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 07-Jul-2021 14:17:36 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/2_msa/A0A0C4DH59_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/3_mltree/A0A0C4DH59 --seed 2 --threads 2 --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 (2 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/2_msa/A0A0C4DH59_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 115 sites

WARNING: Sequences sp_P01654_KV3A1_MOUSE_10090 and sp_P01655_KV3A2_MOUSE_10090 are exactly identical!
WARNING: Sequences sp_P01654_KV3A1_MOUSE_10090 and sp_P01656_KV3A3_MOUSE_10090 are exactly identical!
WARNING: Sequences sp_P01670_KV3AI_MOUSE_10090 and sp_P01671_KV3AJ_MOUSE_10090 are exactly identical!
WARNING: Sequences sp_P01735_TVB86_MOUSE_10090 and sp_P06321_TVB8_MOUSE_10090 are exactly identical!
WARNING: Sequences tr_A0A2I3G644_A0A2I3G644_NOMLE_61853 and tr_A0A2I2Z9P5_A0A2I2Z9P5_GORGO_9595 are exactly identical!
WARNING: Sequences tr_A0A2I2Y621_A0A2I2Y621_GORGO_9595 and tr_A0A2I3SBC7_A0A2I3SBC7_PANTR_9598 are exactly identical!
WARNING: Sequences tr_A0A2I2Y6H0_A0A2I2Y6H0_GORGO_9595 and tr_A0A2I3TNY1_A0A2I3TNY1_PANTR_9598 are exactly identical!
WARNING: Sequences tr_A0A2I2Y6H0_A0A2I2Y6H0_GORGO_9595 and tr_A0A2R8ZB88_A0A2R8ZB88_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I2YDX5_A0A2I2YDX5_GORGO_9595 and tr_A0A2I3SG84_A0A2I3SG84_PANTR_9598 are exactly identical!
WARNING: Sequences tr_A0A2I2YDX5_A0A2I2YDX5_GORGO_9595 and tr_A0A2R8ZPP1_A0A2R8ZPP1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3RA64_A0A2I3RA64_PANTR_9598 and tr_A0A2R8Z5W9_A0A2R8Z5W9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3RKN7_A0A2I3RKN7_PANTR_9598 and tr_A0A2R8ZBA5_A0A2R8ZBA5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3RTB5_A0A2I3RTB5_PANTR_9598 and tr_A0A2R8ZU59_A0A2R8ZU59_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3RX17_A0A2I3RX17_PANTR_9598 and tr_A0A2R8ZMB0_A0A2R8ZMB0_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3RXP8_A0A2I3RXP8_PANTR_9598 and tr_A0A2R8ZM38_A0A2R8ZM38_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3S3B0_A0A2I3S3B0_PANTR_9598 and tr_A0A2R9BNT9_A0A2R9BNT9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3SFL4_A0A2I3SFL4_PANTR_9598 and tr_A0A2R8ZH29_A0A2R8ZH29_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3SRN4_A0A2I3SRN4_PANTR_9598 and tr_A0A2R8ZPA5_A0A2R8ZPA5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3T1C1_A0A2I3T1C1_PANTR_9598 and tr_A0A2R8Z6U1_A0A2R8Z6U1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TAX1_A0A2I3TAX1_PANTR_9598 and tr_A0A2R9AKE1_A0A2R9AKE1_PANPA_9597 are exactly identical!
WARNING: Sequences sp_A0A0J9YXY3_TVB62_HUMAN_9606 and sp_P0DPF7_TVB63_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A1D5QWP8_A0A1D5QWP8_MACMU_9544 and tr_G8F2F0_G8F2F0_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A1D5REJ3_A0A1D5REJ3_MACMU_9544 and tr_A0A2K6DR57_A0A2K6DR57_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_G8F609_G8F609_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K5M4Y2_A0A2K5M4Y2_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K6BRF2_A0A2K6BRF2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K5Y552_A0A2K5Y552_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2R8MJT0_A0A2R8MJT0_CALJA_9483 and tr_A0A2R8P774_A0A2R8P774_CALJA_9483 are exactly identical!
WARNING: Sequences tr_A0A096MV46_A0A096MV46_PAPAN_9555 and tr_A0A2K6ALT7_A0A2K6ALT7_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A096NGH2_A0A096NGH2_PAPAN_9555 and tr_A0A2K5NS08_A0A2K5NS08_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A2I3LFR1_A0A2I3LFR1_PAPAN_9555 and tr_A0A2K5L243_A0A2K5L243_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A2I3NG21_A0A2I3NG21_PAPAN_9555 and tr_A0A2K5XSC0_A0A2K5XSC0_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K5KHN7_A0A2K5KHN7_CERAT_9531 and tr_A0A2K6B5F2_A0A2K6B5F2_MACNE_9545 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/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.reduced.phy

Alignment comprises 1 partitions and 115 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 115 / 115
Gaps: 9.07 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 1 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 / 115 / 9200
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -219305.202626] Initial branch length optimization
[00:00:02 -192532.942257] Model parameter optimization (eps = 10.000000)
[00:00:34 -191531.355503] AUTODETECT spr round 1 (radius: 5)
[00:02:29 -142299.404802] AUTODETECT spr round 2 (radius: 10)
[00:04:37 -100796.657015] AUTODETECT spr round 3 (radius: 15)
[00:07:05 -86031.803115] AUTODETECT spr round 4 (radius: 20)
[00:10:12 -79792.997676] AUTODETECT spr round 5 (radius: 25)
[00:13:28 -78998.687760] SPR radius for FAST iterations: 25 (autodetect)
[00:13:28 -78998.687760] Model parameter optimization (eps = 3.000000)
[00:13:49 -78778.671960] FAST spr round 1 (radius: 25)
[00:16:19 -68812.088303] FAST spr round 2 (radius: 25)
[00:18:18 -68379.716557] FAST spr round 3 (radius: 25)
[00:20:03 -68326.021227] FAST spr round 4 (radius: 25)
[00:21:40 -68325.489056] FAST spr round 5 (radius: 25)
[00:23:15 -68325.488518] Model parameter optimization (eps = 1.000000)
[00:23:27 -68317.713964] SLOW spr round 1 (radius: 5)
[00:25:31 -68290.445992] SLOW spr round 2 (radius: 5)
[00:27:26 -68279.292169] SLOW spr round 3 (radius: 5)
[00:29:16 -68279.292077] SLOW spr round 4 (radius: 10)
[00:31:08 -68278.648361] SLOW spr round 5 (radius: 5)
[00:33:24 -68278.648347] SLOW spr round 6 (radius: 10)
[00:35:30 -68278.233743] SLOW spr round 7 (radius: 5)
[00:37:51 -68278.233625] SLOW spr round 8 (radius: 10)
[00:39:54 -68278.233625] SLOW spr round 9 (radius: 15)
[00:42:48 -68277.158406] SLOW spr round 10 (radius: 5)
[00:45:12 -68277.158366] SLOW spr round 11 (radius: 10)
[00:47:16 -68277.158366] SLOW spr round 12 (radius: 15)
[00:50:09 -68275.953339] SLOW spr round 13 (radius: 5)
[00:52:33 -68274.095624] SLOW spr round 14 (radius: 5)
[00:54:44 -68274.095624] SLOW spr round 15 (radius: 10)
[00:56:44 -68274.095624] SLOW spr round 16 (radius: 15)
[00:59:55 -68274.095624] SLOW spr round 17 (radius: 20)
[01:01:05] [worker #1] ML tree search #2, logLikelihood: -68289.804196
[01:04:43 -68274.095624] SLOW spr round 18 (radius: 25)
[01:11:03 -68274.095624] Model parameter optimization (eps = 0.100000)

[01:11:10] [worker #0] ML tree search #1, logLikelihood: -68274.088556

[01:11:10 -220100.540115] Initial branch length optimization
[01:11:12 -192857.633591] Model parameter optimization (eps = 10.000000)
[01:11:43 -191964.017412] AUTODETECT spr round 1 (radius: 5)
[01:13:48 -138524.384860] AUTODETECT spr round 2 (radius: 10)
[01:16:02 -98052.017541] AUTODETECT spr round 3 (radius: 15)
[01:18:36 -83945.417073] AUTODETECT spr round 4 (radius: 20)
[01:22:04 -78710.405671] AUTODETECT spr round 5 (radius: 25)
[01:26:27 -78414.505413] SPR radius for FAST iterations: 25 (autodetect)
[01:26:27 -78414.505413] Model parameter optimization (eps = 3.000000)
[01:26:37 -78403.987831] FAST spr round 1 (radius: 25)
[01:29:02 -68889.004810] FAST spr round 2 (radius: 25)
[01:30:59 -68510.401681] FAST spr round 3 (radius: 25)
[01:32:43 -68479.157857] FAST spr round 4 (radius: 25)
[01:34:22 -68473.562639] FAST spr round 5 (radius: 25)
[01:35:56 -68472.485156] FAST spr round 6 (radius: 25)
[01:37:31 -68471.364368] FAST spr round 7 (radius: 25)
[01:39:05 -68471.363994] Model parameter optimization (eps = 1.000000)
[01:39:11 -68471.091310] SLOW spr round 1 (radius: 5)
[01:41:17 -68438.487574] SLOW spr round 2 (radius: 5)
[01:43:19 -68435.348935] SLOW spr round 3 (radius: 5)
[01:45:19 -68433.895409] SLOW spr round 4 (radius: 5)
[01:47:15 -68433.895306] SLOW spr round 5 (radius: 10)
[01:49:15 -68433.895305] SLOW spr round 6 (radius: 15)
[01:52:30 -68433.895305] SLOW spr round 7 (radius: 20)
[01:57:21 -68433.895305] SLOW spr round 8 (radius: 25)
[01:58:40] [worker #1] ML tree search #4, logLikelihood: -68301.744171
[02:03:50 -68433.895305] Model parameter optimization (eps = 0.100000)

[02:03:52] [worker #0] ML tree search #3, logLikelihood: -68433.895305

[02:03:52 -219786.570212] Initial branch length optimization
[02:03:53 -192779.406576] Model parameter optimization (eps = 10.000000)
[02:04:22 -191685.582357] AUTODETECT spr round 1 (radius: 5)
[02:06:26 -139887.541937] AUTODETECT spr round 2 (radius: 10)
[02:08:42 -99272.739540] AUTODETECT spr round 3 (radius: 15)
[02:11:14 -86980.008813] AUTODETECT spr round 4 (radius: 20)
[02:14:13 -81698.768384] AUTODETECT spr round 5 (radius: 25)
[02:17:59 -79751.440621] SPR radius for FAST iterations: 25 (autodetect)
[02:17:59 -79751.440621] Model parameter optimization (eps = 3.000000)
[02:18:25 -79560.220678] FAST spr round 1 (radius: 25)
[02:20:58 -69143.180285] FAST spr round 2 (radius: 25)
[02:22:58 -68437.139313] FAST spr round 3 (radius: 25)
[02:24:49 -68378.696201] FAST spr round 4 (radius: 25)
[02:26:29 -68364.250387] FAST spr round 5 (radius: 25)
[02:28:05 -68363.038262] FAST spr round 6 (radius: 25)
[02:29:40 -68363.037768] Model parameter optimization (eps = 1.000000)
[02:29:45 -68362.869919] SLOW spr round 1 (radius: 5)
[02:31:51 -68342.289603] SLOW spr round 2 (radius: 5)
[02:33:54 -68328.606435] SLOW spr round 3 (radius: 5)
[02:35:54 -68326.508380] SLOW spr round 4 (radius: 5)
[02:37:52 -68325.478385] SLOW spr round 5 (radius: 5)
[02:39:49 -68324.565437] SLOW spr round 6 (radius: 5)
[02:41:45 -68324.565402] SLOW spr round 7 (radius: 10)
[02:43:45 -68323.857112] SLOW spr round 8 (radius: 5)
[02:44:21] [worker #1] ML tree search #6, logLikelihood: -68314.330116
[02:46:14 -68316.254853] SLOW spr round 9 (radius: 5)
[02:48:24 -68314.206226] SLOW spr round 10 (radius: 5)
[02:50:26 -68314.205802] SLOW spr round 11 (radius: 10)
[02:52:27 -68312.078676] SLOW spr round 12 (radius: 5)
[02:54:53 -68309.187564] SLOW spr round 13 (radius: 5)
[02:57:03 -68308.191893] SLOW spr round 14 (radius: 5)
[02:59:04 -68308.191893] SLOW spr round 15 (radius: 10)
[03:01:05 -68307.190684] SLOW spr round 16 (radius: 5)
[03:03:37 -68295.553571] SLOW spr round 17 (radius: 5)
[03:05:47 -68295.048098] SLOW spr round 18 (radius: 5)
[03:07:50 -68295.047665] SLOW spr round 19 (radius: 10)
[03:09:52 -68295.047640] SLOW spr round 20 (radius: 15)
[03:13:01 -68295.047639] SLOW spr round 21 (radius: 20)
[03:17:28 -68295.047639] SLOW spr round 22 (radius: 25)
[03:23:15 -68295.047639] Model parameter optimization (eps = 0.100000)

[03:23:19] [worker #0] ML tree search #5, logLikelihood: -68295.015474

[03:23:19 -218256.387103] Initial branch length optimization
[03:23:21 -191847.670146] Model parameter optimization (eps = 10.000000)
[03:23:57 -191158.308764] AUTODETECT spr round 1 (radius: 5)
[03:26:00 -139048.350965] AUTODETECT spr round 2 (radius: 10)
[03:28:18 -98719.506250] AUTODETECT spr round 3 (radius: 15)
[03:30:43 -87504.677167] AUTODETECT spr round 4 (radius: 20)
[03:33:36 -80210.727406] AUTODETECT spr round 5 (radius: 25)
[03:36:50] [worker #1] ML tree search #8, logLikelihood: -68382.581008
[03:36:55 -78876.345383] SPR radius for FAST iterations: 25 (autodetect)
[03:36:55 -78876.345383] Model parameter optimization (eps = 3.000000)
[03:37:04 -78867.696758] FAST spr round 1 (radius: 25)
[03:39:32 -69145.674708] FAST spr round 2 (radius: 25)
[03:41:32 -68576.469747] FAST spr round 3 (radius: 25)
[03:43:22 -68495.392421] FAST spr round 4 (radius: 25)
[03:45:01 -68493.242542] FAST spr round 5 (radius: 25)
[03:46:37 -68493.242065] Model parameter optimization (eps = 1.000000)
[03:46:41 -68492.926158] SLOW spr round 1 (radius: 5)
[03:48:48 -68475.503297] SLOW spr round 2 (radius: 5)
[03:50:49 -68474.059939] SLOW spr round 3 (radius: 5)
[03:52:46 -68474.059937] SLOW spr round 4 (radius: 10)
[03:54:47 -68473.785014] SLOW spr round 5 (radius: 5)
[03:57:11 -68473.785011] SLOW spr round 6 (radius: 10)
[03:59:22 -68473.606126] SLOW spr round 7 (radius: 5)
[04:01:47 -68471.342637] SLOW spr round 8 (radius: 5)
[04:03:56 -68471.243244] SLOW spr round 9 (radius: 10)
[04:05:59 -68471.199347] SLOW spr round 10 (radius: 15)
[04:09:12 -68471.199337] SLOW spr round 11 (radius: 20)
[04:14:07 -68471.199337] SLOW spr round 12 (radius: 25)
[04:20:43 -68471.199337] Model parameter optimization (eps = 0.100000)

[04:20:45] [worker #0] ML tree search #7, logLikelihood: -68471.198728

[04:20:45 -219103.447553] Initial branch length optimization
[04:20:47 -192647.115828] Model parameter optimization (eps = 10.000000)
[04:21:18 -191926.977181] AUTODETECT spr round 1 (radius: 5)
[04:23:22 -137943.824963] AUTODETECT spr round 2 (radius: 10)
[04:25:44 -101241.019365] AUTODETECT spr round 3 (radius: 15)
[04:28:09 -86862.699553] AUTODETECT spr round 4 (radius: 20)
[04:31:22 -79405.885183] AUTODETECT spr round 5 (radius: 25)
[04:35:19 -78842.126533] SPR radius for FAST iterations: 25 (autodetect)
[04:35:20 -78842.126533] Model parameter optimization (eps = 3.000000)
[04:35:50 -78622.118768] FAST spr round 1 (radius: 25)
[04:38:19 -68787.255423] FAST spr round 2 (radius: 25)
[04:39:24] [worker #1] ML tree search #10, logLikelihood: -68482.644505
[04:40:18 -68403.508872] FAST spr round 3 (radius: 25)
[04:42:04 -68342.681150] FAST spr round 4 (radius: 25)
[04:43:46 -68327.130548] FAST spr round 5 (radius: 25)
[04:45:20 -68327.130131] Model parameter optimization (eps = 1.000000)
[04:45:33 -68322.675532] SLOW spr round 1 (radius: 5)
[04:47:39 -68305.307976] SLOW spr round 2 (radius: 5)
[04:49:43 -68301.913223] SLOW spr round 3 (radius: 5)
[04:51:41 -68301.911018] SLOW spr round 4 (radius: 10)
[04:53:41 -68301.096826] SLOW spr round 5 (radius: 5)
[04:56:08 -68294.841683] SLOW spr round 6 (radius: 5)
[04:58:18 -68294.255799] SLOW spr round 7 (radius: 5)
[05:00:20 -68294.255641] SLOW spr round 8 (radius: 10)
[05:02:21 -68293.803755] SLOW spr round 9 (radius: 5)
[05:04:48 -68293.803627] SLOW spr round 10 (radius: 10)
[05:06:56 -68291.570280] SLOW spr round 11 (radius: 5)
[05:09:19 -68289.086971] SLOW spr round 12 (radius: 5)
[05:11:26 -68289.086915] SLOW spr round 13 (radius: 10)
[05:13:27 -68289.086915] SLOW spr round 14 (radius: 15)
[05:16:37 -68289.086915] SLOW spr round 15 (radius: 20)
[05:21:10 -68289.086915] SLOW spr round 16 (radius: 25)
[05:27:07 -68289.086915] Model parameter optimization (eps = 0.100000)

[05:27:11] [worker #0] ML tree search #9, logLikelihood: -68289.083291

[05:27:12 -218750.529873] Initial branch length optimization
[05:27:14 -191853.030280] Model parameter optimization (eps = 10.000000)
[05:27:45 -190827.507232] AUTODETECT spr round 1 (radius: 5)
[05:29:40 -141136.455285] AUTODETECT spr round 2 (radius: 10)
[05:31:47 -98403.253074] AUTODETECT spr round 3 (radius: 15)
[05:34:08 -82641.697114] AUTODETECT spr round 4 (radius: 20)
[05:37:00 -79748.212097] AUTODETECT spr round 5 (radius: 25)
[05:38:42] [worker #1] ML tree search #12, logLikelihood: -68293.396461
[05:41:10 -79305.301498] SPR radius for FAST iterations: 25 (autodetect)
[05:41:10 -79305.301498] Model parameter optimization (eps = 3.000000)
[05:41:19 -79294.302653] FAST spr round 1 (radius: 25)
[05:43:30 -69057.784938] FAST spr round 2 (radius: 25)
[05:45:09 -68560.712270] FAST spr round 3 (radius: 25)
[05:46:37 -68488.450109] FAST spr round 4 (radius: 25)
[05:47:59 -68486.101911] FAST spr round 5 (radius: 25)
[05:49:17 -68486.101456] Model parameter optimization (eps = 1.000000)
[05:49:21 -68485.603682] SLOW spr round 1 (radius: 5)
[05:51:05 -68458.753169] SLOW spr round 2 (radius: 5)
[05:52:49 -68456.462570] SLOW spr round 3 (radius: 5)
[05:54:44 -68456.461255] SLOW spr round 4 (radius: 10)
[05:56:43 -68453.074676] SLOW spr round 5 (radius: 5)
[05:59:08 -68453.074253] SLOW spr round 6 (radius: 10)
[06:01:15 -68453.074252] SLOW spr round 7 (radius: 15)
[06:04:19 -68453.074252] SLOW spr round 8 (radius: 20)
[06:09:16 -68453.074252] SLOW spr round 9 (radius: 25)
[06:15:35 -68453.074252] Model parameter optimization (eps = 0.100000)

[06:15:39] [worker #0] ML tree search #11, logLikelihood: -68453.051152

[06:15:39 -218084.656574] Initial branch length optimization
[06:15:41 -191528.171422] Model parameter optimization (eps = 10.000000)
[06:16:09 -190582.377444] AUTODETECT spr round 1 (radius: 5)
[06:18:12 -136348.724919] AUTODETECT spr round 2 (radius: 10)
[06:20:24 -98865.704788] AUTODETECT spr round 3 (radius: 15)
[06:22:06] [worker #1] ML tree search #14, logLikelihood: -68323.079720
[06:23:01 -85463.715869] AUTODETECT spr round 4 (radius: 20)
[06:26:11 -80753.785799] AUTODETECT spr round 5 (radius: 25)
[06:29:34 -79365.893381] SPR radius for FAST iterations: 25 (autodetect)
[06:29:34 -79365.893381] Model parameter optimization (eps = 3.000000)
[06:30:03 -79162.894381] FAST spr round 1 (radius: 25)
[06:32:30 -68987.972712] FAST spr round 2 (radius: 25)
[06:34:24 -68454.888586] FAST spr round 3 (radius: 25)
[06:36:11 -68404.213668] FAST spr round 4 (radius: 25)
[06:37:53 -68371.259278] FAST spr round 5 (radius: 25)
[06:39:27 -68370.971413] FAST spr round 6 (radius: 25)
[06:41:01 -68370.970899] Model parameter optimization (eps = 1.000000)
[06:41:12 -68368.011407] SLOW spr round 1 (radius: 5)
[06:43:19 -68334.986467] SLOW spr round 2 (radius: 5)
[06:45:21 -68317.246096] SLOW spr round 3 (radius: 5)
[06:47:21 -68306.781114] SLOW spr round 4 (radius: 5)
[06:49:16 -68306.617828] SLOW spr round 5 (radius: 5)
[06:51:10 -68306.615577] SLOW spr round 6 (radius: 10)
[06:53:05 -68306.615259] SLOW spr round 7 (radius: 15)
[06:56:14 -68306.615215] SLOW spr round 8 (radius: 20)
[07:00:41 -68306.615209] SLOW spr round 9 (radius: 25)
[07:06:42 -68306.615208] Model parameter optimization (eps = 0.100000)

[07:06:49] [worker #0] ML tree search #13, logLikelihood: -68306.477341

[07:06:49 -218234.570183] Initial branch length optimization
[07:06:51 -191955.425139] Model parameter optimization (eps = 10.000000)
[07:07:19 -191107.251332] AUTODETECT spr round 1 (radius: 5)
[07:09:25 -138745.619142] AUTODETECT spr round 2 (radius: 10)
[07:11:41 -102486.060487] AUTODETECT spr round 3 (radius: 15)
[07:14:07 -85051.202914] AUTODETECT spr round 4 (radius: 20)
[07:17:26 -80539.466822] AUTODETECT spr round 5 (radius: 25)
[07:21:19 -79657.394886] SPR radius for FAST iterations: 25 (autodetect)
[07:21:20 -79657.394886] Model parameter optimization (eps = 3.000000)
[07:21:28 -79641.799414] FAST spr round 1 (radius: 25)
[07:23:19] [worker #1] ML tree search #16, logLikelihood: -68457.513984
[07:24:01 -69351.097653] FAST spr round 2 (radius: 25)
[07:25:59 -68715.406739] FAST spr round 3 (radius: 25)
[07:27:44 -68563.408368] FAST spr round 4 (radius: 25)
[07:29:24 -68553.763393] FAST spr round 5 (radius: 25)
[07:31:00 -68550.291994] FAST spr round 6 (radius: 25)
[07:32:33 -68550.291706] Model parameter optimization (eps = 1.000000)
[07:32:39 -68549.898567] SLOW spr round 1 (radius: 5)
[07:34:47 -68509.305093] SLOW spr round 2 (radius: 5)
[07:36:47 -68503.789386] SLOW spr round 3 (radius: 5)
[07:38:42 -68503.574525] SLOW spr round 4 (radius: 5)
[07:40:35 -68503.574520] SLOW spr round 5 (radius: 10)
[07:42:35 -68501.810874] SLOW spr round 6 (radius: 5)
[07:44:59 -68501.810866] SLOW spr round 7 (radius: 10)
[07:47:07 -68501.278151] SLOW spr round 8 (radius: 5)
[07:49:29 -68499.973000] SLOW spr round 9 (radius: 5)
[07:51:36 -68499.543464] SLOW spr round 10 (radius: 5)
[07:53:34 -68499.543463] SLOW spr round 11 (radius: 10)
[07:55:34 -68499.543463] SLOW spr round 12 (radius: 15)
[07:58:49 -68499.543463] SLOW spr round 13 (radius: 20)
[08:03:17 -68499.543463] SLOW spr round 14 (radius: 25)
[08:09:14 -68499.543463] Model parameter optimization (eps = 0.100000)

[08:09:17] [worker #0] ML tree search #15, logLikelihood: -68499.541669

[08:09:17 -218479.166045] Initial branch length optimization
[08:09:19 -191809.305740] Model parameter optimization (eps = 10.000000)
[08:09:50 -190963.237893] AUTODETECT spr round 1 (radius: 5)
[08:11:54 -139282.565246] AUTODETECT spr round 2 (radius: 10)
[08:14:08 -99898.437211] AUTODETECT spr round 3 (radius: 15)
[08:16:35 -88629.105601] AUTODETECT spr round 4 (radius: 20)
[08:19:35 -84252.412016] AUTODETECT spr round 5 (radius: 25)
[08:22:53 -83301.552792] SPR radius for FAST iterations: 25 (autodetect)
[08:22:53 -83301.552792] Model parameter optimization (eps = 3.000000)
[08:23:27 -83059.584674] FAST spr round 1 (radius: 25)
[08:25:58 -69462.217009] FAST spr round 2 (radius: 25)
[08:26:22] [worker #1] ML tree search #18, logLikelihood: -68398.149742
[08:27:57 -68491.181263] FAST spr round 3 (radius: 25)
[08:29:45 -68376.777891] FAST spr round 4 (radius: 25)
[08:31:25 -68355.871122] FAST spr round 5 (radius: 25)
[08:32:59 -68351.100414] FAST spr round 6 (radius: 25)
[08:34:33 -68348.098987] FAST spr round 7 (radius: 25)
[08:36:06 -68348.098975] Model parameter optimization (eps = 1.000000)
[08:36:17 -68343.905170] SLOW spr round 1 (radius: 5)
[08:38:21 -68315.053287] SLOW spr round 2 (radius: 5)
[08:40:20 -68305.057251] SLOW spr round 3 (radius: 5)
[08:42:14 -68304.919541] SLOW spr round 4 (radius: 5)
[08:44:06 -68304.918225] SLOW spr round 5 (radius: 10)
[08:46:02 -68304.420823] SLOW spr round 6 (radius: 5)
[08:48:25 -68303.750900] SLOW spr round 7 (radius: 5)
[08:50:30 -68303.750735] SLOW spr round 8 (radius: 10)
[08:52:30 -68303.750734] SLOW spr round 9 (radius: 15)
[08:55:37 -68303.750734] SLOW spr round 10 (radius: 20)
[08:59:52 -68303.750734] SLOW spr round 11 (radius: 25)
[09:05:59 -68303.750734] Model parameter optimization (eps = 0.100000)

[09:06:04] [worker #0] ML tree search #17, logLikelihood: -68303.675446

[09:06:04 -219292.300320] Initial branch length optimization
[09:06:06 -192476.023266] Model parameter optimization (eps = 10.000000)
[09:06:40 -191481.752815] AUTODETECT spr round 1 (radius: 5)
[09:08:43 -140846.906297] AUTODETECT spr round 2 (radius: 10)
[09:10:55 -100153.793763] AUTODETECT spr round 3 (radius: 15)
[09:13:22 -85570.772103] AUTODETECT spr round 4 (radius: 20)
[09:16:18 -80370.670345] AUTODETECT spr round 5 (radius: 25)
[09:20:03 -79559.394763] SPR radius for FAST iterations: 25 (autodetect)
[09:20:03 -79559.394763] Model parameter optimization (eps = 3.000000)
[09:20:24 -79336.686241] FAST spr round 1 (radius: 25)
[09:22:52 -68802.477479] FAST spr round 2 (radius: 25)
[09:24:48 -68408.298208] FAST spr round 3 (radius: 25)
[09:26:36 -68367.428369] FAST spr round 4 (radius: 25)
[09:28:15 -68361.082286] FAST spr round 5 (radius: 25)
[09:28:55] [worker #1] ML tree search #20, logLikelihood: -68282.533135
[09:29:49 -68361.081407] Model parameter optimization (eps = 1.000000)
[09:29:59 -68360.084664] SLOW spr round 1 (radius: 5)
[09:32:05 -68330.431912] SLOW spr round 2 (radius: 5)
[09:34:04 -68329.260019] SLOW spr round 3 (radius: 5)
[09:35:59 -68329.257891] SLOW spr round 4 (radius: 10)
[09:37:58 -68328.983784] SLOW spr round 5 (radius: 5)
[09:40:23 -68328.347019] SLOW spr round 6 (radius: 5)
[09:42:32 -68325.927612] SLOW spr round 7 (radius: 5)
[09:44:32 -68325.927610] SLOW spr round 8 (radius: 10)
[09:46:31 -68325.927610] SLOW spr round 9 (radius: 15)
[09:49:40 -68325.927610] SLOW spr round 10 (radius: 20)
[09:54:03 -68325.927610] SLOW spr round 11 (radius: 25)
[09:59:45 -68325.927610] Model parameter optimization (eps = 0.100000)

[09:59:50] [worker #0] ML tree search #19, logLikelihood: -68325.835277


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.147738,0.542993) (0.104772,0.518310) (0.425687,0.800878) (0.321803,1.630041) 
   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: -68274.088556

AIC score: 140558.177112 / AICc score: 8184618.177112 / BIC score: 146061.766029
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=115).
         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/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH59/3_mltree/A0A0C4DH59.raxml.log

Analysis started: 07-Jul-2021 14:17:36 / finished: 08-Jul-2021 00:17:27

Elapsed time: 35990.943 seconds

Consumed energy: 2919.729 Wh (= 15 km in an electric car, or 73 km with an e-scooter!)