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 01-Jul-2021 00:35:14 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/2_msa/A6NJ64_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64 --seed 2 --threads 1 --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), NONE/sequential

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/2_msa/A6NJ64_trimmed_msa.fasta
[00:00:00] Loaded alignment with 58 taxa and 44 sites

WARNING: Sequences tr_G3RXQ0_G3RXQ0_GORGO_9595 and tr_G3S3Q1_G3S3Q1_GORGO_9595 are exactly identical!
WARNING: Sequences tr_H2NRV8_H2NRV8_PONAB_9601 and tr_H2PUQ8_H2PUQ8_PONAB_9601 are exactly identical!
WARNING: Sequences tr_H2NRV8_H2NRV8_PONAB_9601 and tr_H2PUQ9_H2PUQ9_PONAB_9601 are exactly identical!
WARNING: Sequences tr_H2PUQ4_H2PUQ4_PONAB_9601 and tr_H2PUQ7_H2PUQ7_PONAB_9601 are exactly identical!
WARNING: Sequences tr_H2PUR0_H2PUR0_PONAB_9601 and tr_K7ETA1_K7ETA1_PONAB_9601 are exactly identical!
WARNING: Sequences tr_A0A0A6YYH2_A0A0A6YYH2_HUMAN_9606 and sp_A6NJ64_NPIL2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A0B4J1W7_A0A0B4J1W7_HUMAN_9606 and sp_E9PJI5_NPIA7_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A0B4J1W7_A0A0B4J1W7_HUMAN_9606 and sp_E9PKD4_NPIA5_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A0B4J1W7_A0A0B4J1W7_HUMAN_9606 and sp_P0DM63_NPIA8_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A0B4J1W7_A0A0B4J1W7_HUMAN_9606 and sp_Q9UND3_NPIA1_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NHN6_NPB15_HUMAN_9606 and sp_E5RHQ5_NPB11_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NHN6_NPB15_HUMAN_9606 and sp_E9PJ23_NPIB6_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NHN6_NPB15_HUMAN_9606 and sp_E9PQR5_NPIB8_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NHN6_NPB15_HUMAN_9606 and sp_F8W1W9_NPIB9_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NHN6_NPB15_HUMAN_9606 and sp_O75200_NPIB7_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NJU9_NPB13_HUMAN_9606 and sp_A8MRT5_NPIB5_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_A6NJU9_NPB13_HUMAN_9606 and sp_Q92617_NPIB3_HUMAN_9606 are exactly identical!
WARNING: Sequences sp_E9PIF3_NPIA2_HUMAN_9606 and sp_F8WFD2_NPIA3_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_F6RKJ8_F6RKJ8_MACMU_9544 and tr_A0A2K6BX26_A0A2K6BX26_MACNE_9545 are exactly identical!
WARNING: Duplicate sequences found: 19

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/A6NJ64/3_mltree/A6NJ64.raxml.reduced.phy

Alignment comprises 1 partitions and 44 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 44 / 44
Gaps: 3.88 %
Invariant sites: 11.36 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.rba

Parallelization scheme autoconfig: 1 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 58 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 44 / 3520
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -2638.529593] Initial branch length optimization
[00:00:00 -2161.733228] Model parameter optimization (eps = 10.000000)
[00:00:00 -2152.550031] AUTODETECT spr round 1 (radius: 5)
[00:00:00 -1204.150447] AUTODETECT spr round 2 (radius: 10)
[00:00:01 -978.285572] AUTODETECT spr round 3 (radius: 15)
[00:00:01 -978.284134] SPR radius for FAST iterations: 10 (autodetect)
[00:00:01 -978.284134] Model parameter optimization (eps = 3.000000)
[00:00:02 -958.574821] FAST spr round 1 (radius: 10)
[00:00:03 -924.023443] FAST spr round 2 (radius: 10)
[00:00:03 -924.011535] Model parameter optimization (eps = 1.000000)
[00:00:04 -923.757230] SLOW spr round 1 (radius: 5)
[00:00:04 -921.576323] SLOW spr round 2 (radius: 5)
[00:00:05 -920.880689] SLOW spr round 3 (radius: 5)
[00:00:06 -920.788460] SLOW spr round 4 (radius: 10)
[00:00:06 -920.788460] SLOW spr round 5 (radius: 15)
[00:00:07 -920.788460] SLOW spr round 6 (radius: 20)
[00:00:08 -920.788460] SLOW spr round 7 (radius: 25)
[00:00:08 -920.788460] Model parameter optimization (eps = 0.100000)

[00:00:08] ML tree search #1, logLikelihood: -920.621519

[00:00:08 -2799.188837] Initial branch length optimization
[00:00:08 -2340.197286] Model parameter optimization (eps = 10.000000)
[00:00:09 -2328.430157] AUTODETECT spr round 1 (radius: 5)
[00:00:09 -1275.151899] AUTODETECT spr round 2 (radius: 10)
[00:00:10 -1002.067867] AUTODETECT spr round 3 (radius: 15)
[00:00:10 -1002.061070] SPR radius for FAST iterations: 10 (autodetect)
[00:00:10 -1002.061070] Model parameter optimization (eps = 3.000000)
[00:00:11 -983.949604] FAST spr round 1 (radius: 10)
[00:00:11 -927.911324] FAST spr round 2 (radius: 10)
[00:00:12 -921.069430] FAST spr round 3 (radius: 10)
[00:00:12 -921.069321] Model parameter optimization (eps = 1.000000)
[00:00:13 -920.198811] SLOW spr round 1 (radius: 5)
[00:00:14 -920.195837] SLOW spr round 2 (radius: 10)
[00:00:14 -920.195782] SLOW spr round 3 (radius: 15)
[00:00:15 -920.195781] SLOW spr round 4 (radius: 20)
[00:00:15 -920.195781] SLOW spr round 5 (radius: 25)
[00:00:16 -920.195781] Model parameter optimization (eps = 0.100000)

[00:00:16] ML tree search #2, logLikelihood: -920.195500

[00:00:16 -2537.039469] Initial branch length optimization
[00:00:16 -2127.714938] Model parameter optimization (eps = 10.000000)
[00:00:16 -2119.024506] AUTODETECT spr round 1 (radius: 5)
[00:00:17 -1165.402734] AUTODETECT spr round 2 (radius: 10)
[00:00:17 -1054.266256] AUTODETECT spr round 3 (radius: 15)
[00:00:18 -1036.334357] AUTODETECT spr round 4 (radius: 20)
[00:00:18 -1036.334105] SPR radius for FAST iterations: 15 (autodetect)
[00:00:18 -1036.334105] Model parameter optimization (eps = 3.000000)
[00:00:19 -1016.435020] FAST spr round 1 (radius: 15)
[00:00:19 -926.422753] FAST spr round 2 (radius: 15)
[00:00:20 -923.003126] FAST spr round 3 (radius: 15)
[00:00:20 -923.000011] Model parameter optimization (eps = 1.000000)
[00:00:21 -921.245609] SLOW spr round 1 (radius: 5)
[00:00:22 -920.215395] SLOW spr round 2 (radius: 5)
[00:00:22 -920.214584] SLOW spr round 3 (radius: 10)
[00:00:23 -920.214584] SLOW spr round 4 (radius: 15)
[00:00:24 -920.214584] SLOW spr round 5 (radius: 20)
[00:00:24 -920.214584] SLOW spr round 6 (radius: 25)
[00:00:25 -920.214584] Model parameter optimization (eps = 0.100000)

[00:00:25] ML tree search #3, logLikelihood: -920.195476

[00:00:25 -2532.718020] Initial branch length optimization
[00:00:25 -2111.761966] Model parameter optimization (eps = 10.000000)
[00:00:26 -2097.450091] AUTODETECT spr round 1 (radius: 5)
[00:00:26 -1180.238132] AUTODETECT spr round 2 (radius: 10)
[00:00:27 -1018.468248] AUTODETECT spr round 3 (radius: 15)
[00:00:27 -1016.971790] AUTODETECT spr round 4 (radius: 20)
[00:00:27 -1016.971554] SPR radius for FAST iterations: 15 (autodetect)
[00:00:27 -1016.971554] Model parameter optimization (eps = 3.000000)
[00:00:28 -996.799219] FAST spr round 1 (radius: 15)
[00:00:29 -955.109608] FAST spr round 2 (radius: 15)
[00:00:29 -923.764829] FAST spr round 3 (radius: 15)
[00:00:30 -922.280895] FAST spr round 4 (radius: 15)
[00:00:30 -922.280703] Model parameter optimization (eps = 1.000000)
[00:00:31 -920.641961] SLOW spr round 1 (radius: 5)
[00:00:32 -920.631140] SLOW spr round 2 (radius: 10)
[00:00:32 -920.631140] SLOW spr round 3 (radius: 15)
[00:00:33 -920.631140] SLOW spr round 4 (radius: 20)
[00:00:34 -920.631140] SLOW spr round 5 (radius: 25)
[00:00:34 -920.631140] Model parameter optimization (eps = 0.100000)

[00:00:34] ML tree search #4, logLikelihood: -920.621703

[00:00:34 -2667.334251] Initial branch length optimization
[00:00:34 -2246.705256] Model parameter optimization (eps = 10.000000)
[00:00:35 -2231.212408] AUTODETECT spr round 1 (radius: 5)
[00:00:35 -1084.937763] AUTODETECT spr round 2 (radius: 10)
[00:00:36 -985.041107] AUTODETECT spr round 3 (radius: 15)
[00:00:36 -985.038871] SPR radius for FAST iterations: 10 (autodetect)
[00:00:36 -985.038871] Model parameter optimization (eps = 3.000000)
[00:00:37 -970.382192] FAST spr round 1 (radius: 10)
[00:00:38 -924.788985] FAST spr round 2 (radius: 10)
[00:00:38 -920.824257] FAST spr round 3 (radius: 10)
[00:00:38 -920.824249] Model parameter optimization (eps = 1.000000)
[00:00:39 -920.233166] SLOW spr round 1 (radius: 5)
[00:00:40 -920.232977] SLOW spr round 2 (radius: 10)
[00:00:40 -920.232976] SLOW spr round 3 (radius: 15)
[00:00:41 -920.232976] SLOW spr round 4 (radius: 20)
[00:00:42 -920.232975] SLOW spr round 5 (radius: 25)
[00:00:42 -920.232974] Model parameter optimization (eps = 0.100000)

[00:00:42] ML tree search #5, logLikelihood: -920.232900

[00:00:42 -2682.292532] Initial branch length optimization
[00:00:42 -2193.235637] Model parameter optimization (eps = 10.000000)
[00:00:43 -2179.480933] AUTODETECT spr round 1 (radius: 5)
[00:00:43 -1111.675838] AUTODETECT spr round 2 (radius: 10)
[00:00:44 -985.843098] AUTODETECT spr round 3 (radius: 15)
[00:00:44 -985.836354] SPR radius for FAST iterations: 10 (autodetect)
[00:00:44 -985.836354] Model parameter optimization (eps = 3.000000)
[00:00:45 -965.752742] FAST spr round 1 (radius: 10)
[00:00:46 -925.999223] FAST spr round 2 (radius: 10)
[00:00:46 -920.253462] FAST spr round 3 (radius: 10)
[00:00:46 -918.654163] FAST spr round 4 (radius: 10)
[00:00:47 -918.654158] Model parameter optimization (eps = 1.000000)
[00:00:47 -917.768232] SLOW spr round 1 (radius: 5)
[00:00:48 -917.767693] SLOW spr round 2 (radius: 10)
[00:00:48 -917.767685] SLOW spr round 3 (radius: 15)
[00:00:49 -917.767685] SLOW spr round 4 (radius: 20)
[00:00:50 -917.767685] SLOW spr round 5 (radius: 25)
[00:00:50 -917.767685] Model parameter optimization (eps = 0.100000)

[00:00:50] ML tree search #6, logLikelihood: -917.767626

[00:00:50 -2739.928958] Initial branch length optimization
[00:00:50 -2291.009399] Model parameter optimization (eps = 10.000000)
[00:00:50 -2284.445439] AUTODETECT spr round 1 (radius: 5)
[00:00:51 -1208.595042] AUTODETECT spr round 2 (radius: 10)
[00:00:51 -972.337336] AUTODETECT spr round 3 (radius: 15)
[00:00:52 -972.184344] AUTODETECT spr round 4 (radius: 20)
[00:00:52 -972.175060] SPR radius for FAST iterations: 15 (autodetect)
[00:00:52 -972.175060] Model parameter optimization (eps = 3.000000)
[00:00:53 -953.011306] FAST spr round 1 (radius: 15)
[00:00:53 -928.631480] FAST spr round 2 (radius: 15)
[00:00:54 -919.178208] FAST spr round 3 (radius: 15)
[00:00:54 -919.178086] Model parameter optimization (eps = 1.000000)
[00:00:55 -917.767982] SLOW spr round 1 (radius: 5)
[00:00:56 -917.767698] SLOW spr round 2 (radius: 10)
[00:00:56 -917.767694] SLOW spr round 3 (radius: 15)
[00:00:57 -917.767694] SLOW spr round 4 (radius: 20)
[00:00:57 -917.767694] SLOW spr round 5 (radius: 25)
[00:00:58 -917.767694] Model parameter optimization (eps = 0.100000)

[00:00:58] ML tree search #7, logLikelihood: -917.767620

[00:00:58 -2713.331653] Initial branch length optimization
[00:00:58 -2229.645872] Model parameter optimization (eps = 10.000000)
[00:00:59 -2216.665195] AUTODETECT spr round 1 (radius: 5)
[00:00:59 -1241.968686] AUTODETECT spr round 2 (radius: 10)
[00:00:59 -1051.766924] AUTODETECT spr round 3 (radius: 15)
[00:01:00 -995.104690] AUTODETECT spr round 4 (radius: 20)
[00:01:00 -995.103662] SPR radius for FAST iterations: 15 (autodetect)
[00:01:00 -995.103662] Model parameter optimization (eps = 3.000000)
[00:01:01 -976.851775] FAST spr round 1 (radius: 15)
[00:01:01 -928.674448] FAST spr round 2 (radius: 15)
[00:01:02 -921.100791] FAST spr round 3 (radius: 15)
[00:01:02 -921.100606] Model parameter optimization (eps = 1.000000)
[00:01:03 -920.639558] SLOW spr round 1 (radius: 5)
[00:01:03 -920.638575] SLOW spr round 2 (radius: 10)
[00:01:04 -920.638556] SLOW spr round 3 (radius: 15)
[00:01:05 -920.638556] SLOW spr round 4 (radius: 20)
[00:01:05 -920.638556] SLOW spr round 5 (radius: 25)
[00:01:06 -920.638556] Model parameter optimization (eps = 0.100000)

[00:01:06] ML tree search #8, logLikelihood: -920.638427

[00:01:06 -2658.343313] Initial branch length optimization
[00:01:06 -2196.367131] Model parameter optimization (eps = 10.000000)
[00:01:06 -2188.535091] AUTODETECT spr round 1 (radius: 5)
[00:01:07 -1158.018589] AUTODETECT spr round 2 (radius: 10)
[00:01:07 -1007.289098] AUTODETECT spr round 3 (radius: 15)
[00:01:08 -976.414385] AUTODETECT spr round 4 (radius: 20)
[00:01:08 -976.413946] SPR radius for FAST iterations: 15 (autodetect)
[00:01:08 -976.413946] Model parameter optimization (eps = 3.000000)
[00:01:09 -958.634261] FAST spr round 1 (radius: 15)
[00:01:09 -941.457009] FAST spr round 2 (radius: 15)
[00:01:10 -921.183595] FAST spr round 3 (radius: 15)
[00:01:10 -921.183419] Model parameter optimization (eps = 1.000000)
[00:01:11 -920.197578] SLOW spr round 1 (radius: 5)
[00:01:12 -920.195810] SLOW spr round 2 (radius: 10)
[00:01:12 -920.195777] SLOW spr round 3 (radius: 15)
[00:01:13 -920.195776] SLOW spr round 4 (radius: 20)
[00:01:13 -920.195776] SLOW spr round 5 (radius: 25)
[00:01:14 -920.195776] Model parameter optimization (eps = 0.100000)

[00:01:14] ML tree search #9, logLikelihood: -920.195528

[00:01:14 -2653.623614] Initial branch length optimization
[00:01:14 -2217.078644] Model parameter optimization (eps = 10.000000)
[00:01:14 -2207.634792] AUTODETECT spr round 1 (radius: 5)
[00:01:15 -1182.060713] AUTODETECT spr round 2 (radius: 10)
[00:01:15 -998.545479] AUTODETECT spr round 3 (radius: 15)
[00:01:16 -993.667489] AUTODETECT spr round 4 (radius: 20)
[00:01:16 -993.667048] SPR radius for FAST iterations: 15 (autodetect)
[00:01:16 -993.667048] Model parameter optimization (eps = 3.000000)
[00:01:17 -974.639384] FAST spr round 1 (radius: 15)
[00:01:17 -925.265199] FAST spr round 2 (radius: 15)
[00:01:17 -918.653055] FAST spr round 3 (radius: 15)
[00:01:18 -918.653054] Model parameter optimization (eps = 1.000000)
[00:01:18 -917.807413] SLOW spr round 1 (radius: 5)
[00:01:19 -917.805226] SLOW spr round 2 (radius: 10)
[00:01:20 -917.805195] SLOW spr round 3 (radius: 15)
[00:01:21 -917.805193] SLOW spr round 4 (radius: 20)
[00:01:21 -917.805193] SLOW spr round 5 (radius: 25)
[00:01:21 -917.805192] Model parameter optimization (eps = 0.100000)

[00:01:21] ML tree search #10, logLikelihood: -917.804929

[00:01:21 -2608.333862] Initial branch length optimization
[00:01:21 -2171.239128] Model parameter optimization (eps = 10.000000)
[00:01:22 -2160.006516] AUTODETECT spr round 1 (radius: 5)
[00:01:23 -1206.667543] AUTODETECT spr round 2 (radius: 10)
[00:01:23 -1015.338351] AUTODETECT spr round 3 (radius: 15)
[00:01:23 -1015.331809] SPR radius for FAST iterations: 10 (autodetect)
[00:01:23 -1015.331809] Model parameter optimization (eps = 3.000000)
[00:01:24 -996.059679] FAST spr round 1 (radius: 10)
[00:01:25 -921.048444] FAST spr round 2 (radius: 10)
[00:01:25 -920.575902] FAST spr round 3 (radius: 10)
[00:01:26 -920.575900] Model parameter optimization (eps = 1.000000)
[00:01:26 -918.780913] SLOW spr round 1 (radius: 5)
[00:01:27 -918.780822] SLOW spr round 2 (radius: 10)
[00:01:28 -918.780819] SLOW spr round 3 (radius: 15)
[00:01:29 -918.780816] SLOW spr round 4 (radius: 20)
[00:01:29 -918.780816] SLOW spr round 5 (radius: 25)
[00:01:29 -918.780816] Model parameter optimization (eps = 0.100000)

[00:01:29] ML tree search #11, logLikelihood: -918.780791

[00:01:29 -2562.246241] Initial branch length optimization
[00:01:29 -2100.835041] Model parameter optimization (eps = 10.000000)
[00:01:30 -2092.028676] AUTODETECT spr round 1 (radius: 5)
[00:01:30 -1198.066757] AUTODETECT spr round 2 (radius: 10)
[00:01:31 -1075.442487] AUTODETECT spr round 3 (radius: 15)
[00:01:31 -1026.676657] AUTODETECT spr round 4 (radius: 20)
[00:01:31 -1026.674178] SPR radius for FAST iterations: 15 (autodetect)
[00:01:31 -1026.674178] Model parameter optimization (eps = 3.000000)
[00:01:32 -1006.127891] FAST spr round 1 (radius: 15)
[00:01:33 -928.513245] FAST spr round 2 (radius: 15)
[00:01:33 -920.931916] FAST spr round 3 (radius: 15)
[00:01:34 -920.931855] Model parameter optimization (eps = 1.000000)
[00:01:34 -920.316447] SLOW spr round 1 (radius: 5)
[00:01:35 -917.796276] SLOW spr round 2 (radius: 5)
[00:01:36 -917.796267] SLOW spr round 3 (radius: 10)
[00:01:36 -917.796267] SLOW spr round 4 (radius: 15)
[00:01:37 -917.796267] SLOW spr round 5 (radius: 20)
[00:01:38 -917.796267] SLOW spr round 6 (radius: 25)
[00:01:38 -917.796267] Model parameter optimization (eps = 0.100000)

[00:01:38] ML tree search #12, logLikelihood: -917.767653

[00:01:38 -2574.870646] Initial branch length optimization
[00:01:38 -2091.285249] Model parameter optimization (eps = 10.000000)
[00:01:39 -2078.837475] AUTODETECT spr round 1 (radius: 5)
[00:01:39 -1347.271905] AUTODETECT spr round 2 (radius: 10)
[00:01:40 -992.043103] AUTODETECT spr round 3 (radius: 15)
[00:01:40 -992.042191] SPR radius for FAST iterations: 10 (autodetect)
[00:01:40 -992.042191] Model parameter optimization (eps = 3.000000)
[00:01:41 -971.815061] FAST spr round 1 (radius: 10)
[00:01:41 -925.577934] FAST spr round 2 (radius: 10)
[00:01:42 -918.361662] FAST spr round 3 (radius: 10)
[00:01:42 -918.361626] Model parameter optimization (eps = 1.000000)
[00:01:42 -917.767935] SLOW spr round 1 (radius: 5)
[00:01:43 -917.767660] SLOW spr round 2 (radius: 10)
[00:01:44 -917.767657] SLOW spr round 3 (radius: 15)
[00:01:45 -917.767656] SLOW spr round 4 (radius: 20)
[00:01:45 -917.767656] SLOW spr round 5 (radius: 25)
[00:01:45 -917.767656] Model parameter optimization (eps = 0.100000)

[00:01:45] ML tree search #13, logLikelihood: -917.767603

[00:01:45 -2682.956535] Initial branch length optimization
[00:01:45 -2216.548441] Model parameter optimization (eps = 10.000000)
[00:01:46 -2205.265429] AUTODETECT spr round 1 (radius: 5)
[00:01:47 -1261.689461] AUTODETECT spr round 2 (radius: 10)
[00:01:47 -984.289093] AUTODETECT spr round 3 (radius: 15)
[00:01:47 -984.287247] SPR radius for FAST iterations: 10 (autodetect)
[00:01:47 -984.287247] Model parameter optimization (eps = 3.000000)
[00:01:48 -964.304397] FAST spr round 1 (radius: 10)
[00:01:49 -926.611848] FAST spr round 2 (radius: 10)
[00:01:49 -918.932794] FAST spr round 3 (radius: 10)
[00:01:49 -918.932786] Model parameter optimization (eps = 1.000000)
[00:01:50 -918.553220] SLOW spr round 1 (radius: 5)
[00:01:51 -918.553115] SLOW spr round 2 (radius: 10)
[00:01:51 -918.553115] SLOW spr round 3 (radius: 15)
[00:01:52 -918.553115] SLOW spr round 4 (radius: 20)
[00:01:53 -918.553115] SLOW spr round 5 (radius: 25)
[00:01:53 -918.553115] Model parameter optimization (eps = 0.100000)

[00:01:53] ML tree search #14, logLikelihood: -918.552768

[00:01:53 -2584.018520] Initial branch length optimization
[00:01:53 -2092.428488] Model parameter optimization (eps = 10.000000)
[00:01:53 -2085.814118] AUTODETECT spr round 1 (radius: 5)
[00:01:54 -1238.204191] AUTODETECT spr round 2 (radius: 10)
[00:01:54 -1001.201524] AUTODETECT spr round 3 (radius: 15)
[00:01:55 -972.275438] AUTODETECT spr round 4 (radius: 20)
[00:01:55 -972.254198] SPR radius for FAST iterations: 15 (autodetect)
[00:01:55 -972.254198] Model parameter optimization (eps = 3.000000)
[00:01:56 -954.452852] FAST spr round 1 (radius: 15)
[00:01:56 -926.474652] FAST spr round 2 (radius: 15)
[00:01:57 -921.505271] FAST spr round 3 (radius: 15)
[00:01:57 -919.546456] FAST spr round 4 (radius: 15)
[00:01:57 -919.546413] Model parameter optimization (eps = 1.000000)
[00:01:58 -919.315053] SLOW spr round 1 (radius: 5)
[00:01:59 -919.314990] SLOW spr round 2 (radius: 10)
[00:01:59 -919.314990] SLOW spr round 3 (radius: 15)
[00:02:00 -919.314990] SLOW spr round 4 (radius: 20)
[00:02:01 -919.314990] SLOW spr round 5 (radius: 25)
[00:02:01 -919.314990] Model parameter optimization (eps = 0.100000)

[00:02:01] ML tree search #15, logLikelihood: -919.314981

[00:02:01 -2553.238373] Initial branch length optimization
[00:02:01 -2040.539669] Model parameter optimization (eps = 10.000000)
[00:02:01 -2030.706765] AUTODETECT spr round 1 (radius: 5)
[00:02:02 -1279.095976] AUTODETECT spr round 2 (radius: 10)
[00:02:02 -1060.359867] AUTODETECT spr round 3 (radius: 15)
[00:02:03 -1060.354773] SPR radius for FAST iterations: 10 (autodetect)
[00:02:03 -1060.354773] Model parameter optimization (eps = 3.000000)
[00:02:05 -1042.823875] FAST spr round 1 (radius: 10)
[00:02:06 -926.205513] FAST spr round 2 (radius: 10)
[00:02:06 -926.205079] Model parameter optimization (eps = 1.000000)
[00:02:07 -919.920457] SLOW spr round 1 (radius: 5)
[00:02:08 -919.704648] SLOW spr round 2 (radius: 5)
[00:02:09 -919.704333] SLOW spr round 3 (radius: 10)
[00:02:09 -918.066426] SLOW spr round 4 (radius: 5)
[00:02:11 -918.066408] SLOW spr round 5 (radius: 10)
[00:02:11 -918.066408] SLOW spr round 6 (radius: 15)
[00:02:12 -918.066408] SLOW spr round 7 (radius: 20)
[00:02:12 -918.066408] SLOW spr round 8 (radius: 25)
[00:02:13 -918.066408] Model parameter optimization (eps = 0.100000)

[00:02:13] ML tree search #16, logLikelihood: -917.767614

[00:02:13 -2597.033434] Initial branch length optimization
[00:02:13 -2146.815418] Model parameter optimization (eps = 10.000000)
[00:02:14 -2139.441923] AUTODETECT spr round 1 (radius: 5)
[00:02:14 -1216.706798] AUTODETECT spr round 2 (radius: 10)
[00:02:14 -1016.394303] AUTODETECT spr round 3 (radius: 15)
[00:02:15 -1012.950990] AUTODETECT spr round 4 (radius: 20)
[00:02:15 -1012.950115] SPR radius for FAST iterations: 15 (autodetect)
[00:02:15 -1012.950115] Model parameter optimization (eps = 3.000000)
[00:02:16 -996.223430] FAST spr round 1 (radius: 15)
[00:02:17 -930.537987] FAST spr round 2 (radius: 15)
[00:02:17 -925.919741] FAST spr round 3 (radius: 15)
[00:02:17 -919.872163] FAST spr round 4 (radius: 15)
[00:02:18 -919.872149] Model parameter optimization (eps = 1.000000)
[00:02:18 -917.980848] SLOW spr round 1 (radius: 5)
[00:02:19 -917.771352] SLOW spr round 2 (radius: 5)
[00:02:20 -917.771013] SLOW spr round 3 (radius: 10)
[00:02:20 -917.771008] SLOW spr round 4 (radius: 15)
[00:02:21 -917.771008] SLOW spr round 5 (radius: 20)
[00:02:22 -917.771008] SLOW spr round 6 (radius: 25)
[00:02:22 -917.771008] Model parameter optimization (eps = 0.100000)

[00:02:22] ML tree search #17, logLikelihood: -917.767703

[00:02:22 -2693.136748] Initial branch length optimization
[00:02:22 -2244.233261] Model parameter optimization (eps = 10.000000)
[00:02:23 -2237.706676] AUTODETECT spr round 1 (radius: 5)
[00:02:23 -1257.883051] AUTODETECT spr round 2 (radius: 10)
[00:02:24 -995.696676] AUTODETECT spr round 3 (radius: 15)
[00:02:24 -991.716183] AUTODETECT spr round 4 (radius: 20)
[00:02:24 -991.716020] SPR radius for FAST iterations: 15 (autodetect)
[00:02:24 -991.716020] Model parameter optimization (eps = 3.000000)
[00:02:25 -970.951974] FAST spr round 1 (radius: 15)
[00:02:26 -926.055123] FAST spr round 2 (radius: 15)
[00:02:26 -918.402238] FAST spr round 3 (radius: 15)
[00:02:26 -918.402223] Model parameter optimization (eps = 1.000000)
[00:02:27 -917.768623] SLOW spr round 1 (radius: 5)
[00:02:28 -917.767739] SLOW spr round 2 (radius: 10)
[00:02:28 -917.767735] SLOW spr round 3 (radius: 15)
[00:02:29 -917.767735] SLOW spr round 4 (radius: 20)
[00:02:30 -917.767735] SLOW spr round 5 (radius: 25)
[00:02:30 -917.767735] Model parameter optimization (eps = 0.100000)

[00:02:30] ML tree search #18, logLikelihood: -917.767622

[00:02:30 -2547.343013] Initial branch length optimization
[00:02:30 -2107.683898] Model parameter optimization (eps = 10.000000)
[00:02:31 -2100.110924] AUTODETECT spr round 1 (radius: 5)
[00:02:31 -1281.603532] AUTODETECT spr round 2 (radius: 10)
[00:02:31 -1017.319141] AUTODETECT spr round 3 (radius: 15)
[00:02:32 -1017.306018] SPR radius for FAST iterations: 10 (autodetect)
[00:02:32 -1017.306018] Model parameter optimization (eps = 3.000000)
[00:02:33 -1000.403624] FAST spr round 1 (radius: 10)
[00:02:33 -924.439783] FAST spr round 2 (radius: 10)
[00:02:34 -918.884067] FAST spr round 3 (radius: 10)
[00:02:34 -918.737260] FAST spr round 4 (radius: 10)
[00:02:34 -918.736926] Model parameter optimization (eps = 1.000000)
[00:02:35 -917.768662] SLOW spr round 1 (radius: 5)
[00:02:36 -917.767666] SLOW spr round 2 (radius: 10)
[00:02:36 -917.767651] SLOW spr round 3 (radius: 15)
[00:02:37 -917.767651] SLOW spr round 4 (radius: 20)
[00:02:38 -917.767651] SLOW spr round 5 (radius: 25)
[00:02:38 -917.767651] Model parameter optimization (eps = 0.100000)

[00:02:38] ML tree search #19, logLikelihood: -917.767597

[00:02:38 -2566.147669] Initial branch length optimization
[00:02:38 -2128.358240] Model parameter optimization (eps = 10.000000)
[00:02:38 -2117.630286] AUTODETECT spr round 1 (radius: 5)
[00:02:39 -1210.185081] AUTODETECT spr round 2 (radius: 10)
[00:02:39 -986.352205] AUTODETECT spr round 3 (radius: 15)
[00:02:40 -986.338029] SPR radius for FAST iterations: 10 (autodetect)
[00:02:40 -986.338029] Model parameter optimization (eps = 3.000000)
[00:02:41 -968.498369] FAST spr round 1 (radius: 10)
[00:02:41 -928.103057] FAST spr round 2 (radius: 10)
[00:02:42 -921.297973] FAST spr round 3 (radius: 10)
[00:02:42 -920.894441] FAST spr round 4 (radius: 10)
[00:02:42 -920.894396] Model parameter optimization (eps = 1.000000)
[00:02:43 -920.197231] SLOW spr round 1 (radius: 5)
[00:02:44 -920.197100] SLOW spr round 2 (radius: 10)
[00:02:44 -920.197100] SLOW spr round 3 (radius: 15)
[00:02:45 -920.197100] SLOW spr round 4 (radius: 20)
[00:02:46 -920.197100] SLOW spr round 5 (radius: 25)
[00:02:46 -920.197100] Model parameter optimization (eps = 0.100000)

[00:02:46] ML tree search #20, logLikelihood: -920.196863


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.130896,0.168014) (0.059559,2.432179) (0.408748,0.706419) (0.400797,1.358299) 
   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: -917.767597

AIC score: 2073.535194 / AICc score: 30633.535194 / BIC score: 2285.853760
Free parameters (model + branch lengths): 119

WARNING: Number of free parameters (K=119) is larger than alignment size (n=44).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 10 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NJ64/3_mltree/A6NJ64.raxml.log

Analysis started: 01-Jul-2021 00:35:14 / finished: 01-Jul-2021 00:38:01

Elapsed time: 166.307 seconds

Consumed energy: 13.248 Wh