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 05:15:00 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/2_msa/P26640_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/3_mltree/P26640 --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/P26640/2_msa/P26640_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 977 sites

WARNING: Sequences tr_J3KKS7_J3KKS7_COCIM_246410 and tr_A0A0J6YPP7_A0A0J6YPP7_COCIT_404692 are exactly identical!
WARNING: Sequences tr_B6QM17_B6QM17_TALMQ_441960 and tr_A0A093V097_A0A093V097_TALMA_1077442 are exactly identical!
WARNING: Sequences tr_B2WCA6_B2WCA6_PYRTR_426418 and tr_A0A2W1E8F2_A0A2W1E8F2_9PLEO_45151 are exactly identical!
WARNING: Sequences tr_H2RBW3_H2RBW3_PANTR_9598 and tr_A0A2R9C5F8_A0A2R9C5F8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F9F236_F9F236_FUSOF_660025 and tr_N4TP51_N4TP51_FUSC1_1229664 are exactly identical!
WARNING: Sequences tr_F7BX36_F7BX36_MACMU_9544 and tr_G7P4M7_G7P4M7_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G7XQR5_G7XQR5_ASPKW_1033177 and tr_A0A146FU55_A0A146FU55_9EURO_1069201 are exactly identical!
WARNING: Sequences tr_L0PDB3_L0PDB3_PNEJ8_1209962 and tr_A0A0W4ZES6_A0A0W4ZES6_PNEJ7_1408657 are exactly identical!
WARNING: Sequences tr_L2FG30_L2FG30_COLFN_1213859 and tr_T0LLA4_T0LLA4_COLGC_1237896 are exactly identical!
WARNING: Sequences tr_A0A015MSS7_A0A015MSS7_9GLOM_1432141 and tr_U9TCE3_U9TCE3_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A094E9D6_A0A094E9D6_9PEZI_1420912 and tr_A0A1B8GK47_A0A1B8GK47_9PEZI_342668 are exactly identical!
WARNING: Sequences tr_A0A100ILM1_A0A100ILM1_ASPNG_5061 and tr_A0A1L9N4B7_A0A1L9N4B7_ASPTU_767770 are exactly identical!
WARNING: Duplicate sequences found: 12

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/P26640/3_mltree/P26640.raxml.reduced.phy

Alignment comprises 1 partitions and 977 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 977 / 977
Gaps: 2.21 %
Invariant sites: 2.35 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/3_mltree/P26640.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 / 245 / 19600
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1431913.536977] Initial branch length optimization
[00:00:07 -1257606.355378] Model parameter optimization (eps = 10.000000)
[00:00:56 -1255407.439896] AUTODETECT spr round 1 (radius: 5)
[00:04:37 -886773.871982] AUTODETECT spr round 2 (radius: 10)
[00:08:54 -617498.828942] AUTODETECT spr round 3 (radius: 15)
[00:13:42 -524041.019056] AUTODETECT spr round 4 (radius: 20)
[00:19:41 -509127.434241] AUTODETECT spr round 5 (radius: 25)
[00:27:04 -508368.160010] SPR radius for FAST iterations: 25 (autodetect)
[00:27:04 -508368.160010] Model parameter optimization (eps = 3.000000)
[00:27:30 -508177.723204] FAST spr round 1 (radius: 25)
[00:32:16 -455731.130231] FAST spr round 2 (radius: 25)
[00:35:52 -453743.724521] FAST spr round 3 (radius: 25)
[00:39:00 -453544.306914] FAST spr round 4 (radius: 25)
[00:41:37 -453525.093198] FAST spr round 5 (radius: 25)
[00:44:07 -453525.093131] Model parameter optimization (eps = 1.000000)
[00:44:24 -453518.496013] SLOW spr round 1 (radius: 5)
[00:48:30 -453409.750437] SLOW spr round 2 (radius: 5)
[00:52:18 -453376.201482] SLOW spr round 3 (radius: 5)
[00:55:48 -453374.662297] SLOW spr round 4 (radius: 5)
[00:59:14 -453374.662234] SLOW spr round 5 (radius: 10)
[01:02:52 -453372.508649] SLOW spr round 6 (radius: 5)
[01:07:28 -453372.508527] SLOW spr round 7 (radius: 10)
[01:11:35 -453372.508482] SLOW spr round 8 (radius: 15)
[01:17:24 -453372.508438] SLOW spr round 9 (radius: 20)
[01:27:07 -453372.508394] SLOW spr round 10 (radius: 25)
[01:37:48] [worker #1] ML tree search #2, logLikelihood: -453504.405726
[01:39:21 -453372.508349] Model parameter optimization (eps = 0.100000)

[01:39:32] [worker #0] ML tree search #1, logLikelihood: -453372.402773

[01:39:32 -1437898.810550] Initial branch length optimization
[01:39:38 -1258411.212569] Model parameter optimization (eps = 10.000000)
[01:40:34 -1256088.482757] AUTODETECT spr round 1 (radius: 5)
[01:44:26 -901986.319794] AUTODETECT spr round 2 (radius: 10)
[01:48:57 -630477.156932] AUTODETECT spr round 3 (radius: 15)
[01:53:31 -527392.303133] AUTODETECT spr round 4 (radius: 20)
[01:58:53 -510292.811567] AUTODETECT spr round 5 (radius: 25)
[02:05:49 -506870.423257] SPR radius for FAST iterations: 25 (autodetect)
[02:05:49 -506870.423257] Model parameter optimization (eps = 3.000000)
[02:06:03 -506863.937419] FAST spr round 1 (radius: 25)
[02:10:48 -455215.590531] FAST spr round 2 (radius: 25)
[02:14:20 -453914.092660] FAST spr round 3 (radius: 25)
[02:17:20 -453744.192537] FAST spr round 4 (radius: 25)
[02:19:57 -453723.816817] FAST spr round 5 (radius: 25)
[02:22:18 -453723.816746] Model parameter optimization (eps = 1.000000)
[02:22:24 -453723.554188] SLOW spr round 1 (radius: 5)
[02:26:28 -453574.264769] SLOW spr round 2 (radius: 5)
[02:30:05 -453564.766086] SLOW spr round 3 (radius: 5)
[02:33:36 -453553.410815] SLOW spr round 4 (radius: 5)
[02:36:55 -453553.410677] SLOW spr round 5 (radius: 10)
[02:40:29 -453553.410676] SLOW spr round 6 (radius: 15)
[02:46:38 -453553.410676] SLOW spr round 7 (radius: 20)
[02:56:24 -453553.410676] SLOW spr round 8 (radius: 25)
[03:09:21 -453553.410676] Model parameter optimization (eps = 0.100000)

[03:09:26] [worker #0] ML tree search #3, logLikelihood: -453553.395033

[03:09:26 -1435623.366438] Initial branch length optimization
[03:09:32 -1259579.024122] Model parameter optimization (eps = 10.000000)
[03:10:27 -1257122.866505] AUTODETECT spr round 1 (radius: 5)
[03:11:14] [worker #1] ML tree search #4, logLikelihood: -453366.876510
[03:14:14 -907426.608026] AUTODETECT spr round 2 (radius: 10)
[03:18:18 -642106.254760] AUTODETECT spr round 3 (radius: 15)
[03:22:32 -566226.295935] AUTODETECT spr round 4 (radius: 20)
[03:27:58 -532360.356676] AUTODETECT spr round 5 (radius: 25)
[03:33:47 -525531.943581] SPR radius for FAST iterations: 25 (autodetect)
[03:33:47 -525531.943581] Model parameter optimization (eps = 3.000000)
[03:34:15 -525309.103631] FAST spr round 1 (radius: 25)
[03:39:21 -456085.550323] FAST spr round 2 (radius: 25)
[03:43:03 -453976.062651] FAST spr round 3 (radius: 25)
[03:46:04 -453514.589966] FAST spr round 4 (radius: 25)
[03:48:36 -453487.825895] FAST spr round 5 (radius: 25)
[03:50:59 -453487.825831] Model parameter optimization (eps = 1.000000)
[03:51:22 -453479.064782] SLOW spr round 1 (radius: 5)
[03:55:28 -453405.082282] SLOW spr round 2 (radius: 5)
[03:59:06 -453398.992782] SLOW spr round 3 (radius: 5)
[04:02:31 -453396.999785] SLOW spr round 4 (radius: 5)
[04:05:54 -453396.999784] SLOW spr round 5 (radius: 10)
[04:09:28 -453396.999784] SLOW spr round 6 (radius: 15)
[04:15:47 -453396.999784] SLOW spr round 7 (radius: 20)
[04:25:39 -453396.999784] SLOW spr round 8 (radius: 25)
[04:38:46 -453396.999784] Model parameter optimization (eps = 0.100000)

[04:39:07] [worker #0] ML tree search #5, logLikelihood: -453394.605501

[04:39:07 -1426402.875196] Initial branch length optimization
[04:39:16 -1254044.051552] Model parameter optimization (eps = 10.000000)
[04:40:00 -1251827.495106] AUTODETECT spr round 1 (radius: 5)
[04:43:43 -890900.230759] AUTODETECT spr round 2 (radius: 10)
[04:47:49 -612398.206093] AUTODETECT spr round 3 (radius: 15)
[04:52:04 -533158.230565] AUTODETECT spr round 4 (radius: 20)
[04:53:59] [worker #1] ML tree search #6, logLikelihood: -453375.483125
[04:57:07 -505217.886985] AUTODETECT spr round 5 (radius: 25)
[05:02:56 -503220.316256] SPR radius for FAST iterations: 25 (autodetect)
[05:02:56 -503220.316256] Model parameter optimization (eps = 3.000000)
[05:03:07 -503213.358949] FAST spr round 1 (radius: 25)
[05:07:48 -455904.349504] FAST spr round 2 (radius: 25)
[05:11:14 -453813.186471] FAST spr round 3 (radius: 25)
[05:14:08 -453703.982218] FAST spr round 4 (radius: 25)
[05:16:45 -453679.282457] FAST spr round 5 (radius: 25)
[05:19:11 -453679.282449] Model parameter optimization (eps = 1.000000)
[05:19:36 -453527.827927] SLOW spr round 1 (radius: 5)
[05:23:39 -453396.398092] SLOW spr round 2 (radius: 5)
[05:27:27 -453379.230676] SLOW spr round 3 (radius: 5)
[05:31:10 -453369.664936] SLOW spr round 4 (radius: 5)
[05:34:46 -453366.201816] SLOW spr round 5 (radius: 5)
[05:38:18 -453365.158777] SLOW spr round 6 (radius: 5)
[05:41:46 -453365.158761] SLOW spr round 7 (radius: 10)
[05:45:25 -453362.768736] SLOW spr round 8 (radius: 5)
[05:50:04 -453362.768658] SLOW spr round 9 (radius: 10)
[05:54:18 -453362.768658] SLOW spr round 10 (radius: 15)
[06:00:17 -453362.768658] SLOW spr round 11 (radius: 20)
[06:10:46 -453362.768658] SLOW spr round 12 (radius: 25)
[06:23:45] [worker #1] ML tree search #8, logLikelihood: -453391.872463
[06:24:08 -453362.768658] Model parameter optimization (eps = 0.100000)

[06:24:23] [worker #0] ML tree search #7, logLikelihood: -453362.390781

[06:24:23 -1423760.446143] Initial branch length optimization
[06:24:33 -1248851.872877] Model parameter optimization (eps = 10.000000)
[06:25:19 -1246680.824552] AUTODETECT spr round 1 (radius: 5)
[06:29:09 -908273.530785] AUTODETECT spr round 2 (radius: 10)
[06:33:23 -660964.253163] AUTODETECT spr round 3 (radius: 15)
[06:37:55 -576332.189827] AUTODETECT spr round 4 (radius: 20)
[06:43:36 -527373.791219] AUTODETECT spr round 5 (radius: 25)
[06:49:55 -521326.624420] SPR radius for FAST iterations: 25 (autodetect)
[06:49:55 -521326.624420] Model parameter optimization (eps = 3.000000)
[06:50:23 -521087.977859] FAST spr round 1 (radius: 25)
[06:55:35 -455842.268856] FAST spr round 2 (radius: 25)
[06:59:06 -453693.608610] FAST spr round 3 (radius: 25)
[07:02:08 -453575.780417] FAST spr round 4 (radius: 25)
[07:04:54 -453526.710063] FAST spr round 5 (radius: 25)
[07:07:20 -453526.709935] Model parameter optimization (eps = 1.000000)
[07:07:39 -453520.997143] SLOW spr round 1 (radius: 5)
[07:11:48 -453384.704230] SLOW spr round 2 (radius: 5)
[07:15:28 -453379.100807] SLOW spr round 3 (radius: 5)
[07:18:59 -453376.148761] SLOW spr round 4 (radius: 5)
[07:22:25 -453376.148757] SLOW spr round 5 (radius: 10)
[07:26:01 -453372.823789] SLOW spr round 6 (radius: 5)
[07:30:33 -453372.823778] SLOW spr round 7 (radius: 10)
[07:34:39 -453372.823778] SLOW spr round 8 (radius: 15)
[07:40:01 -453372.823778] SLOW spr round 9 (radius: 20)
[07:48:39 -453372.823778] SLOW spr round 10 (radius: 25)
[08:00:43 -453372.823778] Model parameter optimization (eps = 0.100000)

[08:00:52] [worker #0] ML tree search #9, logLikelihood: -453372.552693

[08:00:52 -1434305.738689] Initial branch length optimization
[08:00:59 -1256874.119327] Model parameter optimization (eps = 10.000000)
[08:01:44 -1254693.694260] AUTODETECT spr round 1 (radius: 5)
[08:05:05 -892429.430381] AUTODETECT spr round 2 (radius: 10)
[08:07:13] [worker #1] ML tree search #10, logLikelihood: -453372.080559
[08:08:59 -653498.518748] AUTODETECT spr round 3 (radius: 15)
[08:13:33 -555490.768358] AUTODETECT spr round 4 (radius: 20)
[08:18:55 -523398.254751] AUTODETECT spr round 5 (radius: 25)
[08:25:22 -522385.924289] SPR radius for FAST iterations: 25 (autodetect)
[08:25:22 -522385.924289] Model parameter optimization (eps = 3.000000)
[08:25:52 -522202.918473] FAST spr round 1 (radius: 25)
[08:30:42 -455785.056748] FAST spr round 2 (radius: 25)
[08:33:59 -453632.831901] FAST spr round 3 (radius: 25)
[08:36:55 -453510.740944] FAST spr round 4 (radius: 25)
[08:39:20 -453504.718975] FAST spr round 5 (radius: 25)
[08:41:36 -453503.133161] FAST spr round 6 (radius: 25)
[08:43:48 -453503.133160] Model parameter optimization (eps = 1.000000)
[08:44:03 -453497.976399] SLOW spr round 1 (radius: 5)
[08:47:50 -453381.678463] SLOW spr round 2 (radius: 5)
[08:51:16 -453368.402292] SLOW spr round 3 (radius: 5)
[08:54:33 -453368.402289] SLOW spr round 4 (radius: 10)
[08:57:52 -453368.402289] SLOW spr round 5 (radius: 15)
[09:03:49 -453368.402289] SLOW spr round 6 (radius: 20)
[09:13:06 -453368.402289] SLOW spr round 7 (radius: 25)
[09:25:45 -453368.402289] Model parameter optimization (eps = 0.100000)

[09:25:57] [worker #0] ML tree search #11, logLikelihood: -453368.236895

[09:25:57 -1437209.191391] Initial branch length optimization
[09:26:03 -1262404.032598] Model parameter optimization (eps = 10.000000)
[09:26:54 -1260047.245771] AUTODETECT spr round 1 (radius: 5)
[09:30:41 -899317.325714] AUTODETECT spr round 2 (radius: 10)
[09:34:20 -639288.970837] AUTODETECT spr round 3 (radius: 15)
[09:38:17 -552541.336683] AUTODETECT spr round 4 (radius: 20)
[09:38:25] [worker #1] ML tree search #12, logLikelihood: -453369.324635
[09:43:19 -527642.222232] AUTODETECT spr round 5 (radius: 25)
[09:48:41 -519773.920579] SPR radius for FAST iterations: 25 (autodetect)
[09:48:41 -519773.920579] Model parameter optimization (eps = 3.000000)
[09:48:51 -519767.239958] FAST spr round 1 (radius: 25)
[09:53:11 -455825.248606] FAST spr round 2 (radius: 25)
[09:56:16 -453792.905011] FAST spr round 3 (radius: 25)
[09:59:01 -453700.385162] FAST spr round 4 (radius: 25)
[10:01:16 -453690.901727] FAST spr round 5 (radius: 25)
[10:03:22 -453688.290430] FAST spr round 6 (radius: 25)
[10:05:26 -453688.290351] Model parameter optimization (eps = 1.000000)
[10:05:46 -453518.999828] SLOW spr round 1 (radius: 5)
[10:09:18 -453398.085878] SLOW spr round 2 (radius: 5)
[10:12:28 -453391.600801] SLOW spr round 3 (radius: 5)
[10:15:26 -453389.245412] SLOW spr round 4 (radius: 5)
[10:18:23 -453389.245412] SLOW spr round 5 (radius: 10)
[10:21:27 -453386.719855] SLOW spr round 6 (radius: 5)
[10:25:18 -453386.719796] SLOW spr round 7 (radius: 10)
[10:28:48 -453386.719795] SLOW spr round 8 (radius: 15)
[10:33:49 -453386.719795] SLOW spr round 9 (radius: 20)
[10:42:33 -453386.719795] SLOW spr round 10 (radius: 25)
[10:53:54 -453386.719795] Model parameter optimization (eps = 0.100000)

[10:54:08] [worker #0] ML tree search #13, logLikelihood: -453386.598309

[10:54:08 -1433083.926336] Initial branch length optimization
[10:54:14 -1261077.366016] Model parameter optimization (eps = 10.000000)
[10:54:52 -1258600.330884] AUTODETECT spr round 1 (radius: 5)
[10:58:06 -904834.844450] AUTODETECT spr round 2 (radius: 10)
[11:01:38 -631198.209496] AUTODETECT spr round 3 (radius: 15)
[11:05:39 -525896.068093] AUTODETECT spr round 4 (radius: 20)
[11:10:55 -512080.564022] AUTODETECT spr round 5 (radius: 25)
[11:17:58 -511211.288195] SPR radius for FAST iterations: 25 (autodetect)
[11:17:58 -511211.288195] Model parameter optimization (eps = 3.000000)
[11:18:29 -510989.208387] FAST spr round 1 (radius: 25)
[11:20:55] [worker #1] ML tree search #14, logLikelihood: -453359.849510
[11:22:40 -456585.143355] FAST spr round 2 (radius: 25)
[11:25:43 -453748.059435] FAST spr round 3 (radius: 25)
[11:28:26 -453521.064530] FAST spr round 4 (radius: 25)
[11:30:55 -453482.278423] FAST spr round 5 (radius: 25)
[11:33:08 -453466.466090] FAST spr round 6 (radius: 25)
[11:35:10 -453465.219933] FAST spr round 7 (radius: 25)
[11:37:11 -453463.208483] FAST spr round 8 (radius: 25)
[11:39:10 -453463.208390] Model parameter optimization (eps = 1.000000)
[11:39:28 -453460.181178] SLOW spr round 1 (radius: 5)
[11:42:56 -453374.227742] SLOW spr round 2 (radius: 5)
[11:46:06 -453365.985533] SLOW spr round 3 (radius: 5)
[11:49:02 -453365.985385] SLOW spr round 4 (radius: 10)
[11:52:05 -453365.985327] SLOW spr round 5 (radius: 15)
[11:57:33 -453365.985269] SLOW spr round 6 (radius: 20)
[12:06:02 -453365.985212] SLOW spr round 7 (radius: 25)
[12:17:27 -453365.985178] Model parameter optimization (eps = 0.100000)

[12:17:38] [worker #0] ML tree search #15, logLikelihood: -453365.643232

[12:17:39 -1439288.278221] Initial branch length optimization
[12:17:43 -1261780.301289] Model parameter optimization (eps = 10.000000)
[12:18:26 -1259345.347169] AUTODETECT spr round 1 (radius: 5)
[12:21:40 -894158.709234] AUTODETECT spr round 2 (radius: 10)
[12:25:10 -629657.023555] AUTODETECT spr round 3 (radius: 15)
[12:28:54 -536724.383377] AUTODETECT spr round 4 (radius: 20)
[12:33:20 -509551.870744] AUTODETECT spr round 5 (radius: 25)
[12:37:56 -506219.094407] SPR radius for FAST iterations: 25 (autodetect)
[12:37:56 -506219.094407] Model parameter optimization (eps = 3.000000)
[12:38:21 -505996.179170] FAST spr round 1 (radius: 25)
[12:41:32] [worker #1] ML tree search #16, logLikelihood: -453368.081554
[12:42:24 -455262.785970] FAST spr round 2 (radius: 25)
[12:45:23 -453771.255660] FAST spr round 3 (radius: 25)
[12:47:55 -453624.441232] FAST spr round 4 (radius: 25)
[12:50:08 -453603.924989] FAST spr round 5 (radius: 25)
[12:52:14 -453593.945560] FAST spr round 6 (radius: 25)
[12:54:18 -453585.671568] FAST spr round 7 (radius: 25)
[12:56:18 -453569.672001] FAST spr round 8 (radius: 25)
[12:58:17 -453569.671941] Model parameter optimization (eps = 1.000000)
[12:58:34 -453565.617548] SLOW spr round 1 (radius: 5)
[13:01:57 -453396.384018] SLOW spr round 2 (radius: 5)
[13:05:05 -453385.576563] SLOW spr round 3 (radius: 5)
[13:08:04 -453383.877989] SLOW spr round 4 (radius: 5)
[13:10:59 -453383.877986] SLOW spr round 5 (radius: 10)
[13:14:05 -453375.850238] SLOW spr round 6 (radius: 5)
[13:18:00 -453375.282711] SLOW spr round 7 (radius: 5)
[13:21:20 -453375.282665] SLOW spr round 8 (radius: 10)
[13:24:31 -453375.282665] SLOW spr round 9 (radius: 15)
[13:29:42 -453375.282665] SLOW spr round 10 (radius: 20)
[13:37:49 -453375.282665] SLOW spr round 11 (radius: 25)
[13:48:16 -453375.282665] Model parameter optimization (eps = 0.100000)

[13:48:23] [worker #0] ML tree search #17, logLikelihood: -453375.226204

[13:48:23 -1429770.977717] Initial branch length optimization
[13:48:29 -1255336.520714] Model parameter optimization (eps = 10.000000)
[13:49:14 -1252983.675199] AUTODETECT spr round 1 (radius: 5)
[13:52:30 -901071.435407] AUTODETECT spr round 2 (radius: 10)
[13:56:00 -640520.881220] AUTODETECT spr round 3 (radius: 15)
[13:56:29] [worker #1] ML tree search #18, logLikelihood: -453382.197809
[13:59:44 -532477.805805] AUTODETECT spr round 4 (radius: 20)
[14:04:11 -524934.804497] AUTODETECT spr round 5 (radius: 25)
[14:09:22 -513246.602527] SPR radius for FAST iterations: 25 (autodetect)
[14:09:22 -513246.602527] Model parameter optimization (eps = 3.000000)
[14:09:53 -513062.135936] FAST spr round 1 (radius: 25)
[14:14:06 -455737.852390] FAST spr round 2 (radius: 25)
[14:17:12 -453669.536056] FAST spr round 3 (radius: 25)
[14:19:54 -453537.778431] FAST spr round 4 (radius: 25)
[14:22:07 -453524.991950] FAST spr round 5 (radius: 25)
[14:24:10 -453524.991949] Model parameter optimization (eps = 1.000000)
[14:24:21 -453523.409197] SLOW spr round 1 (radius: 5)
[14:27:52 -453376.211242] SLOW spr round 2 (radius: 5)
[14:31:05 -453365.170116] SLOW spr round 3 (radius: 5)
[14:34:02 -453365.170099] SLOW spr round 4 (radius: 10)
[14:37:04 -453365.170098] SLOW spr round 5 (radius: 15)
[14:42:24 -453365.170098] SLOW spr round 6 (radius: 20)
[14:50:22 -453365.170098] SLOW spr round 7 (radius: 25)
[15:00:52 -453365.170098] Model parameter optimization (eps = 0.100000)

[15:01:05] [worker #0] ML tree search #19, logLikelihood: -453364.611837

[15:27:09] [worker #1] ML tree search #20, logLikelihood: -453385.863146

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.217921,0.253823) (0.275252,0.474710) (0.297803,0.996539) (0.209023,2.474599) 
   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: -453359.849510

AIC score: 910729.699021 / AICc score: 8954789.699021 / BIC score: 920523.094758
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=977).
         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/P26640/3_mltree/P26640.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/3_mltree/P26640.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/3_mltree/P26640.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P26640/3_mltree/P26640.raxml.log

Analysis started: 06-Jul-2021 05:15:00 / finished: 06-Jul-2021 20:42:10

Elapsed time: 55629.889 seconds

Consumed energy: 5211.215 Wh (= 26 km in an electric car, or 130 km with an e-scooter!)