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 16:06:13 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/2_msa/Q86YT5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5 --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/Q86YT5/2_msa/Q86YT5_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 649 sites

WARNING: Sequences tr_G3QU34_G3QU34_GORGO_9595 and tr_A0A2R9BYP6_A0A2R9BYP6_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A0A0MQQ0_A0A0A0MQQ0_RABIT_9986 and sp_Q28615_S13A2_RABIT_9986 are exactly identical!
WARNING: Sequences tr_A0A2I3T523_A0A2I3T523_PANTR_9598 and tr_A0A2R9BPY3_A0A2R9BPY3_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5R6S4_A0A1D5R6S4_MACMU_9544 and tr_G7PG32_G7PG32_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7G2N1_F7G2N1_MACMU_9544 and tr_A0A2K5NMT9_A0A2K5NMT9_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G0X6X6_G0X6X6_MACMU_9544 and tr_G7PTE4_G7PTE4_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A2Z2I9_A2Z2I9_ORYSI_39946 and tr_A0A0E0QT02_A0A0E0QT02_ORYRU_4529 are exactly identical!
WARNING: Sequences tr_A2Z2I9_A2Z2I9_ORYSI_39946 and tr_Q0J0T0_Q0J0T0_ORYSJ_39947 are exactly identical!
WARNING: Sequences tr_B8BC95_B8BC95_ORYSI_39946 and tr_Q6ZFH7_Q6ZFH7_ORYSJ_39947 are exactly identical!
WARNING: Sequences tr_E3MC70_E3MC70_CAERE_31234 and tr_A0A261CN68_A0A261CN68_9PELO_1503980 are exactly identical!
WARNING: Sequences tr_A0A096NY53_A0A096NY53_PAPAN_9555 and tr_A0A0D9RQS5_A0A0D9RQS5_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A096NY53_A0A096NY53_PAPAN_9555 and tr_A0A2K5P4T1_A0A2K5P4T1_CERAT_9531 are exactly identical!
WARNING: Sequences tr_V4UFY3_V4UFY3_9ROSI_85681 and tr_A0A2H5N558_A0A2H5N558_CITUN_55188 are exactly identical!
WARNING: Sequences tr_A0A0V1LI06_A0A0V1LI06_9BILA_6335 and tr_A0A0V0ZH76_A0A0V0ZH76_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A182EJC6_A0A182EJC6_ONCOC_42157 and tr_A0A182EK35_A0A182EK35_ONCOC_42157 are exactly identical!
WARNING: Sequences tr_A0A1S4B9G8_A0A1S4B9G8_TOBAC_4097 and tr_A0A1U7XW81_A0A1U7XW81_NICSY_4096 are exactly identical!
WARNING: Duplicate sequences found: 16

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/Q86YT5/3_mltree/Q86YT5.raxml.reduced.phy

Alignment comprises 1 partitions and 649 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 649 / 649
Gaps: 21.54 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.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 / 163 / 13040
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -972521.564634] Initial branch length optimization
[00:00:05 -827695.538392] Model parameter optimization (eps = 10.000000)
[00:00:50 -822945.284995] AUTODETECT spr round 1 (radius: 5)
[00:03:32 -592845.379760] AUTODETECT spr round 2 (radius: 10)
[00:06:35 -443418.400967] AUTODETECT spr round 3 (radius: 15)
[00:09:39 -386678.923378] AUTODETECT spr round 4 (radius: 20)
[00:13:32 -348678.517746] AUTODETECT spr round 5 (radius: 25)
[00:19:15 -345585.155203] SPR radius for FAST iterations: 25 (autodetect)
[00:19:15 -345585.155203] Model parameter optimization (eps = 3.000000)
[00:19:25 -345569.224034] FAST spr round 1 (radius: 25)
[00:23:12 -309010.465869] FAST spr round 2 (radius: 25)
[00:26:01 -307714.005708] FAST spr round 3 (radius: 25)
[00:28:30 -307626.866267] FAST spr round 4 (radius: 25)
[00:30:33 -307623.066559] FAST spr round 5 (radius: 25)
[00:32:31 -307623.065941] Model parameter optimization (eps = 1.000000)
[00:33:02 -307026.604890] SLOW spr round 1 (radius: 5)
[00:35:57 -306915.403331] SLOW spr round 2 (radius: 5)
[00:38:35 -306904.673057] SLOW spr round 3 (radius: 5)
[00:41:07 -306904.462170] SLOW spr round 4 (radius: 5)
[00:43:38 -306904.173753] SLOW spr round 5 (radius: 5)
[00:46:06 -306904.172708] SLOW spr round 6 (radius: 10)
[00:48:44 -306904.172132] SLOW spr round 7 (radius: 15)
[00:53:27 -306904.171759] SLOW spr round 8 (radius: 20)
[01:01:27 -306904.171513] SLOW spr round 9 (radius: 25)
[01:11:49 -306904.171350] Model parameter optimization (eps = 0.100000)

[01:12:01] [worker #0] ML tree search #1, logLikelihood: -306903.896523

[01:12:02 -967693.574455] Initial branch length optimization
[01:12:06 -825784.945533] Model parameter optimization (eps = 10.000000)
[01:12:45 -821112.189144] AUTODETECT spr round 1 (radius: 5)
[01:15:37 -589930.513839] AUTODETECT spr round 2 (radius: 10)
[01:16:07] [worker #1] ML tree search #2, logLikelihood: -306905.197595
[01:18:47 -455251.566222] AUTODETECT spr round 3 (radius: 15)
[01:22:05 -385871.306386] AUTODETECT spr round 4 (radius: 20)
[01:25:53 -363860.482494] AUTODETECT spr round 5 (radius: 25)
[01:30:24 -350020.903417] SPR radius for FAST iterations: 25 (autodetect)
[01:30:24 -350020.903417] Model parameter optimization (eps = 3.000000)
[01:30:56 -349348.623704] FAST spr round 1 (radius: 25)
[01:34:52 -308868.691389] FAST spr round 2 (radius: 25)
[01:37:52 -307105.008344] FAST spr round 3 (radius: 25)
[01:40:26 -307005.043539] FAST spr round 4 (radius: 25)
[01:42:43 -306986.079844] FAST spr round 5 (radius: 25)
[01:44:49 -306986.078563] Model parameter optimization (eps = 1.000000)
[01:45:09 -306975.547284] SLOW spr round 1 (radius: 5)
[01:48:08 -306921.182046] SLOW spr round 2 (radius: 5)
[01:50:55 -306918.064794] SLOW spr round 3 (radius: 5)
[01:53:35 -306916.505393] SLOW spr round 4 (radius: 5)
[01:56:14 -306916.505366] SLOW spr round 5 (radius: 10)
[01:59:04 -306910.172749] SLOW spr round 6 (radius: 5)
[02:02:30 -306903.965688] SLOW spr round 7 (radius: 5)
[02:05:28 -306903.673623] SLOW spr round 8 (radius: 5)
[02:08:15 -306903.673415] SLOW spr round 9 (radius: 10)
[02:11:06 -306900.343081] SLOW spr round 10 (radius: 5)
[02:14:28 -306897.453788] SLOW spr round 11 (radius: 5)
[02:17:24 -306897.453673] SLOW spr round 12 (radius: 10)
[02:20:20 -306897.119872] SLOW spr round 13 (radius: 5)
[02:23:38 -306897.119820] SLOW spr round 14 (radius: 10)
[02:26:47 -306897.119819] SLOW spr round 15 (radius: 15)
[02:31:39 -306897.119819] SLOW spr round 16 (radius: 20)
[02:40:25 -306897.119818] SLOW spr round 17 (radius: 25)
[02:42:25] [worker #1] ML tree search #4, logLikelihood: -306902.117974
[02:50:53 -306897.119818] Model parameter optimization (eps = 0.100000)

[02:51:05] [worker #0] ML tree search #3, logLikelihood: -306896.898617

[02:51:06 -970858.337675] Initial branch length optimization
[02:51:10 -827129.164914] Model parameter optimization (eps = 10.000000)
[02:51:55 -822245.808247] AUTODETECT spr round 1 (radius: 5)
[02:54:37 -589684.370903] AUTODETECT spr round 2 (radius: 10)
[02:57:41 -451612.656134] AUTODETECT spr round 3 (radius: 15)
[03:00:53 -384398.774334] AUTODETECT spr round 4 (radius: 20)
[03:04:46 -347969.598887] AUTODETECT spr round 5 (radius: 25)
[03:09:38 -343458.836948] SPR radius for FAST iterations: 25 (autodetect)
[03:09:38 -343458.836948] Model parameter optimization (eps = 3.000000)
[03:10:14 -342744.692398] FAST spr round 1 (radius: 25)
[03:14:01 -308848.285582] FAST spr round 2 (radius: 25)
[03:16:48 -307153.922341] FAST spr round 3 (radius: 25)
[03:19:12 -307005.114366] FAST spr round 4 (radius: 25)
[03:21:18 -307002.106219] FAST spr round 5 (radius: 25)
[03:23:18 -307002.104762] Model parameter optimization (eps = 1.000000)
[03:23:34 -306999.604193] SLOW spr round 1 (radius: 5)
[03:26:23 -306936.727093] SLOW spr round 2 (radius: 5)
[03:29:06 -306929.477320] SLOW spr round 3 (radius: 5)
[03:31:42 -306923.285653] SLOW spr round 4 (radius: 5)
[03:34:13 -306923.285613] SLOW spr round 5 (radius: 10)
[03:36:56 -306921.201487] SLOW spr round 6 (radius: 5)
[03:40:10 -306920.373720] SLOW spr round 7 (radius: 5)
[03:42:59 -306920.369429] SLOW spr round 8 (radius: 10)
[03:45:47 -306920.128898] SLOW spr round 9 (radius: 5)
[03:48:55 -306916.244507] SLOW spr round 10 (radius: 5)
[03:51:42 -306915.577422] SLOW spr round 11 (radius: 5)
[03:54:16 -306915.577156] SLOW spr round 12 (radius: 10)
[03:56:56 -306915.577037] SLOW spr round 13 (radius: 15)
[04:01:52 -306915.576372] SLOW spr round 14 (radius: 20)
[04:09:01] [worker #1] ML tree search #6, logLikelihood: -306907.216981
[04:09:58 -306915.576370] SLOW spr round 15 (radius: 25)
[04:20:32 -306915.576368] Model parameter optimization (eps = 0.100000)

[04:20:49] [worker #0] ML tree search #5, logLikelihood: -306915.218490

[04:20:49 -973202.720074] Initial branch length optimization
[04:20:54 -827274.069112] Model parameter optimization (eps = 10.000000)
[04:21:36 -822717.340747] AUTODETECT spr round 1 (radius: 5)
[04:24:19 -579317.443659] AUTODETECT spr round 2 (radius: 10)
[04:27:17 -444350.376656] AUTODETECT spr round 3 (radius: 15)
[04:30:30 -379473.195446] AUTODETECT spr round 4 (radius: 20)
[04:34:09 -352823.006219] AUTODETECT spr round 5 (radius: 25)
[04:38:45 -345621.584468] SPR radius for FAST iterations: 25 (autodetect)
[04:38:45 -345621.584468] Model parameter optimization (eps = 3.000000)
[04:38:54 -345608.118974] FAST spr round 1 (radius: 25)
[04:42:38 -309451.258449] FAST spr round 2 (radius: 25)
[04:45:32 -307777.721300] FAST spr round 3 (radius: 25)
[04:48:04 -307594.422307] FAST spr round 4 (radius: 25)
[04:50:25 -307554.793665] FAST spr round 5 (radius: 25)
[04:52:31 -307553.274050] FAST spr round 6 (radius: 25)
[04:54:33 -307553.273770] Model parameter optimization (eps = 1.000000)
[04:55:03 -307026.548658] SLOW spr round 1 (radius: 5)
[04:57:56 -306929.919497] SLOW spr round 2 (radius: 5)
[05:00:43 -306921.907508] SLOW spr round 3 (radius: 5)
[05:03:21 -306921.875607] SLOW spr round 4 (radius: 10)
[05:06:08 -306917.986678] SLOW spr round 5 (radius: 5)
[05:09:29 -306917.472290] SLOW spr round 6 (radius: 5)
[05:12:23 -306917.470713] SLOW spr round 7 (radius: 10)
[05:15:15 -306917.383527] SLOW spr round 8 (radius: 15)
[05:20:02 -306917.383525] SLOW spr round 9 (radius: 20)
[05:28:18 -306917.383524] SLOW spr round 10 (radius: 25)
[05:35:09] [worker #1] ML tree search #8, logLikelihood: -306884.432107
[05:39:07 -306917.383524] Model parameter optimization (eps = 0.100000)

[05:39:19] [worker #0] ML tree search #7, logLikelihood: -306917.319859

[05:39:19 -966495.277479] Initial branch length optimization
[05:39:23 -824868.881699] Model parameter optimization (eps = 10.000000)
[05:40:05 -820359.054285] AUTODETECT spr round 1 (radius: 5)
[05:42:54 -588484.861987] AUTODETECT spr round 2 (radius: 10)
[05:46:05 -455140.372488] AUTODETECT spr round 3 (radius: 15)
[05:49:23 -388502.094269] AUTODETECT spr round 4 (radius: 20)
[05:53:05 -368234.349014] AUTODETECT spr round 5 (radius: 25)
[05:57:29 -352699.582114] SPR radius for FAST iterations: 25 (autodetect)
[05:57:29 -352699.582114] Model parameter optimization (eps = 3.000000)
[05:57:39 -352686.915619] FAST spr round 1 (radius: 25)
[06:01:53 -308750.400957] FAST spr round 2 (radius: 25)
[06:04:58 -307665.584041] FAST spr round 3 (radius: 25)
[06:07:36 -307605.069674] FAST spr round 4 (radius: 25)
[06:10:00 -307591.449821] FAST spr round 5 (radius: 25)
[06:12:11 -307569.730897] FAST spr round 6 (radius: 25)
[06:14:13 -307569.729451] Model parameter optimization (eps = 1.000000)
[06:14:43 -307079.279229] SLOW spr round 1 (radius: 5)
[06:17:46 -306922.813056] SLOW spr round 2 (radius: 5)
[06:20:37 -306914.840727] SLOW spr round 3 (radius: 5)
[06:23:17 -306914.837561] SLOW spr round 4 (radius: 10)
[06:26:08 -306902.744821] SLOW spr round 5 (radius: 5)
[06:29:31 -306900.754742] SLOW spr round 6 (radius: 5)
[06:32:27 -306900.754539] SLOW spr round 7 (radius: 10)
[06:35:21 -306900.754486] SLOW spr round 8 (radius: 15)
[06:40:13 -306900.754461] SLOW spr round 9 (radius: 20)
[06:48:37 -306900.754447] SLOW spr round 10 (radius: 25)
[06:59:26 -306900.754439] Model parameter optimization (eps = 0.100000)

[06:59:41] [worker #0] ML tree search #9, logLikelihood: -306899.962616

[06:59:41 -967889.068432] Initial branch length optimization
[06:59:45 -825435.967672] Model parameter optimization (eps = 10.000000)
[07:00:25 -820864.713818] AUTODETECT spr round 1 (radius: 5)
[07:03:14 -590908.035613] AUTODETECT spr round 2 (radius: 10)
[07:06:25 -444763.860954] AUTODETECT spr round 3 (radius: 15)
[07:09:42 -397541.050880] AUTODETECT spr round 4 (radius: 20)
[07:13:23 -378036.221292] AUTODETECT spr round 5 (radius: 25)
[07:14:40] [worker #1] ML tree search #10, logLikelihood: -306915.650791
[07:17:38 -364215.314541] SPR radius for FAST iterations: 25 (autodetect)
[07:17:38 -364215.314541] Model parameter optimization (eps = 3.000000)
[07:17:54 -364171.805331] FAST spr round 1 (radius: 25)
[07:21:57 -310890.443195] FAST spr round 2 (radius: 25)
[07:24:54 -307986.971237] FAST spr round 3 (radius: 25)
[07:27:29 -307710.849078] FAST spr round 4 (radius: 25)
[07:29:48 -307680.145054] FAST spr round 5 (radius: 25)
[07:31:59 -307651.710311] FAST spr round 6 (radius: 25)
[07:34:06 -307643.449829] FAST spr round 7 (radius: 25)
[07:36:08 -307641.959785] FAST spr round 8 (radius: 25)
[07:38:10 -307641.959771] Model parameter optimization (eps = 1.000000)
[07:38:42 -307079.478081] SLOW spr round 1 (radius: 5)
[07:41:39 -306909.019382] SLOW spr round 2 (radius: 5)
[07:44:27 -306893.151652] SLOW spr round 3 (radius: 5)
[07:47:07 -306893.150738] SLOW spr round 4 (radius: 10)
[07:49:49 -306889.407801] SLOW spr round 5 (radius: 5)
[07:52:57 -306887.763840] SLOW spr round 6 (radius: 5)
[07:55:43 -306887.763601] SLOW spr round 7 (radius: 10)
[07:58:25 -306887.763504] SLOW spr round 8 (radius: 15)
[08:02:49 -306887.763435] SLOW spr round 9 (radius: 20)
[08:10:05 -306887.763382] SLOW spr round 10 (radius: 25)
[08:19:31 -306887.763339] Model parameter optimization (eps = 0.100000)

[08:19:46] [worker #0] ML tree search #11, logLikelihood: -306886.723167

[08:19:46 -966810.604675] Initial branch length optimization
[08:19:52 -827550.579293] Model parameter optimization (eps = 10.000000)
[08:20:34 -822635.501225] AUTODETECT spr round 1 (radius: 5)
[08:23:16 -596582.885299] AUTODETECT spr round 2 (radius: 10)
[08:26:21 -445754.726048] AUTODETECT spr round 3 (radius: 15)
[08:29:58 -365087.532377] AUTODETECT spr round 4 (radius: 20)
[08:31:46] [worker #1] ML tree search #12, logLikelihood: -306913.595411
[08:33:47 -353042.863366] AUTODETECT spr round 5 (radius: 25)
[08:38:30 -345940.329988] SPR radius for FAST iterations: 25 (autodetect)
[08:38:30 -345940.329988] Model parameter optimization (eps = 3.000000)
[08:39:13 -345339.980472] FAST spr round 1 (radius: 25)
[08:42:57 -308879.929004] FAST spr round 2 (radius: 25)
[08:45:55 -307164.419693] FAST spr round 3 (radius: 25)
[08:48:19 -307039.443947] FAST spr round 4 (radius: 25)
[08:50:31 -307007.139194] FAST spr round 5 (radius: 25)
[08:52:31 -307005.961364] FAST spr round 6 (radius: 25)
[08:54:26 -307005.961353] Model parameter optimization (eps = 1.000000)
[08:54:47 -306991.574593] SLOW spr round 1 (radius: 5)
[08:57:35 -306939.598837] SLOW spr round 2 (radius: 5)
[09:00:11 -306936.305814] SLOW spr round 3 (radius: 5)
[09:02:42 -306935.257668] SLOW spr round 4 (radius: 5)
[09:05:10 -306935.257598] SLOW spr round 5 (radius: 10)
[09:07:50 -306930.286451] SLOW spr round 6 (radius: 5)
[09:11:01 -306922.457285] SLOW spr round 7 (radius: 5)
[09:13:49 -306921.911136] SLOW spr round 8 (radius: 5)
[09:16:26 -306921.186802] SLOW spr round 9 (radius: 5)
[09:19:02 -306905.142915] SLOW spr round 10 (radius: 5)
[09:21:31 -306905.142462] SLOW spr round 11 (radius: 10)
[09:24:09 -306904.588786] SLOW spr round 12 (radius: 5)
[09:27:17 -306904.588633] SLOW spr round 13 (radius: 10)
[09:30:17 -306904.588620] SLOW spr round 14 (radius: 15)
[09:34:56 -306904.588615] SLOW spr round 15 (radius: 20)
[09:43:17 -306904.588612] SLOW spr round 16 (radius: 25)
[09:49:55] [worker #1] ML tree search #14, logLikelihood: -306896.353713
[09:53:21 -306904.588610] Model parameter optimization (eps = 0.100000)

[09:53:32] [worker #0] ML tree search #13, logLikelihood: -306904.452819

[09:53:32 -971496.309771] Initial branch length optimization
[09:53:36 -828912.442910] Model parameter optimization (eps = 10.000000)
[09:54:14 -824286.714422] AUTODETECT spr round 1 (radius: 5)
[09:56:57 -587417.102827] AUTODETECT spr round 2 (radius: 10)
[09:59:57 -451063.163304] AUTODETECT spr round 3 (radius: 15)
[10:03:08 -381672.489484] AUTODETECT spr round 4 (radius: 20)
[10:06:37 -348359.276346] AUTODETECT spr round 5 (radius: 25)
[10:10:53 -343023.927022] SPR radius for FAST iterations: 25 (autodetect)
[10:10:53 -343023.927022] Model parameter optimization (eps = 3.000000)
[10:11:03 -343007.303479] FAST spr round 1 (radius: 25)
[10:14:40 -309000.713895] FAST spr round 2 (radius: 25)
[10:17:32 -307815.283116] FAST spr round 3 (radius: 25)
[10:20:02 -307730.423388] FAST spr round 4 (radius: 25)
[10:22:10 -307720.024588] FAST spr round 5 (radius: 25)
[10:24:11 -307718.722699] FAST spr round 6 (radius: 25)
[10:26:08 -307718.722396] Model parameter optimization (eps = 1.000000)
[10:26:14 -307718.388425] SLOW spr round 1 (radius: 5)
[10:29:07 -307668.213970] SLOW spr round 2 (radius: 5)
[10:31:53 -307657.370931] SLOW spr round 3 (radius: 5)
[10:34:34 -307654.699245] SLOW spr round 4 (radius: 5)
[10:37:12 -307651.371519] SLOW spr round 5 (radius: 5)
[10:39:48 -307651.371083] SLOW spr round 6 (radius: 10)
[10:42:36 -307650.139756] SLOW spr round 7 (radius: 5)
[10:46:03 -307641.752375] SLOW spr round 8 (radius: 5)
[10:49:02 -307640.857804] SLOW spr round 9 (radius: 5)
[10:51:47 -307640.857423] SLOW spr round 10 (radius: 10)
[10:54:39 -307634.936567] SLOW spr round 11 (radius: 5)
[10:57:46 -307634.935782] SLOW spr round 12 (radius: 10)
[11:00:43 -307634.698887] SLOW spr round 13 (radius: 5)
[11:03:45 -307634.698533] SLOW spr round 14 (radius: 10)
[11:06:39 -307634.698523] SLOW spr round 15 (radius: 15)
[11:10:59 -307634.698521] SLOW spr round 16 (radius: 20)
[11:16:19] [worker #1] ML tree search #16, logLikelihood: -306930.217762
[11:18:56 -307634.698521] SLOW spr round 17 (radius: 25)
[11:29:33 -307634.698521] Model parameter optimization (eps = 0.100000)

[11:29:57] [worker #0] ML tree search #15, logLikelihood: -306992.408106

[11:29:58 -971965.905409] Initial branch length optimization
[11:30:03 -827891.140044] Model parameter optimization (eps = 10.000000)
[11:30:41 -823431.733323] AUTODETECT spr round 1 (radius: 5)
[11:33:22 -587796.440864] AUTODETECT spr round 2 (radius: 10)
[11:36:26 -430645.591120] AUTODETECT spr round 3 (radius: 15)
[11:39:06 -358605.971222] AUTODETECT spr round 4 (radius: 20)
[11:42:01 -344725.940852] AUTODETECT spr round 5 (radius: 25)
[11:45:20 -341680.482925] SPR radius for FAST iterations: 25 (autodetect)
[11:45:20 -341680.482925] Model parameter optimization (eps = 3.000000)
[11:45:48 -341119.949239] FAST spr round 1 (radius: 25)
[11:48:53 -308639.497561] FAST spr round 2 (radius: 25)
[11:51:16 -307141.407436] FAST spr round 3 (radius: 25)
[11:53:22 -307072.507727] FAST spr round 4 (radius: 25)
[11:55:10 -307060.347249] FAST spr round 5 (radius: 25)
[11:56:51 -307060.273316] Model parameter optimization (eps = 1.000000)
[11:57:07 -307041.114750] SLOW spr round 1 (radius: 5)
[11:59:30 -306953.511615] SLOW spr round 2 (radius: 5)
[12:01:46 -306934.138155] SLOW spr round 3 (radius: 5)
[12:03:57 -306926.377120] SLOW spr round 4 (radius: 5)
[12:06:07 -306922.625364] SLOW spr round 5 (radius: 5)
[12:08:16 -306917.137593] SLOW spr round 6 (radius: 5)
[12:10:22 -306917.137350] SLOW spr round 7 (radius: 10)
[12:12:37 -306914.408188] SLOW spr round 8 (radius: 5)
[12:15:18 -306913.351577] SLOW spr round 9 (radius: 5)
[12:17:39 -306913.351378] SLOW spr round 10 (radius: 10)
[12:20:00 -306913.351354] SLOW spr round 11 (radius: 15)
[12:24:01 -306913.351332] SLOW spr round 12 (radius: 20)
[12:24:01] [worker #1] ML tree search #18, logLikelihood: -306926.705806
[12:30:50 -306913.351311] SLOW spr round 13 (radius: 25)
[12:39:40 -306913.351290] Model parameter optimization (eps = 0.100000)

[12:39:50] [worker #0] ML tree search #17, logLikelihood: -306913.071047

[12:39:50 -971263.255624] Initial branch length optimization
[12:39:54 -827101.748875] Model parameter optimization (eps = 10.000000)
[12:40:37 -822372.609169] AUTODETECT spr round 1 (radius: 5)
[12:42:56 -593001.891835] AUTODETECT spr round 2 (radius: 10)
[12:45:33 -433463.830400] AUTODETECT spr round 3 (radius: 15)
[12:48:20 -373115.338043] AUTODETECT spr round 4 (radius: 20)
[12:51:23 -342399.126046] AUTODETECT spr round 5 (radius: 25)
[12:54:56 -337920.732678] SPR radius for FAST iterations: 25 (autodetect)
[12:54:56 -337920.732678] Model parameter optimization (eps = 3.000000)
[12:55:20 -337274.810505] FAST spr round 1 (radius: 25)
[12:58:34 -307796.854086] FAST spr round 2 (radius: 25)
[13:00:53 -307125.404042] FAST spr round 3 (radius: 25)
[13:02:57 -307044.772078] FAST spr round 4 (radius: 25)
[13:04:53 -307005.327380] FAST spr round 5 (radius: 25)
[13:06:34 -307005.327248] Model parameter optimization (eps = 1.000000)
[13:06:44 -307004.560974] SLOW spr round 1 (radius: 5)
[13:09:08 -306912.625130] SLOW spr round 2 (radius: 5)
[13:11:23 -306903.013542] SLOW spr round 3 (radius: 5)
[13:13:30 -306903.008499] SLOW spr round 4 (radius: 10)
[13:15:44 -306901.402271] SLOW spr round 5 (radius: 5)
[13:18:23 -306901.401832] SLOW spr round 6 (radius: 10)
[13:20:54 -306901.401567] SLOW spr round 7 (radius: 15)
[13:24:47 -306901.401383] SLOW spr round 8 (radius: 20)
[13:28:07] [worker #1] ML tree search #20, logLikelihood: -306904.957973
[13:31:42 -306901.401252] SLOW spr round 9 (radius: 25)
[13:40:23 -306901.401156] Model parameter optimization (eps = 0.100000)

[13:40:33] [worker #0] ML tree search #19, logLikelihood: -306901.186584


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.172846,0.347336) (0.254460,0.399468) (0.284675,0.912220) (0.288019,2.008998) 
   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: -306884.432107

AIC score: 617778.864215 / AICc score: 8661838.864215 / BIC score: 626752.106812
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=649).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 43 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q86YT5/3_mltree/Q86YT5.raxml.log

Analysis started: 04-Jul-2021 16:06:13 / finished: 05-Jul-2021 05:46:47

Elapsed time: 49234.093 seconds

Consumed energy: 4685.293 Wh (= 23 km in an electric car, or 117 km with an e-scooter!)