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 06-Jul-2021 13:01:09 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/2_msa/O94886_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/3_mltree/O94886 --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/O94886/2_msa/O94886_trimmed_msa.fasta
[00:00:00] Loaded alignment with 423 taxa and 755 sites

WARNING: Sequences tr_M3YMY9_M3YMY9_MUSPF_9669 and tr_A0A2Y9JNZ8_A0A2Y9JNZ8_ENHLU_391180 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_K7CJ87_K7CJ87_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and sp_Q5T3F8_CSCL2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_G7MPF9_G7MPF9_MACMU_9544 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_G7P403_G7P403_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_A0A0D9RIH6_A0A0D9RIH6_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_A0A2K5NKT3_A0A2K5NKT3_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_A0A2K6D880_A0A2K6D880_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_A0A2K5Z8V4_A0A2K5Z8V4_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G3QKP3_G3QKP3_GORGO_9595 and tr_A0A2R8ZS96_A0A2R8ZS96_PANPA_9597 are exactly identical!
WARNING: Sequences sp_O94886_CSCL1_HUMAN_9606 and tr_A0A2R9B2E1_A0A2R9B2E1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G7MYW2_G7MYW2_MACMU_9544 and tr_A0A096NS77_A0A096NS77_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G7MYW2_G7MYW2_MACMU_9544 and tr_A0A2K6BEJ5_A0A2K6BEJ5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A1S3JLU6_A0A1S3JLU6_LINUN_7574 and tr_A0A1S3JN52_A0A1S3JN52_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A226NCV0_A0A226NCV0_CALSU_9009 and tr_A0A226PA82_A0A226PA82_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2D0T6G1_A0A2D0T6G1_ICTPU_7998 and tr_W5UK26_W5UK26_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2Y9NUL0_A0A2Y9NUL0_DELLE_9749 and tr_A0A2Y9ESX0_A0A2Y9ESX0_PHYCD_9755 are exactly identical!
WARNING: Sequences tr_A0A2Y9NUL0_A0A2Y9NUL0_DELLE_9749 and tr_A0A384B2K6_A0A384B2K6_BALAS_310752 are exactly identical!
WARNING: Duplicate sequences found: 18

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/O94886/3_mltree/O94886.raxml.reduced.phy

Alignment comprises 1 partitions and 755 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 755 / 755
Gaps: 13.48 %
Invariant sites: 0.53 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/3_mltree/O94886.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 423 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 -430433.125038] Initial branch length optimization
[00:00:02 -346734.464330] Model parameter optimization (eps = 10.000000)
[00:00:23 -345415.906465] AUTODETECT spr round 1 (radius: 5)
[00:00:59 -233634.824531] AUTODETECT spr round 2 (radius: 10)
[00:01:41 -180213.696880] AUTODETECT spr round 3 (radius: 15)
[00:02:29 -156015.104758] AUTODETECT spr round 4 (radius: 20)
[00:03:27 -153160.456489] AUTODETECT spr round 5 (radius: 25)
[00:04:30 -140720.590025] SPR radius for FAST iterations: 25 (autodetect)
[00:04:30 -140720.590025] Model parameter optimization (eps = 3.000000)
[00:04:45 -140562.659423] FAST spr round 1 (radius: 25)
[00:05:33 -120362.729236] FAST spr round 2 (radius: 25)
[00:06:14 -118651.823162] FAST spr round 3 (radius: 25)
[00:06:49 -118393.238477] FAST spr round 4 (radius: 25)
[00:07:22 -118376.537332] FAST spr round 5 (radius: 25)
[00:07:52 -118371.104888] FAST spr round 6 (radius: 25)
[00:08:21 -118371.101063] Model parameter optimization (eps = 1.000000)
[00:08:37 -118323.776518] SLOW spr round 1 (radius: 5)
[00:09:22 -118296.520623] SLOW spr round 2 (radius: 5)
[00:10:04 -118294.565908] SLOW spr round 3 (radius: 5)
[00:10:44 -118294.565807] SLOW spr round 4 (radius: 10)
[00:11:27 -118293.508181] SLOW spr round 5 (radius: 5)
[00:12:24 -118293.507600] SLOW spr round 6 (radius: 10)
[00:13:14 -118293.507563] SLOW spr round 7 (radius: 15)
[00:14:21 -118293.507535] SLOW spr round 8 (radius: 20)
[00:16:02 -118292.454357] SLOW spr round 9 (radius: 5)
[00:17:08 -118291.644666] SLOW spr round 10 (radius: 5)
[00:17:43] [worker #1] ML tree search #2, logLikelihood: -118315.451624
[00:18:02 -118291.644630] SLOW spr round 11 (radius: 10)
[00:18:49 -118291.644602] SLOW spr round 12 (radius: 15)
[00:19:57 -118291.644577] SLOW spr round 13 (radius: 20)
[00:21:34 -118291.644552] SLOW spr round 14 (radius: 25)
[00:23:31 -118291.644527] Model parameter optimization (eps = 0.100000)

[00:23:36] [worker #0] ML tree search #1, logLikelihood: -118291.381006

[00:23:37 -430865.080618] Initial branch length optimization
[00:23:39 -347032.633219] Model parameter optimization (eps = 10.000000)
[00:24:01 -345666.462306] AUTODETECT spr round 1 (radius: 5)
[00:24:40 -229810.090821] AUTODETECT spr round 2 (radius: 10)
[00:25:20 -179614.848691] AUTODETECT spr round 3 (radius: 15)
[00:26:15 -157978.955399] AUTODETECT spr round 4 (radius: 20)
[00:27:16 -142936.894113] AUTODETECT spr round 5 (radius: 25)
[00:28:24 -141221.964048] SPR radius for FAST iterations: 25 (autodetect)
[00:28:24 -141221.964048] Model parameter optimization (eps = 3.000000)
[00:28:42 -140930.418109] FAST spr round 1 (radius: 25)
[00:29:36 -120211.556167] FAST spr round 2 (radius: 25)
[00:30:17 -118412.840353] FAST spr round 3 (radius: 25)
[00:30:50 -118365.012935] FAST spr round 4 (radius: 25)
[00:31:19 -118363.797501] FAST spr round 5 (radius: 25)
[00:31:47 -118363.796391] Model parameter optimization (eps = 1.000000)
[00:32:11 -118336.664745] SLOW spr round 1 (radius: 5)
[00:32:55 -118301.679127] SLOW spr round 2 (radius: 5)
[00:33:38 -118299.572906] SLOW spr round 3 (radius: 5)
[00:34:22 -118298.662347] SLOW spr round 4 (radius: 5)
[00:35:04 -118298.661767] SLOW spr round 5 (radius: 10)
[00:35:49 -118298.661518] SLOW spr round 6 (radius: 15)
[00:37:03 -118297.833231] SLOW spr round 7 (radius: 5)
[00:38:05 -118297.833102] SLOW spr round 8 (radius: 10)
[00:38:59 -118297.833046] SLOW spr round 9 (radius: 15)
[00:40:02] [worker #1] ML tree search #4, logLikelihood: -118302.920725
[00:40:07 -118297.833006] SLOW spr round 10 (radius: 20)
[00:41:46 -118297.832974] SLOW spr round 11 (radius: 25)
[00:43:41 -118297.832947] Model parameter optimization (eps = 0.100000)

[00:43:47] [worker #0] ML tree search #3, logLikelihood: -118297.659069

[00:43:47 -426146.688242] Initial branch length optimization
[00:43:50 -341303.885295] Model parameter optimization (eps = 10.000000)
[00:44:12 -339965.222558] AUTODETECT spr round 1 (radius: 5)
[00:44:49 -225761.062835] AUTODETECT spr round 2 (radius: 10)
[00:45:29 -172404.414550] AUTODETECT spr round 3 (radius: 15)
[00:46:14 -152455.493948] AUTODETECT spr round 4 (radius: 20)
[00:47:12 -139225.274883] AUTODETECT spr round 5 (radius: 25)
[00:48:31 -136726.578057] SPR radius for FAST iterations: 25 (autodetect)
[00:48:31 -136726.578057] Model parameter optimization (eps = 3.000000)
[00:48:45 -136589.890052] FAST spr round 1 (radius: 25)
[00:49:38 -119095.437729] FAST spr round 2 (radius: 25)
[00:50:18 -118414.016749] FAST spr round 3 (radius: 25)
[00:50:51 -118385.713818] FAST spr round 4 (radius: 25)
[00:51:20 -118377.587287] FAST spr round 5 (radius: 25)
[00:51:46 -118377.586865] Model parameter optimization (eps = 1.000000)
[00:52:03 -118352.929783] SLOW spr round 1 (radius: 5)
[00:52:48 -118313.954894] SLOW spr round 2 (radius: 5)
[00:53:33 -118309.808242] SLOW spr round 3 (radius: 5)
[00:54:16 -118309.804247] SLOW spr round 4 (radius: 10)
[00:55:02 -118309.802753] SLOW spr round 5 (radius: 15)
[00:56:22 -118309.043307] SLOW spr round 6 (radius: 5)
[00:57:25 -118309.043019] SLOW spr round 7 (radius: 10)
[00:58:20 -118309.042901] SLOW spr round 8 (radius: 15)
[00:59:29] [worker #1] ML tree search #6, logLikelihood: -118317.104639
[00:59:32 -118309.042843] SLOW spr round 9 (radius: 20)
[01:01:18 -118309.042810] SLOW spr round 10 (radius: 25)
[01:03:24 -118309.042785] Model parameter optimization (eps = 0.100000)

[01:03:36] [worker #0] ML tree search #5, logLikelihood: -118305.371452

[01:03:36 -429045.761008] Initial branch length optimization
[01:03:39 -348853.800529] Model parameter optimization (eps = 10.000000)
[01:03:59 -347534.816235] AUTODETECT spr round 1 (radius: 5)
[01:04:39 -218549.608393] AUTODETECT spr round 2 (radius: 10)
[01:05:21 -155319.101960] AUTODETECT spr round 3 (radius: 15)
[01:06:10 -139303.244807] AUTODETECT spr round 4 (radius: 20)
[01:07:13 -134722.126195] AUTODETECT spr round 5 (radius: 25)
[01:08:27 -132360.292995] SPR radius for FAST iterations: 25 (autodetect)
[01:08:27 -132360.292995] Model parameter optimization (eps = 3.000000)
[01:08:47 -132120.605620] FAST spr round 1 (radius: 25)
[01:09:41 -118742.161024] FAST spr round 2 (radius: 25)
[01:10:20 -118402.867778] FAST spr round 3 (radius: 25)
[01:10:57 -118387.124346] FAST spr round 4 (radius: 25)
[01:11:26 -118387.122480] Model parameter optimization (eps = 1.000000)
[01:11:46 -118360.220662] SLOW spr round 1 (radius: 5)
[01:12:34 -118319.808813] SLOW spr round 2 (radius: 5)
[01:13:19 -118318.251529] SLOW spr round 3 (radius: 5)
[01:14:03 -118317.694227] SLOW spr round 4 (radius: 5)
[01:14:45 -118317.694046] SLOW spr round 5 (radius: 10)
[01:15:30 -118316.753884] SLOW spr round 6 (radius: 5)
[01:16:30 -118316.753524] SLOW spr round 7 (radius: 10)
[01:17:22 -118316.753486] SLOW spr round 8 (radius: 15)
[01:18:28 -118316.020754] SLOW spr round 9 (radius: 5)
[01:19:32 -118314.231984] SLOW spr round 10 (radius: 5)
[01:20:25 -118314.231964] SLOW spr round 11 (radius: 10)
[01:21:13 -118314.231947] SLOW spr round 12 (radius: 15)
[01:22:21 -118314.231931] SLOW spr round 13 (radius: 20)
[01:22:55] [worker #1] ML tree search #8, logLikelihood: -118296.133251
[01:23:56 -118314.231914] SLOW spr round 14 (radius: 25)
[01:25:45 -118314.231897] Model parameter optimization (eps = 0.100000)

[01:25:48] [worker #0] ML tree search #7, logLikelihood: -118314.187960

[01:25:48 -427316.191160] Initial branch length optimization
[01:25:51 -341891.035623] Model parameter optimization (eps = 10.000000)
[01:26:14 -340573.175263] AUTODETECT spr round 1 (radius: 5)
[01:26:50 -220885.002901] AUTODETECT spr round 2 (radius: 10)
[01:27:31 -164100.807048] AUTODETECT spr round 3 (radius: 15)
[01:28:21 -150598.699758] AUTODETECT spr round 4 (radius: 20)
[01:29:15 -149958.164992] AUTODETECT spr round 5 (radius: 25)
[01:30:14 -148037.280806] SPR radius for FAST iterations: 25 (autodetect)
[01:30:14 -148037.280806] Model parameter optimization (eps = 3.000000)
[01:30:31 -147872.194043] FAST spr round 1 (radius: 25)
[01:31:30 -122369.445583] FAST spr round 2 (radius: 25)
[01:32:15 -118803.563934] FAST spr round 3 (radius: 25)
[01:32:54 -118376.601250] FAST spr round 4 (radius: 25)
[01:33:26 -118368.986855] FAST spr round 5 (radius: 25)
[01:33:55 -118368.964172] Model parameter optimization (eps = 1.000000)
[01:34:12 -118336.447614] SLOW spr round 1 (radius: 5)
[01:35:00 -118305.157777] SLOW spr round 2 (radius: 5)
[01:35:46 -118301.074422] SLOW spr round 3 (radius: 5)
[01:36:28 -118301.073808] SLOW spr round 4 (radius: 10)
[01:37:13 -118301.073565] SLOW spr round 5 (radius: 15)
[01:38:33 -118300.030636] SLOW spr round 6 (radius: 5)
[01:39:36 -118299.242567] SLOW spr round 7 (radius: 5)
[01:40:29 -118299.242534] SLOW spr round 8 (radius: 10)
[01:41:17 -118299.242510] SLOW spr round 9 (radius: 15)
[01:42:33 -118299.242490] SLOW spr round 10 (radius: 20)
[01:44:28 -118299.242470] SLOW spr round 11 (radius: 25)
[01:46:00] [worker #1] ML tree search #10, logLikelihood: -118298.359593
[01:46:39 -118299.242451] Model parameter optimization (eps = 0.100000)

[01:46:49] [worker #0] ML tree search #9, logLikelihood: -118295.080618

[01:46:49 -430798.444899] Initial branch length optimization
[01:46:51 -344059.380425] Model parameter optimization (eps = 10.000000)
[01:47:15 -342786.899480] AUTODETECT spr round 1 (radius: 5)
[01:47:52 -217402.568607] AUTODETECT spr round 2 (radius: 10)
[01:48:32 -166561.641633] AUTODETECT spr round 3 (radius: 15)
[01:49:16 -143966.334134] AUTODETECT spr round 4 (radius: 20)
[01:50:11 -136310.261560] AUTODETECT spr round 5 (radius: 25)
[01:51:13 -135777.925982] SPR radius for FAST iterations: 25 (autodetect)
[01:51:13 -135777.925982] Model parameter optimization (eps = 3.000000)
[01:51:34 -135508.242353] FAST spr round 1 (radius: 25)
[01:52:22 -118935.242275] FAST spr round 2 (radius: 25)
[01:53:00 -118424.916345] FAST spr round 3 (radius: 25)
[01:53:35 -118394.079072] FAST spr round 4 (radius: 25)
[01:54:03 -118391.406163] FAST spr round 5 (radius: 25)
[01:54:30 -118391.406113] Model parameter optimization (eps = 1.000000)
[01:54:41 -118378.463887] SLOW spr round 1 (radius: 5)
[01:55:26 -118329.792717] SLOW spr round 2 (radius: 5)
[01:56:09 -118324.736835] SLOW spr round 3 (radius: 5)
[01:56:51 -118319.381488] SLOW spr round 4 (radius: 5)
[01:57:31 -118319.379555] SLOW spr round 5 (radius: 10)
[01:58:14 -118315.829381] SLOW spr round 6 (radius: 5)
[01:59:10 -118315.826314] SLOW spr round 7 (radius: 10)
[01:59:59 -118315.825810] SLOW spr round 8 (radius: 15)
[02:01:14 -118313.435336] SLOW spr round 9 (radius: 5)
[02:02:13 -118312.664518] SLOW spr round 10 (radius: 5)
[02:03:03 -118312.664482] SLOW spr round 11 (radius: 10)
[02:03:47 -118312.664454] SLOW spr round 12 (radius: 15)
[02:05:03 -118312.664429] SLOW spr round 13 (radius: 20)
[02:06:50 -118309.320993] SLOW spr round 14 (radius: 5)
[02:07:52 -118307.535783] SLOW spr round 15 (radius: 5)
[02:08:44 -118307.534572] SLOW spr round 16 (radius: 10)
[02:09:30 -118307.534369] SLOW spr round 17 (radius: 15)
[02:10:17] [worker #1] ML tree search #12, logLikelihood: -118292.587401
[02:10:37 -118307.534304] SLOW spr round 18 (radius: 20)
[02:12:04 -118307.534267] SLOW spr round 19 (radius: 25)
[02:13:45 -118307.534238] Model parameter optimization (eps = 0.100000)

[02:13:53] [worker #0] ML tree search #11, logLikelihood: -118306.770457

[02:13:53 -428600.424865] Initial branch length optimization
[02:13:56 -345208.423433] Model parameter optimization (eps = 10.000000)
[02:14:36 -343963.805618] AUTODETECT spr round 1 (radius: 5)
[02:15:11 -226053.431184] AUTODETECT spr round 2 (radius: 10)
[02:15:51 -167864.547438] AUTODETECT spr round 3 (radius: 15)
[02:16:35 -139417.843253] AUTODETECT spr round 4 (radius: 20)
[02:17:39 -131580.489174] AUTODETECT spr round 5 (radius: 25)
[02:18:55 -131112.357051] SPR radius for FAST iterations: 25 (autodetect)
[02:18:55 -131112.357051] Model parameter optimization (eps = 3.000000)
[02:19:10 -130971.051000] FAST spr round 1 (radius: 25)
[02:19:55 -118873.717362] FAST spr round 2 (radius: 25)
[02:20:33 -118426.042741] FAST spr round 3 (radius: 25)
[02:21:06 -118364.861933] FAST spr round 4 (radius: 25)
[02:21:35 -118361.171855] FAST spr round 5 (radius: 25)
[02:22:02 -118361.171523] Model parameter optimization (eps = 1.000000)
[02:22:15 -118325.878929] SLOW spr round 1 (radius: 5)
[02:22:58 -118305.844326] SLOW spr round 2 (radius: 5)
[02:23:41 -118301.456777] SLOW spr round 3 (radius: 5)
[02:24:22 -118300.756467] SLOW spr round 4 (radius: 5)
[02:25:02 -118300.755870] SLOW spr round 5 (radius: 10)
[02:25:44 -118299.937523] SLOW spr round 6 (radius: 5)
[02:26:41 -118299.937312] SLOW spr round 7 (radius: 10)
[02:27:30 -118299.937269] SLOW spr round 8 (radius: 15)
[02:28:37 -118299.937239] SLOW spr round 9 (radius: 20)
[02:30:13 -118299.937212] SLOW spr round 10 (radius: 25)
[02:30:35] [worker #1] ML tree search #14, logLikelihood: -118307.801962
[02:32:08 -118299.937188] Model parameter optimization (eps = 0.100000)

[02:32:18] [worker #0] ML tree search #13, logLikelihood: -118293.273322

[02:32:18 -435646.861063] Initial branch length optimization
[02:32:20 -345668.104639] Model parameter optimization (eps = 10.000000)
[02:32:41 -344368.998613] AUTODETECT spr round 1 (radius: 5)
[02:33:19 -232776.349718] AUTODETECT spr round 2 (radius: 10)
[02:33:58 -180670.962429] AUTODETECT spr round 3 (radius: 15)
[02:34:52 -144301.000854] AUTODETECT spr round 4 (radius: 20)
[02:35:44 -138443.693665] AUTODETECT spr round 5 (radius: 25)
[02:36:50 -138275.185867] SPR radius for FAST iterations: 25 (autodetect)
[02:36:50 -138275.185867] Model parameter optimization (eps = 3.000000)
[02:37:07 -137921.657421] FAST spr round 1 (radius: 25)
[02:37:58 -119088.106243] FAST spr round 2 (radius: 25)
[02:38:40 -118382.380480] FAST spr round 3 (radius: 25)
[02:39:12 -118350.099403] FAST spr round 4 (radius: 25)
[02:39:40 -118349.024425] FAST spr round 5 (radius: 25)
[02:40:07 -118349.024204] Model parameter optimization (eps = 1.000000)
[02:40:24 -118343.437345] SLOW spr round 1 (radius: 5)
[02:41:10 -118305.603753] SLOW spr round 2 (radius: 5)
[02:41:53 -118297.054154] SLOW spr round 3 (radius: 5)
[02:42:33 -118297.052647] SLOW spr round 4 (radius: 10)
[02:43:17 -118294.509782] SLOW spr round 5 (radius: 5)
[02:44:13 -118294.499967] SLOW spr round 6 (radius: 10)
[02:45:03 -118294.499446] SLOW spr round 7 (radius: 15)
[02:46:13 -118293.660494] SLOW spr round 8 (radius: 5)
[02:47:13 -118293.660418] SLOW spr round 9 (radius: 10)
[02:48:06 -118293.660400] SLOW spr round 10 (radius: 15)
[02:48:19] [worker #1] ML tree search #16, logLikelihood: -118298.087764
[02:49:16 -118293.660385] SLOW spr round 11 (radius: 20)
[02:50:59 -118293.660370] SLOW spr round 12 (radius: 25)
[02:53:02 -118293.660356] Model parameter optimization (eps = 0.100000)

[02:53:07] [worker #0] ML tree search #15, logLikelihood: -118293.504183

[02:53:07 -428911.127388] Initial branch length optimization
[02:53:10 -345597.288644] Model parameter optimization (eps = 10.000000)
[02:53:32 -344369.537563] AUTODETECT spr round 1 (radius: 5)
[02:54:06 -222161.367102] AUTODETECT spr round 2 (radius: 10)
[02:54:45 -166411.371626] AUTODETECT spr round 3 (radius: 15)
[02:55:33 -138488.187799] AUTODETECT spr round 4 (radius: 20)
[02:56:29 -133938.466405] AUTODETECT spr round 5 (radius: 25)
[02:57:33 -133451.797622] SPR radius for FAST iterations: 25 (autodetect)
[02:57:33 -133451.797622] Model parameter optimization (eps = 3.000000)
[02:57:50 -133323.884384] FAST spr round 1 (radius: 25)
[02:58:37 -119094.719683] FAST spr round 2 (radius: 25)
[02:59:12 -118394.911154] FAST spr round 3 (radius: 25)
[02:59:46 -118364.060214] FAST spr round 4 (radius: 25)
[03:00:16 -118361.451438] FAST spr round 5 (radius: 25)
[03:00:43 -118361.449550] Model parameter optimization (eps = 1.000000)
[03:00:57 -118351.169210] SLOW spr round 1 (radius: 5)
[03:01:40 -118315.703224] SLOW spr round 2 (radius: 5)
[03:02:23 -118305.751888] SLOW spr round 3 (radius: 5)
[03:03:04 -118305.747786] SLOW spr round 4 (radius: 10)
[03:03:48 -118299.757212] SLOW spr round 5 (radius: 5)
[03:04:44 -118299.239057] SLOW spr round 6 (radius: 5)
[03:05:31 -118299.238652] SLOW spr round 7 (radius: 10)
[03:06:17 -118299.238514] SLOW spr round 8 (radius: 15)
[03:07:24 -118299.238428] SLOW spr round 9 (radius: 20)
[03:08:10] [worker #1] ML tree search #18, logLikelihood: -118303.910601
[03:08:59 -118299.238369] SLOW spr round 10 (radius: 25)
[03:11:01 -118299.238326] Model parameter optimization (eps = 0.100000)

[03:11:09] [worker #0] ML tree search #17, logLikelihood: -118297.908069

[03:11:09 -428110.229649] Initial branch length optimization
[03:11:11 -344279.864526] Model parameter optimization (eps = 10.000000)
[03:11:32 -343019.639922] AUTODETECT spr round 1 (radius: 5)
[03:12:10 -229060.173823] AUTODETECT spr round 2 (radius: 10)
[03:12:52 -169092.879825] AUTODETECT spr round 3 (radius: 15)
[03:13:39 -152672.390847] AUTODETECT spr round 4 (radius: 20)
[03:14:42 -134013.021886] AUTODETECT spr round 5 (radius: 25)
[03:15:41 -133734.230939] SPR radius for FAST iterations: 25 (autodetect)
[03:15:41 -133734.230939] Model parameter optimization (eps = 3.000000)
[03:15:59 -133548.854185] FAST spr round 1 (radius: 25)
[03:16:42 -118884.342190] FAST spr round 2 (radius: 25)
[03:17:18 -118430.380436] FAST spr round 3 (radius: 25)
[03:17:49 -118394.983420] FAST spr round 4 (radius: 25)
[03:18:19 -118386.168784] FAST spr round 5 (radius: 25)
[03:18:46 -118386.168707] Model parameter optimization (eps = 1.000000)
[03:19:01 -118349.568989] SLOW spr round 1 (radius: 5)
[03:19:43 -118308.806472] SLOW spr round 2 (radius: 5)
[03:20:24 -118308.668384] SLOW spr round 3 (radius: 5)
[03:21:03 -118308.666818] SLOW spr round 4 (radius: 10)
[03:21:47 -118308.666162] SLOW spr round 5 (radius: 15)
[03:23:01 -118307.909256] SLOW spr round 6 (radius: 5)
[03:24:01 -118307.909105] SLOW spr round 7 (radius: 10)
[03:24:54 -118307.909043] SLOW spr round 8 (radius: 15)
[03:26:02 -118307.909009] SLOW spr round 9 (radius: 20)
[03:27:43 -118307.908987] SLOW spr round 10 (radius: 25)
[03:28:14] [worker #1] ML tree search #20, logLikelihood: -118305.697646
[03:29:48 -118307.908970] Model parameter optimization (eps = 0.100000)

[03:29:59] [worker #0] ML tree search #19, logLikelihood: -118302.378916


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.242807,0.537577) (0.188290,0.913464) (0.352979,0.823331) (0.215924,1.884265) 
   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: -118291.381006

AIC score: 238280.762011 / AICc score: 1681580.762011 / BIC score: 242208.845380
Free parameters (model + branch lengths): 849

WARNING: Number of free parameters (K=849) is larger than alignment size (n=755).
         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/O94886/3_mltree/O94886.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/3_mltree/O94886.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/3_mltree/O94886.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/O94886/3_mltree/O94886.raxml.log

Analysis started: 06-Jul-2021 13:01:09 / finished: 06-Jul-2021 16:31:09

Elapsed time: 12599.756 seconds

Consumed energy: 845.730 Wh (= 4 km in an electric car, or 21 km with an e-scooter!)