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 6258R CPU @ 2.70GHz, 56 cores, 187 GB RAM

RAxML-NG was called at 04-Jun-2021 17:15:01 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/2_msa/Q6ZWL3_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3 --seed 2 --threads 7 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (7 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/2_msa/Q6ZWL3_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 485 sites

WARNING: Sequences tr_B4R344_B4R344_DROSI_7240 and sp_Q9VYY4_C4G15_DROME_7227 are exactly identical!
WARNING: Sequences tr_B4R344_B4R344_DROSI_7240 and tr_B4IK20_B4IK20_DROSE_7238 are exactly identical!
WARNING: Sequences tr_Q28WR0_Q28WR0_DROPS_46245 and tr_B4HCS1_B4HCS1_DROPE_7234 are exactly identical!
WARNING: Sequences tr_Q29JM1_Q29JM1_DROPS_46245 and tr_B4H385_B4H385_DROPE_7234 are exactly identical!
WARNING: Sequences tr_A0A2I3S036_A0A2I3S036_PANTR_9598 and sp_P78329_CP4F2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2I3S036_A0A2I3S036_PANTR_9598 and tr_A0A2R8ZQU9_A0A2R8ZQU9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6PJB6_F6PJB6_MACMU_9544 and tr_A0A2K6EAW2_A0A2K6EAW2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V1CUR6_A0A0V1CUR6_TRIBR_45882 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V0W725_A0A0V0W725_9BILA_92179 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V0VTM1_A0A0V0VTM1_9BILA_181606 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V1L9X3_A0A0V1L9X3_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V1A4K6_A0A0V1A4K6_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V1P5H7_A0A0V1P5H7_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V0SML7_A0A0V0SML7_9BILA_6336 and tr_A0A0V0U3T1_A0A0V0U3T1_9BILA_144512 are exactly identical!
WARNING: Duplicate sequences found: 14

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.reduced.phy

Alignment comprises 1 partitions and 485 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 485 / 485
Gaps: 5.73 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.rba

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

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

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 70 / 5600
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -920684.610771] Initial branch length optimization
[00:00:02 -796721.383488] Model parameter optimization (eps = 10.000000)
[00:00:32 -793868.292912] AUTODETECT spr round 1 (radius: 5)
[00:02:19 -662733.565036] AUTODETECT spr round 2 (radius: 10)
[00:04:30 -509955.420581] AUTODETECT spr round 3 (radius: 15)
[00:06:56 -442698.044350] AUTODETECT spr round 4 (radius: 20)
[00:09:57 -427906.006151] AUTODETECT spr round 5 (radius: 25)
[00:13:50 -427005.987267] SPR radius for FAST iterations: 25 (autodetect)
[00:13:50 -427005.987267] Model parameter optimization (eps = 3.000000)
[00:14:07 -426858.669580] FAST spr round 1 (radius: 25)
[00:17:36 -380401.918564] FAST spr round 2 (radius: 25)
[00:20:03 -378697.387635] FAST spr round 3 (radius: 25)
[00:22:05 -378589.769327] FAST spr round 4 (radius: 25)
[00:23:52 -378566.104173] FAST spr round 5 (radius: 25)
[00:25:31 -378566.103888] Model parameter optimization (eps = 1.000000)
[00:25:46 -378560.297172] SLOW spr round 1 (radius: 5)
[00:28:14 -378431.610622] SLOW spr round 2 (radius: 5)
[00:30:26 -378426.632638] SLOW spr round 3 (radius: 5)
[00:32:28 -378426.632561] SLOW spr round 4 (radius: 10)
[00:34:36 -378424.765689] SLOW spr round 5 (radius: 5)
[00:37:08 -378421.994624] SLOW spr round 6 (radius: 5)
[00:39:26 -378421.994309] SLOW spr round 7 (radius: 10)
[00:41:41 -378421.994306] SLOW spr round 8 (radius: 15)
[00:46:15 -378421.994306] SLOW spr round 9 (radius: 20)
[00:53:10 -378421.994306] SLOW spr round 10 (radius: 25)
[01:01:16 -378421.994306] Model parameter optimization (eps = 0.100000)

[01:01:23] ML tree search #1, logLikelihood: -378421.883004

[01:01:23 -921354.405086] Initial branch length optimization
[01:01:26 -796090.824249] Model parameter optimization (eps = 10.000000)
[01:01:53 -793346.854374] AUTODETECT spr round 1 (radius: 5)
[01:03:42 -675295.314353] AUTODETECT spr round 2 (radius: 10)
[01:05:51 -502194.946008] AUTODETECT spr round 3 (radius: 15)
[01:08:12 -437199.898506] AUTODETECT spr round 4 (radius: 20)
[01:11:02 -419734.144888] AUTODETECT spr round 5 (radius: 25)
[01:14:29 -418757.142364] SPR radius for FAST iterations: 25 (autodetect)
[01:14:29 -418757.142364] Model parameter optimization (eps = 3.000000)
[01:14:49 -418594.799861] FAST spr round 1 (radius: 25)
[01:18:01 -380001.223878] FAST spr round 2 (radius: 25)
[01:20:14 -378658.603161] FAST spr round 3 (radius: 25)
[01:22:09 -378549.420589] FAST spr round 4 (radius: 25)
[01:23:48 -378534.330938] FAST spr round 5 (radius: 25)
[01:25:21 -378529.663378] FAST spr round 6 (radius: 25)
[01:26:54 -378529.663301] Model parameter optimization (eps = 1.000000)
[01:27:08 -378524.964604] SLOW spr round 1 (radius: 5)
[01:29:21 -378437.214529] SLOW spr round 2 (radius: 5)
[01:31:25 -378418.493352] SLOW spr round 3 (radius: 5)
[01:33:22 -378410.517810] SLOW spr round 4 (radius: 5)
[01:35:15 -378410.108861] SLOW spr round 5 (radius: 5)
[01:37:06 -378410.108861] SLOW spr round 6 (radius: 10)
[01:39:11 -378397.634253] SLOW spr round 7 (radius: 5)
[01:41:34 -378397.634208] SLOW spr round 8 (radius: 10)
[01:43:59 -378397.634208] SLOW spr round 9 (radius: 15)
[01:48:12 -378397.634208] SLOW spr round 10 (radius: 20)
[01:55:42 -378397.634208] SLOW spr round 11 (radius: 25)
[02:03:50 -378397.634208] Model parameter optimization (eps = 0.100000)

[02:03:59] ML tree search #2, logLikelihood: -378396.617230

[02:03:59 -921203.498621] Initial branch length optimization
[02:04:02 -796205.923061] Model parameter optimization (eps = 10.000000)
[02:04:25 -793551.293619] AUTODETECT spr round 1 (radius: 5)
[02:06:15 -680533.564211] AUTODETECT spr round 2 (radius: 10)
[02:08:23 -519813.172629] AUTODETECT spr round 3 (radius: 15)
[02:10:43 -442537.184401] AUTODETECT spr round 4 (radius: 20)
[02:13:41 -421281.106545] AUTODETECT spr round 5 (radius: 25)
[02:17:44 -420585.548927] SPR radius for FAST iterations: 25 (autodetect)
[02:17:44 -420585.548927] Model parameter optimization (eps = 3.000000)
[02:17:59 -420445.782698] FAST spr round 1 (radius: 25)
[02:21:27 -380118.709371] FAST spr round 2 (radius: 25)
[02:23:45 -378627.760549] FAST spr round 3 (radius: 25)
[02:25:43 -378546.795426] FAST spr round 4 (radius: 25)
[02:27:22 -378542.575948] FAST spr round 5 (radius: 25)
[02:28:55 -378536.985958] FAST spr round 6 (radius: 25)
[02:30:26 -378536.984285] Model parameter optimization (eps = 1.000000)
[02:30:39 -378525.914981] SLOW spr round 1 (radius: 5)
[02:32:50 -378433.261518] SLOW spr round 2 (radius: 5)
[02:34:50 -378413.039690] SLOW spr round 3 (radius: 5)
[02:36:45 -378407.860181] SLOW spr round 4 (radius: 5)
[02:38:41 -378407.860060] SLOW spr round 5 (radius: 10)
[02:40:46 -378404.252542] SLOW spr round 6 (radius: 5)
[02:43:11 -378395.204558] SLOW spr round 7 (radius: 5)
[02:45:16 -378395.204541] SLOW spr round 8 (radius: 10)
[02:47:24 -378394.668435] SLOW spr round 9 (radius: 5)
[02:49:47 -378388.489735] SLOW spr round 10 (radius: 5)
[02:51:50 -378388.489728] SLOW spr round 11 (radius: 10)
[02:53:57 -378388.489728] SLOW spr round 12 (radius: 15)
[02:58:22 -378388.489728] SLOW spr round 13 (radius: 20)
[03:05:20 -378388.489728] SLOW spr round 14 (radius: 25)
[03:13:29 -378388.489728] Model parameter optimization (eps = 0.100000)

[03:13:38] ML tree search #3, logLikelihood: -378387.549135

[03:13:38 -921155.151165] Initial branch length optimization
[03:13:40 -795687.670177] Model parameter optimization (eps = 10.000000)
[03:14:02 -792958.539571] AUTODETECT spr round 1 (radius: 5)
[03:15:50 -667956.670736] AUTODETECT spr round 2 (radius: 10)
[03:18:03 -514616.465510] AUTODETECT spr round 3 (radius: 15)
[03:20:26 -446116.532397] AUTODETECT spr round 4 (radius: 20)
[03:23:34 -428427.951932] AUTODETECT spr round 5 (radius: 25)
[03:27:31 -427635.578600] SPR radius for FAST iterations: 25 (autodetect)
[03:27:31 -427635.578600] Model parameter optimization (eps = 3.000000)
[03:27:48 -427490.138510] FAST spr round 1 (radius: 25)
[03:31:12 -380721.590569] FAST spr round 2 (radius: 25)
[03:33:27 -378707.014442] FAST spr round 3 (radius: 25)
[03:35:22 -378593.100806] FAST spr round 4 (radius: 25)
[03:37:02 -378568.543069] FAST spr round 5 (radius: 25)
[03:38:36 -378552.940475] FAST spr round 6 (radius: 25)
[03:40:06 -378552.940105] Model parameter optimization (eps = 1.000000)
[03:40:18 -378538.045682] SLOW spr round 1 (radius: 5)
[03:42:25 -378435.719604] SLOW spr round 2 (radius: 5)
[03:44:26 -378416.270937] SLOW spr round 3 (radius: 5)
[03:46:23 -378414.831877] SLOW spr round 4 (radius: 5)
[03:48:20 -378411.422439] SLOW spr round 5 (radius: 5)
[03:50:17 -378409.189731] SLOW spr round 6 (radius: 5)
[03:52:10 -378409.189724] SLOW spr round 7 (radius: 10)
[03:54:11 -378409.189724] SLOW spr round 8 (radius: 15)
[03:58:59 -378409.189724] SLOW spr round 9 (radius: 20)
[04:05:53 -378409.189724] SLOW spr round 10 (radius: 25)
[04:14:05 -378409.189724] Model parameter optimization (eps = 0.100000)

[04:14:19] ML tree search #4, logLikelihood: -378408.824628

[04:14:19 -920987.765773] Initial branch length optimization
[04:14:21 -796316.113288] Model parameter optimization (eps = 10.000000)
[04:14:45 -793638.575258] AUTODETECT spr round 1 (radius: 5)
[04:16:37 -667160.750182] AUTODETECT spr round 2 (radius: 10)
[04:18:48 -511443.984635] AUTODETECT spr round 3 (radius: 15)
[04:21:23 -433227.695681] AUTODETECT spr round 4 (radius: 20)
[04:24:39 -422131.437454] AUTODETECT spr round 5 (radius: 25)
[04:28:38 -421156.520675] SPR radius for FAST iterations: 25 (autodetect)
[04:28:38 -421156.520675] Model parameter optimization (eps = 3.000000)
[04:28:57 -421023.873235] FAST spr round 1 (radius: 25)
[04:32:16 -380244.014323] FAST spr round 2 (radius: 25)
[04:34:32 -378648.749279] FAST spr round 3 (radius: 25)
[04:36:27 -378585.384196] FAST spr round 4 (radius: 25)
[04:38:07 -378570.337769] FAST spr round 5 (radius: 25)
[04:39:41 -378567.247609] FAST spr round 6 (radius: 25)
[04:41:12 -378563.716128] FAST spr round 7 (radius: 25)
[04:42:40 -378563.716124] Model parameter optimization (eps = 1.000000)
[04:42:55 -378559.669021] SLOW spr round 1 (radius: 5)
[04:45:03 -378431.394439] SLOW spr round 2 (radius: 5)
[04:47:00 -378421.426848] SLOW spr round 3 (radius: 5)
[04:48:51 -378418.799643] SLOW spr round 4 (radius: 5)
[04:50:40 -378418.799607] SLOW spr round 5 (radius: 10)
[04:52:39 -378418.799606] SLOW spr round 6 (radius: 15)
[04:57:23 -378418.799606] SLOW spr round 7 (radius: 20)
[05:04:22 -378418.799606] SLOW spr round 8 (radius: 25)
[05:12:25 -378418.799606] Model parameter optimization (eps = 0.100000)

[05:12:33] ML tree search #5, logLikelihood: -378418.461344

[05:12:33 -919155.146734] Initial branch length optimization
[05:12:35 -795562.394660] Model parameter optimization (eps = 10.000000)
[05:13:02 -792861.404287] AUTODETECT spr round 1 (radius: 5)
[05:14:52 -661413.638906] AUTODETECT spr round 2 (radius: 10)
[05:17:02 -504689.786034] AUTODETECT spr round 3 (radius: 15)
[05:19:23 -440131.530849] AUTODETECT spr round 4 (radius: 20)
[05:22:18 -421263.490460] AUTODETECT spr round 5 (radius: 25)
[05:26:24 -419202.854528] SPR radius for FAST iterations: 25 (autodetect)
[05:26:24 -419202.854528] Model parameter optimization (eps = 3.000000)
[05:26:41 -419057.393686] FAST spr round 1 (radius: 25)
[05:30:12 -379684.616183] FAST spr round 2 (radius: 25)
[05:32:37 -378652.072054] FAST spr round 3 (radius: 25)
[05:34:40 -378578.551015] FAST spr round 4 (radius: 25)
[05:36:27 -378554.837167] FAST spr round 5 (radius: 25)
[05:38:04 -378552.978809] FAST spr round 6 (radius: 25)
[05:39:40 -378545.347514] FAST spr round 7 (radius: 25)
[05:41:12 -378545.347370] Model parameter optimization (eps = 1.000000)
[05:41:26 -378536.366422] SLOW spr round 1 (radius: 5)
[05:43:39 -378397.372115] SLOW spr round 2 (radius: 5)
[05:45:42 -378385.472589] SLOW spr round 3 (radius: 5)
[05:47:39 -378383.611903] SLOW spr round 4 (radius: 5)
[05:49:34 -378382.890776] SLOW spr round 5 (radius: 5)
[05:51:27 -378382.195022] SLOW spr round 6 (radius: 5)
[05:53:18 -378382.194925] SLOW spr round 7 (radius: 10)
[05:55:19 -378382.194924] SLOW spr round 8 (radius: 15)
[06:00:08 -378382.194924] SLOW spr round 9 (radius: 20)
[06:07:01 -378382.194924] SLOW spr round 10 (radius: 25)
[06:15:14 -378382.194924] Model parameter optimization (eps = 0.100000)

[06:15:24] ML tree search #6, logLikelihood: -378382.046263

[06:15:24 -921201.570531] Initial branch length optimization
[06:15:27 -796858.476165] Model parameter optimization (eps = 10.000000)
[06:15:52 -794129.972233] AUTODETECT spr round 1 (radius: 5)
[06:17:39 -676573.568819] AUTODETECT spr round 2 (radius: 10)
[06:19:44 -519401.929862] AUTODETECT spr round 3 (radius: 15)
[06:22:06 -445284.569968] AUTODETECT spr round 4 (radius: 20)
[06:25:09 -420405.110571] AUTODETECT spr round 5 (radius: 25)
[06:29:10 -418194.667974] SPR radius for FAST iterations: 25 (autodetect)
[06:29:10 -418194.667974] Model parameter optimization (eps = 3.000000)
[06:29:29 -418097.905432] FAST spr round 1 (radius: 25)
[06:32:50 -379784.819085] FAST spr round 2 (radius: 25)
[06:35:08 -378651.856539] FAST spr round 3 (radius: 25)
[06:37:07 -378564.308964] FAST spr round 4 (radius: 25)
[06:38:46 -378548.026088] FAST spr round 5 (radius: 25)
[06:40:19 -378546.083106] FAST spr round 6 (radius: 25)
[06:41:50 -378546.083050] Model parameter optimization (eps = 1.000000)
[06:42:03 -378522.982661] SLOW spr round 1 (radius: 5)
[06:44:13 -378428.431641] SLOW spr round 2 (radius: 5)
[06:46:12 -378417.073207] SLOW spr round 3 (radius: 5)
[06:48:03 -378417.073193] SLOW spr round 4 (radius: 10)
[06:50:02 -378415.974730] SLOW spr round 5 (radius: 5)
[06:52:25 -378402.552688] SLOW spr round 6 (radius: 5)
[06:54:30 -378398.955851] SLOW spr round 7 (radius: 5)
[06:56:27 -378397.590003] SLOW spr round 8 (radius: 5)
[06:58:19 -378397.589930] SLOW spr round 9 (radius: 10)
[07:00:19 -378395.981958] SLOW spr round 10 (radius: 5)
[07:02:39 -378392.864169] SLOW spr round 11 (radius: 5)
[07:04:41 -378392.863611] SLOW spr round 12 (radius: 10)
[07:06:46 -378392.863609] SLOW spr round 13 (radius: 15)
[07:11:18 -378392.863609] SLOW spr round 14 (radius: 20)
[07:18:32 -378392.863609] SLOW spr round 15 (radius: 25)
[07:26:58 -378392.863609] Model parameter optimization (eps = 0.100000)

[07:27:06] ML tree search #7, logLikelihood: -378392.601932

[07:27:06 -921333.532970] Initial branch length optimization
[07:27:09 -794567.048862] Model parameter optimization (eps = 10.000000)
[07:27:34 -791937.402337] AUTODETECT spr round 1 (radius: 5)
[07:29:19 -674127.416563] AUTODETECT spr round 2 (radius: 10)
[07:31:24 -517938.981764] AUTODETECT spr round 3 (radius: 15)
[07:33:41 -452506.637135] AUTODETECT spr round 4 (radius: 20)
[07:36:39 -429368.647138] AUTODETECT spr round 5 (radius: 25)
[07:40:30 -424758.704261] SPR radius for FAST iterations: 25 (autodetect)
[07:40:30 -424758.704261] Model parameter optimization (eps = 3.000000)
[07:40:47 -424576.223699] FAST spr round 1 (radius: 25)
[07:44:08 -380228.923831] FAST spr round 2 (radius: 25)
[07:46:27 -378674.204323] FAST spr round 3 (radius: 25)
[07:48:19 -378577.733932] FAST spr round 4 (radius: 25)
[07:49:56 -378566.826932] FAST spr round 5 (radius: 25)
[07:51:28 -378566.826922] Model parameter optimization (eps = 1.000000)
[07:51:40 -378562.245453] SLOW spr round 1 (radius: 5)
[07:53:46 -378450.793731] SLOW spr round 2 (radius: 5)
[07:55:40 -378448.403464] SLOW spr round 3 (radius: 5)
[07:57:32 -378445.702906] SLOW spr round 4 (radius: 5)
[07:59:20 -378445.702706] SLOW spr round 5 (radius: 10)
[08:01:18 -378445.702705] SLOW spr round 6 (radius: 15)
[08:06:19 -378445.702705] SLOW spr round 7 (radius: 20)
[08:13:41 -378445.702705] SLOW spr round 8 (radius: 25)
[08:21:19 -378445.702705] Model parameter optimization (eps = 0.100000)

[08:21:26] ML tree search #8, logLikelihood: -378445.567076

[08:21:26 -919550.792957] Initial branch length optimization
[08:21:28 -794240.908567] Model parameter optimization (eps = 10.000000)
[08:21:59 -791589.559419] AUTODETECT spr round 1 (radius: 5)
[08:23:43 -664857.581237] AUTODETECT spr round 2 (radius: 10)
[08:25:46 -513074.151514] AUTODETECT spr round 3 (radius: 15)
[08:28:02 -445347.224885] AUTODETECT spr round 4 (radius: 20)
[08:30:53 -425479.757887] AUTODETECT spr round 5 (radius: 25)
[08:34:47 -422222.297683] SPR radius for FAST iterations: 25 (autodetect)
[08:34:47 -422222.297683] Model parameter optimization (eps = 3.000000)
[08:35:04 -422082.331820] FAST spr round 1 (radius: 25)
[08:38:21 -380039.798030] FAST spr round 2 (radius: 25)
[08:40:36 -378764.484974] FAST spr round 3 (radius: 25)
[08:42:34 -378621.014998] FAST spr round 4 (radius: 25)
[08:44:12 -378603.307887] FAST spr round 5 (radius: 25)
[08:45:44 -378594.352330] FAST spr round 6 (radius: 25)
[08:47:13 -378593.150807] FAST spr round 7 (radius: 25)
[08:48:40 -378593.150770] Model parameter optimization (eps = 1.000000)
[08:48:52 -378583.008080] SLOW spr round 1 (radius: 5)
[08:50:59 -378443.071823] SLOW spr round 2 (radius: 5)
[08:52:58 -378421.114728] SLOW spr round 3 (radius: 5)
[08:54:48 -378421.114719] SLOW spr round 4 (radius: 10)
[08:56:44 -378421.114719] SLOW spr round 5 (radius: 15)
[09:01:17 -378421.114719] SLOW spr round 6 (radius: 20)
[09:07:51 -378421.114719] SLOW spr round 7 (radius: 25)
[09:15:46 -378421.114719] Model parameter optimization (eps = 0.100000)

[09:15:50] ML tree search #9, logLikelihood: -378421.081682

[09:15:51 -922427.672527] Initial branch length optimization
[09:15:53 -798090.200980] Model parameter optimization (eps = 10.000000)
[09:16:16 -795475.955001] AUTODETECT spr round 1 (radius: 5)
[09:18:01 -670740.710769] AUTODETECT spr round 2 (radius: 10)
[09:20:06 -516693.980476] AUTODETECT spr round 3 (radius: 15)
[09:22:24 -440400.448132] AUTODETECT spr round 4 (radius: 20)
[09:25:35 -421134.251168] AUTODETECT spr round 5 (radius: 25)
[09:29:47 -417703.326810] SPR radius for FAST iterations: 25 (autodetect)
[09:29:47 -417703.326810] Model parameter optimization (eps = 3.000000)
[09:30:02 -417594.447675] FAST spr round 1 (radius: 25)
[09:33:20 -379855.587158] FAST spr round 2 (radius: 25)
[09:35:35 -378707.279141] FAST spr round 3 (radius: 25)
[09:37:31 -378625.971038] FAST spr round 4 (radius: 25)
[09:39:16 -378564.403156] FAST spr round 5 (radius: 25)
[09:40:55 -378545.627281] FAST spr round 6 (radius: 25)
[09:42:24 -378535.832052] FAST spr round 7 (radius: 25)
[09:43:51 -378535.831984] Model parameter optimization (eps = 1.000000)
[09:44:05 -378502.092008] SLOW spr round 1 (radius: 5)
[09:46:11 -378429.903920] SLOW spr round 2 (radius: 5)
[09:48:10 -378410.244024] SLOW spr round 3 (radius: 5)
[09:50:01 -378408.827189] SLOW spr round 4 (radius: 5)
[09:51:49 -378408.827126] SLOW spr round 5 (radius: 10)
[09:53:49 -378400.851498] SLOW spr round 6 (radius: 5)
[09:56:09 -378392.432529] SLOW spr round 7 (radius: 5)
[09:58:13 -378387.362864] SLOW spr round 8 (radius: 5)
[10:00:07 -378387.362823] SLOW spr round 9 (radius: 10)
[10:02:08 -378387.362823] SLOW spr round 10 (radius: 15)
[10:06:38 -378387.362823] SLOW spr round 11 (radius: 20)
[10:13:22 -378387.362823] SLOW spr round 12 (radius: 25)
[10:21:28 -378387.362823] Model parameter optimization (eps = 0.100000)

[10:21:36] ML tree search #10, logLikelihood: -378387.227798

[10:21:36 -920834.926836] Initial branch length optimization
[10:21:39 -794962.486463] Model parameter optimization (eps = 10.000000)
[10:22:11 -792306.337593] AUTODETECT spr round 1 (radius: 5)
[10:23:55 -671000.851498] AUTODETECT spr round 2 (radius: 10)
[10:26:03 -522300.255686] AUTODETECT spr round 3 (radius: 15)
[10:28:19 -432488.493814] AUTODETECT spr round 4 (radius: 20)
[10:31:12 -418553.383182] AUTODETECT spr round 5 (radius: 25)
[10:35:11 -417303.016916] SPR radius for FAST iterations: 25 (autodetect)
[10:35:11 -417303.016916] Model parameter optimization (eps = 3.000000)
[10:35:26 -417217.561358] FAST spr round 1 (radius: 25)
[10:38:43 -380120.313447] FAST spr round 2 (radius: 25)
[10:41:00 -378794.665253] FAST spr round 3 (radius: 25)
[10:42:56 -378629.825722] FAST spr round 4 (radius: 25)
[10:44:39 -378602.540037] FAST spr round 5 (radius: 25)
[10:46:11 -378602.539967] Model parameter optimization (eps = 1.000000)
[10:46:25 -378578.466776] SLOW spr round 1 (radius: 5)
[10:48:36 -378469.088939] SLOW spr round 2 (radius: 5)
[10:50:38 -378452.874402] SLOW spr round 3 (radius: 5)
[10:52:37 -378431.009647] SLOW spr round 4 (radius: 5)
[10:54:28 -378430.083837] SLOW spr round 5 (radius: 5)
[10:56:17 -378430.083812] SLOW spr round 6 (radius: 10)
[10:58:12 -378430.083812] SLOW spr round 7 (radius: 15)
[11:02:31 -378430.083812] SLOW spr round 8 (radius: 20)
[11:08:36 -378430.083812] SLOW spr round 9 (radius: 25)
[11:16:08 -378430.083812] Model parameter optimization (eps = 0.100000)

[11:16:20] ML tree search #11, logLikelihood: -378429.019174

[11:16:20 -919612.448335] Initial branch length optimization
[11:16:22 -795484.008798] Model parameter optimization (eps = 10.000000)
[11:16:45 -792711.175119] AUTODETECT spr round 1 (radius: 5)
[11:18:27 -673822.779217] AUTODETECT spr round 2 (radius: 10)
[11:20:29 -514694.339473] AUTODETECT spr round 3 (radius: 15)
[11:22:56 -441256.090034] AUTODETECT spr round 4 (radius: 20)
[11:25:56 -423372.908340] AUTODETECT spr round 5 (radius: 25)
[11:29:42 -422140.669686] SPR radius for FAST iterations: 25 (autodetect)
[11:29:42 -422140.669686] Model parameter optimization (eps = 3.000000)
[11:30:03 -422019.505239] FAST spr round 1 (radius: 25)
[11:33:29 -379671.971316] FAST spr round 2 (radius: 25)
[11:35:45 -378599.872614] FAST spr round 3 (radius: 25)
[11:37:39 -378539.869878] FAST spr round 4 (radius: 25)
[11:39:19 -378524.412904] FAST spr round 5 (radius: 25)
[11:40:50 -378523.381139] FAST spr round 6 (radius: 25)
[11:42:20 -378523.381071] Model parameter optimization (eps = 1.000000)
[11:42:34 -378516.168869] SLOW spr round 1 (radius: 5)
[11:44:40 -378431.848330] SLOW spr round 2 (radius: 5)
[11:46:36 -378421.554397] SLOW spr round 3 (radius: 5)
[11:48:27 -378419.271964] SLOW spr round 4 (radius: 5)
[11:50:17 -378419.271755] SLOW spr round 5 (radius: 10)
[11:52:15 -378419.271752] SLOW spr round 6 (radius: 15)
[11:56:54 -378419.271751] SLOW spr round 7 (radius: 20)
[12:03:38 -378419.271751] SLOW spr round 8 (radius: 25)
[12:11:26 -378419.271751] Model parameter optimization (eps = 0.100000)

[12:11:30] ML tree search #12, logLikelihood: -378419.213895

[12:11:30 -923641.803088] Initial branch length optimization
[12:11:32 -798333.424554] Model parameter optimization (eps = 10.000000)
[12:11:56 -795536.130123] AUTODETECT spr round 1 (radius: 5)
[12:13:40 -672574.006471] AUTODETECT spr round 2 (radius: 10)
[12:15:41 -520925.275937] AUTODETECT spr round 3 (radius: 15)
[12:18:01 -441992.668702] AUTODETECT spr round 4 (radius: 20)
[12:20:54 -423894.290824] AUTODETECT spr round 5 (radius: 25)
[12:25:10 -421855.505051] SPR radius for FAST iterations: 25 (autodetect)
[12:25:10 -421855.505051] Model parameter optimization (eps = 3.000000)
[12:25:28 -421752.663242] FAST spr round 1 (radius: 25)
[12:29:02 -380103.444202] FAST spr round 2 (radius: 25)
[12:31:16 -378653.812141] FAST spr round 3 (radius: 25)
[12:33:08 -378611.031013] FAST spr round 4 (radius: 25)
[12:34:43 -378607.024424] FAST spr round 5 (radius: 25)
[12:36:12 -378607.024410] Model parameter optimization (eps = 1.000000)
[12:36:25 -378598.369976] SLOW spr round 1 (radius: 5)
[12:38:30 -378494.654377] SLOW spr round 2 (radius: 5)
[12:40:27 -378478.727021] SLOW spr round 3 (radius: 5)
[12:42:20 -378461.034364] SLOW spr round 4 (radius: 5)
[12:44:08 -378460.211908] SLOW spr round 5 (radius: 5)
[12:45:54 -378460.211820] SLOW spr round 6 (radius: 10)
[12:47:48 -378458.110906] SLOW spr round 7 (radius: 5)
[12:50:05 -378453.126189] SLOW spr round 8 (radius: 5)
[12:52:05 -378453.126159] SLOW spr round 9 (radius: 10)
[12:54:05 -378451.829730] SLOW spr round 10 (radius: 5)
[12:56:18 -378451.829656] SLOW spr round 11 (radius: 10)
[12:58:29 -378451.829656] SLOW spr round 12 (radius: 15)
[13:02:46 -378451.829656] SLOW spr round 13 (radius: 20)
[13:10:16 -378451.829656] SLOW spr round 14 (radius: 25)
[13:18:01 -378451.829656] Model parameter optimization (eps = 0.100000)

[13:18:06] ML tree search #13, logLikelihood: -378451.769301

[13:18:06 -923099.914860] Initial branch length optimization
[13:18:09 -797570.700979] Model parameter optimization (eps = 10.000000)
[13:18:32 -794834.311709] AUTODETECT spr round 1 (radius: 5)
[13:20:15 -676019.542730] AUTODETECT spr round 2 (radius: 10)
[13:22:15 -522208.572819] AUTODETECT spr round 3 (radius: 15)
[13:24:35 -441208.188184] AUTODETECT spr round 4 (radius: 20)
[13:27:20 -421261.247445] AUTODETECT spr round 5 (radius: 25)
[13:31:11 -419124.178392] SPR radius for FAST iterations: 25 (autodetect)
[13:31:11 -419124.178392] Model parameter optimization (eps = 3.000000)
[13:31:27 -418946.757644] FAST spr round 1 (radius: 25)
[13:34:38 -380289.098083] FAST spr round 2 (radius: 25)
[13:36:54 -378660.010745] FAST spr round 3 (radius: 25)
[13:38:48 -378586.126784] FAST spr round 4 (radius: 25)
[13:40:26 -378582.192190] FAST spr round 5 (radius: 25)
[13:41:56 -378580.932172] FAST spr round 6 (radius: 25)
[13:43:23 -378580.932166] Model parameter optimization (eps = 1.000000)
[13:43:36 -378574.282844] SLOW spr round 1 (radius: 5)
[13:45:44 -378465.518945] SLOW spr round 2 (radius: 5)
[13:47:37 -378450.988598] SLOW spr round 3 (radius: 5)
[13:49:29 -378439.507893] SLOW spr round 4 (radius: 5)
[13:51:18 -378430.911980] SLOW spr round 5 (radius: 5)
[13:53:05 -378430.335746] SLOW spr round 6 (radius: 5)
[13:54:51 -378430.335677] SLOW spr round 7 (radius: 10)
[13:56:48 -378426.243822] SLOW spr round 8 (radius: 5)
[13:59:08 -378413.287200] SLOW spr round 9 (radius: 5)
[14:01:17 -378397.622528] SLOW spr round 10 (radius: 5)
[14:03:10 -378397.375761] SLOW spr round 11 (radius: 5)
[14:05:00 -378397.375684] SLOW spr round 12 (radius: 10)
[14:06:56 -378397.375683] SLOW spr round 13 (radius: 15)
[14:11:48 -378397.375683] SLOW spr round 14 (radius: 20)
[14:18:57 -378397.375683] SLOW spr round 15 (radius: 25)
[14:27:08 -378397.375683] Model parameter optimization (eps = 0.100000)

[14:27:19] ML tree search #14, logLikelihood: -378395.937974

[14:27:19 -921871.676853] Initial branch length optimization
[14:27:21 -795453.034813] Model parameter optimization (eps = 10.000000)
[14:27:46 -792819.451950] AUTODETECT spr round 1 (radius: 5)
[14:29:28 -672523.694279] AUTODETECT spr round 2 (radius: 10)
[14:31:29 -515395.352421] AUTODETECT spr round 3 (radius: 15)
[14:33:43 -445489.909502] AUTODETECT spr round 4 (radius: 20)
[14:36:26 -423805.977683] AUTODETECT spr round 5 (radius: 25)
[14:40:14 -422507.289351] SPR radius for FAST iterations: 25 (autodetect)
[14:40:14 -422507.289351] Model parameter optimization (eps = 3.000000)
[14:40:30 -422361.047368] FAST spr round 1 (radius: 25)
[14:43:39 -380064.742801] FAST spr round 2 (radius: 25)
[14:45:50 -378569.541317] FAST spr round 3 (radius: 25)
[14:47:43 -378511.858923] FAST spr round 4 (radius: 25)
[14:49:20 -378500.800682] FAST spr round 5 (radius: 25)
[14:50:49 -378499.317712] FAST spr round 6 (radius: 25)
[14:52:16 -378496.129055] FAST spr round 7 (radius: 25)
[14:53:40 -378496.129026] Model parameter optimization (eps = 1.000000)
[14:53:55 -378483.376425] SLOW spr round 1 (radius: 5)
[14:55:58 -378400.757025] SLOW spr round 2 (radius: 5)
[14:57:52 -378394.092665] SLOW spr round 3 (radius: 5)
[14:59:39 -378394.092603] SLOW spr round 4 (radius: 10)
[15:01:34 -378388.226444] SLOW spr round 5 (radius: 5)
[15:03:51 -378386.124423] SLOW spr round 6 (radius: 5)
[15:05:52 -378384.870325] SLOW spr round 7 (radius: 5)
[15:07:44 -378384.870167] SLOW spr round 8 (radius: 10)
[15:09:40 -378384.870165] SLOW spr round 9 (radius: 15)
[15:14:24 -378384.870165] SLOW spr round 10 (radius: 20)
[15:21:31 -378384.870165] SLOW spr round 11 (radius: 25)
[15:29:30 -378384.870165] Model parameter optimization (eps = 0.100000)

[15:29:34] ML tree search #15, logLikelihood: -378384.834790

[15:29:34 -921479.043557] Initial branch length optimization
[15:29:37 -797106.067056] Model parameter optimization (eps = 10.000000)
[15:29:59 -794166.204414] AUTODETECT spr round 1 (radius: 5)
[15:31:42 -676755.521789] AUTODETECT spr round 2 (radius: 10)
[15:33:45 -518433.361614] AUTODETECT spr round 3 (radius: 15)
[15:36:06 -445972.264089] AUTODETECT spr round 4 (radius: 20)
[15:38:48 -426856.498899] AUTODETECT spr round 5 (radius: 25)
[15:42:38 -425010.683387] SPR radius for FAST iterations: 25 (autodetect)
[15:42:38 -425010.683387] Model parameter optimization (eps = 3.000000)
[15:42:54 -424850.176728] FAST spr round 1 (radius: 25)
[15:46:18 -380036.982210] FAST spr round 2 (radius: 25)
[15:48:33 -378718.873558] FAST spr round 3 (radius: 25)
[15:50:28 -378606.712688] FAST spr round 4 (radius: 25)
[15:52:03 -378602.093252] FAST spr round 5 (radius: 25)
[15:53:34 -378598.995453] FAST spr round 6 (radius: 25)
[15:55:00 -378598.995429] Model parameter optimization (eps = 1.000000)
[15:55:13 -378592.599345] SLOW spr round 1 (radius: 5)
[15:57:19 -378452.931764] SLOW spr round 2 (radius: 5)
[15:59:12 -378440.032210] SLOW spr round 3 (radius: 5)
[16:01:02 -378434.672002] SLOW spr round 4 (radius: 5)
[16:02:49 -378432.791797] SLOW spr round 5 (radius: 5)
[16:04:35 -378432.791753] SLOW spr round 6 (radius: 10)
[16:06:27 -378428.862366] SLOW spr round 7 (radius: 5)
[16:08:46 -378417.951356] SLOW spr round 8 (radius: 5)
[16:10:48 -378410.684476] SLOW spr round 9 (radius: 5)
[16:12:41 -378409.891906] SLOW spr round 10 (radius: 5)
[16:14:29 -378409.891789] SLOW spr round 11 (radius: 10)
[16:16:24 -378404.078128] SLOW spr round 12 (radius: 5)
[16:18:39 -378400.868319] SLOW spr round 13 (radius: 5)
[16:20:38 -378400.868293] SLOW spr round 14 (radius: 10)
[16:22:36 -378400.868293] SLOW spr round 15 (radius: 15)
[16:27:02 -378400.868293] SLOW spr round 16 (radius: 20)
[16:34:05 -378400.868293] SLOW spr round 17 (radius: 25)
[16:41:59 -378400.868293] Model parameter optimization (eps = 0.100000)

[16:42:08] ML tree search #16, logLikelihood: -378399.513369

[16:42:08 -918855.825180] Initial branch length optimization
[16:42:10 -796365.079375] Model parameter optimization (eps = 10.000000)
[16:42:37 -793639.731299] AUTODETECT spr round 1 (radius: 5)
[16:44:19 -669408.592499] AUTODETECT spr round 2 (radius: 10)
[16:46:21 -516410.245111] AUTODETECT spr round 3 (radius: 15)
[16:48:46 -432418.198960] AUTODETECT spr round 4 (radius: 20)
[16:51:54 -419731.440497] AUTODETECT spr round 5 (radius: 25)
[16:56:09 -419146.951538] SPR radius for FAST iterations: 25 (autodetect)
[16:56:09 -419146.951538] Model parameter optimization (eps = 3.000000)
[16:56:25 -418955.952694] FAST spr round 1 (radius: 25)
[16:59:49 -379971.749139] FAST spr round 2 (radius: 25)
[17:01:56 -378643.717947] FAST spr round 3 (radius: 25)
[17:03:40 -378617.282895] FAST spr round 4 (radius: 25)
[17:05:13 -378608.606589] FAST spr round 5 (radius: 25)
[17:06:41 -378608.606544] Model parameter optimization (eps = 1.000000)
[17:06:56 -378600.487173] SLOW spr round 1 (radius: 5)
[17:09:03 -378425.431048] SLOW spr round 2 (radius: 5)
[17:10:59 -378400.134597] SLOW spr round 3 (radius: 5)
[17:12:49 -378396.911985] SLOW spr round 4 (radius: 5)
[17:14:36 -378394.370227] SLOW spr round 5 (radius: 5)
[17:16:22 -378394.368725] SLOW spr round 6 (radius: 10)
[17:18:17 -378394.368661] SLOW spr round 7 (radius: 15)
[17:23:06 -378394.368658] SLOW spr round 8 (radius: 20)
[17:30:04 -378394.368658] SLOW spr round 9 (radius: 25)
[17:38:08 -378394.368658] Model parameter optimization (eps = 0.100000)

[17:38:13] ML tree search #17, logLikelihood: -378394.304854

[17:38:13 -923726.854799] Initial branch length optimization
[17:38:16 -797967.764951] Model parameter optimization (eps = 10.000000)
[17:38:37 -795211.848295] AUTODETECT spr round 1 (radius: 5)
[17:40:18 -672365.204356] AUTODETECT spr round 2 (radius: 10)
[17:42:18 -512753.771358] AUTODETECT spr round 3 (radius: 15)
[17:44:43 -433004.774276] AUTODETECT spr round 4 (radius: 20)
[17:47:36 -421527.610228] AUTODETECT spr round 5 (radius: 25)
[17:51:18 -420827.858480] SPR radius for FAST iterations: 25 (autodetect)
[17:51:18 -420827.858480] Model parameter optimization (eps = 3.000000)
[17:51:32 -420665.422172] FAST spr round 1 (radius: 25)
[17:54:46 -379943.761579] FAST spr round 2 (radius: 25)
[17:56:58 -378628.887279] FAST spr round 3 (radius: 25)
[17:58:50 -378553.268833] FAST spr round 4 (radius: 25)
[18:00:25 -378543.793988] FAST spr round 5 (radius: 25)
[18:01:53 -378543.793964] Model parameter optimization (eps = 1.000000)
[18:02:02 -378529.961340] SLOW spr round 1 (radius: 5)
[18:04:07 -378422.014496] SLOW spr round 2 (radius: 5)
[18:06:05 -378406.831168] SLOW spr round 3 (radius: 5)
[18:07:53 -378406.831158] SLOW spr round 4 (radius: 10)
[18:09:49 -378400.755880] SLOW spr round 5 (radius: 5)
[18:12:06 -378395.703372] SLOW spr round 6 (radius: 5)
[18:14:04 -378395.618135] SLOW spr round 7 (radius: 10)
[18:16:04 -378395.618076] SLOW spr round 8 (radius: 15)
[18:20:17 -378395.618076] SLOW spr round 9 (radius: 20)
[18:26:54 -378395.618076] SLOW spr round 10 (radius: 25)
[18:34:47 -378395.618076] Model parameter optimization (eps = 0.100000)

[18:34:54] ML tree search #18, logLikelihood: -378395.541198

[18:34:54 -920839.319017] Initial branch length optimization
[18:34:57 -795148.787597] Model parameter optimization (eps = 10.000000)
[18:35:18 -792436.910740] AUTODETECT spr round 1 (radius: 5)
[18:37:00 -676207.395447] AUTODETECT spr round 2 (radius: 10)
[18:39:02 -519236.321683] AUTODETECT spr round 3 (radius: 15)
[18:41:18 -443395.477095] AUTODETECT spr round 4 (radius: 20)
[18:43:56 -423247.197735] AUTODETECT spr round 5 (radius: 25)
[18:47:23 -421334.355911] SPR radius for FAST iterations: 25 (autodetect)
[18:47:23 -421334.355911] Model parameter optimization (eps = 3.000000)
[18:47:43 -421260.852141] FAST spr round 1 (radius: 25)
[18:50:56 -380034.693609] FAST spr round 2 (radius: 25)
[18:53:10 -378621.087767] FAST spr round 3 (radius: 25)
[18:55:01 -378573.105843] FAST spr round 4 (radius: 25)
[18:56:39 -378561.077363] FAST spr round 5 (radius: 25)
[18:58:09 -378556.348403] FAST spr round 6 (radius: 25)
[18:59:35 -378556.348315] Model parameter optimization (eps = 1.000000)
[18:59:48 -378532.165838] SLOW spr round 1 (radius: 5)
[19:01:53 -378435.229106] SLOW spr round 2 (radius: 5)
[19:03:46 -378428.635689] SLOW spr round 3 (radius: 5)
[19:05:34 -378421.844356] SLOW spr round 4 (radius: 5)
[19:07:20 -378421.844040] SLOW spr round 5 (radius: 10)
[19:09:15 -378418.919089] SLOW spr round 6 (radius: 5)
[19:11:33 -378412.577014] SLOW spr round 7 (radius: 5)
[19:13:36 -378412.145863] SLOW spr round 8 (radius: 5)
[19:15:32 -378409.952871] SLOW spr round 9 (radius: 5)
[19:17:29 -378398.830242] SLOW spr round 10 (radius: 5)
[19:19:25 -378392.838510] SLOW spr round 11 (radius: 5)
[19:21:17 -378392.441103] SLOW spr round 12 (radius: 5)
[19:23:08 -378392.441103] SLOW spr round 13 (radius: 10)
[19:25:19 -378392.441103] SLOW spr round 14 (radius: 15)
[19:30:33 -378392.441103] SLOW spr round 15 (radius: 20)
[19:38:17 -378392.441103] SLOW spr round 16 (radius: 25)
[19:47:18 -378392.441103] Model parameter optimization (eps = 0.100000)

[19:47:26] ML tree search #19, logLikelihood: -378392.123858

[19:47:26 -923686.680978] Initial branch length optimization
[19:47:29 -798932.452528] Model parameter optimization (eps = 10.000000)
[19:47:53 -796246.234490] AUTODETECT spr round 1 (radius: 5)
[19:49:45 -666920.238609] AUTODETECT spr round 2 (radius: 10)
[19:51:58 -510633.264228] AUTODETECT spr round 3 (radius: 15)
[19:54:29 -442003.091134] AUTODETECT spr round 4 (radius: 20)
[19:57:45 -424111.008669] AUTODETECT spr round 5 (radius: 25)
[20:01:56 -422346.039376] SPR radius for FAST iterations: 25 (autodetect)
[20:01:56 -422346.039376] Model parameter optimization (eps = 3.000000)
[20:02:13 -422259.762610] FAST spr round 1 (radius: 25)
[20:05:45 -379968.100931] FAST spr round 2 (radius: 25)
[20:08:11 -378728.646728] FAST spr round 3 (radius: 25)
[20:10:20 -378626.093500] FAST spr round 4 (radius: 25)
[20:12:13 -378589.358222] FAST spr round 5 (radius: 25)
[20:13:58 -378581.391282] FAST spr round 6 (radius: 25)
[20:15:38 -378581.391246] Model parameter optimization (eps = 1.000000)
[20:15:53 -378554.894610] SLOW spr round 1 (radius: 5)
[20:18:18 -378438.942896] SLOW spr round 2 (radius: 5)
[20:20:31 -378419.163618] SLOW spr round 3 (radius: 5)
[20:22:34 -378419.163458] SLOW spr round 4 (radius: 10)
[20:24:48 -378414.847133] SLOW spr round 5 (radius: 5)
[20:27:27 -378392.360802] SLOW spr round 6 (radius: 5)
[20:29:42 -378392.360758] SLOW spr round 7 (radius: 10)
[20:31:59 -378389.724971] SLOW spr round 8 (radius: 5)
[20:34:32 -378386.438452] SLOW spr round 9 (radius: 5)
[20:36:53 -378386.438432] SLOW spr round 10 (radius: 10)
[20:39:11 -378386.438432] SLOW spr round 11 (radius: 15)
[20:44:14 -378386.438432] SLOW spr round 12 (radius: 20)
[20:52:14 -378386.438432] SLOW spr round 13 (radius: 25)
[21:01:21 -378386.438432] Model parameter optimization (eps = 0.100000)

[21:01:38] ML tree search #20, logLikelihood: -378382.314859


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.157014,0.314649) (0.261153,0.472605) (0.364925,1.149238) (0.216908,1.880004) 
   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: -378382.046263

AIC score: 760774.092526 / AICc score: 8804834.092526 / BIC score: 769163.311052
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=485).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 19 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/020621_run/phylogeny-snakemake/results/Q6ZWL3/3_mltree/Q6ZWL3.raxml.log

Analysis started: 04-Jun-2021 17:15:01 / finished: 05-Jun-2021 14:16:39

Elapsed time: 75698.495 seconds

Consumed energy: 6560.118 Wh (= 33 km in an electric car, or 164 km with an e-scooter!)