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 01-Jul-2021 09:16:45 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/2_msa/Q9P255_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255 --seed 2 --threads 8 --tree rand{20} pars{20}

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

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/2_msa/Q9P255_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 680 sites

WARNING: Sequences tr_A0A2I3GIT9_A0A2I3GIT9_NOMLE_61853 and tr_A0A2I2ZQV4_A0A2I2ZQV4_GORGO_9595 are exactly identical!
WARNING: Sequences tr_G3S228_G3S228_GORGO_9595 and tr_A0A2J8SK65_A0A2J8SK65_PONAB_9601 are exactly identical!
WARNING: Sequences tr_G3S228_G3S228_GORGO_9595 and tr_A0A2I3T1I2_A0A2I3T1I2_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3S228_G3S228_GORGO_9595 and tr_A0A2R9C8X5_A0A2R9C8X5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6UR85_F6UR85_MACMU_9544 and tr_A0A2K6ADH3_A0A2K6ADH3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F7C0K1_F7C0K1_MACMU_9544 and tr_A0A2K6B5R4_A0A2K6B5R4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7DJD1_F7DJD1_MACMU_9544 and tr_G7PZ21_G7PZ21_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7DJD1_F7DJD1_MACMU_9544 and tr_A0A2K6CU82_A0A2K6CU82_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GB84_F7GB84_MACMU_9544 and tr_A0A2K5LBC9_A0A2K5LBC9_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7GB84_F7GB84_MACMU_9544 and tr_A0A2K6BN44_A0A2K6BN44_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GTJ8_F7GTJ8_MACMU_9544 and tr_A0A2K6BJH0_A0A2K6BJH0_MACNE_9545 are exactly identical!
WARNING: Duplicate sequences found: 11

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.raxml.reduced.phy

Alignment comprises 1 partitions and 680 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 680 / 680
Gaps: 20.29 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.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 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 170 / 13600
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -786334.690296] Initial branch length optimization
[00:00:06 -697906.478918] Model parameter optimization (eps = 10.000000)
[00:00:54 -694758.186831] AUTODETECT spr round 1 (radius: 5)
[00:04:02 -574774.569846] AUTODETECT spr round 2 (radius: 10)
[00:07:48 -386550.286761] AUTODETECT spr round 3 (radius: 15)
[00:11:22 -311791.921141] AUTODETECT spr round 4 (radius: 20)
[00:15:57 -294389.344656] AUTODETECT spr round 5 (radius: 25)
[00:20:48 -292479.801241] SPR radius for FAST iterations: 25 (autodetect)
[00:20:48 -292479.801241] Model parameter optimization (eps = 3.000000)
[00:21:18 -292111.678057] FAST spr round 1 (radius: 25)
[00:24:58 -260864.180257] FAST spr round 2 (radius: 25)
[00:27:58 -259724.026159] FAST spr round 3 (radius: 25)
[00:30:40 -259621.412550] FAST spr round 4 (radius: 25)
[00:33:03 -259595.694547] FAST spr round 5 (radius: 25)
[00:35:17 -259577.893897] FAST spr round 6 (radius: 25)
[00:37:26 -259577.893890] Model parameter optimization (eps = 1.000000)
[00:37:43 -259572.386144] SLOW spr round 1 (radius: 5)
[00:40:51 -259478.742809] SLOW spr round 2 (radius: 5)
[00:43:47 -259461.569368] SLOW spr round 3 (radius: 5)
[00:46:33 -259461.569346] SLOW spr round 4 (radius: 10)
[00:49:33 -259461.569345] SLOW spr round 5 (radius: 15)
[00:56:12 -259461.504007] SLOW spr round 6 (radius: 20)
[01:05:08 -259456.700246] SLOW spr round 7 (radius: 5)
[01:08:49 -259452.058427] SLOW spr round 8 (radius: 5)
[01:12:00 -259449.897718] SLOW spr round 9 (radius: 5)
[01:14:52 -259449.897487] SLOW spr round 10 (radius: 10)
[01:15:43] [worker #1] ML tree search #2, logLikelihood: -259485.335562
[01:17:56 -259447.833604] SLOW spr round 11 (radius: 5)
[01:21:15 -259447.833535] SLOW spr round 12 (radius: 10)
[01:24:36 -259447.833535] SLOW spr round 13 (radius: 15)
[01:30:46 -259447.068488] SLOW spr round 14 (radius: 5)
[01:34:18 -259441.661633] SLOW spr round 15 (radius: 5)
[01:37:21 -259441.661442] SLOW spr round 16 (radius: 10)
[01:40:29 -259441.661441] SLOW spr round 17 (radius: 15)
[01:46:55 -259441.661441] SLOW spr round 18 (radius: 20)
[01:56:08 -259441.661441] SLOW spr round 19 (radius: 25)
[02:05:00 -259441.661441] Model parameter optimization (eps = 0.100000)

[02:05:12] [worker #0] ML tree search #1, logLikelihood: -259441.055745

[02:05:13 -786829.065868] Initial branch length optimization
[02:05:18 -697281.385206] Model parameter optimization (eps = 10.000000)
[02:06:11 -694142.216635] AUTODETECT spr round 1 (radius: 5)
[02:09:17 -585232.549826] AUTODETECT spr round 2 (radius: 10)
[02:12:50 -396122.272780] AUTODETECT spr round 3 (radius: 15)
[02:16:40 -308579.375907] AUTODETECT spr round 4 (radius: 20)
[02:21:34 -291670.739856] AUTODETECT spr round 5 (radius: 25)
[02:27:29 -291224.922688] SPR radius for FAST iterations: 25 (autodetect)
[02:27:29 -291224.922688] Model parameter optimization (eps = 3.000000)
[02:27:55 -290870.715478] FAST spr round 1 (radius: 25)
[02:31:42 -260849.594931] FAST spr round 2 (radius: 25)
[02:34:40 -259691.898571] FAST spr round 3 (radius: 25)
[02:37:14 -259616.259488] FAST spr round 4 (radius: 25)
[02:39:35 -259592.997778] FAST spr round 5 (radius: 25)
[02:41:46 -259592.997176] Model parameter optimization (eps = 1.000000)
[02:42:13 -259580.572659] SLOW spr round 1 (radius: 5)
[02:45:15 -259487.774068] SLOW spr round 2 (radius: 5)
[02:48:10 -259468.446434] SLOW spr round 3 (radius: 5)
[02:50:55 -259468.446343] SLOW spr round 4 (radius: 10)
[02:53:52 -259467.479112] SLOW spr round 5 (radius: 5)
[02:57:17 -259459.874986] SLOW spr round 6 (radius: 5)
[03:00:16 -259458.969198] SLOW spr round 7 (radius: 5)
[03:03:05 -259458.968934] SLOW spr round 8 (radius: 10)
[03:03:43] [worker #1] ML tree search #4, logLikelihood: -259425.638068
[03:06:05 -259448.015999] SLOW spr round 9 (radius: 5)
[03:09:35 -259425.401683] SLOW spr round 10 (radius: 5)
[03:12:36 -259421.866886] SLOW spr round 11 (radius: 5)
[03:15:29 -259417.415946] SLOW spr round 12 (radius: 5)
[03:18:16 -259416.349683] SLOW spr round 13 (radius: 5)
[03:21:02 -259416.349675] SLOW spr round 14 (radius: 10)
[03:24:00 -259416.349675] SLOW spr round 15 (radius: 15)
[03:30:34 -259416.349674] SLOW spr round 16 (radius: 20)
[03:39:51 -259416.349674] SLOW spr round 17 (radius: 25)
[03:49:51 -259416.349674] Model parameter optimization (eps = 0.100000)

[03:50:11] [worker #0] ML tree search #3, logLikelihood: -259413.794404

[03:50:11 -782827.651340] Initial branch length optimization
[03:50:17 -695011.248480] Model parameter optimization (eps = 10.000000)
[03:51:05 -691738.488462] AUTODETECT spr round 1 (radius: 5)
[03:54:12 -581040.364595] AUTODETECT spr round 2 (radius: 10)
[03:57:48 -396538.721940] AUTODETECT spr round 3 (radius: 15)
[04:01:25 -313310.014144] AUTODETECT spr round 4 (radius: 20)
[04:06:17 -295452.597381] AUTODETECT spr round 5 (radius: 25)
[04:11:18 -294468.887211] SPR radius for FAST iterations: 25 (autodetect)
[04:11:18 -294468.887211] Model parameter optimization (eps = 3.000000)
[04:11:43 -294035.543965] FAST spr round 1 (radius: 25)
[04:15:27 -260878.391819] FAST spr round 2 (radius: 25)
[04:18:19 -259599.286288] FAST spr round 3 (radius: 25)
[04:20:53 -259539.941260] FAST spr round 4 (radius: 25)
[04:23:10 -259532.120673] FAST spr round 5 (radius: 25)
[04:25:20 -259532.120667] Model parameter optimization (eps = 1.000000)
[04:25:36 -259528.812667] SLOW spr round 1 (radius: 5)
[04:27:13] [worker #1] ML tree search #6, logLikelihood: -259453.109182
[04:28:40 -259453.400902] SLOW spr round 2 (radius: 5)
[04:31:36 -259445.439705] SLOW spr round 3 (radius: 5)
[04:34:23 -259444.016466] SLOW spr round 4 (radius: 5)
[04:37:08 -259444.016437] SLOW spr round 5 (radius: 10)
[04:40:06 -259443.301307] SLOW spr round 6 (radius: 5)
[04:43:28 -259438.834632] SLOW spr round 7 (radius: 5)
[04:46:27 -259437.848885] SLOW spr round 8 (radius: 5)
[04:49:16 -259437.848860] SLOW spr round 9 (radius: 10)
[04:52:14 -259437.848859] SLOW spr round 10 (radius: 15)
[04:58:46 -259437.848859] SLOW spr round 11 (radius: 20)
[05:07:55 -259437.848859] SLOW spr round 12 (radius: 25)
[05:16:31 -259437.848859] Model parameter optimization (eps = 0.100000)

[05:16:38] [worker #0] ML tree search #5, logLikelihood: -259437.762388

[05:16:38 -786507.062345] Initial branch length optimization
[05:16:44 -697037.909965] Model parameter optimization (eps = 10.000000)
[05:17:39 -693851.629497] AUTODETECT spr round 1 (radius: 5)
[05:20:45 -582715.723469] AUTODETECT spr round 2 (radius: 10)
[05:24:18 -404882.372185] AUTODETECT spr round 3 (radius: 15)
[05:27:48 -322675.750029] AUTODETECT spr round 4 (radius: 20)
[05:32:07 -305445.077265] AUTODETECT spr round 5 (radius: 25)
[05:37:11 -301002.106292] SPR radius for FAST iterations: 25 (autodetect)
[05:37:11 -301002.106292] Model parameter optimization (eps = 3.000000)
[05:37:42 -300560.448547] FAST spr round 1 (radius: 25)
[05:41:30 -261218.677484] FAST spr round 2 (radius: 25)
[05:44:25 -259646.493744] FAST spr round 3 (radius: 25)
[05:47:02 -259548.748911] FAST spr round 4 (radius: 25)
[05:49:21 -259534.897669] FAST spr round 5 (radius: 25)
[05:51:33 -259531.070479] FAST spr round 6 (radius: 25)
[05:53:41 -259531.070219] Model parameter optimization (eps = 1.000000)
[05:53:59 -259522.795502] SLOW spr round 1 (radius: 5)
[05:57:00 -259464.761020] SLOW spr round 2 (radius: 5)
[05:59:56 -259439.932644] SLOW spr round 3 (radius: 5)
[06:02:43 -259436.002971] SLOW spr round 4 (radius: 5)
[06:03:47] [worker #1] ML tree search #8, logLikelihood: -259452.810966
[06:05:27 -259436.002939] SLOW spr round 5 (radius: 10)
[06:08:25 -259436.002939] SLOW spr round 6 (radius: 15)
[06:14:56 -259436.002938] SLOW spr round 7 (radius: 20)
[06:24:09 -259425.134342] SLOW spr round 8 (radius: 5)
[06:27:45 -259425.133117] SLOW spr round 9 (radius: 10)
[06:31:28 -259425.133104] SLOW spr round 10 (radius: 15)
[06:37:23 -259425.133104] SLOW spr round 11 (radius: 20)
[06:46:48 -259425.133103] SLOW spr round 12 (radius: 25)
[06:56:01 -259425.133103] Model parameter optimization (eps = 0.100000)

[06:56:16] [worker #0] ML tree search #7, logLikelihood: -259424.229965

[06:56:16 -782838.710177] Initial branch length optimization
[06:56:21 -695504.816152] Model parameter optimization (eps = 10.000000)
[06:57:05 -692311.225762] AUTODETECT spr round 1 (radius: 5)
[07:00:09 -579773.732597] AUTODETECT spr round 2 (radius: 10)
[07:03:42 -378445.945076] AUTODETECT spr round 3 (radius: 15)
[07:07:22 -311143.988933] AUTODETECT spr round 4 (radius: 20)
[07:11:46 -294738.998764] AUTODETECT spr round 5 (radius: 25)
[07:15:36] [worker #1] ML tree search #10, logLikelihood: -259448.770730
[07:16:32 -293138.386422] SPR radius for FAST iterations: 25 (autodetect)
[07:16:32 -293138.386422] Model parameter optimization (eps = 3.000000)
[07:17:02 -292749.106336] FAST spr round 1 (radius: 25)
[07:20:49 -261034.670131] FAST spr round 2 (radius: 25)
[07:23:42 -259639.262420] FAST spr round 3 (radius: 25)
[07:26:17 -259563.836381] FAST spr round 4 (radius: 25)
[07:28:36 -259552.271140] FAST spr round 5 (radius: 25)
[07:30:48 -259551.187106] FAST spr round 6 (radius: 25)
[07:32:57 -259551.186963] Model parameter optimization (eps = 1.000000)
[07:33:12 -259548.112672] SLOW spr round 1 (radius: 5)
[07:36:19 -259461.764596] SLOW spr round 2 (radius: 5)
[07:39:12 -259446.725082] SLOW spr round 3 (radius: 5)
[07:41:58 -259446.725003] SLOW spr round 4 (radius: 10)
[07:45:01 -259433.214346] SLOW spr round 5 (radius: 5)
[07:48:27 -259423.951021] SLOW spr round 6 (radius: 5)
[07:51:28 -259422.732290] SLOW spr round 7 (radius: 5)
[07:54:19 -259422.732197] SLOW spr round 8 (radius: 10)
[07:57:21 -259422.282904] SLOW spr round 9 (radius: 5)
[08:00:46 -259411.799158] SLOW spr round 10 (radius: 5)
[08:03:47 -259406.988530] SLOW spr round 11 (radius: 5)
[08:06:40 -259405.957570] SLOW spr round 12 (radius: 5)
[08:09:26 -259405.957524] SLOW spr round 13 (radius: 10)
[08:12:25 -259405.957524] SLOW spr round 14 (radius: 15)
[08:18:54 -259405.957524] SLOW spr round 15 (radius: 20)
[08:27:50 -259405.957524] SLOW spr round 16 (radius: 25)
[08:37:02 -259405.957524] Model parameter optimization (eps = 0.100000)

[08:37:18] [worker #0] ML tree search #9, logLikelihood: -259404.343759

[08:37:18 -783025.610290] Initial branch length optimization
[08:37:23 -695841.340976] Model parameter optimization (eps = 10.000000)
[08:38:06 -692631.194664] AUTODETECT spr round 1 (radius: 5)
[08:41:14 -578670.865994] AUTODETECT spr round 2 (radius: 10)
[08:41:28] [worker #1] ML tree search #12, logLikelihood: -259425.790080
[08:44:54 -387393.400735] AUTODETECT spr round 3 (radius: 15)
[08:48:33 -316343.675856] AUTODETECT spr round 4 (radius: 20)
[08:53:13 -298560.561334] AUTODETECT spr round 5 (radius: 25)
[08:58:48 -295441.588357] SPR radius for FAST iterations: 25 (autodetect)
[08:58:48 -295441.588357] Model parameter optimization (eps = 3.000000)
[08:59:18 -295035.452813] FAST spr round 1 (radius: 25)
[09:03:00 -260809.996212] FAST spr round 2 (radius: 25)
[09:05:52 -259768.199724] FAST spr round 3 (radius: 25)
[09:08:29 -259600.857085] FAST spr round 4 (radius: 25)
[09:10:53 -259574.099943] FAST spr round 5 (radius: 25)
[09:13:08 -259568.977199] FAST spr round 6 (radius: 25)
[09:15:18 -259568.977190] Model parameter optimization (eps = 1.000000)
[09:15:36 -259565.309582] SLOW spr round 1 (radius: 5)
[09:18:42 -259503.833729] SLOW spr round 2 (radius: 5)
[09:21:42 -259493.451436] SLOW spr round 3 (radius: 5)
[09:24:38 -259477.682414] SLOW spr round 4 (radius: 5)
[09:27:26 -259477.141092] SLOW spr round 5 (radius: 5)
[09:30:12 -259477.140891] SLOW spr round 6 (radius: 10)
[09:33:12 -259477.140889] SLOW spr round 7 (radius: 15)
[09:39:42 -259471.534918] SLOW spr round 8 (radius: 5)
[09:43:18 -259466.210673] SLOW spr round 9 (radius: 5)
[09:46:25 -259459.022039] SLOW spr round 10 (radius: 5)
[09:49:18 -259458.545197] SLOW spr round 11 (radius: 5)
[09:52:07 -259458.545195] SLOW spr round 12 (radius: 10)
[09:55:07 -259458.545195] SLOW spr round 13 (radius: 15)
[10:01:41 -259458.545195] SLOW spr round 14 (radius: 20)
[10:10:57 -259458.545195] SLOW spr round 15 (radius: 25)
[10:19:08] [worker #1] ML tree search #14, logLikelihood: -259427.492014
[10:20:41 -259458.545195] Model parameter optimization (eps = 0.100000)

[10:20:58] [worker #0] ML tree search #11, logLikelihood: -259458.276008

[10:20:58 -783929.411280] Initial branch length optimization
[10:21:03 -695067.122608] Model parameter optimization (eps = 10.000000)
[10:21:47 -691844.486179] AUTODETECT spr round 1 (radius: 5)
[10:24:56 -580787.185627] AUTODETECT spr round 2 (radius: 10)
[10:28:37 -387947.337444] AUTODETECT spr round 3 (radius: 15)
[10:32:10 -311344.161748] AUTODETECT spr round 4 (radius: 20)
[10:36:23 -295084.065872] AUTODETECT spr round 5 (radius: 25)
[10:41:13 -289789.369969] SPR radius for FAST iterations: 25 (autodetect)
[10:41:13 -289789.369969] Model parameter optimization (eps = 3.000000)
[10:41:37 -289366.868047] FAST spr round 1 (radius: 25)
[10:45:22 -261133.503965] FAST spr round 2 (radius: 25)
[10:48:21 -260053.418305] FAST spr round 3 (radius: 25)
[10:51:06 -259619.541059] FAST spr round 4 (radius: 25)
[10:53:28 -259597.468538] FAST spr round 5 (radius: 25)
[10:55:44 -259589.302931] FAST spr round 6 (radius: 25)
[10:57:56 -259584.815826] FAST spr round 7 (radius: 25)
[11:00:04 -259584.815499] Model parameter optimization (eps = 1.000000)
[11:00:30 -259567.348676] SLOW spr round 1 (radius: 5)
[11:03:31 -259469.004788] SLOW spr round 2 (radius: 5)
[11:06:28 -259462.193571] SLOW spr round 3 (radius: 5)
[11:09:18 -259461.314709] SLOW spr round 4 (radius: 5)
[11:12:05 -259461.314633] SLOW spr round 5 (radius: 10)
[11:15:03 -259460.454320] SLOW spr round 6 (radius: 5)
[11:18:26 -259459.600664] SLOW spr round 7 (radius: 5)
[11:21:26 -259459.600588] SLOW spr round 8 (radius: 10)
[11:24:30 -259459.600587] SLOW spr round 9 (radius: 15)
[11:30:48 -259452.214883] SLOW spr round 10 (radius: 5)
[11:34:27 -259432.916919] SLOW spr round 11 (radius: 5)
[11:37:34 -259429.857790] SLOW spr round 12 (radius: 5)
[11:40:26 -259429.857618] SLOW spr round 13 (radius: 10)
[11:43:28 -259429.857513] SLOW spr round 14 (radius: 15)
[11:49:50 -259429.857431] SLOW spr round 15 (radius: 20)
[11:58:54 -259429.857371] SLOW spr round 16 (radius: 25)
[12:07:20] [worker #1] ML tree search #16, logLikelihood: -259441.526309
[12:08:10 -259429.857330] Model parameter optimization (eps = 0.100000)

[12:08:29] [worker #0] ML tree search #13, logLikelihood: -259424.253848

[12:08:29 -786898.662847] Initial branch length optimization
[12:08:35 -697695.787207] Model parameter optimization (eps = 10.000000)
[12:09:41 -694477.860692] AUTODETECT spr round 1 (radius: 5)
[12:12:50 -586592.699239] AUTODETECT spr round 2 (radius: 10)
[12:16:27 -397655.032778] AUTODETECT spr round 3 (radius: 15)
[12:20:05 -313022.711546] AUTODETECT spr round 4 (radius: 20)
[12:24:42 -296460.619080] AUTODETECT spr round 5 (radius: 25)
[12:29:51 -293317.452962] SPR radius for FAST iterations: 25 (autodetect)
[12:29:51 -293317.452962] Model parameter optimization (eps = 3.000000)
[12:30:03 -293292.429240] FAST spr round 1 (radius: 25)
[12:33:53 -261507.801816] FAST spr round 2 (radius: 25)
[12:36:54 -259941.101820] FAST spr round 3 (radius: 25)
[12:39:39 -259822.025238] FAST spr round 4 (radius: 25)
[12:42:04 -259796.983593] FAST spr round 5 (radius: 25)
[12:44:20 -259786.974656] FAST spr round 6 (radius: 25)
[12:46:29 -259786.974648] Model parameter optimization (eps = 1.000000)
[12:47:05 -259527.826137] SLOW spr round 1 (radius: 5)
[12:50:18 -259474.286835] SLOW spr round 2 (radius: 5)
[12:53:21 -259448.944191] SLOW spr round 3 (radius: 5)
[12:56:11 -259444.459620] SLOW spr round 4 (radius: 5)
[12:58:55 -259444.459566] SLOW spr round 5 (radius: 10)
[13:01:53 -259438.966320] SLOW spr round 6 (radius: 5)
[13:05:17 -259431.855764] SLOW spr round 7 (radius: 5)
[13:08:16 -259430.590667] SLOW spr round 8 (radius: 5)
[13:11:06 -259430.590558] SLOW spr round 9 (radius: 10)
[13:14:05 -259430.590556] SLOW spr round 10 (radius: 15)
[13:20:19] [worker #1] ML tree search #18, logLikelihood: -259420.171117
[13:20:32 -259430.590554] SLOW spr round 11 (radius: 20)
[13:29:49 -259430.590552] SLOW spr round 12 (radius: 25)
[13:38:58 -259430.590550] Model parameter optimization (eps = 0.100000)

[13:39:04] [worker #0] ML tree search #15, logLikelihood: -259430.579309

[13:39:04 -783312.683211] Initial branch length optimization
[13:39:11 -695942.143920] Model parameter optimization (eps = 10.000000)
[13:39:54 -692764.545523] AUTODETECT spr round 1 (radius: 5)
[13:43:03 -580907.436832] AUTODETECT spr round 2 (radius: 10)
[13:46:38 -390688.771717] AUTODETECT spr round 3 (radius: 15)
[13:50:09 -318151.656999] AUTODETECT spr round 4 (radius: 20)
[13:54:07 -300215.729121] AUTODETECT spr round 5 (radius: 25)
[13:58:48 -297246.825585] SPR radius for FAST iterations: 25 (autodetect)
[13:58:48 -297246.825585] Model parameter optimization (eps = 3.000000)
[13:59:14 -296868.924348] FAST spr round 1 (radius: 25)
[14:02:55 -260881.616885] FAST spr round 2 (radius: 25)
[14:05:49 -259637.653672] FAST spr round 3 (radius: 25)
[14:08:25 -259550.240889] FAST spr round 4 (radius: 25)
[14:10:46 -259534.437032] FAST spr round 5 (radius: 25)
[14:13:00 -259513.487561] FAST spr round 6 (radius: 25)
[14:15:12 -259513.487560] Model parameter optimization (eps = 1.000000)
[14:15:30 -259510.668069] SLOW spr round 1 (radius: 5)
[14:18:39 -259451.957163] SLOW spr round 2 (radius: 5)
[14:21:31 -259450.939757] SLOW spr round 3 (radius: 5)
[14:24:19 -259450.939755] SLOW spr round 4 (radius: 10)
[14:27:14 -259450.939755] SLOW spr round 5 (radius: 15)
[14:33:37 -259450.939755] SLOW spr round 6 (radius: 20)
[14:43:06 -259450.939755] SLOW spr round 7 (radius: 25)
[14:50:12] [worker #1] ML tree search #20, logLikelihood: -259431.809555
[14:53:09 -259450.939755] Model parameter optimization (eps = 0.100000)

[14:53:23] [worker #0] ML tree search #17, logLikelihood: -259450.179588

[14:53:23 -784102.378865] Initial branch length optimization
[14:53:29 -697358.465171] Model parameter optimization (eps = 10.000000)
[14:54:14 -694187.802004] AUTODETECT spr round 1 (radius: 5)
[14:57:19 -588383.211934] AUTODETECT spr round 2 (radius: 10)
[15:00:54 -390778.505270] AUTODETECT spr round 3 (radius: 15)
[15:04:26 -315000.751435] AUTODETECT spr round 4 (radius: 20)
[15:08:34 -299307.538152] AUTODETECT spr round 5 (radius: 25)
[15:13:41 -296313.694303] SPR radius for FAST iterations: 25 (autodetect)
[15:13:41 -296313.694303] Model parameter optimization (eps = 3.000000)
[15:14:06 -295863.782375] FAST spr round 1 (radius: 25)
[15:17:39 -260849.824843] FAST spr round 2 (radius: 25)
[15:20:28 -259699.525154] FAST spr round 3 (radius: 25)
[15:23:01 -259616.940247] FAST spr round 4 (radius: 25)
[15:25:18 -259559.575448] FAST spr round 5 (radius: 25)
[15:27:30 -259555.048692] FAST spr round 6 (radius: 25)
[15:29:36 -259555.048332] Model parameter optimization (eps = 1.000000)
[15:29:57 -259544.457866] SLOW spr round 1 (radius: 5)
[15:32:55 -259471.025809] SLOW spr round 2 (radius: 5)
[15:35:46 -259461.985982] SLOW spr round 3 (radius: 5)
[15:38:30 -259461.453139] SLOW spr round 4 (radius: 5)
[15:41:13 -259461.452562] SLOW spr round 5 (radius: 10)
[15:44:08 -259461.452541] SLOW spr round 6 (radius: 15)
[15:50:35 -259461.452534] SLOW spr round 7 (radius: 20)
[15:59:20 -259461.452530] SLOW spr round 8 (radius: 25)
[16:08:11 -259461.452527] Model parameter optimization (eps = 0.100000)

[16:08:17] [worker #0] ML tree search #19, logLikelihood: -259461.363212


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.158073,0.462650) (0.152722,0.840303) (0.347311,0.778882) (0.341894,1.544398) 
   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: -259404.343759

AIC score: 522818.687518 / AICc score: 8566878.687518 / BIC score: 531885.483579
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=680).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P255/3_mltree/Q9P255.raxml.log

Analysis started: 01-Jul-2021 09:16:45 / finished: 02-Jul-2021 01:25:03

Elapsed time: 58097.925 seconds

Consumed energy: 5254.958 Wh (= 26 km in an electric car, or 131 km with an e-scooter!)