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 13-Jul-2021 16:23:51 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/2_msa/Q8NET8_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8 --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/Q8NET8/2_msa/Q8NET8_trimmed_msa.fasta
[00:00:00] Loaded alignment with 511 taxa and 1088 sites

WARNING: Sequences tr_H2QBW6_H2QBW6_PANTR_9598 and tr_A0A2R8ZD78_A0A2R8ZD78_PANPA_9597 are exactly identical!
WARNING: Sequences tr_K7CF92_K7CF92_PANTR_9598 and tr_A0A2R9A7Z8_A0A2R9A7Z8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G7PI70_G7PI70_MACFA_9541 and tr_A0A2K5KWZ3_A0A2K5KWZ3_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G7PI70_G7PI70_MACFA_9541 and tr_A0A2K6E6A6_A0A2K6E6A6_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G7PI70_G7PI70_MACFA_9541 and tr_A0A2K5Z7Q7_A0A2K5Z7Q7_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A226MAF5_A0A226MAF5_COLVI_9014 and tr_A0A226NMM8_A0A226NMM8_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2D0QAY8_A0A2D0QAY8_ICTPU_7998 and tr_A0A2D0QDL1_A0A2D0QDL1_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 7

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/Q8NET8/3_mltree/Q8NET8.raxml.reduced.phy

Alignment comprises 1 partitions and 1088 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1088 / 1088
Gaps: 36.26 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8.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 511 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 -665254.143523] Initial branch length optimization
[00:00:03 -545602.787993] Model parameter optimization (eps = 10.000000)
[00:00:33 -544189.998590] AUTODETECT spr round 1 (radius: 5)
[00:01:14 -328948.623585] AUTODETECT spr round 2 (radius: 10)
[00:01:57 -246454.356921] AUTODETECT spr round 3 (radius: 15)
[00:02:47 -202115.389212] AUTODETECT spr round 4 (radius: 20)
[00:03:50 -184347.973796] AUTODETECT spr round 5 (radius: 25)
[00:05:01 -183945.348017] SPR radius for FAST iterations: 25 (autodetect)
[00:05:01 -183945.348017] Model parameter optimization (eps = 3.000000)
[00:05:25 -183103.593994] FAST spr round 1 (radius: 25)
[00:06:19 -167464.051815] FAST spr round 2 (radius: 25)
[00:07:01 -166779.011801] FAST spr round 3 (radius: 25)
[00:07:36 -166702.178827] FAST spr round 4 (radius: 25)
[00:08:06 -166696.135582] FAST spr round 5 (radius: 25)
[00:08:36 -166696.135546] Model parameter optimization (eps = 1.000000)
[00:08:47 -166690.299728] SLOW spr round 1 (radius: 5)
[00:09:37 -166669.679681] SLOW spr round 2 (radius: 5)
[00:10:22 -166669.669407] SLOW spr round 3 (radius: 10)
[00:11:10 -166669.270591] SLOW spr round 4 (radius: 5)
[00:12:12 -166669.266836] SLOW spr round 5 (radius: 10)
[00:13:09 -166669.266645] SLOW spr round 6 (radius: 15)
[00:14:39 -166667.978396] SLOW spr round 7 (radius: 5)
[00:15:45 -166667.006798] SLOW spr round 8 (radius: 5)
[00:16:40 -166667.006558] SLOW spr round 9 (radius: 10)
[00:17:33 -166667.000988] SLOW spr round 10 (radius: 15)
[00:19:07 -166667.000985] SLOW spr round 11 (radius: 20)
[00:21:27 -166667.000983] SLOW spr round 12 (radius: 25)
[00:24:02 -166667.000981] Model parameter optimization (eps = 0.100000)

[00:24:06] ML tree search #1, logLikelihood: -166666.944217

[00:24:06 -657204.741954] Initial branch length optimization
[00:24:09 -536257.250048] Model parameter optimization (eps = 10.000000)
[00:24:35 -534899.888903] AUTODETECT spr round 1 (radius: 5)
[00:25:16 -330003.888598] AUTODETECT spr round 2 (radius: 10)
[00:25:59 -223774.289502] AUTODETECT spr round 3 (radius: 15)
[00:26:47 -193377.122331] AUTODETECT spr round 4 (radius: 20)
[00:27:46 -187007.134093] AUTODETECT spr round 5 (radius: 25)
[00:28:58 -186575.068249] SPR radius for FAST iterations: 25 (autodetect)
[00:28:58 -186575.068249] Model parameter optimization (eps = 3.000000)
[00:29:24 -185738.516202] FAST spr round 1 (radius: 25)
[00:30:16 -167797.780820] FAST spr round 2 (radius: 25)
[00:30:56 -166768.619370] FAST spr round 3 (radius: 25)
[00:31:32 -166739.766032] FAST spr round 4 (radius: 25)
[00:32:04 -166735.782835] FAST spr round 5 (radius: 25)
[00:32:34 -166735.781850] Model parameter optimization (eps = 1.000000)
[00:32:45 -166730.017148] SLOW spr round 1 (radius: 5)
[00:33:35 -166683.016468] SLOW spr round 2 (radius: 5)
[00:34:25 -166667.481514] SLOW spr round 3 (radius: 5)
[00:35:09 -166667.481245] SLOW spr round 4 (radius: 10)
[00:35:58 -166665.570331] SLOW spr round 5 (radius: 5)
[00:37:01 -166664.624006] SLOW spr round 6 (radius: 5)
[00:37:53 -166664.623754] SLOW spr round 7 (radius: 10)
[00:38:45 -166664.459916] SLOW spr round 8 (radius: 5)
[00:39:47 -166662.377470] SLOW spr round 9 (radius: 5)
[00:40:39 -166662.377389] SLOW spr round 10 (radius: 10)
[00:41:30 -166660.527730] SLOW spr round 11 (radius: 5)
[00:42:32 -166660.526542] SLOW spr round 12 (radius: 10)
[00:43:29 -166660.526481] SLOW spr round 13 (radius: 15)
[00:45:00 -166660.526477] SLOW spr round 14 (radius: 20)
[00:47:19 -166660.526476] SLOW spr round 15 (radius: 25)
[00:49:54 -166660.526475] Model parameter optimization (eps = 0.100000)

[00:49:58] ML tree search #2, logLikelihood: -166660.479694

[00:49:58 -666173.479958] Initial branch length optimization
[00:50:01 -544590.606104] Model parameter optimization (eps = 10.000000)
[00:50:40 -543276.093644] AUTODETECT spr round 1 (radius: 5)
[00:51:20 -334687.614921] AUTODETECT spr round 2 (radius: 10)
[00:52:04 -242019.013294] AUTODETECT spr round 3 (radius: 15)
[00:52:59 -193740.985911] AUTODETECT spr round 4 (radius: 20)
[00:54:10 -184715.800586] AUTODETECT spr round 5 (radius: 25)
[00:55:20 -184218.338980] SPR radius for FAST iterations: 25 (autodetect)
[00:55:20 -184218.338980] Model parameter optimization (eps = 3.000000)
[00:55:41 -183414.531358] FAST spr round 1 (radius: 25)
[00:56:36 -167532.010566] FAST spr round 2 (radius: 25)
[00:57:18 -166717.521813] FAST spr round 3 (radius: 25)
[00:57:54 -166699.724140] FAST spr round 4 (radius: 25)
[00:58:27 -166691.439642] FAST spr round 5 (radius: 25)
[00:58:58 -166690.554479] FAST spr round 6 (radius: 25)
[00:59:28 -166689.801437] FAST spr round 7 (radius: 25)
[00:59:58 -166689.800948] Model parameter optimization (eps = 1.000000)
[01:00:07 -166685.923403] SLOW spr round 1 (radius: 5)
[01:00:56 -166664.646425] SLOW spr round 2 (radius: 5)
[01:01:42 -166664.480408] SLOW spr round 3 (radius: 5)
[01:02:27 -166664.460514] SLOW spr round 4 (radius: 10)
[01:03:16 -166663.001342] SLOW spr round 5 (radius: 5)
[01:04:18 -166662.999652] SLOW spr round 6 (radius: 10)
[01:05:16 -166662.999544] SLOW spr round 7 (radius: 15)
[01:06:46 -166662.999532] SLOW spr round 8 (radius: 20)
[01:09:05 -166662.999527] SLOW spr round 9 (radius: 25)
[01:11:40 -166662.999524] Model parameter optimization (eps = 0.100000)

[01:11:44] ML tree search #3, logLikelihood: -166662.905591

[01:11:44 -661719.186101] Initial branch length optimization
[01:11:47 -540375.314722] Model parameter optimization (eps = 10.000000)
[01:12:17 -539250.259656] AUTODETECT spr round 1 (radius: 5)
[01:12:59 -348087.686776] AUTODETECT spr round 2 (radius: 10)
[01:13:42 -248869.656816] AUTODETECT spr round 3 (radius: 15)
[01:14:35 -194079.383669] AUTODETECT spr round 4 (radius: 20)
[01:15:38 -186152.493162] AUTODETECT spr round 5 (radius: 25)
[01:16:51 -185843.645038] SPR radius for FAST iterations: 25 (autodetect)
[01:16:51 -185843.645038] Model parameter optimization (eps = 3.000000)
[01:17:17 -185041.039183] FAST spr round 1 (radius: 25)
[01:18:08 -167450.677049] FAST spr round 2 (radius: 25)
[01:18:51 -166764.208000] FAST spr round 3 (radius: 25)
[01:19:26 -166714.427298] FAST spr round 4 (radius: 25)
[01:20:00 -166693.920121] FAST spr round 5 (radius: 25)
[01:20:31 -166693.918716] Model parameter optimization (eps = 1.000000)
[01:20:40 -166689.700248] SLOW spr round 1 (radius: 5)
[01:21:29 -166658.063475] SLOW spr round 2 (radius: 5)
[01:22:15 -166655.380446] SLOW spr round 3 (radius: 5)
[01:23:00 -166655.379054] SLOW spr round 4 (radius: 10)
[01:23:49 -166655.378419] SLOW spr round 5 (radius: 15)
[01:25:27 -166655.378127] SLOW spr round 6 (radius: 20)
[01:27:44 -166655.377992] SLOW spr round 7 (radius: 25)
[01:30:21 -166655.377930] Model parameter optimization (eps = 0.100000)

[01:30:25] ML tree search #4, logLikelihood: -166655.319567

[01:30:25 -657928.492450] Initial branch length optimization
[01:30:28 -543274.936471] Model parameter optimization (eps = 10.000000)
[01:30:58 -542109.971599] AUTODETECT spr round 1 (radius: 5)
[01:31:39 -331551.284391] AUTODETECT spr round 2 (radius: 10)
[01:32:22 -241675.297219] AUTODETECT spr round 3 (radius: 15)
[01:33:19 -190359.938321] AUTODETECT spr round 4 (radius: 20)
[01:34:20 -185280.405359] AUTODETECT spr round 5 (radius: 25)
[01:35:41 -183335.859435] SPR radius for FAST iterations: 25 (autodetect)
[01:35:41 -183335.859435] Model parameter optimization (eps = 3.000000)
[01:36:02 -182510.119675] FAST spr round 1 (radius: 25)
[01:36:55 -167683.488898] FAST spr round 2 (radius: 25)
[01:37:36 -166751.458418] FAST spr round 3 (radius: 25)
[01:38:12 -166721.499072] FAST spr round 4 (radius: 25)
[01:38:43 -166721.496536] Model parameter optimization (eps = 1.000000)
[01:38:53 -166715.160170] SLOW spr round 1 (radius: 5)
[01:39:44 -166666.251713] SLOW spr round 2 (radius: 5)
[01:40:31 -166661.898449] SLOW spr round 3 (radius: 5)
[01:41:16 -166661.897964] SLOW spr round 4 (radius: 10)
[01:42:04 -166659.568111] SLOW spr round 5 (radius: 5)
[01:43:06 -166659.567953] SLOW spr round 6 (radius: 10)
[01:44:04 -166659.567932] SLOW spr round 7 (radius: 15)
[01:45:36 -166659.567918] SLOW spr round 8 (radius: 20)
[01:47:57 -166659.567906] SLOW spr round 9 (radius: 25)
[01:50:33 -166659.567895] Model parameter optimization (eps = 0.100000)

[01:50:42] ML tree search #5, logLikelihood: -166659.173810

[01:50:42 -664808.950372] Initial branch length optimization
[01:50:45 -548444.808814] Model parameter optimization (eps = 10.000000)
[01:51:19 -546998.345379] AUTODETECT spr round 1 (radius: 5)
[01:52:00 -326365.535739] AUTODETECT spr round 2 (radius: 10)
[01:52:43 -217247.198333] AUTODETECT spr round 3 (radius: 15)
[01:53:31 -191361.834435] AUTODETECT spr round 4 (radius: 20)
[01:54:36 -186645.319899] AUTODETECT spr round 5 (radius: 25)
[01:56:02 -186118.830034] SPR radius for FAST iterations: 25 (autodetect)
[01:56:02 -186118.830034] Model parameter optimization (eps = 3.000000)
[01:56:29 -185236.402761] FAST spr round 1 (radius: 25)
[01:57:25 -167405.758289] FAST spr round 2 (radius: 25)
[01:58:08 -166713.514032] FAST spr round 3 (radius: 25)
[01:58:45 -166683.805180] FAST spr round 4 (radius: 25)
[01:59:17 -166683.064422] FAST spr round 5 (radius: 25)
[01:59:47 -166683.063902] Model parameter optimization (eps = 1.000000)
[01:59:56 -166678.292746] SLOW spr round 1 (radius: 5)
[02:00:46 -166662.452992] SLOW spr round 2 (radius: 5)
[02:01:34 -166657.560337] SLOW spr round 3 (radius: 5)
[02:02:19 -166657.558598] SLOW spr round 4 (radius: 10)
[02:03:07 -166656.232702] SLOW spr round 5 (radius: 5)
[02:04:09 -166655.426230] SLOW spr round 6 (radius: 5)
[02:05:02 -166655.425850] SLOW spr round 7 (radius: 10)
[02:05:53 -166655.420469] SLOW spr round 8 (radius: 15)
[02:07:28 -166655.420452] SLOW spr round 9 (radius: 20)
[02:09:48 -166655.420445] SLOW spr round 10 (radius: 25)
[02:12:23 -166655.420441] Model parameter optimization (eps = 0.100000)

[02:12:27] ML tree search #6, logLikelihood: -166655.352623

[02:12:27 -664882.726934] Initial branch length optimization
[02:12:30 -542968.033625] Model parameter optimization (eps = 10.000000)
[02:13:01 -541630.425281] AUTODETECT spr round 1 (radius: 5)
[02:13:42 -336486.436100] AUTODETECT spr round 2 (radius: 10)
[02:14:26 -237463.146316] AUTODETECT spr round 3 (radius: 15)
[02:15:21 -198899.505126] AUTODETECT spr round 4 (radius: 20)
[02:16:29 -190263.493818] AUTODETECT spr round 5 (radius: 25)
[02:17:57 -186910.876620] SPR radius for FAST iterations: 25 (autodetect)
[02:17:57 -186910.876620] Model parameter optimization (eps = 3.000000)
[02:18:23 -186024.183053] FAST spr round 1 (radius: 25)
[02:19:17 -167842.772098] FAST spr round 2 (radius: 25)
[02:20:03 -166819.277559] FAST spr round 3 (radius: 25)
[02:20:42 -166723.635226] FAST spr round 4 (radius: 25)
[02:21:16 -166704.731920] FAST spr round 5 (radius: 25)
[02:21:46 -166704.731872] Model parameter optimization (eps = 1.000000)
[02:22:01 -166693.444474] SLOW spr round 1 (radius: 5)
[02:22:53 -166661.780702] SLOW spr round 2 (radius: 5)
[02:23:39 -166660.835403] SLOW spr round 3 (radius: 5)
[02:24:24 -166660.833934] SLOW spr round 4 (radius: 10)
[02:25:13 -166657.553689] SLOW spr round 5 (radius: 5)
[02:26:16 -166655.656308] SLOW spr round 6 (radius: 5)
[02:27:10 -166655.655896] SLOW spr round 7 (radius: 10)
[02:28:01 -166655.650536] SLOW spr round 8 (radius: 15)
[02:29:38 -166655.650533] SLOW spr round 9 (radius: 20)
[02:31:59 -166655.650532] SLOW spr round 10 (radius: 25)
[02:34:36 -166655.650530] Model parameter optimization (eps = 0.100000)

[02:34:39] ML tree search #7, logLikelihood: -166655.645622

[02:34:39 -659125.404558] Initial branch length optimization
[02:34:41 -541006.291382] Model parameter optimization (eps = 10.000000)
[02:35:07 -539623.425226] AUTODETECT spr round 1 (radius: 5)
[02:35:48 -338821.380040] AUTODETECT spr round 2 (radius: 10)
[02:36:31 -235635.336915] AUTODETECT spr round 3 (radius: 15)
[02:37:25 -194381.653589] AUTODETECT spr round 4 (radius: 20)
[02:38:25 -187232.969272] AUTODETECT spr round 5 (radius: 25)
[02:39:30 -186062.386352] SPR radius for FAST iterations: 25 (autodetect)
[02:39:30 -186062.386352] Model parameter optimization (eps = 3.000000)
[02:39:53 -185214.017147] FAST spr round 1 (radius: 25)
[02:40:47 -167804.600291] FAST spr round 2 (radius: 25)
[02:41:29 -166730.746904] FAST spr round 3 (radius: 25)
[02:42:05 -166704.482375] FAST spr round 4 (radius: 25)
[02:42:36 -166702.084725] FAST spr round 5 (radius: 25)
[02:43:07 -166702.084712] Model parameter optimization (eps = 1.000000)
[02:43:17 -166694.729750] SLOW spr round 1 (radius: 5)
[02:44:07 -166664.220602] SLOW spr round 2 (radius: 5)
[02:44:53 -166660.333529] SLOW spr round 3 (radius: 5)
[02:45:38 -166660.332927] SLOW spr round 4 (radius: 10)
[02:46:26 -166660.332835] SLOW spr round 5 (radius: 15)
[02:48:03 -166660.332805] SLOW spr round 6 (radius: 20)
[02:50:18 -166660.332792] SLOW spr round 7 (radius: 25)
[02:52:53 -166660.332785] Model parameter optimization (eps = 0.100000)

[02:53:04] ML tree search #8, logLikelihood: -166659.841801

[02:53:04 -654077.216818] Initial branch length optimization
[02:53:06 -534792.869249] Model parameter optimization (eps = 10.000000)
[02:53:37 -533469.558619] AUTODETECT spr round 1 (radius: 5)
[02:54:17 -331689.334192] AUTODETECT spr round 2 (radius: 10)
[02:55:02 -230975.108896] AUTODETECT spr round 3 (radius: 15)
[02:55:53 -194068.312947] AUTODETECT spr round 4 (radius: 20)
[02:56:56 -185924.634908] AUTODETECT spr round 5 (radius: 25)
[02:58:02 -185204.752425] SPR radius for FAST iterations: 25 (autodetect)
[02:58:02 -185204.752425] Model parameter optimization (eps = 3.000000)
[02:58:28 -184410.194061] FAST spr round 1 (radius: 25)
[02:59:20 -167528.367437] FAST spr round 2 (radius: 25)
[03:00:03 -166743.050919] FAST spr round 3 (radius: 25)
[03:00:40 -166707.608388] FAST spr round 4 (radius: 25)
[03:01:11 -166703.579280] FAST spr round 5 (radius: 25)
[03:01:42 -166700.689658] FAST spr round 6 (radius: 25)
[03:02:12 -166700.688885] Model parameter optimization (eps = 1.000000)
[03:02:20 -166697.285928] SLOW spr round 1 (radius: 5)
[03:03:09 -166657.104593] SLOW spr round 2 (radius: 5)
[03:03:55 -166657.101775] SLOW spr round 3 (radius: 10)
[03:04:43 -166653.522422] SLOW spr round 4 (radius: 5)
[03:05:45 -166652.617345] SLOW spr round 5 (radius: 5)
[03:06:37 -166652.617071] SLOW spr round 6 (radius: 10)
[03:07:28 -166652.611636] SLOW spr round 7 (radius: 15)
[03:09:03 -166652.611635] SLOW spr round 8 (radius: 20)
[03:11:21 -166652.611634] SLOW spr round 9 (radius: 25)
[03:13:56 -166652.611634] Model parameter optimization (eps = 0.100000)

[03:14:07] ML tree search #9, logLikelihood: -166652.225137

[03:14:07 -654632.943808] Initial branch length optimization
[03:14:10 -538665.829890] Model parameter optimization (eps = 10.000000)
[03:14:38 -537328.133010] AUTODETECT spr round 1 (radius: 5)
[03:15:18 -329976.550008] AUTODETECT spr round 2 (radius: 10)
[03:16:03 -237506.561457] AUTODETECT spr round 3 (radius: 15)
[03:16:56 -202845.766370] AUTODETECT spr round 4 (radius: 20)
[03:18:06 -188673.680862] AUTODETECT spr round 5 (radius: 25)
[03:19:11 -186717.179679] SPR radius for FAST iterations: 25 (autodetect)
[03:19:11 -186717.179679] Model parameter optimization (eps = 3.000000)
[03:19:34 -185943.094515] FAST spr round 1 (radius: 25)
[03:20:27 -167747.693910] FAST spr round 2 (radius: 25)
[03:21:10 -166801.734097] FAST spr round 3 (radius: 25)
[03:21:48 -166762.737752] FAST spr round 4 (radius: 25)
[03:22:23 -166745.406986] FAST spr round 5 (radius: 25)
[03:22:56 -166738.874357] FAST spr round 6 (radius: 25)
[03:23:27 -166737.211768] FAST spr round 7 (radius: 25)
[03:23:57 -166737.211633] Model parameter optimization (eps = 1.000000)
[03:24:09 -166730.307176] SLOW spr round 1 (radius: 5)
[03:24:58 -166688.105613] SLOW spr round 2 (radius: 5)
[03:25:44 -166686.315184] SLOW spr round 3 (radius: 5)
[03:26:28 -166686.314825] SLOW spr round 4 (radius: 10)
[03:27:15 -166684.997309] SLOW spr round 5 (radius: 5)
[03:28:17 -166684.036023] SLOW spr round 6 (radius: 5)
[03:29:09 -166684.035804] SLOW spr round 7 (radius: 10)
[03:30:00 -166684.030399] SLOW spr round 8 (radius: 15)
[03:31:35 -166684.030397] SLOW spr round 9 (radius: 20)
[03:33:53 -166684.030396] SLOW spr round 10 (radius: 25)
[03:36:29 -166684.030395] Model parameter optimization (eps = 0.100000)

[03:36:33] ML tree search #10, logLikelihood: -166683.959349

[03:36:33 -656698.820377] Initial branch length optimization
[03:36:37 -541792.045217] Model parameter optimization (eps = 10.000000)
[03:37:06 -540415.149381] AUTODETECT spr round 1 (radius: 5)
[03:37:47 -332852.104240] AUTODETECT spr round 2 (radius: 10)
[03:38:31 -237069.644921] AUTODETECT spr round 3 (radius: 15)
[03:39:26 -197192.963082] AUTODETECT spr round 4 (radius: 20)
[03:40:29 -187682.120568] AUTODETECT spr round 5 (radius: 25)
[03:41:36 -187529.423796] SPR radius for FAST iterations: 25 (autodetect)
[03:41:36 -187529.423796] Model parameter optimization (eps = 3.000000)
[03:42:00 -186688.293881] FAST spr round 1 (radius: 25)
[03:42:52 -167420.302083] FAST spr round 2 (radius: 25)
[03:43:37 -166720.448257] FAST spr round 3 (radius: 25)
[03:44:12 -166701.231113] FAST spr round 4 (radius: 25)
[03:44:44 -166691.013395] FAST spr round 5 (radius: 25)
[03:45:13 -166691.013322] Model parameter optimization (eps = 1.000000)
[03:45:23 -166687.452855] SLOW spr round 1 (radius: 5)
[03:46:12 -166662.949182] SLOW spr round 2 (radius: 5)
[03:46:59 -166658.861999] SLOW spr round 3 (radius: 5)
[03:47:44 -166658.861904] SLOW spr round 4 (radius: 10)
[03:48:32 -166658.861892] SLOW spr round 5 (radius: 15)
[03:50:10 -166658.861888] SLOW spr round 6 (radius: 20)
[03:52:29 -166658.861886] SLOW spr round 7 (radius: 25)
[03:55:04 -166658.861885] Model parameter optimization (eps = 0.100000)

[03:55:13] ML tree search #11, logLikelihood: -166658.677700

[03:55:13 -653875.860475] Initial branch length optimization
[03:55:16 -539174.325806] Model parameter optimization (eps = 10.000000)
[03:55:50 -537864.004636] AUTODETECT spr round 1 (radius: 5)
[03:56:30 -322146.469700] AUTODETECT spr round 2 (radius: 10)
[03:57:13 -227468.911838] AUTODETECT spr round 3 (radius: 15)
[03:58:02 -200133.107461] AUTODETECT spr round 4 (radius: 20)
[03:59:11 -190663.067231] AUTODETECT spr round 5 (radius: 25)
[04:00:36 -188878.779027] SPR radius for FAST iterations: 25 (autodetect)
[04:00:36 -188878.779027] Model parameter optimization (eps = 3.000000)
[04:00:59 -188107.839314] FAST spr round 1 (radius: 25)
[04:02:01 -167516.484681] FAST spr round 2 (radius: 25)
[04:02:47 -166734.632251] FAST spr round 3 (radius: 25)
[04:03:27 -166687.396549] FAST spr round 4 (radius: 25)
[04:03:59 -166685.695779] FAST spr round 5 (radius: 25)
[04:04:29 -166680.427608] FAST spr round 6 (radius: 25)
[04:05:00 -166680.425840] Model parameter optimization (eps = 1.000000)
[04:05:11 -166673.967133] SLOW spr round 1 (radius: 5)
[04:06:02 -166656.824750] SLOW spr round 2 (radius: 5)
[04:06:49 -166655.205525] SLOW spr round 3 (radius: 5)
[04:07:34 -166655.203954] SLOW spr round 4 (radius: 10)
[04:08:22 -166654.651554] SLOW spr round 5 (radius: 5)
[04:09:24 -166654.651370] SLOW spr round 6 (radius: 10)
[04:10:22 -166654.651366] SLOW spr round 7 (radius: 15)
[04:11:51 -166654.651365] SLOW spr round 8 (radius: 20)
[04:14:10 -166654.651364] SLOW spr round 9 (radius: 25)
[04:16:44 -166654.651363] Model parameter optimization (eps = 0.100000)

[04:16:49] ML tree search #12, logLikelihood: -166654.570740

[04:16:49 -655884.904132] Initial branch length optimization
[04:16:51 -542227.781931] Model parameter optimization (eps = 10.000000)
[04:17:20 -540845.455619] AUTODETECT spr round 1 (radius: 5)
[04:18:00 -319662.357608] AUTODETECT spr round 2 (radius: 10)
[04:18:45 -223905.381844] AUTODETECT spr round 3 (radius: 15)
[04:19:35 -191903.547006] AUTODETECT spr round 4 (radius: 20)
[04:20:37 -183181.631674] AUTODETECT spr round 5 (radius: 25)
[04:21:51 -182868.699979] SPR radius for FAST iterations: 25 (autodetect)
[04:21:51 -182868.699979] Model parameter optimization (eps = 3.000000)
[04:22:14 -182037.069824] FAST spr round 1 (radius: 25)
[04:23:09 -167282.317831] FAST spr round 2 (radius: 25)
[04:23:51 -166724.287453] FAST spr round 3 (radius: 25)
[04:24:27 -166699.609460] FAST spr round 4 (radius: 25)
[04:24:58 -166695.366500] FAST spr round 5 (radius: 25)
[04:25:29 -166695.365588] Model parameter optimization (eps = 1.000000)
[04:25:40 -166686.942601] SLOW spr round 1 (radius: 5)
[04:26:29 -166666.351326] SLOW spr round 2 (radius: 5)
[04:27:16 -166664.793141] SLOW spr round 3 (radius: 5)
[04:28:01 -166664.791467] SLOW spr round 4 (radius: 10)
[04:28:48 -166664.791122] SLOW spr round 5 (radius: 15)
[04:30:26 -166663.493373] SLOW spr round 6 (radius: 5)
[04:31:33 -166662.546949] SLOW spr round 7 (radius: 5)
[04:32:27 -166662.546696] SLOW spr round 8 (radius: 10)
[04:33:20 -166662.541376] SLOW spr round 9 (radius: 15)
[04:34:54 -166662.541374] SLOW spr round 10 (radius: 20)
[04:37:14 -166662.541373] SLOW spr round 11 (radius: 25)
[04:39:49 -166662.541372] Model parameter optimization (eps = 0.100000)

[04:39:53] ML tree search #13, logLikelihood: -166662.480554

[04:39:53 -652679.376750] Initial branch length optimization
[04:39:56 -531409.585651] Model parameter optimization (eps = 10.000000)
[04:40:29 -530282.368450] AUTODETECT spr round 1 (radius: 5)
[04:41:10 -333325.449960] AUTODETECT spr round 2 (radius: 10)
[04:41:53 -249604.884079] AUTODETECT spr round 3 (radius: 15)
[04:42:43 -201659.686211] AUTODETECT spr round 4 (radius: 20)
[04:43:43 -189938.706715] AUTODETECT spr round 5 (radius: 25)
[04:44:54 -186578.535661] SPR radius for FAST iterations: 25 (autodetect)
[04:44:54 -186578.535661] Model parameter optimization (eps = 3.000000)
[04:45:16 -185730.467982] FAST spr round 1 (radius: 25)
[04:46:11 -167565.667832] FAST spr round 2 (radius: 25)
[04:46:55 -166748.431709] FAST spr round 3 (radius: 25)
[04:47:31 -166711.797465] FAST spr round 4 (radius: 25)
[04:48:02 -166710.431110] FAST spr round 5 (radius: 25)
[04:48:32 -166710.429744] Model parameter optimization (eps = 1.000000)
[04:48:43 -166700.781294] SLOW spr round 1 (radius: 5)
[04:49:32 -166666.296291] SLOW spr round 2 (radius: 5)
[04:50:20 -166664.118136] SLOW spr round 3 (radius: 5)
[04:51:05 -166664.117048] SLOW spr round 4 (radius: 10)
[04:51:53 -166662.010307] SLOW spr round 5 (radius: 5)
[04:52:56 -166661.248855] SLOW spr round 6 (radius: 5)
[04:53:48 -166661.248742] SLOW spr round 7 (radius: 10)
[04:54:39 -166659.974619] SLOW spr round 8 (radius: 5)
[04:55:40 -166658.978669] SLOW spr round 9 (radius: 5)
[04:56:32 -166658.978378] SLOW spr round 10 (radius: 10)
[04:57:23 -166658.972887] SLOW spr round 11 (radius: 15)
[04:58:58 -166658.972885] SLOW spr round 12 (radius: 20)
[05:01:17 -166658.972885] SLOW spr round 13 (radius: 25)
[05:03:52 -166658.972885] Model parameter optimization (eps = 0.100000)

[05:04:02] ML tree search #14, logLikelihood: -166658.295614

[05:04:02 -664275.159258] Initial branch length optimization
[05:04:05 -547546.087625] Model parameter optimization (eps = 10.000000)
[05:04:31 -546000.768897] AUTODETECT spr round 1 (radius: 5)
[05:05:13 -337587.731881] AUTODETECT spr round 2 (radius: 10)
[05:05:57 -246449.087666] AUTODETECT spr round 3 (radius: 15)
[05:06:54 -197970.538650] AUTODETECT spr round 4 (radius: 20)
[05:07:53 -188842.519189] AUTODETECT spr round 5 (radius: 25)
[05:09:02 -187860.569472] SPR radius for FAST iterations: 25 (autodetect)
[05:09:02 -187860.569472] Model parameter optimization (eps = 3.000000)
[05:09:26 -187095.879139] FAST spr round 1 (radius: 25)
[05:10:17 -167873.803830] FAST spr round 2 (radius: 25)
[05:11:01 -166811.078571] FAST spr round 3 (radius: 25)
[05:11:37 -166718.881331] FAST spr round 4 (radius: 25)
[05:12:10 -166701.444898] FAST spr round 5 (radius: 25)
[05:12:41 -166701.444834] Model parameter optimization (eps = 1.000000)
[05:12:53 -166692.003804] SLOW spr round 1 (radius: 5)
[05:13:42 -166667.208840] SLOW spr round 2 (radius: 5)
[05:14:28 -166666.002808] SLOW spr round 3 (radius: 5)
[05:15:13 -166666.002611] SLOW spr round 4 (radius: 10)
[05:16:01 -166664.519733] SLOW spr round 5 (radius: 5)
[05:17:03 -166663.618342] SLOW spr round 6 (radius: 5)
[05:17:55 -166663.618100] SLOW spr round 7 (radius: 10)
[05:18:46 -166663.612866] SLOW spr round 8 (radius: 15)
[05:20:19 -166663.612861] SLOW spr round 9 (radius: 20)
[05:22:35 -166663.612859] SLOW spr round 10 (radius: 25)
[05:25:10 -166663.612857] Model parameter optimization (eps = 0.100000)

[05:25:14] ML tree search #15, logLikelihood: -166663.571577

[05:25:14 -653156.331513] Initial branch length optimization
[05:25:18 -539900.186208] Model parameter optimization (eps = 10.000000)
[05:25:50 -538690.789636] AUTODETECT spr round 1 (radius: 5)
[05:26:31 -329487.551073] AUTODETECT spr round 2 (radius: 10)
[05:27:13 -234052.249849] AUTODETECT spr round 3 (radius: 15)
[05:28:05 -199559.307474] AUTODETECT spr round 4 (radius: 20)
[05:29:10 -186362.985590] AUTODETECT spr round 5 (radius: 25)
[05:30:15 -185548.023340] SPR radius for FAST iterations: 25 (autodetect)
[05:30:15 -185548.023340] Model parameter optimization (eps = 3.000000)
[05:30:37 -184819.057046] FAST spr round 1 (radius: 25)
[05:31:35 -167105.963617] FAST spr round 2 (radius: 25)
[05:32:17 -166743.801680] FAST spr round 3 (radius: 25)
[05:32:54 -166720.034783] FAST spr round 4 (radius: 25)
[05:33:25 -166718.434798] FAST spr round 5 (radius: 25)
[05:33:55 -166718.434421] Model parameter optimization (eps = 1.000000)
[05:34:06 -166714.058168] SLOW spr round 1 (radius: 5)
[05:34:56 -166678.386454] SLOW spr round 2 (radius: 5)
[05:35:43 -166677.164581] SLOW spr round 3 (radius: 5)
[05:36:28 -166677.162103] SLOW spr round 4 (radius: 10)
[05:37:17 -166670.798901] SLOW spr round 5 (radius: 5)
[05:38:20 -166664.691651] SLOW spr round 6 (radius: 5)
[05:39:13 -166658.205399] SLOW spr round 7 (radius: 5)
[05:40:01 -166657.223007] SLOW spr round 8 (radius: 5)
[05:40:47 -166657.222935] SLOW spr round 9 (radius: 10)
[05:41:35 -166657.217518] SLOW spr round 10 (radius: 15)
[05:43:13 -166657.217515] SLOW spr round 11 (radius: 20)
[05:45:30 -166657.217513] SLOW spr round 12 (radius: 25)
[05:48:06 -166657.217512] Model parameter optimization (eps = 0.100000)

[05:48:13] ML tree search #16, logLikelihood: -166656.972921

[05:48:13 -660241.793745] Initial branch length optimization
[05:48:16 -539728.943003] Model parameter optimization (eps = 10.000000)
[05:48:53 -538435.330916] AUTODETECT spr round 1 (radius: 5)
[05:49:33 -325228.405311] AUTODETECT spr round 2 (radius: 10)
[05:50:15 -240564.485482] AUTODETECT spr round 3 (radius: 15)
[05:51:08 -196633.342838] AUTODETECT spr round 4 (radius: 20)
[05:52:13 -186165.464028] AUTODETECT spr round 5 (radius: 25)
[05:53:35 -186029.748607] SPR radius for FAST iterations: 25 (autodetect)
[05:53:35 -186029.748607] Model parameter optimization (eps = 3.000000)
[05:53:56 -185215.490106] FAST spr round 1 (radius: 25)
[05:54:48 -167549.525851] FAST spr round 2 (radius: 25)
[05:55:32 -166726.628521] FAST spr round 3 (radius: 25)
[05:56:08 -166692.770575] FAST spr round 4 (radius: 25)
[05:56:38 -166691.428204] FAST spr round 5 (radius: 25)
[05:57:08 -166691.428197] Model parameter optimization (eps = 1.000000)
[05:57:19 -166686.351291] SLOW spr round 1 (radius: 5)
[05:58:08 -166661.721710] SLOW spr round 2 (radius: 5)
[05:58:54 -166660.818498] SLOW spr round 3 (radius: 5)
[05:59:39 -166660.818468] SLOW spr round 4 (radius: 10)
[06:00:26 -166659.057395] SLOW spr round 5 (radius: 5)
[06:01:29 -166658.127487] SLOW spr round 6 (radius: 5)
[06:02:21 -166658.127198] SLOW spr round 7 (radius: 10)
[06:03:12 -166658.121744] SLOW spr round 8 (radius: 15)
[06:04:47 -166658.121742] SLOW spr round 9 (radius: 20)
[06:07:06 -166658.121740] SLOW spr round 10 (radius: 25)
[06:09:43 -166658.121739] Model parameter optimization (eps = 0.100000)

[06:09:48] ML tree search #17, logLikelihood: -166658.037355

[06:09:48 -662760.419564] Initial branch length optimization
[06:09:51 -547048.554073] Model parameter optimization (eps = 10.000000)
[06:10:25 -545791.015511] AUTODETECT spr round 1 (radius: 5)
[06:11:04 -336658.892939] AUTODETECT spr round 2 (radius: 10)
[06:11:48 -232591.049832] AUTODETECT spr round 3 (radius: 15)
[06:12:37 -205700.636752] AUTODETECT spr round 4 (radius: 20)
[06:13:43 -187159.880501] AUTODETECT spr round 5 (radius: 25)
[06:15:06 -185453.096711] SPR radius for FAST iterations: 25 (autodetect)
[06:15:06 -185453.096711] Model parameter optimization (eps = 3.000000)
[06:15:32 -184673.904070] FAST spr round 1 (radius: 25)
[06:16:25 -168581.355463] FAST spr round 2 (radius: 25)
[06:17:11 -166728.587023] FAST spr round 3 (radius: 25)
[06:17:47 -166711.943300] FAST spr round 4 (radius: 25)
[06:18:20 -166697.294567] FAST spr round 5 (radius: 25)
[06:18:51 -166694.210587] FAST spr round 6 (radius: 25)
[06:19:22 -166688.707599] FAST spr round 7 (radius: 25)
[06:19:53 -166688.707594] Model parameter optimization (eps = 1.000000)
[06:20:04 -166681.023978] SLOW spr round 1 (radius: 5)
[06:20:55 -166659.674248] SLOW spr round 2 (radius: 5)
[06:21:42 -166658.436562] SLOW spr round 3 (radius: 5)
[06:22:27 -166658.434502] SLOW spr round 4 (radius: 10)
[06:23:15 -166656.126241] SLOW spr round 5 (radius: 5)
[06:24:17 -166656.125828] SLOW spr round 6 (radius: 10)
[06:25:14 -166656.125737] SLOW spr round 7 (radius: 15)
[06:26:45 -166654.727504] SLOW spr round 8 (radius: 5)
[06:27:51 -166653.870764] SLOW spr round 9 (radius: 5)
[06:28:45 -166653.870466] SLOW spr round 10 (radius: 10)
[06:29:38 -166653.865183] SLOW spr round 11 (radius: 15)
[06:31:12 -166653.865182] SLOW spr round 12 (radius: 20)
[06:33:31 -166653.865181] SLOW spr round 13 (radius: 25)
[06:36:07 -166653.865180] Model parameter optimization (eps = 0.100000)

[06:36:10] ML tree search #18, logLikelihood: -166653.846565

[06:36:10 -661183.242946] Initial branch length optimization
[06:36:13 -544576.059081] Model parameter optimization (eps = 10.000000)
[06:36:40 -543317.537892] AUTODETECT spr round 1 (radius: 5)
[06:37:20 -330970.242954] AUTODETECT spr round 2 (radius: 10)
[06:38:04 -229294.877598] AUTODETECT spr round 3 (radius: 15)
[06:39:00 -195380.872114] AUTODETECT spr round 4 (radius: 20)
[06:40:06 -188050.460869] AUTODETECT spr round 5 (radius: 25)
[06:41:29 -187805.661574] SPR radius for FAST iterations: 25 (autodetect)
[06:41:29 -187805.661574] Model parameter optimization (eps = 3.000000)
[06:41:49 -186723.237742] FAST spr round 1 (radius: 25)
[06:42:44 -167966.234782] FAST spr round 2 (radius: 25)
[06:43:27 -166815.302103] FAST spr round 3 (radius: 25)
[06:44:06 -166727.818221] FAST spr round 4 (radius: 25)
[06:44:37 -166727.800686] Model parameter optimization (eps = 1.000000)
[06:44:51 -166716.626548] SLOW spr round 1 (radius: 5)
[06:45:43 -166667.256248] SLOW spr round 2 (radius: 5)
[06:46:31 -166663.044564] SLOW spr round 3 (radius: 5)
[06:47:16 -166663.044491] SLOW spr round 4 (radius: 10)
[06:48:05 -166659.322446] SLOW spr round 5 (radius: 5)
[06:49:08 -166658.315030] SLOW spr round 6 (radius: 5)
[06:50:01 -166658.302490] SLOW spr round 7 (radius: 10)
[06:50:52 -166658.276669] SLOW spr round 8 (radius: 15)
[06:52:28 -166658.275666] SLOW spr round 9 (radius: 20)
[06:54:47 -166658.274864] SLOW spr round 10 (radius: 25)
[06:57:22 -166658.274061] Model parameter optimization (eps = 0.100000)

[06:57:26] ML tree search #19, logLikelihood: -166658.235600

[06:57:27 -664882.976616] Initial branch length optimization
[06:57:29 -548343.974403] Model parameter optimization (eps = 10.000000)
[06:58:01 -547242.340341] AUTODETECT spr round 1 (radius: 5)
[06:58:42 -327056.828623] AUTODETECT spr round 2 (radius: 10)
[06:59:25 -236703.122088] AUTODETECT spr round 3 (radius: 15)
[07:00:14 -200387.154530] AUTODETECT spr round 4 (radius: 20)
[07:01:13 -191177.269232] AUTODETECT spr round 5 (radius: 25)
[07:02:15 -190247.189286] SPR radius for FAST iterations: 25 (autodetect)
[07:02:15 -190247.189286] Model parameter optimization (eps = 3.000000)
[07:02:45 -189388.568340] FAST spr round 1 (radius: 25)
[07:03:38 -167426.956299] FAST spr round 2 (radius: 25)
[07:04:18 -166737.422415] FAST spr round 3 (radius: 25)
[07:04:55 -166710.620683] FAST spr round 4 (radius: 25)
[07:05:26 -166707.980737] FAST spr round 5 (radius: 25)
[07:05:56 -166707.979990] Model parameter optimization (eps = 1.000000)
[07:06:04 -166704.886217] SLOW spr round 1 (radius: 5)
[07:06:53 -166670.032817] SLOW spr round 2 (radius: 5)
[07:07:41 -166664.188073] SLOW spr round 3 (radius: 5)
[07:08:27 -166658.422643] SLOW spr round 4 (radius: 5)
[07:09:12 -166658.422466] SLOW spr round 5 (radius: 10)
[07:10:00 -166656.485555] SLOW spr round 6 (radius: 5)
[07:11:03 -166655.595481] SLOW spr round 7 (radius: 5)
[07:11:55 -166655.595261] SLOW spr round 8 (radius: 10)
[07:12:46 -166655.589774] SLOW spr round 9 (radius: 15)
[07:14:22 -166655.589773] SLOW spr round 10 (radius: 20)
[07:16:39 -166655.589772] SLOW spr round 11 (radius: 25)
[07:19:14 -166655.589771] Model parameter optimization (eps = 0.100000)

[07:19:18] ML tree search #20, logLikelihood: -166655.501919


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.168855,0.448297) (0.100191,0.995887) (0.362100,0.608360) (0.368853,1.638148) 
   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: -166652.225137

AIC score: 335354.450275 / AICc score: 369278.643823 / BIC score: 340471.349113
Free parameters (model + branch lengths): 1025

Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NET8/3_mltree/Q8NET8.raxml.log

Analysis started: 13-Jul-2021 16:23:51 / finished: 13-Jul-2021 23:43:10

Elapsed time: 26358.674 seconds

Consumed energy: 2371.527 Wh (= 12 km in an electric car, or 59 km with an e-scooter!)