect)
[03:00:34 -534238.864857] Model parameter optimization (eps = 3.000000)
[03:01:05 -533887.512798] FAST spr round 1 (radius: 25)
[03:04:09 -463832.482342] FAST spr round 2 (radius: 25)
[03:06:31 -461641.918023] FAST spr round 3 (radius: 25)
[03:08:36 -461209.848208] FAST spr round 4 (radius: 25)
[03:10:30 -461196.837956] FAST spr round 5 (radius: 25)
[03:12:15 -461196.837875] Model parameter optimization (eps = 1.000000)
[03:12:27 -461191.822401] SLOW spr round 1 (radius: 5)
[03:14:55 -461062.532021] SLOW spr round 2 (radius: 5)
[03:17:16 -461059.788733] SLOW spr round 3 (radius: 5)
[03:19:28 -461059.788449] SLOW spr round 4 (radius: 10)
[03:21:46 -461048.236679] SLOW spr round 5 (radius: 5)
[03:24:37 -461041.423821] SLOW spr round 6 (radius: 5)
[03:27:06 -461040.930725] SLOW spr round 7 (radius: 5)
[03:29:24 -461040.930725] SLOW spr round 8 (radius: 10)
[03:31:44 -461040.566087] SLOW spr round 9 (radius: 5)
[03:34:31 -461040.566070] SLOW spr round 10 (radius: 10)
[03:37:04 -461040.566070] SLOW spr round 11 (radius: 15)
[03:41:08 -461040.566069] SLOW spr round 12 (radius: 20)
[03:49:38 -461040.566069] SLOW spr round 13 (radius: 25)
[04:00:22 -461040.566069] Model parameter optimization (eps = 0.100000)

[04:00:32] ML tree search #3, logLikelihood: -461040.167500

[04:00:32 -1827923.148458] Initial branch length optimization
[04:00:43 -1553948.703282] Model parameter optimization (eps = 10.000000)
[04:01:32 -1553018.879922] AUTODETECT spr round 1 (radius: 5)
[04:04:01 -1072023.301090] AUTODETECT spr round 2 (radius: 10)
[04:07:53 -780385.504855] AUTODETECT spr round 3 (radius: 15)
[04:10:56 -623537.549760] AUTODETECT spr round 4 (radius: 20)
[04:14:31 -561774.637110] AUTODETECT spr round 5 (radius: 25)
[04:18:11 -539564.715733] SPR radius for FAST iterations: 25 (autodetect)
[04:18:11 -539564.715733] Model parameter optimization (eps = 3.000000)
[04:18:36 -539280.696637] FAST spr round 1 (radius: 25)
[04:21:31 -463223.391116] FAST spr round 2 (radius: 25)
[04:23:49 -461271.030618] FAST spr round 3 (radius: 25)
[04:25:50 -461195.298507] FAST spr round 4 (radius: 25)
[04:27:43 -461168.700214] FAST spr round 5 (radius: 25)
[04:29:30 -461159.642045] FAST spr round 6 (radius: 25)
[04:31:14 -461159.641475] Model parameter optimization (eps = 1.000000)
[04:31:27 -461155.160991] SLOW spr round 1 (radius: 5)
[04:33:53 -461056.491855] SLOW spr round 2 (radius: 5)
[04:36:14 -461046.004621] SLOW spr round 3 (radius: 5)
[04:38:32 -461039.438233] SLOW spr round 4 (radius: 5)
[04:40:45 -461039.095988] SLOW spr round 5 (radius: 5)
[04:42:56 -461039.095733] SLOW spr round 6 (radius: 10)
[04:45:14 -461038.184671] SLOW spr round 7 (radius: 5)
[04:48:03 -461038.180869] SLOW spr round 8 (radius: 10)
[04:50:37 -461037.934259] SLOW spr round 9 (radius: 5)
[04:53:24 -461034.325218] SLOW spr round 10 (radius: 5)
[04:55:52 -461034.325184] SLOW spr round 11 (radius: 10)
[04:58:14 -461034.089807] SLOW spr round 12 (radius: 5)
[05:01:03 -461034.089749] SLOW spr round 13 (radius: 10)
[05:03:35 -461034.089748] SLOW spr round 14 (radius: 15)
[05:07:42 -461034.089748] SLOW spr round 15 (radius: 20)
[05:16:24 -461034.089748] SLOW spr round 16 (radius: 25)
[05:27:14 -461034.089748] Model parameter optimization (eps = 0.100000)

[05:27:26] ML tree search #4, logLikelihood: -461033.380273

[05:27:26 -1832490.642798] Initial branch length optimization
[05:27:34 -1554888.528086] Model parameter optimization (eps = 10.000000)
[05:28:08 -1553904.377075] AUTODETECT spr round 1 (radius: 5)
[05:30:37 -1058913.957662] AUTODETECT spr round 2 (radius: 10)
[05:33:14 -765659.941262] AUTODETECT spr round 3 (radius: 15)
[05:36:06 -634861.476845] AUTODETECT spr round 4 (radius: 20)
[05:39:27 -575270.130759] AUTODETECT spr round 5 (radius: 25)
[05:43:36 -552182.392080] SPR radius for FAST iterations: 25 (autodetect)
[05:43:36 -552182.392080] Model parameter optimization (eps = 3.000000)
[05:44:03 -551812.439523] FAST spr round 1 (radius: 25)
[05:47:02 -464039.113879] FAST spr round 2 (radius: 25)
[05:49:17 -461374.240813] FAST spr round 3 (radius: 25)
[05:51:20 -461216.041895] FAST spr round 4 (radius: 25)
[05:53:06 -461201.033180] FAST spr round 5 (radius: 25)
[05:54:47 -461201.032830] Model parameter optimization (eps = 1.000000)
[05:55:04 -461189.722094] SLOW spr round 1 (radius: 5)
[05:57:27 -461063.561213] SLOW spr round 2 (radius: 5)
[05:59:41 -461061.193712] SLOW spr round 3 (radius: 5)
[06:01:48 -461061.193587] SLOW spr round 4 (radius: 10)
[06:04:01 -461054.191127] SLOW spr round 5 (radius: 5)
[06:06:48 -461050.107003] SLOW spr round 6 (radius: 5)
[06:09:12 -461050.106911] SLOW spr round 7 (radius: 10)
[06:11:26 -461049.953727] SLOW spr round 8 (radius: 5)
[06:14:07 -461049.953603] SLOW spr round 9 (radius: 10)
[06:16:31 -461049.953598] SLOW spr round 10 (radius: 15)
[06:20:35 -461049.953597] SLOW spr round 11 (radius: 20)
[06:28:57 -461049.953596] SLOW spr round 12 (radius: 25)
[06:39:44 -461049.953595] Model parameter optimization (eps = 0.100000)

[06:39:53] ML tree search #5, logLikelihood: -461049.594157

[06:39:53 -1823642.486017] Initial branch length optimization
[06:40:03 -1544110.288016] Model parameter optimization (eps = 10.000000)
[06:40:56 -1543230.600957] AUTODETECT spr round 1 (radius: 5)
[06:43:27 -1030103.202345] AUTODETECT spr round 2 (radius: 10)
[06:46:10 -765476.903786] AUTODETECT spr round 3 (radius: 15)
[06:49:13 -616680.854702] AUTODETECT spr round 4 (radius: 20)
[06:52:44 -536585.942477] AUTODETECT spr round 5 (radius: 25)
[06:56:35 -528968.711569] SPR radius for FAST iterations: 25 (autodetect)
[06:56:35 -528968.711569] Model parameter optimization (eps = 3.000000)
[06:57:02 -528691.340981] FAST spr round 1 (radius: 25)
[07:00:11 -463134.561216] FAST spr round 2 (radius: 25)
[07:02:29 -461511.120987] FAST spr round 3 (radius: 25)
[07:04:29 -461202.419171] FAST spr round 4 (radius: 25)
[07:06:20 -461165.587556] FAST spr round 5 (radius: 25)
[07:08:10 -461158.368739] FAST spr round 6 (radius: 25)
[07:09:56 -461158.368371] Model parameter optimization (eps = 1.000000)
[07:10:12 -461156.970718] SLOW spr round 1 (radius: 5)
[07:12:44 -461054.995587] SLOW spr round 2 (radius: 5)
[07:15:06 -461050.728788] SLOW spr round 3 (radius: 5)
[07:17:22 -461050.728697] SLOW spr round 4 (radius: 10)
[07:19:43 -461046.325776] SLOW spr round 5 (radius: 5)
[07:22:37 -461046.325767] SLOW spr round 6 (radius: 10)
[07:25:13 -461046.325763] SLOW spr round 7 (radius: 15)
[07:29:28 -461046.325761] SLOW spr round 8 (radius: 20)
[07:38:30 -461046.325760] SLOW spr round 9 (radius: 25)
[07:50:04 -461046.325759] Model parameter optimization (eps = 0.100000)

[07:50:18] ML tree search #6, logLikelihood: -461045.868723

[07:50:18 -1832012.689674] Initial branch length optimization
[07:50:27 -1556278.994205] Model parameter optimization (eps = 10.000000)
[07:51:23 -1555250.493563] AUTODETECT spr round 1 (radius: 5)
[07:53:53 -1062819.321302] AUTODETECT spr round 2 (radius: 10)
[07:56:40 -773829.947513] AUTODETECT spr round 3 (radius: 15)
[07:59:53 -641740.765364] AUTODETECT spr round 4 (radius: 20)
[08:03:25 -550410.851251] AUTODETECT spr round 5 (radius: 25)
[08:07:26 -537053.289800] SPR radius for FAST iterations: 25 (autodetect)
[08:07:26 -537053.289800] Model parameter optimization (eps = 3.000000)
[08:07:53 -536727.818820] FAST spr round 1 (radius: 25)
[08:10:52 -465195.832050] FAST spr round 2 (radius: 25)
[08:13:18 -461521.222585] FAST spr round 3 (radius: 25)
[08:15:24 -461288.611586] FAST spr round 4 (radius: 25)
[08:17:20 -461221.084853] FAST spr round 5 (radius: 25)
[08:19:06 -461221.084752] Model parameter optimization (eps = 1.000000)
[08:19:23 -461206.236387] SLOW spr round 1 (radius: 5)
[08:21:55 -461076.950923] SLOW spr round 2 (radius: 5)
[08:24:20 -461056.889781] SLOW spr round 3 (radius: 5)
[08:26:36 -461052.750860] SLOW spr round 4 (radius: 5)
[08:28:50 -461052.750813] SLOW spr round 5 (radius: 10)
[08:31:11 -461050.495084] SLOW spr round 6 (radius: 5)
[08:34:04 -461050.303822] SLOW spr round 7 (radius: 5)
[08:36:36 -461050.303159] SLOW spr round 8 (radius: 10)
[08:39:01 -461050.303159] SLOW spr round 9 (radius: 15)
[08:43:29 -461050.303158] SLOW spr round 10 (radius: 20)
[08:52:12 -461050.303158] SLOW spr round 11 (radius: 25)
[09:03:29 -461050.303158] Model parameter optimization (eps = 0.100000)

[09:03:40] ML tree search #7, logLikelihood: -461049.877246

[09:03:40 -1839309.489275] Initial branch length optimization
[09:03:47 -1554704.360320] Model parameter optimization (eps = 10.000000)
[09:04:39 -1553828.003261] AUTODETECT spr round 1 (radius: 5)
[09:07:11 -1069355.230980] AUTODETECT spr round 2 (radius: 10)
[09:09:54 -782874.628058] AUTODETECT spr round 3 (radius: 15)
[09:12:53 -635806.853816] AUTODETECT spr round 4 (radius: 20)
[09:15:57 -551665.439279] AUTODETECT spr round 5 (radius: 25)
[09:19:10 -536884.335484] SPR radius for FAST iterations: 25 (autodetect)
[09:19:10 -536884.335484] Model parameter optimization (eps = 3.000000)
[09:19:36 -536533.801694] FAST spr round 1 (radius: 25)
[09:22:43 -465011.099798] FAST spr round 2 (radius: 25)
[09:25:02 -461399.662790] FAST spr round 3 (radius: 25)
[09:27:09 -461180.249675] FAST spr round 4 (radius: 25)
[09:28:58 -461159.613909] FAST spr round 5 (radius: 25)
[09:30:43 -461155.362700] FAST spr round 6 (radius: 25)
[09:32:26 -461155.362306] Model parameter optimization (eps = 1.000000)
[09:32:44 -461145.404559] SLOW spr round 1 (radius: 5)
[09:35:07 -461064.879370] SLOW spr round 2 (radius: 5)
[09:37:23 -461064.556680] SLOW spr round 3 (radius: 5)
[09:39:36 -461064.555803] SLOW spr round 4 (radius: 10)
[09:41:56 -461061.717899] SLOW spr round 5 (radius: 5)
[09:44:49 -461059.811743] SLOW spr round 6 (radius: 5)
[09:47:21 -461057.615048] SLOW spr round 7 (radius: 5)
[09:49:42 -461057.614368] SLOW spr round 8 (radius: 10)
[09:52:01 -461057.613863] SLOW spr round 9 (radius: 15)
[09:56:41 -461057.613379] SLOW spr round 10 (radius: 20)
[10:05:23 -461057.612916] SLOW spr round 11 (radius: 25)
[10:16:43 -461057.612473] Model parameter optimization (eps = 0.100000)

[10:16:55] ML tree search #8, logLikelihood: -461057.384255

[10:16:56 -1826989.893153] Initial branch length optimization
[10:17:04 -1553689.783245] Model parameter optimization (eps = 10.000000)
[10:18:06 -1552429.441879] AUTODETECT spr round 1 (radius: 5)
[10:20:35 -1029923.914228] AUTODETECT spr round 2 (radius: 10)
[10:23:18 -748877.185225] AUTODETECT spr round 3 (radius: 15)
[10:26:12 -586803.419054] AUTODETECT spr round 4 (radius: 20)
[10:29:34 -538651.645726] AUTODETECT spr round 5 (radius: 25)
[10:33:36 -524879.655276] SPR radius for FAST iterations: 25 (autodetect)
[10:33:36 -524879.655276] Model parameter optimization (eps = 3.000000)
[10:34:03 -524585.658923] FAST spr round 1 (radius: 25)
[10:37:00 -462886.007388] FAST spr round 2 (radius: 25)
[10:39:13 -461351.087592] FAST spr round 3 (radius: 25)
[10:41:12 -461194.410933] FAST spr round 4 (radius: 25)
[10:43:01 -461188.679011] FAST spr round 5 (radius: 25)
[10:44:45 -461188.676665] Model parameter optimization (eps = 1.000000)
[10:44:57 -461181.103451] SLOW spr round 1 (radius: 5)
[10:47:22 -461069.882612] SLOW spr round 2 (radius: 5)
[10:49:41 -461064.906874] SLOW spr round 3 (radius: 5)
[10:51:55 -461064.906370] SLOW spr round 4 (radius: 10)
[10:54:15 -461060.600501] SLOW spr round 5 (radius: 5)
[10:57:06 -461060.600476] SLOW spr round 6 (radius: 10)
[10:59:41 -461056.992934] SLOW spr round 7 (radius: 5)
[11:02:28 -461056.978695] SLOW spr round 8 (radius: 10)
[11:05:00 -461056.975665] SLOW spr round 9 (radius: 15)
[11:09:21 -461056.975016] SLOW spr round 10 (radius: 20)
[11:18:15 -461056.974879] SLOW spr round 11 (radius: 25)
[11:30:07 -461056.974850] Model parameter optimization (eps = 0.100000)

[11:30:18] ML tree search #9, logLikelihood: -461056.684814

[11:30:18 -1826618.098352] Initial branch length optimization
[11:30:26 -1540757.955479] Model parameter optimization (eps = 10.000000)
[11:31:04 -1539837.420935] AUTODETECT spr round 1 (radius: 5)
[11:33:35 -1082363.033541] AUTODETECT spr round 2 (radius: 10)
[11:36:21 -784798.067121] AUTODETECT spr round 3 (radius: 15)
[11:39:14 -663933.755812] AUTODETECT spr round 4 (radius: 20)
[11:42:53 -586788.677381] AUTODETECT spr round 5 (radius: 25)
[11:47:14 -545763.494375] SPR radius for FAST iterations: 25 (autodetect)
[11:47:14 -545763.494375] Model parameter optimization (eps = 3.000000)
[11:47:37 -545346.962035] FAST spr round 1 (radius: 25)
[11:50:41 -465389.748678] FAST spr round 2 (radius: 25)
[11:53:01 -461454.668697] FAST spr round 3 (radius: 25)
[11:55:02 -461255.260685] FAST spr round 4 (radius: 25)
[11:56:53 -461233.545667] FAST spr round 5 (radius: 25)
[11:58:42 -461209.687217] FAST spr round 6 (radius: 25)
[12:00:25 -461209.687209] Model parameter optimization (eps = 1.000000)
[12:00:43 -461175.419992] SLOW spr round 1 (radius: 5)
[12:03:15 -461060.802103] SLOW spr round 2 (radius: 5)
[12:05:39 -461057.681358] SLOW spr round 3 (radius: 5)
[12:07:57 -461056.980816] SLOW spr round 4 (radius: 5)
[12:10:13 -461056.980756] SLOW spr round 5 (radius: 10)
[12:12:40 -461050.738172] SLOW spr round 6 (radius: 5)
[12:15:43 -461048.977417] SLOW spr round 7 (radius: 5)
[12:18:20 -461048.976973] SLOW spr round 8 (radius: 10)
[12:20:49 -461044.571008] SLOW spr round 9 (radius: 5)
[12:25:21 -461044.570992] SLOW spr round 10 (radius: 10)
[12:29:45 -461044.570989] SLOW spr round 11 (radius: 15)
[12:37:38 -461044.570987] SLOW spr round 12 (radius: 20)
[12:53:23 -461044.570987] SLOW spr round 13 (radius: 25)
[13:05:29 -461044.570987] Model parameter optimization (eps = 0.100000)

[13:05:37] ML tree search #10, logLikelihood: -461044.512811

[13:05:38 -1829739.886350] Initial branch length optimization
[13:05:50 -1557831.282894] Model parameter optimization (eps = 10.000000)
[13:06:54 -1556671.982115] AUTODETECT spr round 1 (radius: 5)
[13:09:26 -1056110.697240] AUTODETECT spr round 2 (radius: 10)
[13:12:11 -764725.304911] AUTODETECT spr round 3 (radius: 15)
[13:15:23 -619867.182962] AUTODETECT spr round 4 (radius: 20)
[13:18:56 -553104.238177] AUTODETECT spr round 5 (radius: 25)
[13:22:33 -538793.228005] SPR radius for FAST iterations: 25 (autodetect)
[13:22:33 -538793.228005] Model parameter optimization (eps = 3.000000)
[13:22:58 -538489.106497] FAST spr round 1 (radius: 25)
[13:26:01 -464311.947146] FAST spr round 2 (radius: 25)
[13:28:22 -461518.102110] FAST spr round 3 (radius: 25)
[13:30:27 -461187.517205] FAST spr round 4 (radius: 25)
[13:32:19 -461164.183456] FAST spr round 5 (radius: 25)
[13:34:06 -461160.257271] FAST spr round 6 (radius: 25)
[13:35:51 -461160.256301] Model parameter optimization (eps = 1.000000)
[13:36:12 -461153.387858] SLOW spr round 1 (radius: 5)
[13:38:42 -461068.667101] SLOW spr round 2 (radius: 5)
[13:41:07 -461059.496310] SLOW spr round 3 (radius: 5)
[13:43:25 -461059.495376] SLOW spr round 4 (radius: 10)
[13:45:50 -461055.244341] SLOW spr round 5 (radius: 5)
[13:48:49 -461055.244339] SLOW spr round 6 (radius: 10)
[13:51:30 -461053.909369] SLOW spr round 7 (radius: 5)
[13:54:26 -461051.832587] SLOW spr round 8 (radius: 5)
[13:57:00 -461051.832586] SLOW spr round 9 (radius: 10)
[13:59:27 -461051.470522] SLOW spr round 10 (radius: 5)
[14:02:25 -461051.470503] SLOW spr round 11 (radius: 10)
[14:05:04 -461051.470503] SLOW spr round 12 (radius: 15)
[14:09:39 -461051.470503] SLOW spr round 13 (radius: 20)
[14:19:23 -461051.470503] SLOW spr round 14 (radius: 25)
[14:31:36 -461051.470503] Model parameter optimization (eps = 0.100000)

[14:31:49] ML tree search #11, logLikelihood: -461051.258017

[14:31:49 -1821760.206494] Initial branch length optimization
[14:31:56 -1546702.950828] Model parameter optimization (eps = 10.000000)
[14:32:42 -1545808.761152] AUTODETECT spr round 1 (radius: 5)
[14:35:10 -1103747.774455] AUTODETECT spr round 2 (radius: 10)
[14:37:57 -768890.212740] AUTODETECT spr round 3 (radius: 15)
[14:41:05 -652430.407482] AUTODETECT spr round 4 (radius: 20)
[14:44:31 -577466.637371] AUTODETECT spr round 5 (radius: 25)
[14:48:08 -550504.024451] SPR radius for FAST iterations: 25 (autodetect)
[14:48:08 -550504.024451] Model parameter optimization (eps = 3.000000)
[14:48:32 -550196.927799] FAST spr round 1 (radius: 25)
[14:51:10 -466514.660784] FAST spr round 2 (radius: 25)
[14:53:08 -461495.713556] FAST spr round 3 (radius: 25)
[14:54:57 -461197.506887] FAST spr round 4 (radius: 25)
[14:56:33 -461176.162138] FAST spr round 5 (radius: 25)
[14:58:07 -461171.319304] FAST spr round 6 (radius: 25)
[14:59:38 -461171.319027] Model parameter optimization (eps = 1.000000)
[14:59:52 -461164.986582] SLOW spr round 1 (radius: 5)
[15:02:08 -461078.637467] SLOW spr round 2 (radius: 5)
[15:04:24 -461058.658355] SLOW spr round 3 (radius: 5)
[15:06:39 -461054.479740] SLOW spr round 4 (radius: 5)
[15:08:49 -461054.476982] SLOW spr round 5 (radius: 10)
[15:11:04 -461053.730160] SLOW spr round 6 (radius: 5)
[15:13:53 -461053.154082] SLOW spr round 7 (radius: 5)
[15:16:22 -461053.154071] SLOW spr round 8 (radius: 10)
[15:18:39 -461053.154069] SLOW spr round 9 (radius: 15)
[15:23:10 -461053.154068] SLOW spr round 10 (radius: 20)
[15:31:54 -461053.154068] SLOW spr round 11 (radius: 25)
[15:42:22 -461053.154067] Model parameter optimization (eps = 0.100000)

[15:42:32] ML tree search #12, logLikelihood: -461052.329940

[15:42:32 -1828264.795053] Initial branch length optimization
[15:42:39 -1547515.086168] Model parameter optimization (eps = 10.000000)
[15:43:20 -1546648.576367] AUTODETECT spr round 1 (radius: 5)
[15:45:31 -1062903.167178] AUTODETECT spr round 2 (radius: 10)
[15:47:55 -775985.097616] AUTODETECT spr round 3 (radius: 15)
[15:50:36 -597716.164330] AUTODETECT spr round 4 (radius: 20)
[15:53:27 -553657.738988] AUTODETECT spr round 5 (radius: 25)
[15:57:03 -546206.293226] SPR radius for FAST iterations: 25 (autodetect)
[15:57:03 -546206.293226] Model parameter optimization (eps = 3.000000)
[15:57:24 -545844.735941] FAST spr round 1 (radius: 25)
[16:00:18 -469968.936693] FAST spr round 2 (radius: 25)
[16:02:23 -462489.922543] FAST spr round 3 (radius: 25)
[16:04:12 -461307.967862] FAST spr round 4 (radius: 25)
[16:06:05 -461172.097019] FAST spr round 5 (radius: 25)
[16:07:39 -461164.624566] FAST spr round 6 (radius: 25)
[16:09:10 -461164.624401] Model parameter optimization (eps = 1.000000)
[16:09:25 -461161.897460] SLOW spr round 1 (radius: 5)
[16:11:32 -461047.005899] SLOW spr round 2 (radius: 5)
[16:13:32 -461046.877041] SLOW spr round 3 (radius: 5)
[16:15:28 -461046.876422] SLOW spr round 4 (radius: 10)
[16:17:31 -461039.561158] SLOW spr round 5 (radius: 5)
[16:20:00 -461039.553348] SLOW spr round 6 (radius: 10)
[16:22:16 -461039.551721] SLOW spr round 7 (radius: 15)
[16:25:52 -461039.551330] SLOW spr round 8 (radius: 20)
[16:33:28 -461039.551196] SLOW spr round 9 (radius: 25)
[16:43:14 -461039.551158] Model parameter optimization (eps = 0.100000)

[16:43:24] ML tree search #13, logLikelihood: -461039.278438

[16:43:24 -1822913.870125] Initial branch length optimization
[16:43:32 -1542821.728012] Model parameter optimization (eps = 10.000000)
[16:44:04 -1541950.108646] AUTODETECT spr round 1 (radius: 5)
[16:46:15 -1068416.570960] AUTODETECT spr round 2 (radius: 10)
[16:48:53 -753675.523559] AUTODETECT spr round 3 (radius: 15)
[16:51:35 -636993.666647] AUTODETECT spr round 4 (radius: 20)
[16:54:51 -570271.433820] AUTODETECT spr round 5 (radius: 25)
[16:59:16 -544108.994412] SPR radius for FAST iterations: 25 (autodetect)
[16:59:16 -544108.994412] Model parameter optimization (eps = 3.000000)
[16:59:42 -543708.466853] FAST spr round 1 (radius: 25)
[17:02:34 -464424.873869] FAST spr round 2 (radius: 25)
[17:04:48 -461388.805710] FAST spr round 3 (radius: 25)
[17:06:50 -461201.501599] FAST spr round 4 (radius: 25)
[17:08:35 -461179.851846] FAST spr round 5 (radius: 25)
[17:10:18 -461175.970253] FAST spr round 6 (radius: 25)
[17:12:01 -461175.499867] FAST spr round 7 (radius: 25)
[17:13:40 -461175.499189] Model parameter optimization (eps = 1.000000)
[17:13:57 -461162.968934] SLOW spr round 1 (radius: 5)
[17:16:27 -461054.621669] SLOW spr round 2 (radius: 5)
[17:18:47 -461032.334068] SLOW spr round 3 (radius: 5)
[17:20:58 -461031.303739] SLOW spr round 4 (radius: 5)
[17:23:07 -461031.303159] SLOW spr round 5 (radius: 10)
[17:25:24 -461030.460474] SLOW spr round 6 (radius: 5)
[17:28:16 -461030.456364] SLOW spr round 7 (radius: 10)
[17:30:49 -461029.974879] SLOW spr round 8 (radius: 5)
[17:33:33 -461029.974831] SLOW spr round 9 (radius: 10)
[17:36:00 -461029.974829] SLOW spr round 10 (radius: 15)
[17:40:19 -461029.974827] SLOW spr round 11 (radius: 20)
[17:49:13 -461029.974826] SLOW spr round 12 (radius: 25)
[18:00:28 -461029.974825] Model parameter optimization (eps = 0.100000)

[18:00:39] ML tree search #14, logLikelihood: -461029.538444

[18:00:39 -1823357.224174] Initial branch length optimization
[18:00:45 -1547776.547139] Model parameter optimization (eps = 10.000000)
[18:01:31 -1546799.883016] AUTODETECT spr round 1 (radius: 5)
[18:03:50 -1080245.463427] AUTODETECT spr round 2 (radius: 10)
[18:06:25 -755510.171601] AUTODETECT spr round 3 (radius: 15)
[18:09:29 -608332.002786] AUTODETECT spr round 4 (radius: 20)
[18:12:42 -550379.579005] AUTODETECT spr round 5 (radius: 25)
[18:16:24 -546031.043912] SPR radius for FAST iterations: 25 (autodetect)
[18:16:24 -546031.043912] Model parameter optimization (eps = 3.000000)
[18:16:51 -545698.742304] FAST spr round 1 (radius: 25)
[18:19:50 -462783.251844] FAST spr round 2 (radius: 25)
[18:22:03 -461276.300505] FAST spr round 3 (radius: 25)
[18:24:04 -461177.277385] FAST spr round 4 (radius: 25)
[18:25:50 -461156.403010] FAST spr round 5 (radius: 25)
[18:27:29 -461156.402320] Model parameter optimization (eps = 1.000000)
[18:27:41 -461151.503342] SLOW spr round 1 (radius: 5)
[18:30:07 -461060.340133] SLOW spr round 2 (radius: 5)
[18:32:23 -461056.443284] SLOW spr round 3 (radius: 5)
[18:34:35 -461051.538283] SLOW spr round 4 (radius: 5)
[18:36:44 -461051.043924] SLOW spr round 5 (radius: 5)
[18:38:53 -461051.043699] SLOW spr round 6 (radius: 10)
[18:41:08 -461049.183080] SLOW spr round 7 (radius: 5)
[18:43:59 -461041.720612] SLOW spr round 8 (radius: 5)
[18:46:27 -461041.720073] SLOW spr round 9 (radius: 10)
[18:48:44 -461041.501170] SLOW spr round 10 (radius: 5)
[18:51:35 -461037.887543] SLOW spr round 11 (radius: 5)
[18:54:02 -461037.887503] SLOW spr round 12 (radius: 10)
[18:56:22 -461037.669119] SLOW spr round 13 (radius: 5)
[18:59:10 -461037.669047] SLOW spr round 14 (radius: 10)
[19:01:40 -461037.669045] SLOW spr round 15 (radius: 15)
[19:05:59 -461037.669044] SLOW spr round 16 (radius: 20)
[19:15:07 -461037.669044] SLOW spr round 17 (radius: 25)
[19:26:18 -461037.669044] Model parameter optimization (eps = 0.100000)

[19:26:28] ML tree search #15, logLikelihood: -461037.189189

[19:26:28 -1826149.367213] Initial branch length optimization
[19:26:34 -1546981.981914] Model parameter optimization (eps = 10.000000)
[19:27:19 -1546143.157253] AUTODETECT spr round 1 (radius: 5)
[19:29:40 -1064782.892741] AUTODETECT spr round 2 (radius: 10)
[19:32:17 -771702.409244] AUTODETECT spr round 3 (radius: 15)
[19:35:18 -639339.626965] AUTODETECT spr round 4 (radius: 20)
[19:38:40 -573933.373879] AUTODETECT spr round 5 (radius: 25)
[19:42:05 -545767.062176] SPR radius for FAST iterations: 25 (autodetect)
[19:42:05 -545767.062176] Model parameter optimization (eps = 3.000000)
[19:42:32 -545425.202248] FAST spr round 1 (radius: 25)
[19:45:20 -465732.678789] FAST spr round 2 (radius: 25)
[19:47:32 -461550.159740] FAST spr round 3 (radius: 25)
[19:49:32 -461207.825786] FAST spr round 4 (radius: 25)
[19:51:22 -461165.395647] FAST spr round 5 (radius: 25)
[19:53:04 -461163.426216] FAST spr round 6 (radius: 25)
[19:54:43 -461163.426184] Model parameter optimization (eps = 1.000000)
[19:55:00 -461142.033690] SLOW spr round 1 (radius: 5)
[19:57:22 -461065.409085] SLOW spr round 2 (radius: 5)
[19:59:37 -461064.349403] SLOW spr round 3 (radius: 5)
[20:01:49 -461064.348935] SLOW spr round 4 (radius: 10)
[20:04:09 -461044.407996] SLOW spr round 5 (radius: 5)
[20:07:02 -461043.065435] SLOW spr round 6 (radius: 5)
[20:09:31 -461043.065276] SLOW spr round 7 (radius: 10)
[20:11:49 -461043.065217] SLOW spr round 8 (radius: 15)
[20:16:24 -461043.065196] SLOW spr round 9 (radius: 20)
[20:25:20 -461043.065187] SLOW spr round 10 (radius: 25)
[20:36:52 -461043.065184] Model parameter optimization (eps = 0.100000)

[20:37:01] ML tree search #16, logLikelihood: -461042.792201

[20:37:01 -1830095.125173] Initial branch length optimization
[20:37:10 -1559478.950781] Model parameter optimization (eps = 10.000000)
[20:38:00 -1558472.952213] AUTODETECT spr round 1 (radius: 5)
[20:40:21 -1065941.748060] AUTODETECT spr round 2 (radius: 10)
[20:42:54 -760010.475948] AUTODETECT spr round 3 (radius: 15)
[20:45:39 -651689.957797] AUTODETECT spr round 4 (radius: 20)
[20:48:53 -570982.381672] AUTODETECT spr round 5 (radius: 25)
[20:52:28 -538185.878376] SPR radius for FAST iterations: 25 (autodetect)
[20:52:28 -538185.878376] Model parameter optimization (eps = 3.000000)
[20:52:56 -537728.881816] FAST spr round 1 (radius: 25)
[20:55:53 -467363.732350] FAST spr round 2 (radius: 25)
[20:58:14 -461579.902081] FAST spr round 3 (radius: 25)
[21:00:21 -461226.892285] FAST spr round 4 (radius: 25)
[21:02:09 -461203.525032] FAST spr round 5 (radius: 25)
[21:03:51 -461203.522629] Model parameter optimization (eps = 1.000000)
[21:04:06 -461189.716249] SLOW spr round 1 (radius: 5)
[21:06:36 -461043.913164] SLOW spr round 2 (radius: 5)
[21:08:58 -461036.333797] SLOW spr round 3 (radius: 5)
[21:11:11 -461036.332215] SLOW spr round 4 (radius: 10)
[21:13:34 -461036.332029] SLOW spr round 5 (radius: 15)
[21:18:25 -461036.332028] SLOW spr round 6 (radius: 20)
[21:27:08 -461036.332027] SLOW spr round 7 (radius: 25)
[21:38:25 -461036.332027] Model parameter optimization (eps = 0.100000)

[21:38:35] ML tree search #17, logLikelihood: -461036.232323

[21:38:35 -1825392.703555] Initial branch length optimization
[21:38:43 -1548154.283873] Model parameter optimization (eps = 10.000000)
[21:39:25 -1547185.619912] AUTODETECT spr round 1 (radius: 5)
[21:41:33 -1069455.362800] AUTODETECT spr round 2 (radius: 10)
[21:43:59 -751015.172878] AUTODETECT spr round 3 (radius: 15)
[21:46:35 -641584.168341] AUTODETECT spr round 4 (radius: 20)
[21:49:36 -593367.735382] AUTODETECT spr round 5 (radius: 25)
[21:53:50 -552315.581326] SPR radius for FAST iterations: 25 (autodetect)
[21:53:50 -552315.581326] Model parameter optimization (eps = 3.000000)
[21:54:15 -551988.491846] FAST spr round 1 (radius: 25)
[21:57:02 -464533.811319] FAST spr round 2 (radius: 25)
[21:59:05 -461386.381351] FAST spr round 3 (radius: 25)
[22:00:57 -461169.073768] FAST spr round 4 (radius: 25)
[22:02:31 -461169.073176] Model parameter optimization (eps = 1.000000)
[22:02:43 -461164.122907] SLOW spr round 1 (radius: 5)
[22:05:00 -461074.011175] SLOW spr round 2 (radius: 5)
[22:07:49 -461067.045165] SLOW spr round 3 (radius: 5)
[22:09:52 -461066.145316] SLOW spr round 4 (radius: 5)
[22:11:52 -461066.145187] SLOW spr round 5 (radius: 10)
[22:13:57 -461060.631218] SLOW spr round 6 (radius: 5)
[22:16:37 -461058.509311] SLOW spr round 7 (radius: 5)
[22:18:54 -461058.509298] SLOW spr round 8 (radius: 10)
[22:21:03 -461058.064388] SLOW spr round 9 (radius: 5)
[22:23:37 -461058.064278] SLOW spr round 10 (radius: 10)
[22:25:56 -461057.150732] SLOW spr round 11 (radius: 5)
[22:28:28 -461057.127661] SLOW spr round 12 (radius: 10)
[22:30:46 -461056.765423] SLOW spr round 13 (radius: 5)
[22:33:19 -461056.765348] SLOW spr round 14 (radius: 10)
[22:35:36 -461056.765333] SLOW spr round 15 (radius: 15)
[22:39:23 -461056.765329] SLOW spr round 16 (radius: 20)
[22:47:17 -461056.765328] SLOW spr round 17 (radius: 25)
[22:57:20 -461056.765328] Model parameter optimization (eps = 0.100000)

[22:57:28] ML tree search #18, logLikelihood: -461056.372733

[22:57:28 -1829771.673813] Initial branch length optimization
[22:57:36 -1549259.456466] Model parameter optimization (eps = 10.000000)
[22:58:05 -1548188.007428] AUTODETECT spr round 1 (radius: 5)
[23:00:10 -1046292.985897] AUTODETECT spr round 2 (radius: 10)
[23:02:26 -765086.932618] AUTODETECT spr round 3 (radius: 15)
[23:04:59 -587785.410991] AUTODETECT spr round 4 (radius: 20)
[23:08:08 -545756.837988] AUTODETECT spr round 5 (radius: 25)
[23:12:47 -540260.491376] SPR radius for FAST iterations: 25 (autodetect)
[23:12:47 -540260.491376] Model parameter optimization (eps = 3.000000)
[23:13:10 -539933.140795] FAST spr round 1 (radius: 25)
[23:16:24 -465198.889726] FAST spr round 2 (radius: 25)
[23:18:58 -461487.165249] FAST spr round 3 (radius: 25)
[23:23:04 -461268.796181] FAST spr round 4 (radius: 25)
[23:26:33 -461215.700033] FAST spr round 5 (radius: 25)
[23:30:00 -461213.522934] FAST spr round 6 (radius: 25)
[23:32:03 -461213.522113] Model parameter optimization (eps = 1.000000)
[23:32:17 -461186.536105] SLOW spr round 1 (radius: 5)
[23:34:35 -461093.133573] SLOW spr round 2 (radius: 5)
[23:36:41 -461089.996261] SLOW spr round 3 (radius: 5)
[23:38:55 -461089.996105] SLOW spr round 4 (radius: 10)
[23:41:14 -461082.581706] SLOW spr round 5 (radius: 5)
[23:44:01 -461078.909969] SLOW spr round 6 (radius: 5)
[23:46:58 -461078.909965] SLOW spr round 7 (radius: 10)
[23:49:35 -461074.660886] SLOW spr round 8 (radius: 5)
[23:52:25 -461074.660882] SLOW spr round 9 (radius: 10)
[23:54:49 -461074.660881] SLOW spr round 10 (radius: 15)
[23:59:14 -461074.660881] SLOW spr round 11 (radius: 20)
[24:08:03 -461074.660881] SLOW spr round 12 (radius: 25)
[24:19:58 -461074.660880] Model parameter optimization (eps = 0.100000)

[24:20:03] ML tree search #19, logLikelihood: -461074.589754

[24:20:03 -1827473.258167] Initial branch length optimization
[24:20:09 -1548052.240777] Model parameter optimization (eps = 10.000000)
[24:20:42 -1546867.948519] AUTODETECT spr round 1 (radius: 5)
[24:22:55 -1087892.452941] AUTODETECT spr round 2 (radius: 10)
[24:25:41 -796929.426916] AUTODETECT spr round 3 (radius: 15)
[24:28:35 -658180.931361] AUTODETECT spr round 4 (radius: 20)
[24:31:44 -572969.249106] AUTODETECT spr round 5 (radius: 25)
[24:35:13 -553399.229931] SPR radius for FAST iterations: 25 (autodetect)
[24:35:13 -553399.229931] Model parameter optimization (eps = 3.000000)
[24:35:38 -552963.037808] FAST spr round 1 (radius: 25)
[24:38:13 -465352.959277] FAST spr round 2 (radius: 25)
[24:40:10 -461530.613972] FAST spr round 3 (radius: 25)
[24:41:52 -461190.598214] FAST spr round 4 (radius: 25)
[24:43:20 -461189.151150] FAST spr round 5 (radius: 25)
[24:44:47 -461189.150404] Model parameter optimization (eps = 1.000000)
[24:45:07 -461172.898160] SLOW spr round 1 (radius: 5)
[24:47:15 -461069.427311] SLOW spr round 2 (radius: 5)
[24:49:16 -461048.371634] SLOW spr round 3 (radius: 5)
[24:51:12 -461048.371458] SLOW spr round 4 (radius: 10)
[24:53:12 -461047.957977] SLOW spr round 5 (radius: 5)
[24:55:43 -461046.480535] SLOW spr round 6 (radius: 5)
[24:57:54 -461046.480214] SLOW spr round 7 (radius: 10)
[24:59:58 -461046.480160] SLOW spr round 8 (radius: 15)
[25:03:56 -461046.480146] SLOW spr round 9 (radius: 20)
[25:11:40 -461046.480143] SLOW spr round 10 (radius: 25)
[25:21:37 -461046.480142] Model parameter optimization (eps = 0.100000)

[25:21:46] ML tree search #20, logLikelihood: -461046.105182


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.123181,0.213495) (0.114080,0.382357) (0.359641,0.779186) (0.403098,1.612151) 
   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: -461029.538444

AIC score: 926069.076888 / AICc score: 8970129.076888 / BIC score: 936076.386547
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=1087).
         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/P09619/3_mltree/P09619.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/3_mltree/P09619.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/3_mltree/P09619.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P09619/3_mltree/P09619.raxml.log

Analysis started: 14-Jul-2021 12:52:25 / finished: 15-Jul-2021 14:14:12

Elapsed time: 91306.852 seconds

Consumed energy: 7818.365 Wh (= 39 km in an electric car, or 195 km with an e-scooter!)