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 04-Jul-2021 07:07:37 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/2_msa/O95672_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/3_mltree/O95672 --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/O95672/2_msa/O95672_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 756 sites

WARNING: Sequences tr_A0A2I3ST75_A0A2I3ST75_PANTR_9598 and tr_A0A2R8ZX15_A0A2R8ZX15_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5QKC2_A0A1D5QKC2_MACMU_9544 and tr_G7NZK8_G7NZK8_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A1D5QKC2_A0A1D5QKC2_MACMU_9544 and tr_A0A2K5MZ14_A0A2K5MZ14_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A1D5QKC2_A0A1D5QKC2_MACMU_9544 and tr_A0A2K6E3V2_A0A2K6E3V2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A1D5QKC2_A0A1D5QKC2_MACMU_9544 and tr_A0A2K6A4Q3_A0A2K6A4Q3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A1D5QMJ9_A0A1D5QMJ9_MACMU_9544 and tr_A0A0D9S8B6_A0A0D9S8B6_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A1D5QMJ9_A0A1D5QMJ9_MACMU_9544 and tr_A0A2K6BPS4_A0A2K6BPS4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A1D5QMJ9_A0A1D5QMJ9_MACMU_9544 and tr_A0A2K6AIN5_A0A2K6AIN5_MANLE_9568 are exactly identical!
WARNING: Sequences tr_H9H3W2_H9H3W2_MACMU_9544 and tr_A0A2K6DWV5_A0A2K6DWV5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G7Q2D1_G7Q2D1_MACFA_9541 and tr_A0A2K6BMB4_A0A2K6BMB4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A0V1CNS6_A0A0V1CNS6_TRIBR_45882 and tr_A0A0V0WJN5_A0A0V0WJN5_9BILA_92179 are exactly identical!
WARNING: Sequences tr_A0A0V1CNS6_A0A0V1CNS6_TRIBR_45882 and tr_A0A0V1L7Z3_A0A0V1L7Z3_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V1CNS6_A0A0V1CNS6_TRIBR_45882 and tr_A0A0V1NQX7_A0A0V1NQX7_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V1CNS6_A0A0V1CNS6_TRIBR_45882 and tr_A0A0V0UBP1_A0A0V0UBP1_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A0V0WMT9_A0A0V0WMT9_9BILA_92179 and tr_A0A0V1A8C9_A0A0V1A8C9_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A1S3HMA4_A0A1S3HMA4_LINUN_7574 and tr_A0A1S3HMB4_A0A1S3HMB4_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A1S3HMA4_A0A1S3HMA4_LINUN_7574 and tr_A0A1S3HMH7_A0A1S3HMH7_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A1S3HMA4_A0A1S3HMA4_LINUN_7574 and tr_A0A1S3HNW2_A0A1S3HNW2_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A2D0SU77_A0A2D0SU77_ICTPU_7998 and tr_A0A2D0SUQ0_A0A2D0SUQ0_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0SU77_A0A2D0SU77_ICTPU_7998 and tr_A0A2D0SVA0_A0A2D0SVA0_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2K5LQG5_A0A2K5LQG5_CERAT_9531 and tr_A0A2K5ZAA4_A0A2K5ZAA4_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K5M322_A0A2K5M322_CERAT_9531 and tr_A0A2K5ZQZ1_A0A2K5ZQZ1_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 22

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/O95672/3_mltree/O95672.raxml.reduced.phy

Alignment comprises 1 partitions and 756 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 756 / 756
Gaps: 7.89 %
Invariant sites: 0.13 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/3_mltree/O95672.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 / 189 / 15120
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1363136.889508] Initial branch length optimization
[00:00:09 -1169809.924794] Model parameter optimization (eps = 10.000000)
[00:00:51 -1166708.790601] AUTODETECT spr round 1 (radius: 5)
[00:04:19 -797774.410464] AUTODETECT spr round 2 (radius: 10)
[00:08:04 -568820.354566] AUTODETECT spr round 3 (radius: 15)
[00:12:05 -451160.507934] AUTODETECT spr round 4 (radius: 20)
[00:16:47 -421946.672515] AUTODETECT spr round 5 (radius: 25)
[00:21:41 -417543.580958] SPR radius for FAST iterations: 25 (autodetect)
[00:21:41 -417543.580958] Model parameter optimization (eps = 3.000000)
[00:22:09 -417261.610954] FAST spr round 1 (radius: 25)
[00:26:24 -372408.869047] FAST spr round 2 (radius: 25)
[00:29:24 -370842.335508] FAST spr round 3 (radius: 25)
[00:32:09 -370672.457908] FAST spr round 4 (radius: 25)
[00:34:32 -370645.238759] FAST spr round 5 (radius: 25)
[00:36:44 -370644.053496] FAST spr round 6 (radius: 25)
[00:38:53 -370644.053491] Model parameter optimization (eps = 1.000000)
[00:39:10 -370637.056045] SLOW spr round 1 (radius: 5)
[00:42:25 -370577.876483] SLOW spr round 2 (radius: 5)
[00:45:30 -370569.308521] SLOW spr round 3 (radius: 5)
[00:48:28 -370566.534839] SLOW spr round 4 (radius: 5)
[00:51:23 -370566.534838] SLOW spr round 5 (radius: 10)
[00:54:24 -370542.913878] SLOW spr round 6 (radius: 5)
[00:58:15 -370539.988078] SLOW spr round 7 (radius: 5)
[01:01:35 -370539.987793] SLOW spr round 8 (radius: 10)
[01:04:47 -370539.987792] SLOW spr round 9 (radius: 15)
[01:10:16 -370539.987792] SLOW spr round 10 (radius: 20)
[01:20:35 -370539.987792] SLOW spr round 11 (radius: 25)
[01:28:39] [worker #1] ML tree search #2, logLikelihood: -370545.868924
[01:32:20 -370539.987792] Model parameter optimization (eps = 0.100000)

[01:32:28] [worker #0] ML tree search #1, logLikelihood: -370539.460980

[01:32:28 -1364911.600819] Initial branch length optimization
[01:32:34 -1168961.021876] Model parameter optimization (eps = 10.000000)
[01:33:17 -1166111.583805] AUTODETECT spr round 1 (radius: 5)
[01:36:03 -807890.657010] AUTODETECT spr round 2 (radius: 10)
[01:39:02 -581433.159168] AUTODETECT spr round 3 (radius: 15)
[01:42:25 -493383.799454] AUTODETECT spr round 4 (radius: 20)
[01:46:38 -430687.217315] AUTODETECT spr round 5 (radius: 25)
[01:51:54 -423054.770197] SPR radius for FAST iterations: 25 (autodetect)
[01:51:54 -423054.770197] Model parameter optimization (eps = 3.000000)
[01:52:16 -422870.721439] FAST spr round 1 (radius: 25)
[01:56:05 -372330.118372] FAST spr round 2 (radius: 25)
[01:58:39 -370778.422791] FAST spr round 3 (radius: 25)
[02:01:06 -370673.331661] FAST spr round 4 (radius: 25)
[02:03:15 -370630.829279] FAST spr round 5 (radius: 25)
[02:05:05 -370630.829154] Model parameter optimization (eps = 1.000000)
[02:05:20 -370623.458915] SLOW spr round 1 (radius: 5)
[02:08:24 -370565.967754] SLOW spr round 2 (radius: 5)
[02:11:14 -370561.174446] SLOW spr round 3 (radius: 5)
[02:14:02 -370560.520487] SLOW spr round 4 (radius: 5)
[02:16:47 -370558.598294] SLOW spr round 5 (radius: 5)
[02:19:26 -370558.598178] SLOW spr round 6 (radius: 10)
[02:22:11 -370558.598174] SLOW spr round 7 (radius: 15)
[02:27:21 -370558.598174] SLOW spr round 8 (radius: 20)
[02:36:07 -370558.598174] SLOW spr round 9 (radius: 25)
[02:47:55 -370558.598174] Model parameter optimization (eps = 0.100000)

[02:48:06] [worker #0] ML tree search #3, logLikelihood: -370558.313699

[02:48:06 -1362693.603746] Initial branch length optimization
[02:48:12 -1165013.769166] Model parameter optimization (eps = 10.000000)
[02:48:53 -1161985.299463] AUTODETECT spr round 1 (radius: 5)
[02:50:43] [worker #1] ML tree search #4, logLikelihood: -370546.875517
[02:51:55 -806976.814667] AUTODETECT spr round 2 (radius: 10)
[02:55:14 -597322.134922] AUTODETECT spr round 3 (radius: 15)
[02:59:03 -520609.250906] AUTODETECT spr round 4 (radius: 20)
[03:03:26 -481723.001221] AUTODETECT spr round 5 (radius: 25)
[03:09:31 -440014.249556] SPR radius for FAST iterations: 25 (autodetect)
[03:09:31 -440014.249556] Model parameter optimization (eps = 3.000000)
[03:09:56 -439702.331020] FAST spr round 1 (radius: 25)
[03:14:04 -375548.188451] FAST spr round 2 (radius: 25)
[03:16:58 -371033.172790] FAST spr round 3 (radius: 25)
[03:19:25 -370682.466938] FAST spr round 4 (radius: 25)
[03:21:32 -370673.673458] FAST spr round 5 (radius: 25)
[03:23:33 -370673.673229] Model parameter optimization (eps = 1.000000)
[03:23:45 -370671.311258] SLOW spr round 1 (radius: 5)
[03:26:44 -370582.467959] SLOW spr round 2 (radius: 5)
[03:29:36 -370574.033287] SLOW spr round 3 (radius: 5)
[03:32:19 -370573.918948] SLOW spr round 4 (radius: 5)
[03:35:00 -370573.917105] SLOW spr round 5 (radius: 10)
[03:37:48 -370572.997162] SLOW spr round 6 (radius: 5)
[03:41:08 -370568.528246] SLOW spr round 7 (radius: 5)
[03:43:54 -370568.528245] SLOW spr round 8 (radius: 10)
[03:46:35 -370568.528245] SLOW spr round 9 (radius: 15)
[03:51:09 -370568.528245] SLOW spr round 10 (radius: 20)
[04:00:32] [worker #1] ML tree search #6, logLikelihood: -370550.753181
[04:01:28 -370568.528245] SLOW spr round 11 (radius: 25)
[04:14:10 -370568.528245] Model parameter optimization (eps = 0.100000)

[04:14:22] [worker #0] ML tree search #5, logLikelihood: -370568.346470

[04:14:22 -1356410.617950] Initial branch length optimization
[04:14:30 -1168119.598809] Model parameter optimization (eps = 10.000000)
[04:15:29 -1165035.662582] AUTODETECT spr round 1 (radius: 5)
[04:18:48 -796249.389676] AUTODETECT spr round 2 (radius: 10)
[04:22:21 -581608.552368] AUTODETECT spr round 3 (radius: 15)
[04:26:22 -471579.680242] AUTODETECT spr round 4 (radius: 20)
[04:31:18 -423892.159027] AUTODETECT spr round 5 (radius: 25)
[04:36:46 -421397.296298] SPR radius for FAST iterations: 25 (autodetect)
[04:36:46 -421397.296298] Model parameter optimization (eps = 3.000000)
[04:37:14 -421128.676814] FAST spr round 1 (radius: 25)
[04:41:56 -373055.604697] FAST spr round 2 (radius: 25)
[04:45:18 -370751.663479] FAST spr round 3 (radius: 25)
[04:48:09 -370645.366240] FAST spr round 4 (radius: 25)
[04:50:27 -370635.843620] FAST spr round 5 (radius: 25)
[04:52:41 -370635.843499] Model parameter optimization (eps = 1.000000)
[04:53:03 -370630.957487] SLOW spr round 1 (radius: 5)
[04:56:25 -370576.539379] SLOW spr round 2 (radius: 5)
[04:59:31 -370567.374530] SLOW spr round 3 (radius: 5)
[05:02:29 -370566.046697] SLOW spr round 4 (radius: 5)
[05:05:25 -370566.046678] SLOW spr round 5 (radius: 10)
[05:08:30 -370566.046678] SLOW spr round 6 (radius: 15)
[05:14:28 -370566.046678] SLOW spr round 7 (radius: 20)
[05:25:12 -370566.046678] SLOW spr round 8 (radius: 25)
[05:26:24] [worker #1] ML tree search #8, logLikelihood: -370564.869508
[05:38:56 -370566.046678] Model parameter optimization (eps = 0.100000)

[05:39:06] [worker #0] ML tree search #7, logLikelihood: -370565.743501

[05:39:06 -1353971.682138] Initial branch length optimization
[05:39:16 -1157687.365089] Model parameter optimization (eps = 10.000000)
[05:40:17 -1154818.130975] AUTODETECT spr round 1 (radius: 5)
[05:43:35 -800112.360421] AUTODETECT spr round 2 (radius: 10)
[05:47:16 -600626.930282] AUTODETECT spr round 3 (radius: 15)
[05:51:34 -473004.302989] AUTODETECT spr round 4 (radius: 20)
[05:56:19 -430460.839123] AUTODETECT spr round 5 (radius: 25)
[06:01:42 -427452.542127] SPR radius for FAST iterations: 25 (autodetect)
[06:01:42 -427452.542127] Model parameter optimization (eps = 3.000000)
[06:02:08 -427195.186547] FAST spr round 1 (radius: 25)
[06:06:35 -372852.052438] FAST spr round 2 (radius: 25)
[06:09:41 -370822.371760] FAST spr round 3 (radius: 25)
[06:12:21 -370684.458106] FAST spr round 4 (radius: 25)
[06:14:39 -370678.619553] FAST spr round 5 (radius: 25)
[06:16:53 -370643.159248] FAST spr round 6 (radius: 25)
[06:19:01 -370643.159211] Model parameter optimization (eps = 1.000000)
[06:19:20 -370640.985014] SLOW spr round 1 (radius: 5)
[06:22:37 -370586.847273] SLOW spr round 2 (radius: 5)
[06:25:51 -370572.576748] SLOW spr round 3 (radius: 5)
[06:28:48 -370570.841238] SLOW spr round 4 (radius: 5)
[06:31:44 -370569.216281] SLOW spr round 5 (radius: 5)
[06:34:37 -370569.216135] SLOW spr round 6 (radius: 10)
[06:37:38 -370568.355264] SLOW spr round 7 (radius: 5)
[06:41:30 -370563.082811] SLOW spr round 8 (radius: 5)
[06:44:47 -370563.082810] SLOW spr round 9 (radius: 10)
[06:47:57 -370563.082810] SLOW spr round 10 (radius: 15)
[06:51:11] [worker #1] ML tree search #10, logLikelihood: -370557.799674
[06:53:29 -370563.082810] SLOW spr round 11 (radius: 20)
[07:04:11 -370563.082810] SLOW spr round 12 (radius: 25)
[07:17:18 -370563.082810] Model parameter optimization (eps = 0.100000)

[07:17:35] [worker #0] ML tree search #9, logLikelihood: -370562.820499

[07:17:35 -1363439.977953] Initial branch length optimization
[07:17:45 -1167591.337242] Model parameter optimization (eps = 10.000000)
[07:18:36 -1164674.498041] AUTODETECT spr round 1 (radius: 5)
[07:21:57 -805636.347191] AUTODETECT spr round 2 (radius: 10)
[07:25:45 -571988.813634] AUTODETECT spr round 3 (radius: 15)
[07:29:53 -484113.197434] AUTODETECT spr round 4 (radius: 20)
[07:34:23 -427427.157214] AUTODETECT spr round 5 (radius: 25)
[07:40:25 -417468.109377] SPR radius for FAST iterations: 25 (autodetect)
[07:40:25 -417468.109377] Model parameter optimization (eps = 3.000000)
[07:40:51 -417278.260600] FAST spr round 1 (radius: 25)
[07:45:32 -373305.154781] FAST spr round 2 (radius: 25)
[07:48:35 -370855.110522] FAST spr round 3 (radius: 25)
[07:51:15 -370694.041519] FAST spr round 4 (radius: 25)
[07:53:40 -370682.907867] FAST spr round 5 (radius: 25)
[07:55:56 -370680.328671] FAST spr round 6 (radius: 25)
[07:58:10 -370676.208178] FAST spr round 7 (radius: 25)
[08:00:22 -370674.647391] FAST spr round 8 (radius: 25)
[08:02:31 -370674.647390] Model parameter optimization (eps = 1.000000)
[08:02:45 -370671.544833] SLOW spr round 1 (radius: 5)
[08:05:55 -370586.950571] SLOW spr round 2 (radius: 5)
[08:09:02 -370572.243133] SLOW spr round 3 (radius: 5)
[08:12:01 -370568.898549] SLOW spr round 4 (radius: 5)
[08:15:00 -370566.742518] SLOW spr round 5 (radius: 5)
[08:17:55 -370566.742515] SLOW spr round 6 (radius: 10)
[08:20:59 -370566.742515] SLOW spr round 7 (radius: 15)
[08:22:39] [worker #1] ML tree search #12, logLikelihood: -370547.529075
[08:26:59 -370566.742515] SLOW spr round 8 (radius: 20)
[08:37:41 -370566.742515] SLOW spr round 9 (radius: 25)
[08:51:20 -370566.742515] Model parameter optimization (eps = 0.100000)

[08:51:33] [worker #0] ML tree search #11, logLikelihood: -370566.632310

[08:51:33 -1350814.077175] Initial branch length optimization
[08:51:42 -1154426.608769] Model parameter optimization (eps = 10.000000)
[08:52:23 -1151569.858757] AUTODETECT spr round 1 (radius: 5)
[08:55:45 -814965.799451] AUTODETECT spr round 2 (radius: 10)
[08:59:28 -583819.480992] AUTODETECT spr round 3 (radius: 15)
[09:03:41 -496804.508957] AUTODETECT spr round 4 (radius: 20)
[09:07:49 -434956.265933] AUTODETECT spr round 5 (radius: 25)
[09:13:31 -430070.687217] SPR radius for FAST iterations: 25 (autodetect)
[09:13:31 -430070.687217] Model parameter optimization (eps = 3.000000)
[09:13:56 -429850.060775] FAST spr round 1 (radius: 25)
[09:18:13 -373000.900912] FAST spr round 2 (radius: 25)
[09:21:18 -370876.108683] FAST spr round 3 (radius: 25)
[09:23:59 -370684.251973] FAST spr round 4 (radius: 25)
[09:26:20 -370658.256826] FAST spr round 5 (radius: 25)
[09:28:33 -370650.408660] FAST spr round 6 (radius: 25)
[09:30:40 -370650.408543] Model parameter optimization (eps = 1.000000)
[09:30:54 -370642.102621] SLOW spr round 1 (radius: 5)
[09:34:09 -370561.136336] SLOW spr round 2 (radius: 5)
[09:37:20 -370548.873705] SLOW spr round 3 (radius: 5)
[09:40:17 -370548.873683] SLOW spr round 4 (radius: 10)
[09:40:37] [worker #1] ML tree search #14, logLikelihood: -370549.159815
[09:43:20 -370548.873683] SLOW spr round 5 (radius: 15)
[09:49:12 -370548.873683] SLOW spr round 6 (radius: 20)
[09:59:19 -370548.873683] SLOW spr round 7 (radius: 25)
[10:12:12 -370548.873683] Model parameter optimization (eps = 0.100000)

[10:12:21] [worker #0] ML tree search #13, logLikelihood: -370548.670939

[10:12:21 -1354889.744829] Initial branch length optimization
[10:12:28 -1166615.602414] Model parameter optimization (eps = 10.000000)
[10:13:25 -1163458.815077] AUTODETECT spr round 1 (radius: 5)
[10:16:47 -805459.448065] AUTODETECT spr round 2 (radius: 10)
[10:20:23 -562261.600063] AUTODETECT spr round 3 (radius: 15)
[10:24:13 -457258.452059] AUTODETECT spr round 4 (radius: 20)
[10:28:58 -421419.800234] AUTODETECT spr round 5 (radius: 25)
[10:35:01 -418923.158495] SPR radius for FAST iterations: 25 (autodetect)
[10:35:01 -418923.158495] Model parameter optimization (eps = 3.000000)
[10:35:29 -418649.516518] FAST spr round 1 (radius: 25)
[10:40:04 -372247.870986] FAST spr round 2 (radius: 25)
[10:43:14 -370738.236722] FAST spr round 3 (radius: 25)
[10:45:54 -370643.771745] FAST spr round 4 (radius: 25)
[10:48:18 -370628.644393] FAST spr round 5 (radius: 25)
[10:50:32 -370628.644260] Model parameter optimization (eps = 1.000000)
[10:50:43 -370625.725603] SLOW spr round 1 (radius: 5)
[10:54:10 -370571.616566] SLOW spr round 2 (radius: 5)
[10:57:14 -370570.551900] SLOW spr round 3 (radius: 5)
[11:00:13 -370570.550982] SLOW spr round 4 (radius: 10)
[11:03:17 -370569.641048] SLOW spr round 5 (radius: 5)
[11:07:17 -370564.563537] SLOW spr round 6 (radius: 5)
[11:10:36 -370564.563523] SLOW spr round 7 (radius: 10)
[11:13:49 -370559.759181] SLOW spr round 8 (radius: 5)
[11:17:35 -370557.948887] SLOW spr round 9 (radius: 5)
[11:20:52 -370557.948410] SLOW spr round 10 (radius: 10)
[11:24:02 -370557.948406] SLOW spr round 11 (radius: 15)
[11:29:33 -370557.948406] SLOW spr round 12 (radius: 20)
[11:30:41] [worker #1] ML tree search #16, logLikelihood: -370555.187524
[11:39:56 -370557.948406] SLOW spr round 13 (radius: 25)
[11:53:14 -370557.948406] Model parameter optimization (eps = 0.100000)

[11:53:32] [worker #0] ML tree search #15, logLikelihood: -370556.887485

[11:53:32 -1358688.377020] Initial branch length optimization
[11:53:39 -1161036.987178] Model parameter optimization (eps = 10.000000)
[11:54:25 -1158305.963062] AUTODETECT spr round 1 (radius: 5)
[11:57:45 -807579.155744] AUTODETECT spr round 2 (radius: 10)
[12:01:25 -580819.157899] AUTODETECT spr round 3 (radius: 15)
[12:05:41 -458784.257936] AUTODETECT spr round 4 (radius: 20)
[12:10:58 -422456.261700] AUTODETECT spr round 5 (radius: 25)
[12:17:35 -421311.254269] SPR radius for FAST iterations: 25 (autodetect)
[12:17:35 -421311.254269] Model parameter optimization (eps = 3.000000)
[12:18:01 -421066.238337] FAST spr round 1 (radius: 25)
[12:22:27 -372390.218130] FAST spr round 2 (radius: 25)
[12:25:25 -370713.356853] FAST spr round 3 (radius: 25)
[12:28:02 -370641.138920] FAST spr round 4 (radius: 25)
[12:30:21 -370639.523997] FAST spr round 5 (radius: 25)
[12:32:32 -370639.523885] Model parameter optimization (eps = 1.000000)
[12:32:45 -370633.649505] SLOW spr round 1 (radius: 5)
[12:36:04 -370588.679654] SLOW spr round 2 (radius: 5)
[12:39:13 -370564.469746] SLOW spr round 3 (radius: 5)
[12:42:12 -370560.553251] SLOW spr round 4 (radius: 5)
[12:45:07 -370560.553050] SLOW spr round 5 (radius: 10)
[12:48:09 -370550.398038] SLOW spr round 6 (radius: 5)
[12:51:55 -370550.398030] SLOW spr round 7 (radius: 10)
[12:55:26 -370550.398030] SLOW spr round 8 (radius: 15)
[12:59:21] [worker #1] ML tree search #18, logLikelihood: -370557.344761
[13:00:40 -370550.398030] SLOW spr round 9 (radius: 20)
[13:11:11 -370550.398030] SLOW spr round 10 (radius: 25)
[13:24:08 -370550.398030] Model parameter optimization (eps = 0.100000)

[13:24:24] [worker #0] ML tree search #17, logLikelihood: -370549.075700

[13:24:24 -1355538.654138] Initial branch length optimization
[13:24:31 -1158751.076134] Model parameter optimization (eps = 10.000000)
[13:25:25 -1155840.824809] AUTODETECT spr round 1 (radius: 5)
[13:28:47 -813271.751343] AUTODETECT spr round 2 (radius: 10)
[13:32:27 -597294.658973] AUTODETECT spr round 3 (radius: 15)
[13:36:32 -485376.319493] AUTODETECT spr round 4 (radius: 20)
[13:41:06 -428392.604816] AUTODETECT spr round 5 (radius: 25)
[13:47:13 -423185.690969] SPR radius for FAST iterations: 25 (autodetect)
[13:47:13 -423185.690969] Model parameter optimization (eps = 3.000000)
[13:47:37 -422962.164033] FAST spr round 1 (radius: 25)
[13:52:18 -373102.597168] FAST spr round 2 (radius: 25)
[13:55:20 -370852.025470] FAST spr round 3 (radius: 25)
[13:57:59 -370696.504791] FAST spr round 4 (radius: 25)
[14:00:20 -370683.339195] FAST spr round 5 (radius: 25)
[14:02:34 -370679.083259] FAST spr round 6 (radius: 25)
[14:04:43 -370679.083259] Model parameter optimization (eps = 1.000000)
[14:04:59 -370670.351410] SLOW spr round 1 (radius: 5)
[14:08:09 -370595.954936] SLOW spr round 2 (radius: 5)
[14:11:08 -370591.678277] SLOW spr round 3 (radius: 5)
[14:14:05 -370587.813197] SLOW spr round 4 (radius: 5)
[14:16:59 -370587.813160] SLOW spr round 5 (radius: 10)
[14:20:02 -370581.101252] SLOW spr round 6 (radius: 5)
[14:23:50 -370580.258523] SLOW spr round 7 (radius: 5)
[14:26:55] [worker #1] ML tree search #20, logLikelihood: -370548.229062
[14:27:10 -370578.314062] SLOW spr round 8 (radius: 5)
[14:30:13 -370573.232932] SLOW spr round 9 (radius: 5)
[14:33:11 -370571.352167] SLOW spr round 10 (radius: 5)
[14:36:04 -370571.352141] SLOW spr round 11 (radius: 10)
[14:39:05 -370571.352141] SLOW spr round 12 (radius: 15)
[14:45:07 -370571.352141] SLOW spr round 13 (radius: 20)
[14:55:57 -370571.352141] SLOW spr round 14 (radius: 25)
[15:09:28 -370571.352141] Model parameter optimization (eps = 0.100000)

[15:09:38] [worker #0] ML tree search #19, logLikelihood: -370571.278592


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.139255,0.255988) (0.197032,0.399885) (0.411979,0.895365) (0.251733,2.052530) 
   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: -370539.460980

AIC score: 745088.921961 / AICc score: 8789148.921961 / BIC score: 754368.144920
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=756).
         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/O95672/3_mltree/O95672.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/3_mltree/O95672.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/3_mltree/O95672.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O95672/3_mltree/O95672.raxml.log

Analysis started: 04-Jul-2021 07:07:37 / finished: 04-Jul-2021 22:17:16

Elapsed time: 54579.168 seconds

Consumed energy: 4930.679 Wh (= 25 km in an electric car, or 123 km with an e-scooter!)