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 03-Jul-2021 23:35:20 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/2_msa/Q5VY43_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/3_mltree/Q5VY43 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/2_msa/Q5VY43_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1000 taxa and 428 sites

WARNING: Sequences tr_H9GVM0_H9GVM0_ANOCA_28377 and tr_K7FYI2_K7FYI2_PELSI_13735 are exactly identical!
WARNING: Sequences tr_H9GVM0_H9GVM0_ANOCA_28377 and tr_A0A3Q0G6N2_A0A3Q0G6N2_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_K7BS94_K7BS94_PANTR_9598 and tr_F7GYX1_F7GYX1_MACMU_9544 are exactly identical!
WARNING: Sequences tr_K7BS94_K7BS94_PANTR_9598 and tr_A0A0D9RIM0_A0A0D9RIM0_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_K7BS94_K7BS94_PANTR_9598 and tr_A0A2K5P625_A0A2K5P625_CERAT_9531 are exactly identical!
WARNING: Sequences tr_B3S0P5_B3S0P5_TRIAD_10228 and tr_A0A369SD37_A0A369SD37_9METZ_287889 are exactly identical!
WARNING: Sequences tr_G7P861_G7P861_MACFA_9541 and tr_A0A096MUN6_A0A096MUN6_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G7P861_G7P861_MACFA_9541 and tr_A0A0D9RPN7_A0A0D9RPN7_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A091EA19_A0A091EA19_CORBR_85066 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A091JRT8_A0A091JRT8_EGRGA_188379 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A093PU38_A0A093PU38_9PASS_328815 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A091VJ73_A0A091VJ73_NIPNI_128390 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A087R4C8_A0A087R4C8_APTFO_9233 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A093HZZ6_A0A093HZZ6_STRCA_441894 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A099YT92_A0A099YT92_TINGU_94827 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A091H471_A0A091H471_9AVES_55661 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A099ZY91_A0A099ZY91_CHAVO_50402 are exactly identical!
WARNING: Sequences tr_U3J6K9_U3J6K9_ANAPL_8839 and tr_A0A091HRM8_A0A091HRM8_CALAN_9244 are exactly identical!
WARNING: Sequences tr_A0A0V1D1K4_A0A0V1D1K4_TRIBR_45882 and tr_A0A0V0VUW0_A0A0V0VUW0_9BILA_181606 are exactly identical!
WARNING: Sequences tr_A0A0V1D1K4_A0A0V1D1K4_TRIBR_45882 and tr_A0A0V1LI50_A0A0V1LI50_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V1D1K4_A0A0V1D1K4_TRIBR_45882 and tr_A0A0V0ZGK5_A0A0V0ZGK5_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A0V1D1K4_A0A0V1D1K4_TRIBR_45882 and tr_A0A0V0UAL9_A0A0V0UAL9_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A0V1D7Z2_A0A0V1D7Z2_TRIBR_45882 and tr_A0A0V0WG54_A0A0V0WG54_9BILA_92179 are exactly identical!
WARNING: Sequences tr_A0A0V1D7Z2_A0A0V1D7Z2_TRIBR_45882 and tr_A0A0V1L2M7_A0A0V1L2M7_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A2D0PMI0_A0A2D0PMI0_ICTPU_7998 and tr_A0A2D0PMI5_A0A2D0PMI5_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PMI0_A0A2D0PMI0_ICTPU_7998 and tr_A0A2D0PP65_A0A2D0PP65_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PMI0_A0A2D0PMI0_ICTPU_7998 and tr_A0A2D0PQU6_A0A2D0PQU6_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PMI0_A0A2D0PMI0_ICTPU_7998 and tr_A0A2D0PQV1_A0A2D0PQV1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PMI0_A0A2D0PMI0_ICTPU_7998 and tr_A0A2D0PRU9_A0A2D0PRU9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0QWB9_A0A2D0QWB9_ICTPU_7998 and tr_A0A2D0QX16_A0A2D0QX16_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2K5LWM3_A0A2K5LWM3_CERAT_9531 and tr_A0A2K6B9U3_A0A2K6B9U3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2K5NLJ6_A0A2K5NLJ6_CERAT_9531 and tr_A0A2K6DZQ5_A0A2K6DZQ5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2U4ALG5_A0A2U4ALG5_TURTR_9739 and tr_A0A2Y9LNQ7_A0A2Y9LNQ7_DELLE_9749 are exactly identical!
WARNING: Duplicate sequences found: 33

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/Q5VY43/3_mltree/Q5VY43.raxml.reduced.phy

Alignment comprises 1 partitions and 428 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 428 / 428
Gaps: 17.91 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/3_mltree/Q5VY43.raxml.rba

Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 1000 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 214 / 17120
[00:00:00] Data distribution: max. searches per worker: 7

Starting ML tree search with 20 distinct starting trees

[00:00:00 -662270.239452] Initial branch length optimization
[00:00:05 -552191.292876] Model parameter optimization (eps = 10.000000)
[00:00:44 -551922.693709] AUTODETECT spr round 1 (radius: 5)
[00:03:41 -418943.354723] AUTODETECT spr round 2 (radius: 10)
[00:07:06 -325105.838498] AUTODETECT spr round 3 (radius: 15)
[00:11:31 -290151.889335] AUTODETECT spr round 4 (radius: 20)
[00:15:55 -249907.886682] AUTODETECT spr round 5 (radius: 25)
[00:21:33 -244441.170238] SPR radius for FAST iterations: 25 (autodetect)
[00:21:33 -244441.170238] Model parameter optimization (eps = 3.000000)
[00:22:09 -243775.733318] FAST spr round 1 (radius: 25)
[00:28:50 -221420.351818] FAST spr round 2 (radius: 25)
[00:32:33 -220242.803057] FAST spr round 3 (radius: 25)
[00:35:41 -220135.838503] FAST spr round 4 (radius: 25)
[00:38:21 -220118.269624] FAST spr round 5 (radius: 25)
[00:40:39 -220117.082228] FAST spr round 6 (radius: 25)
[00:42:52 -220117.081187] Model parameter optimization (eps = 1.000000)
[00:43:11 -220109.638409] SLOW spr round 1 (radius: 5)
[00:46:07 -220064.362490] SLOW spr round 2 (radius: 5)
[00:48:58 -220060.556772] SLOW spr round 3 (radius: 5)
[00:51:38 -220057.681282] SLOW spr round 4 (radius: 5)
[00:54:15 -220057.679809] SLOW spr round 5 (radius: 10)
[00:57:09 -220056.970829] SLOW spr round 6 (radius: 5)
[01:00:32 -220056.968304] SLOW spr round 7 (radius: 10)
[01:03:57 -220056.967924] SLOW spr round 8 (radius: 15)
[01:09:16 -220056.125989] SLOW spr round 9 (radius: 5)
[01:12:54 -220055.710295] SLOW spr round 10 (radius: 5)
[01:16:09 -220055.710220] SLOW spr round 11 (radius: 10)
[01:19:26 -220050.905292] SLOW spr round 12 (radius: 5)
[01:22:54 -220047.656768] SLOW spr round 13 (radius: 5)
[01:25:58 -220047.656070] SLOW spr round 14 (radius: 10)
[01:29:08 -220047.655997] SLOW spr round 15 (radius: 15)
[01:34:33 -220044.936220] SLOW spr round 16 (radius: 5)
[01:38:02 -220040.636788] SLOW spr round 17 (radius: 5)
[01:41:09 -220036.886109] SLOW spr round 18 (radius: 5)
[01:44:03 -220036.885536] SLOW spr round 19 (radius: 10)
[01:47:01 -220036.885477] SLOW spr round 20 (radius: 15)
[01:52:27 -220034.777296] SLOW spr round 21 (radius: 5)
[01:56:14 -220032.038679] SLOW spr round 22 (radius: 5)
[01:59:30 -220032.037287] SLOW spr round 23 (radius: 10)
[02:02:46 -220029.451266] SLOW spr round 24 (radius: 5)
[02:06:21 -220029.450273] SLOW spr round 25 (radius: 10)
[02:09:57 -220029.450236] SLOW spr round 26 (radius: 15)
[02:15:29 -220029.450225] SLOW spr round 27 (radius: 20)
[02:24:02 -220029.450216] SLOW spr round 28 (radius: 25)
[02:30:14] [worker #2] ML tree search #3, logLikelihood: -220081.820663
[02:34:41] [worker #1] ML tree search #2, logLikelihood: -220042.973151
[02:35:14 -220029.450206] Model parameter optimization (eps = 0.100000)

[02:35:26] [worker #0] ML tree search #1, logLikelihood: -220029.148944

[02:35:26 -662067.863170] Initial branch length optimization
[02:35:32 -550560.936454] Model parameter optimization (eps = 10.000000)
[02:36:19 -550295.687333] AUTODETECT spr round 1 (radius: 5)
[02:39:35 -424153.215394] AUTODETECT spr round 2 (radius: 10)
[02:43:11 -330204.111697] AUTODETECT spr round 3 (radius: 15)
[02:47:40 -291758.272079] AUTODETECT spr round 4 (radius: 20)
[02:52:20 -259548.132172] AUTODETECT spr round 5 (radius: 25)
[02:58:22 -251314.188899] SPR radius for FAST iterations: 25 (autodetect)
[02:58:23 -251314.188899] Model parameter optimization (eps = 3.000000)
[02:59:07 -250593.939835] FAST spr round 1 (radius: 25)
[03:06:46 -221660.110312] FAST spr round 2 (radius: 25)
[03:10:54 -220278.095349] FAST spr round 3 (radius: 25)
[03:14:06 -220194.477403] FAST spr round 4 (radius: 25)
[03:16:57 -220172.502362] FAST spr round 5 (radius: 25)
[03:19:38 -220163.733247] FAST spr round 6 (radius: 25)
[03:22:07 -220162.430449] FAST spr round 7 (radius: 25)
[03:24:33 -220162.429768] Model parameter optimization (eps = 1.000000)
[03:24:58 -220152.272762] SLOW spr round 1 (radius: 5)
[03:28:19 -220087.488580] SLOW spr round 2 (radius: 5)
[03:31:24 -220086.375726] SLOW spr round 3 (radius: 5)
[03:34:27 -220086.375089] SLOW spr round 4 (radius: 10)
[03:37:39 -220082.922704] SLOW spr round 5 (radius: 5)
[03:41:18 -220082.297817] SLOW spr round 6 (radius: 5)
[03:44:34 -220081.447845] SLOW spr round 7 (radius: 5)
[03:47:42 -220081.445697] SLOW spr round 8 (radius: 10)
[03:50:55 -220081.445405] SLOW spr round 9 (radius: 15)
[03:56:36 -220081.388742] SLOW spr round 10 (radius: 20)
[04:05:10 -220081.384091] SLOW spr round 11 (radius: 25)
[04:16:40 -220081.383018] Model parameter optimization (eps = 0.100000)

[04:16:48] [worker #0] ML tree search #4, logLikelihood: -220081.339087

[04:16:48 -662342.590292] Initial branch length optimization
[04:16:53 -550095.185478] Model parameter optimization (eps = 10.000000)
[04:17:38 -549799.337808] AUTODETECT spr round 1 (radius: 5)
[04:20:54 -424724.519710] AUTODETECT spr round 2 (radius: 10)
[04:24:37 -330101.767073] AUTODETECT spr round 3 (radius: 15)
[04:29:22 -288182.776482] AUTODETECT spr round 4 (radius: 20)
[04:34:02 -251431.047060] AUTODETECT spr round 5 (radius: 25)
[04:40:32 -248627.335700] SPR radius for FAST iterations: 25 (autodetect)
[04:40:32 -248627.335700] Model parameter optimization (eps = 3.000000)
[04:41:11 -247884.324393] FAST spr round 1 (radius: 25)
[04:48:34 -221231.769472] FAST spr round 2 (radius: 25)
[04:52:44 -220311.464720] FAST spr round 3 (radius: 25)
[04:56:02 -220204.910468] FAST spr round 4 (radius: 25)
[04:58:48 -220193.498750] FAST spr round 5 (radius: 25)
[05:01:18 -220193.496957] Model parameter optimization (eps = 1.000000)
[05:01:36 -220186.062719] SLOW spr round 1 (radius: 5)
[05:04:42 -220133.674656] SLOW spr round 2 (radius: 5)
[05:07:40 -220129.297050] SLOW spr round 3 (radius: 5)
[05:10:31 -220129.296709] SLOW spr round 4 (radius: 10)
[05:13:47 -220122.167582] SLOW spr round 5 (radius: 5)
[05:17:20 -220114.155110] SLOW spr round 6 (radius: 5)
[05:20:30 -220114.147006] SLOW spr round 7 (radius: 10)
[05:22:38] [worker #2] ML tree search #6, logLikelihood: -220068.230550
[05:23:47 -220113.605739] SLOW spr round 8 (radius: 5)
[05:27:15 -220113.605725] SLOW spr round 9 (radius: 10)
[05:30:47 -220112.855465] SLOW spr round 10 (radius: 5)
[05:34:12 -220112.855457] SLOW spr round 11 (radius: 10)
[05:37:41 -220111.752435] SLOW spr round 12 (radius: 5)
[05:41:06 -220111.752432] SLOW spr round 13 (radius: 10)
[05:44:32 -220111.752429] SLOW spr round 14 (radius: 15)
[05:47:37] [worker #1] ML tree search #5, logLikelihood: -220034.311283
[05:49:57 -220108.186378] SLOW spr round 15 (radius: 5)
[05:53:40 -220107.630348] SLOW spr round 16 (radius: 5)
[05:56:59 -220107.627675] SLOW spr round 17 (radius: 10)
[06:00:19 -220103.676574] SLOW spr round 18 (radius: 5)
[06:03:51 -220099.503246] SLOW spr round 19 (radius: 5)
[06:06:59 -220099.502378] SLOW spr round 20 (radius: 10)
[06:10:15 -220097.975621] SLOW spr round 21 (radius: 5)
[06:13:49 -220097.359483] SLOW spr round 22 (radius: 5)
[06:17:02 -220095.941993] SLOW spr round 23 (radius: 5)
[06:20:04 -220095.941698] SLOW spr round 24 (radius: 10)
[06:23:13 -220095.941667] SLOW spr round 25 (radius: 15)
[06:28:41 -220095.941655] SLOW spr round 26 (radius: 20)
[06:36:33 -220095.941643] SLOW spr round 27 (radius: 25)
[06:46:57 -220095.758412] SLOW spr round 28 (radius: 5)
[06:50:42 -220095.757979] SLOW spr round 29 (radius: 10)
[06:54:28 -220095.757939] SLOW spr round 30 (radius: 15)
[06:59:41 -220095.757932] SLOW spr round 31 (radius: 20)
[07:07:41 -220095.757926] SLOW spr round 32 (radius: 25)
[07:17:59 -220095.757922] Model parameter optimization (eps = 0.100000)

[07:18:10] [worker #0] ML tree search #7, logLikelihood: -220095.574029

[07:18:10 -665589.113564] Initial branch length optimization
[07:18:15 -553218.959631] Model parameter optimization (eps = 10.000000)
[07:18:56 -552997.986643] AUTODETECT spr round 1 (radius: 5)
[07:22:06 -425444.793309] AUTODETECT spr round 2 (radius: 10)
[07:25:34 -335774.925460] AUTODETECT spr round 3 (radius: 15)
[07:30:07 -277880.210137] AUTODETECT spr round 4 (radius: 20)
[07:34:16 -254619.320339] AUTODETECT spr round 5 (radius: 25)
[07:40:07 -249585.231937] SPR radius for FAST iterations: 25 (autodetect)
[07:40:07 -249585.231937] Model parameter optimization (eps = 3.000000)
[07:40:46 -248836.493273] FAST spr round 1 (radius: 25)
[07:47:26 -221787.748986] FAST spr round 2 (radius: 25)
[07:51:24 -220297.883391] FAST spr round 3 (radius: 25)
[07:54:35 -220192.637645] FAST spr round 4 (radius: 25)
[07:57:21 -220183.392648] FAST spr round 5 (radius: 25)
[07:59:54 -220159.138191] FAST spr round 6 (radius: 25)
[08:02:24 -220147.195566] FAST spr round 7 (radius: 25)
[08:04:44 -220146.042022] FAST spr round 8 (radius: 25)
[08:07:00 -220146.040618] Model parameter optimization (eps = 1.000000)
[08:07:25 -220120.656611] SLOW spr round 1 (radius: 5)
[08:10:27 -220079.513836] SLOW spr round 2 (radius: 5)
[08:11:18] [worker #2] ML tree search #9, logLikelihood: -220039.045464
[08:13:29 -220069.336507] SLOW spr round 3 (radius: 5)
[08:16:25 -220068.374351] SLOW spr round 4 (radius: 5)
[08:19:19 -220066.519510] SLOW spr round 5 (radius: 5)
[08:22:18 -220063.496550] SLOW spr round 6 (radius: 5)
[08:25:12 -220063.493325] SLOW spr round 7 (radius: 10)
[08:28:18 -220061.398869] SLOW spr round 8 (radius: 5)
[08:31:48 -220059.503201] SLOW spr round 9 (radius: 5)
[08:34:59 -220059.376466] SLOW spr round 10 (radius: 5)
[08:37:57 -220059.376306] SLOW spr round 11 (radius: 10)
[08:41:02 -220059.376287] SLOW spr round 12 (radius: 15)
[08:46:56 -220055.275665] SLOW spr round 13 (radius: 5)
[08:50:31 -220055.129439] SLOW spr round 14 (radius: 5)
[08:52:12] [worker #1] ML tree search #8, logLikelihood: -220052.439206
[08:53:44 -220055.128897] SLOW spr round 15 (radius: 10)
[08:56:59 -220055.128809] SLOW spr round 16 (radius: 15)
[09:02:47 -220055.128770] SLOW spr round 17 (radius: 20)
[09:11:24 -220055.128745] SLOW spr round 18 (radius: 25)
[09:22:41 -220055.128728] Model parameter optimization (eps = 0.100000)

[09:22:51] [worker #0] ML tree search #10, logLikelihood: -220055.075280

[09:22:51 -664989.795746] Initial branch length optimization
[09:22:57 -552523.908636] Model parameter optimization (eps = 10.000000)
[09:23:40 -552248.045107] AUTODETECT spr round 1 (radius: 5)
[09:26:49 -432323.697939] AUTODETECT spr round 2 (radius: 10)
[09:30:23 -333139.241524] AUTODETECT spr round 3 (radius: 15)
[09:34:51 -283681.797192] AUTODETECT spr round 4 (radius: 20)
[09:38:59] [worker #2] ML tree search #12, logLikelihood: -220053.365820
[09:39:17 -254099.589737] AUTODETECT spr round 5 (radius: 25)
[09:46:05 -250145.781760] SPR radius for FAST iterations: 25 (autodetect)
[09:46:05 -250145.781760] Model parameter optimization (eps = 3.000000)
[09:46:39 -249319.409319] FAST spr round 1 (radius: 25)
[09:53:41 -221297.950658] FAST spr round 2 (radius: 25)
[09:57:20 -220309.251998] FAST spr round 3 (radius: 25)
[10:00:24 -220188.677309] FAST spr round 4 (radius: 25)
[10:03:00 -220180.050580] FAST spr round 5 (radius: 25)
[10:05:27 -220173.778374] FAST spr round 6 (radius: 25)
[10:07:49 -220170.599024] FAST spr round 7 (radius: 25)
[10:10:07 -220170.515599] Model parameter optimization (eps = 1.000000)
[10:10:28 -220164.026487] SLOW spr round 1 (radius: 5)
[10:13:30 -220109.915211] SLOW spr round 2 (radius: 5)
[10:16:29 -220104.861338] SLOW spr round 3 (radius: 5)
[10:19:28 -220101.042172] SLOW spr round 4 (radius: 5)
[10:22:19 -220100.788619] SLOW spr round 5 (radius: 5)
[10:25:09 -220100.788364] SLOW spr round 6 (radius: 10)
[10:28:03 -220095.307731] SLOW spr round 7 (radius: 5)
[10:31:17 -220095.128652] SLOW spr round 8 (radius: 5)
[10:34:12 -220095.128242] SLOW spr round 9 (radius: 10)
[10:37:12 -220095.128120] SLOW spr round 10 (radius: 15)
[10:42:31 -220094.787587] SLOW spr round 11 (radius: 5)
[10:45:55 -220088.461602] SLOW spr round 12 (radius: 5)
[10:48:55 -220088.355510] SLOW spr round 13 (radius: 5)
[10:51:42 -220088.355481] SLOW spr round 14 (radius: 10)
[10:54:38 -220086.533945] SLOW spr round 15 (radius: 5)
[10:56:26] [worker #1] ML tree search #11, logLikelihood: -220075.715975
[10:57:51 -220086.191321] SLOW spr round 16 (radius: 5)
[11:00:46 -220086.191041] SLOW spr round 17 (radius: 10)
[11:03:49 -220086.191028] SLOW spr round 18 (radius: 15)
[11:09:14 -220085.429392] SLOW spr round 19 (radius: 5)
[11:12:36 -220082.283606] SLOW spr round 20 (radius: 5)
[11:15:35 -220082.217078] SLOW spr round 21 (radius: 10)
[11:18:38 -220082.216700] SLOW spr round 22 (radius: 15)
[11:23:52 -220082.216687] SLOW spr round 23 (radius: 20)
[11:29:39] [worker #2] ML tree search #15, logLikelihood: -220045.125619
[11:31:51 -220082.216680] SLOW spr round 24 (radius: 25)
[11:41:58 -220082.068858] SLOW spr round 25 (radius: 5)
[11:45:26 -220082.067737] SLOW spr round 26 (radius: 10)
[11:49:05 -220082.067459] SLOW spr round 27 (radius: 15)
[11:54:12 -220082.067386] SLOW spr round 28 (radius: 20)
[12:02:15 -220082.067363] SLOW spr round 29 (radius: 25)
[12:12:22 -220082.067352] Model parameter optimization (eps = 0.100000)

[12:12:34] [worker #0] ML tree search #13, logLikelihood: -220081.710173

[12:12:34 -664707.850152] Initial branch length optimization
[12:12:38 -552027.780655] Model parameter optimization (eps = 10.000000)
[12:13:15 -551736.572493] AUTODETECT spr round 1 (radius: 5)
[12:16:11 -429329.615233] AUTODETECT spr round 2 (radius: 10)
[12:19:25 -332420.568171] AUTODETECT spr round 3 (radius: 15)
[12:23:41 -268190.403518] AUTODETECT spr round 4 (radius: 20)
[12:28:01 -249910.835104] AUTODETECT spr round 5 (radius: 25)
[12:34:47 -245988.850211] SPR radius for FAST iterations: 25 (autodetect)
[12:34:47 -245988.850211] Model parameter optimization (eps = 3.000000)
[12:35:27 -245261.535375] FAST spr round 1 (radius: 25)
[12:37:12] [worker #1] ML tree search #14, logLikelihood: -220041.014444
[12:41:40 -221098.010417] FAST spr round 2 (radius: 25)
[12:45:12 -220220.852431] FAST spr round 3 (radius: 25)
[12:48:07 -220144.869646] FAST spr round 4 (radius: 25)
[12:50:40 -220127.196764] FAST spr round 5 (radius: 25)
[12:53:01 -220106.652796] FAST spr round 6 (radius: 25)
[12:55:14 -220096.826698] FAST spr round 7 (radius: 25)
[12:57:25 -220093.448637] FAST spr round 8 (radius: 25)
[12:59:33 -220093.448212] Model parameter optimization (eps = 1.000000)
[12:59:53 -220085.623924] SLOW spr round 1 (radius: 5)
[13:02:41 -220057.303289] SLOW spr round 2 (radius: 5)
[13:05:27 -220052.996507] SLOW spr round 3 (radius: 5)
[13:08:07 -220052.996216] SLOW spr round 4 (radius: 10)
[13:10:58 -220052.976176] SLOW spr round 5 (radius: 15)
[13:16:34 -220052.837733] SLOW spr round 6 (radius: 5)
[13:19:57 -220052.090218] SLOW spr round 7 (radius: 5)
[13:22:56 -220052.090085] SLOW spr round 8 (radius: 10)
[13:26:02 -220050.268364] SLOW spr round 9 (radius: 5)
[13:29:15 -220049.438208] SLOW spr round 10 (radius: 5)
[13:32:10 -220049.436942] SLOW spr round 11 (radius: 10)
[13:35:10 -220049.436821] SLOW spr round 12 (radius: 15)
[13:40:32 -220049.436802] SLOW spr round 13 (radius: 20)
[13:48:55 -220049.436791] SLOW spr round 14 (radius: 25)
[13:59:44 -220049.281346] SLOW spr round 15 (radius: 5)
[14:00:04] [worker #2] ML tree search #18, logLikelihood: -220050.892393
[14:03:09 -220049.280216] SLOW spr round 16 (radius: 10)
[14:06:48 -220049.279934] SLOW spr round 17 (radius: 15)
[14:11:52 -220049.279858] SLOW spr round 18 (radius: 20)
[14:20:18 -220049.279832] SLOW spr round 19 (radius: 25)
[14:25:05] [worker #1] ML tree search #17, logLikelihood: -220045.351822
[14:31:05 -220049.279819] Model parameter optimization (eps = 0.100000)

[14:31:11] [worker #0] ML tree search #16, logLikelihood: -220049.245267

[14:31:11 -666806.178520] Initial branch length optimization
[14:31:16 -553146.414906] Model parameter optimization (eps = 10.000000)
[14:31:55 -552855.102377] AUTODETECT spr round 1 (radius: 5)
[14:34:50 -426575.358199] AUTODETECT spr round 2 (radius: 10)
[14:38:10 -343698.144515] AUTODETECT spr round 3 (radius: 15)
[14:42:20 -293342.340316] AUTODETECT spr round 4 (radius: 20)
[14:46:46 -259717.848653] AUTODETECT spr round 5 (radius: 25)
[14:52:21 -253193.328917] SPR radius for FAST iterations: 25 (autodetect)
[14:52:21 -253193.328917] Model parameter optimization (eps = 3.000000)
[14:52:51 -252504.142329] FAST spr round 1 (radius: 25)
[14:59:01 -221888.319272] FAST spr round 2 (radius: 25)
[15:02:46 -220264.574084] FAST spr round 3 (radius: 25)
[15:05:51 -220156.233186] FAST spr round 4 (radius: 25)
[15:08:19 -220143.564457] FAST spr round 5 (radius: 25)
[15:10:36 -220142.570144] FAST spr round 6 (radius: 25)
[15:12:47 -220142.565055] Model parameter optimization (eps = 1.000000)
[15:13:20 -220129.114373] SLOW spr round 1 (radius: 5)
[15:16:14 -220046.813767] SLOW spr round 2 (radius: 5)
[15:19:07 -220036.281694] SLOW spr round 3 (radius: 5)
[15:21:48 -220034.885271] SLOW spr round 4 (radius: 5)
[15:24:25 -220034.885229] SLOW spr round 5 (radius: 10)
[15:27:18 -220029.807086] SLOW spr round 6 (radius: 5)
[15:30:31 -220028.818858] SLOW spr round 7 (radius: 5)
[15:33:24 -220028.818099] SLOW spr round 8 (radius: 10)
[15:36:51 -220028.817928] SLOW spr round 9 (radius: 15)
[15:43:36 -220028.817873] SLOW spr round 10 (radius: 20)
[15:54:21 -220028.817849] SLOW spr round 11 (radius: 25)
[16:08:18 -220028.817835] Model parameter optimization (eps = 0.100000)

[16:08:31] [worker #0] ML tree search #19, logLikelihood: -220028.748672

[17:05:24] [worker #1] ML tree search #20, logLikelihood: -220033.462960

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.242864,0.208027) (0.100612,1.161641) (0.362787,1.006817) (0.293737,1.591025) 
   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: -220028.748672

AIC score: 444063.497345 / AICc score: 8472087.497345 / BIC score: 452193.921105
Free parameters (model + branch lengths): 2003

WARNING: Number of free parameters (K=2003) is larger than alignment size (n=428).
         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/Q5VY43/3_mltree/Q5VY43.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/3_mltree/Q5VY43.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/3_mltree/Q5VY43.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q5VY43/3_mltree/Q5VY43.raxml.log

Analysis started: 03-Jul-2021 23:35:20 / finished: 04-Jul-2021 16:40:45

Elapsed time: 61525.047 seconds

Consumed energy: 5366.836 Wh (= 27 km in an electric car, or 134 km with an e-scooter!)