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 6140 CPU @ 2.30GHz, 36 cores, 251 GB RAM

RAxML-NG was called at 19-Jul-2021 15:01:18 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/2_msa/B5MCN3_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3 --seed 2 --threads 8 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/2_msa/B5MCN3_trimmed_msa.fasta
[00:00:00] Loaded alignment with 730 taxa and 753 sites

WARNING: Sequences tr_H2RCN1_H2RCN1_PANTR_9598 and tr_A0A2R9BBZ1_A0A2R9BBZ1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6U5Q0_F6U5Q0_MACMU_9544 and tr_G8F5S7_G8F5S7_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7HAA2_F7HAA2_MACMU_9544 and tr_G7PF68_G7PF68_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7HAA2_F7HAA2_MACMU_9544 and tr_A0A2K5NBZ8_A0A2K5NBZ8_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7HAA2_F7HAA2_MACMU_9544 and tr_A0A2K6BZB5_A0A2K6BZB5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G7PF71_G7PF71_MACFA_9541 and tr_A0A2K5ZQS4_A0A2K5ZQS4_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G7PF71_G7PF71_MACFA_9541 and tr_A0A2R9CMK1_A0A2R9CMK1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A0F8XBU3_A0A0F8XBU3_9EURO_308745 and tr_A0A2T5LMA2_A0A2T5LMA2_9EURO_1392256 are exactly identical!
WARNING: Sequences tr_A0A151N3C5_A0A151N3C5_ALLMI_8496 and tr_A0A3Q0G1C8_A0A3Q0G1C8_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_A0A0V0WUH9_A0A0V0WUH9_9BILA_92179 and tr_A0A0V1LFT6_A0A0V1LFT6_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V0WUH9_A0A0V0WUH9_9BILA_92179 and tr_A0A0V0ZXY4_A0A0V0ZXY4_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A226NED7_A0A226NED7_CALSU_9009 and tr_A0A226PAA1_A0A226PAA1_COLVI_9014 are exactly identical!
WARNING: Duplicate sequences found: 12

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.reduced.phy

Alignment comprises 1 partitions and 753 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 753 / 753
Gaps: 42.42 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 730 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 189 / 15120
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -587533.149887] Initial branch length optimization
[00:00:05 -477129.273467] Model parameter optimization (eps = 10.000000)
[00:00:56 -474266.067362] AUTODETECT spr round 1 (radius: 5)
[00:02:38 -345424.140911] AUTODETECT spr round 2 (radius: 10)
[00:04:25 -282436.549780] AUTODETECT spr round 3 (radius: 15)
[00:06:36 -239776.571966] AUTODETECT spr round 4 (radius: 20)
[00:09:02 -228258.068336] AUTODETECT spr round 5 (radius: 25)
[00:11:52 -220449.068301] SPR radius for FAST iterations: 25 (autodetect)
[00:11:52 -220449.068301] Model parameter optimization (eps = 3.000000)
[00:12:19 -220209.073191] FAST spr round 1 (radius: 25)
[00:14:59 -198730.742526] FAST spr round 2 (radius: 25)
[00:16:56 -197806.576620] FAST spr round 3 (radius: 25)
[00:18:40 -197718.871082] FAST spr round 4 (radius: 25)
[00:20:06 -197705.983846] FAST spr round 5 (radius: 25)
[00:21:25 -197701.754804] FAST spr round 6 (radius: 25)
[00:22:42 -197701.754738] Model parameter optimization (eps = 1.000000)
[00:23:00 -197693.085010] SLOW spr round 1 (radius: 5)
[00:24:57 -197642.782035] SLOW spr round 2 (radius: 5)
[00:26:44 -197642.146521] SLOW spr round 3 (radius: 5)
[00:28:28 -197642.130211] SLOW spr round 4 (radius: 10)
[00:30:19 -197639.666013] SLOW spr round 5 (radius: 5)
[00:32:37 -197635.748927] SLOW spr round 6 (radius: 5)
[00:34:37 -197635.463525] SLOW spr round 7 (radius: 5)
[00:36:26 -197635.463141] SLOW spr round 8 (radius: 10)
[00:38:17 -197635.463107] SLOW spr round 9 (radius: 15)
[00:41:48 -197635.463086] SLOW spr round 10 (radius: 20)
[00:46:58 -197635.463079] SLOW spr round 11 (radius: 25)
[00:50:26] [worker #1] ML tree search #2, logLikelihood: -197637.982962
[00:53:16 -197635.463074] Model parameter optimization (eps = 0.100000)

[00:53:22] [worker #0] ML tree search #1, logLikelihood: -197635.392470

[00:53:22 -583649.708385] Initial branch length optimization
[00:53:26 -478716.880344] Model parameter optimization (eps = 10.000000)
[00:54:12 -475983.187661] AUTODETECT spr round 1 (radius: 5)
[00:55:55 -347972.670013] AUTODETECT spr round 2 (radius: 10)
[00:57:46 -285204.896671] AUTODETECT spr round 3 (radius: 15)
[00:59:53 -239765.136873] AUTODETECT spr round 4 (radius: 20)
[01:02:36 -226111.108743] AUTODETECT spr round 5 (radius: 25)
[01:05:24 -222660.293586] SPR radius for FAST iterations: 25 (autodetect)
[01:05:24 -222660.293586] Model parameter optimization (eps = 3.000000)
[01:05:43 -222454.085105] FAST spr round 1 (radius: 25)
[01:08:28 -198472.780361] FAST spr round 2 (radius: 25)
[01:10:29 -197786.374560] FAST spr round 3 (radius: 25)
[01:12:10 -197717.583659] FAST spr round 4 (radius: 25)
[01:13:36 -197712.612060] FAST spr round 5 (radius: 25)
[01:14:55 -197712.611357] Model parameter optimization (eps = 1.000000)
[01:15:16 -197701.082764] SLOW spr round 1 (radius: 5)
[01:17:14 -197646.107790] SLOW spr round 2 (radius: 5)
[01:19:01 -197645.810394] SLOW spr round 3 (radius: 5)
[01:20:48 -197645.810150] SLOW spr round 4 (radius: 10)
[01:22:37 -197645.810092] SLOW spr round 5 (radius: 15)
[01:26:08 -197645.810064] SLOW spr round 6 (radius: 20)
[01:31:15 -197645.810046] SLOW spr round 7 (radius: 25)
[01:37:17 -197645.810033] Model parameter optimization (eps = 0.100000)

[01:37:23] [worker #0] ML tree search #3, logLikelihood: -197645.770566

[01:37:23 -584608.944140] Initial branch length optimization
[01:37:27 -478956.270289] Model parameter optimization (eps = 10.000000)
[01:38:00] [worker #1] ML tree search #4, logLikelihood: -197683.185897
[01:38:14 -476195.584573] AUTODETECT spr round 1 (radius: 5)
[01:39:56 -347171.350770] AUTODETECT spr round 2 (radius: 10)
[01:41:50 -272912.459823] AUTODETECT spr round 3 (radius: 15)
[01:43:59 -230784.395668] AUTODETECT spr round 4 (radius: 20)
[01:46:35 -223364.052498] AUTODETECT spr round 5 (radius: 25)
[01:49:31 -221778.917286] SPR radius for FAST iterations: 25 (autodetect)
[01:49:31 -221778.917286] Model parameter optimization (eps = 3.000000)
[01:49:49 -221568.162762] FAST spr round 1 (radius: 25)
[01:52:30 -198848.997812] FAST spr round 2 (radius: 25)
[01:54:27 -197736.314401] FAST spr round 3 (radius: 25)
[01:56:06 -197693.351037] FAST spr round 4 (radius: 25)
[01:57:29 -197690.528307] FAST spr round 5 (radius: 25)
[01:58:48 -197690.528298] Model parameter optimization (eps = 1.000000)
[01:59:06 -197674.819139] SLOW spr round 1 (radius: 5)
[02:01:03 -197637.859479] SLOW spr round 2 (radius: 5)
[02:02:49 -197637.858334] SLOW spr round 3 (radius: 10)
[02:04:42 -197637.857731] SLOW spr round 4 (radius: 15)
[02:08:24 -197637.857447] SLOW spr round 5 (radius: 20)
[02:13:39 -197637.857258] SLOW spr round 6 (radius: 25)
[02:19:58 -197637.857130] Model parameter optimization (eps = 0.100000)

[02:20:04] [worker #0] ML tree search #5, logLikelihood: -197637.809198

[02:20:04 -584094.575932] Initial branch length optimization
[02:20:08 -474765.425277] Model parameter optimization (eps = 10.000000)
[02:20:53 -471880.653151] AUTODETECT spr round 1 (radius: 5)
[02:22:35 -340208.351518] AUTODETECT spr round 2 (radius: 10)
[02:24:24 -270692.543758] AUTODETECT spr round 3 (radius: 15)
[02:26:29 -245232.664023] AUTODETECT spr round 4 (radius: 20)
[02:29:17 -222831.841975] AUTODETECT spr round 5 (radius: 25)
[02:32:02 -222317.921488] SPR radius for FAST iterations: 25 (autodetect)
[02:32:03 -222317.921488] Model parameter optimization (eps = 3.000000)
[02:32:29 -222113.463344] FAST spr round 1 (radius: 25)
[02:34:58] [worker #1] ML tree search #6, logLikelihood: -197646.126727
[02:35:16 -198477.365435] FAST spr round 2 (radius: 25)
[02:37:16 -197835.781330] FAST spr round 3 (radius: 25)
[02:38:54 -197773.058628] FAST spr round 4 (radius: 25)
[02:40:18 -197764.739834] FAST spr round 5 (radius: 25)
[02:41:36 -197764.739321] Model parameter optimization (eps = 1.000000)
[02:41:53 -197744.451288] SLOW spr round 1 (radius: 5)
[02:43:53 -197682.119156] SLOW spr round 2 (radius: 5)
[02:45:44 -197666.550242] SLOW spr round 3 (radius: 5)
[02:47:31 -197664.515035] SLOW spr round 4 (radius: 5)
[02:49:15 -197664.514988] SLOW spr round 5 (radius: 10)
[02:51:04 -197664.514986] SLOW spr round 6 (radius: 15)
[02:54:36 -197662.957911] SLOW spr round 7 (radius: 5)
[02:57:00 -197657.590367] SLOW spr round 8 (radius: 5)
[02:59:05 -197655.230475] SLOW spr round 9 (radius: 5)
[03:00:57 -197655.228257] SLOW spr round 10 (radius: 10)
[03:02:50 -197655.226849] SLOW spr round 11 (radius: 15)
[03:06:14 -197655.225955] SLOW spr round 12 (radius: 20)
[03:11:19 -197655.225388] SLOW spr round 13 (radius: 25)
[03:17:20 -197655.225029] Model parameter optimization (eps = 0.100000)

[03:17:29] [worker #0] ML tree search #7, logLikelihood: -197655.071333

[03:17:29 -585165.551894] Initial branch length optimization
[03:17:33 -479173.791439] Model parameter optimization (eps = 10.000000)
[03:18:26 -476504.152703] AUTODETECT spr round 1 (radius: 5)
[03:20:08 -344708.642269] AUTODETECT spr round 2 (radius: 10)
[03:22:00 -268790.136986] AUTODETECT spr round 3 (radius: 15)
[03:24:18 -232889.890171] AUTODETECT spr round 4 (radius: 20)
[03:26:42 -218964.063926] AUTODETECT spr round 5 (radius: 25)
[03:29:28 -215981.722305] SPR radius for FAST iterations: 25 (autodetect)
[03:29:28 -215981.722305] Model parameter optimization (eps = 3.000000)
[03:29:51 -215782.358135] FAST spr round 1 (radius: 25)
[03:32:28 -198427.413551] FAST spr round 2 (radius: 25)
[03:34:30 -197780.231957] FAST spr round 3 (radius: 25)
[03:36:16 -197687.092299] FAST spr round 4 (radius: 25)
[03:37:40 -197684.656107] FAST spr round 5 (radius: 25)
[03:39:00 -197681.621458] FAST spr round 6 (radius: 25)
[03:40:16 -197681.619995] Model parameter optimization (eps = 1.000000)
[03:40:31 -197676.051281] SLOW spr round 1 (radius: 5)
[03:42:07] [worker #1] ML tree search #8, logLikelihood: -197646.611720
[03:42:24 -197638.732027] SLOW spr round 2 (radius: 5)
[03:44:16 -197634.938575] SLOW spr round 3 (radius: 5)
[03:46:02 -197634.937951] SLOW spr round 4 (radius: 10)
[03:47:53 -197634.821930] SLOW spr round 5 (radius: 5)
[03:50:12 -197634.819846] SLOW spr round 6 (radius: 10)
[03:52:21 -197634.819775] SLOW spr round 7 (radius: 15)
[03:55:40 -197634.819727] SLOW spr round 8 (radius: 20)
[04:00:44 -197634.819693] SLOW spr round 9 (radius: 25)
[04:06:35 -197634.819670] Model parameter optimization (eps = 0.100000)

[04:06:45] [worker #0] ML tree search #9, logLikelihood: -197634.704058

[04:06:45 -586058.851111] Initial branch length optimization
[04:06:49 -476832.073808] Model parameter optimization (eps = 10.000000)
[04:07:44 -473823.045963] AUTODETECT spr round 1 (radius: 5)
[04:09:27 -340890.979424] AUTODETECT spr round 2 (radius: 10)
[04:11:19 -268619.574564] AUTODETECT spr round 3 (radius: 15)
[04:13:26 -232335.348427] AUTODETECT spr round 4 (radius: 20)
[04:15:52 -219472.498368] AUTODETECT spr round 5 (radius: 25)
[04:18:50 -216140.266134] SPR radius for FAST iterations: 25 (autodetect)
[04:18:50 -216140.266134] Model parameter optimization (eps = 3.000000)
[04:19:20 -215920.694279] FAST spr round 1 (radius: 25)
[04:21:59 -198619.631636] FAST spr round 2 (radius: 25)
[04:23:59 -197777.760298] FAST spr round 3 (radius: 25)
[04:25:41 -197724.135398] FAST spr round 4 (radius: 25)
[04:27:06 -197718.173010] FAST spr round 5 (radius: 25)
[04:28:24 -197718.172190] Model parameter optimization (eps = 1.000000)
[04:28:42 -197700.041160] SLOW spr round 1 (radius: 5)
[04:30:38 -197640.074619] SLOW spr round 2 (radius: 5)
[04:32:29 -197633.062229] SLOW spr round 3 (radius: 5)
[04:34:14 -197632.162456] SLOW spr round 4 (radius: 5)
[04:35:58 -197632.162243] SLOW spr round 5 (radius: 10)
[04:37:48 -197631.427296] SLOW spr round 6 (radius: 5)
[04:40:04 -197631.424506] SLOW spr round 7 (radius: 10)
[04:42:14 -197631.422612] SLOW spr round 8 (radius: 15)
[04:44:01] [worker #1] ML tree search #10, logLikelihood: -197653.795050
[04:45:38 -197631.038512] SLOW spr round 9 (radius: 5)
[04:48:03 -197631.036374] SLOW spr round 10 (radius: 10)
[04:50:24 -197631.035006] SLOW spr round 11 (radius: 15)
[04:53:45 -197631.034117] SLOW spr round 12 (radius: 20)
[04:59:16 -197631.033535] SLOW spr round 13 (radius: 25)
[05:05:41 -197631.033154] Model parameter optimization (eps = 0.100000)

[05:05:52] [worker #0] ML tree search #11, logLikelihood: -197630.598474

[05:05:52 -583858.155009] Initial branch length optimization
[05:05:57 -473847.709553] Model parameter optimization (eps = 10.000000)
[05:06:53 -471407.154495] AUTODETECT spr round 1 (radius: 5)
[05:08:36 -342437.328231] AUTODETECT spr round 2 (radius: 10)
[05:10:26 -276902.365884] AUTODETECT spr round 3 (radius: 15)
[05:12:30 -247804.916206] AUTODETECT spr round 4 (radius: 20)
[05:14:58 -234344.356369] AUTODETECT spr round 5 (radius: 25)
[05:18:04 -225735.793900] SPR radius for FAST iterations: 25 (autodetect)
[05:18:04 -225735.793900] Model parameter optimization (eps = 3.000000)
[05:18:30 -225516.078689] FAST spr round 1 (radius: 25)
[05:21:15 -198662.304687] FAST spr round 2 (radius: 25)
[05:23:16 -197762.859222] FAST spr round 3 (radius: 25)
[05:24:55 -197719.589912] FAST spr round 4 (radius: 25)
[05:26:22 -197713.873358] FAST spr round 5 (radius: 25)
[05:27:41 -197713.870556] Model parameter optimization (eps = 1.000000)
[05:27:54 -197708.765121] SLOW spr round 1 (radius: 5)
[05:29:49 -197650.543348] SLOW spr round 2 (radius: 5)
[05:31:41 -197644.482147] SLOW spr round 3 (radius: 5)
[05:33:28 -197643.746416] SLOW spr round 4 (radius: 5)
[05:35:13 -197643.744535] SLOW spr round 5 (radius: 10)
[05:35:59] [worker #1] ML tree search #12, logLikelihood: -197652.697818
[05:37:05 -197639.938851] SLOW spr round 6 (radius: 5)
[05:39:23 -197639.919936] SLOW spr round 7 (radius: 10)
[05:41:36 -197639.919201] SLOW spr round 8 (radius: 15)
[05:44:59 -197639.919127] SLOW spr round 9 (radius: 20)
[05:50:18 -197639.919104] SLOW spr round 10 (radius: 25)
[05:56:31 -197639.919089] Model parameter optimization (eps = 0.100000)

[05:56:38] [worker #0] ML tree search #13, logLikelihood: -197639.818333

[05:56:38 -582043.820431] Initial branch length optimization
[05:56:42 -475285.901570] Model parameter optimization (eps = 10.000000)
[05:57:26 -472569.918914] AUTODETECT spr round 1 (radius: 5)
[05:59:10 -347506.931105] AUTODETECT spr round 2 (radius: 10)
[06:01:03 -277507.378795] AUTODETECT spr round 3 (radius: 15)
[06:03:14 -243030.698995] AUTODETECT spr round 4 (radius: 20)
[06:05:53 -224417.613140] AUTODETECT spr round 5 (radius: 25)
[06:08:49 -220512.143501] SPR radius for FAST iterations: 25 (autodetect)
[06:08:49 -220512.143501] Model parameter optimization (eps = 3.000000)
[06:09:14 -220259.955027] FAST spr round 1 (radius: 25)
[06:12:00 -198598.575581] FAST spr round 2 (radius: 25)
[06:14:05 -197774.523690] FAST spr round 3 (radius: 25)
[06:15:51 -197714.890214] FAST spr round 4 (radius: 25)
[06:17:17 -197694.177420] FAST spr round 5 (radius: 25)
[06:17:27] [worker #1] ML tree search #14, logLikelihood: -197641.035278
[06:18:38 -197692.346999] FAST spr round 6 (radius: 25)
[06:19:56 -197691.337929] FAST spr round 7 (radius: 25)
[06:21:12 -197691.336357] Model parameter optimization (eps = 1.000000)
[06:21:30 -197688.901443] SLOW spr round 1 (radius: 5)
[06:23:27 -197640.208949] SLOW spr round 2 (radius: 5)
[06:25:19 -197630.305950] SLOW spr round 3 (radius: 5)
[06:27:05 -197630.301924] SLOW spr round 4 (radius: 10)
[06:28:58 -197630.300175] SLOW spr round 5 (radius: 15)
[06:32:44 -197630.298975] SLOW spr round 6 (radius: 20)
[06:38:23 -197630.298129] SLOW spr round 7 (radius: 25)
[06:44:59 -197630.297530] Model parameter optimization (eps = 0.100000)

[06:45:04] [worker #0] ML tree search #15, logLikelihood: -197630.273624

[06:45:05 -585462.324001] Initial branch length optimization
[06:45:09 -482248.660505] Model parameter optimization (eps = 10.000000)
[06:45:55 -479497.959020] AUTODETECT spr round 1 (radius: 5)
[06:47:39 -343890.099525] AUTODETECT spr round 2 (radius: 10)
[06:49:29 -279508.306853] AUTODETECT spr round 3 (radius: 15)
[06:51:37 -238211.904868] AUTODETECT spr round 4 (radius: 20)
[06:54:10 -224168.195552] AUTODETECT spr round 5 (radius: 25)
[06:57:23 -220161.843870] SPR radius for FAST iterations: 25 (autodetect)
[06:57:23 -220161.843870] Model parameter optimization (eps = 3.000000)
[06:57:50 -219916.314204] FAST spr round 1 (radius: 25)
[07:00:35 -198565.638944] FAST spr round 2 (radius: 25)
[07:02:37 -197792.429163] FAST spr round 3 (radius: 25)
[07:04:20 -197699.016920] FAST spr round 4 (radius: 25)
[07:05:44 -197686.062621] FAST spr round 5 (radius: 25)
[07:07:04 -197679.633181] FAST spr round 6 (radius: 25)
[07:08:20 -197677.414281] FAST spr round 7 (radius: 25)
[07:09:34 -197677.412829] Model parameter optimization (eps = 1.000000)
[07:09:46 -197667.208466] SLOW spr round 1 (radius: 5)
[07:11:38 -197642.119029] SLOW spr round 2 (radius: 5)
[07:13:20] [worker #1] ML tree search #16, logLikelihood: -197651.125907
[07:13:24 -197641.647866] SLOW spr round 3 (radius: 5)
[07:15:09 -197641.646201] SLOW spr round 4 (radius: 10)
[07:17:00 -197641.646034] SLOW spr round 5 (radius: 15)
[07:20:33 -197641.646008] SLOW spr round 6 (radius: 20)
[07:25:47 -197641.645998] SLOW spr round 7 (radius: 25)
[07:32:08 -197641.645992] Model parameter optimization (eps = 0.100000)

[07:32:12] [worker #0] ML tree search #17, logLikelihood: -197641.640440

[07:32:13 -581790.104652] Initial branch length optimization
[07:32:17 -477855.008089] Model parameter optimization (eps = 10.000000)
[07:33:04 -475134.253661] AUTODETECT spr round 1 (radius: 5)
[07:34:47 -335815.356542] AUTODETECT spr round 2 (radius: 10)
[07:36:36 -269717.364733] AUTODETECT spr round 3 (radius: 15)
[07:38:49 -234460.448658] AUTODETECT spr round 4 (radius: 20)
[07:41:17 -227171.899879] AUTODETECT spr round 5 (radius: 25)
[07:44:03 -221969.346894] SPR radius for FAST iterations: 25 (autodetect)
[07:44:03 -221969.346894] Model parameter optimization (eps = 3.000000)
[07:44:40 -221761.849799] FAST spr round 1 (radius: 25)
[07:47:24 -198887.941528] FAST spr round 2 (radius: 25)
[07:49:24 -197787.340362] FAST spr round 3 (radius: 25)
[07:51:08 -197699.288565] FAST spr round 4 (radius: 25)
[07:52:33 -197691.327186] FAST spr round 5 (radius: 25)
[07:53:53 -197690.502790] FAST spr round 6 (radius: 25)
[07:55:09 -197690.501565] Model parameter optimization (eps = 1.000000)
[07:55:19 -197687.532030] SLOW spr round 1 (radius: 5)
[07:57:12 -197652.711693] SLOW spr round 2 (radius: 5)
[07:58:57 -197652.709682] SLOW spr round 3 (radius: 10)
[08:00:47 -197652.709139] SLOW spr round 4 (radius: 15)
[08:04:19 -197652.708954] SLOW spr round 5 (radius: 20)
[08:09:19 -197652.708837] SLOW spr round 6 (radius: 25)
[08:12:27] [worker #1] ML tree search #18, logLikelihood: -197647.343184
[08:15:23 -197652.708761] Model parameter optimization (eps = 0.100000)

[08:15:28] [worker #0] ML tree search #19, logLikelihood: -197652.659702

[09:01:36] [worker #1] ML tree search #20, logLikelihood: -197643.685988

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.133933,0.601337) (0.119871,0.577613) (0.420899,0.743762) (0.325297,1.651331) 
   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: -197630.273624

AIC score: 398186.547249 / AICc score: 4681850.547249 / BIC score: 404951.554677
Free parameters (model + branch lengths): 1463

WARNING: Number of free parameters (K=1463) is larger than alignment size (n=753).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 39 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.bestTreeCollapsed
Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/B5MCN3/3_mltree/B5MCN3.raxml.log

Analysis started: 19-Jul-2021 15:01:18 / finished: 20-Jul-2021 00:02:54

Elapsed time: 32496.275 seconds