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 05-Jul-2021 06:10:15 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/2_msa/A0A0C4DH28_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/3_mltree/A0A0C4DH28 --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/A0A0C4DH28/2_msa/A0A0C4DH28_trimmed_msa.fasta
[00:00:00] Loaded alignment with 195 taxa and 83 sites

WARNING: Sequences tr_A0A0B4J1Q5_A0A0B4J1Q5_RABIT_9986 and tr_U3KLT2_U3KLT2_RABIT_9986 are exactly identical!
WARNING: Sequences tr_A0A2I3T1F1_A0A2I3T1F1_PANTR_9598 and tr_A0A2R8ZNK8_A0A2R8ZNK8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TAX1_A0A2I3TAX1_PANTR_9598 and tr_A0A2R9AKE1_A0A2R9AKE1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A3B5K3K7_A0A3B5K3K7_TAKRU_31033 and tr_A0A3B5K6D8_A0A3B5K6D8_TAKRU_31033 are exactly identical!
WARNING: Sequences tr_F7H2U3_F7H2U3_MACMU_9544 and tr_A0A2I3N776_A0A2I3N776_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7H2U3_F7H2U3_MACMU_9544 and tr_A0A2K5NT28_A0A2K5NT28_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7H2U3_F7H2U3_MACMU_9544 and tr_A0A2K6ALR0_A0A2K6ALR0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A0B4J193_A0A0B4J193_BOVIN_9913 and tr_E1B780_E1B780_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_A0A226MH86_A0A226MH86_CALSU_9009 and tr_A0A226MHA1_A0A226MHA1_CALSU_9009 are exactly identical!
WARNING: Duplicate sequences found: 9

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/A0A0C4DH28/3_mltree/A0A0C4DH28.raxml.reduced.phy

Alignment comprises 1 partitions and 83 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 83 / 83
Gaps: 2.93 %
Invariant sites: 1.20 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/3_mltree/A0A0C4DH28.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 195 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 83 / 6640
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -33127.328259] Initial branch length optimization
[00:00:00 -27632.789560] Model parameter optimization (eps = 10.000000)
[00:00:04 -27517.807363] AUTODETECT spr round 1 (radius: 5)
[00:00:09 -20107.004968] AUTODETECT spr round 2 (radius: 10)
[00:00:16 -16516.509979] AUTODETECT spr round 3 (radius: 15)
[00:00:24 -15117.696373] AUTODETECT spr round 4 (radius: 20)
[00:00:34 -14969.644040] AUTODETECT spr round 5 (radius: 25)
[00:00:44 -14768.345331] SPR radius for FAST iterations: 25 (autodetect)
[00:00:44 -14768.345331] Model parameter optimization (eps = 3.000000)
[00:00:47 -14757.433709] FAST spr round 1 (radius: 25)
[00:00:54 -13508.151534] FAST spr round 2 (radius: 25)
[00:01:01 -13398.856868] FAST spr round 3 (radius: 25)
[00:01:06 -13390.614344] FAST spr round 4 (radius: 25)
[00:01:10 -13390.614332] Model parameter optimization (eps = 1.000000)
[00:01:13 -13380.709384] SLOW spr round 1 (radius: 5)
[00:01:22 -13372.427817] SLOW spr round 2 (radius: 5)
[00:01:30 -13371.734996] SLOW spr round 3 (radius: 5)
[00:01:37 -13371.576761] SLOW spr round 4 (radius: 5)
[00:01:44 -13371.576558] SLOW spr round 5 (radius: 10)
[00:01:52 -13370.187796] SLOW spr round 6 (radius: 5)
[00:02:04 -13370.187332] SLOW spr round 7 (radius: 10)
[00:02:13] [worker #1] ML tree search #2, logLikelihood: -13372.862220
[00:02:14 -13370.187130] SLOW spr round 8 (radius: 15)
[00:02:27 -13370.187130] SLOW spr round 9 (radius: 20)
[00:02:42 -13370.187130] SLOW spr round 10 (radius: 25)
[00:02:53 -13370.187130] Model parameter optimization (eps = 0.100000)

[00:02:56] [worker #0] ML tree search #1, logLikelihood: -13369.949516

[00:02:56 -33262.257713] Initial branch length optimization
[00:02:56 -27588.918799] Model parameter optimization (eps = 10.000000)
[00:03:01 -27489.909748] AUTODETECT spr round 1 (radius: 5)
[00:03:06 -19673.703619] AUTODETECT spr round 2 (radius: 10)
[00:03:13 -16007.678053] AUTODETECT spr round 3 (radius: 15)
[00:03:21 -14815.511512] AUTODETECT spr round 4 (radius: 20)
[00:03:30 -14793.638221] AUTODETECT spr round 5 (radius: 25)
[00:03:38 -14793.632831] SPR radius for FAST iterations: 20 (autodetect)
[00:03:38 -14793.632831] Model parameter optimization (eps = 3.000000)
[00:03:42 -14771.857864] FAST spr round 1 (radius: 20)
[00:03:49 -13469.963371] FAST spr round 2 (radius: 20)
[00:03:56 -13395.349377] FAST spr round 3 (radius: 20)
[00:04:00 -13392.332715] FAST spr round 4 (radius: 20)
[00:04:05 -13392.332683] Model parameter optimization (eps = 1.000000)
[00:04:08 -13381.957009] SLOW spr round 1 (radius: 5)
[00:04:17 -13377.144831] SLOW spr round 2 (radius: 5)
[00:04:25 -13376.726142] SLOW spr round 3 (radius: 5)
[00:04:33 -13376.726072] SLOW spr round 4 (radius: 10)
[00:04:41 -13375.240981] SLOW spr round 5 (radius: 5)
[00:04:53 -13373.783940] SLOW spr round 6 (radius: 5)
[00:05:03 -13373.783935] SLOW spr round 7 (radius: 10)
[00:05:12 -13372.671596] SLOW spr round 8 (radius: 5)
[00:05:23] [worker #1] ML tree search #4, logLikelihood: -13372.178810
[00:05:24 -13372.671594] SLOW spr round 9 (radius: 10)
[00:05:33 -13372.671594] SLOW spr round 10 (radius: 15)
[00:05:46 -13372.671594] SLOW spr round 11 (radius: 20)
[00:06:01 -13372.671594] SLOW spr round 12 (radius: 25)
[00:06:12 -13372.671594] Model parameter optimization (eps = 0.100000)

[00:06:14] [worker #0] ML tree search #3, logLikelihood: -13372.222252

[00:06:14 -33297.498936] Initial branch length optimization
[00:06:15 -28114.632100] Model parameter optimization (eps = 10.000000)
[00:06:20 -28054.450098] AUTODETECT spr round 1 (radius: 5)
[00:06:25 -19206.562756] AUTODETECT spr round 2 (radius: 10)
[00:06:32 -15866.607542] AUTODETECT spr round 3 (radius: 15)
[00:06:40 -14575.815903] AUTODETECT spr round 4 (radius: 20)
[00:06:49 -14501.343706] AUTODETECT spr round 5 (radius: 25)
[00:06:57 -14501.334998] SPR radius for FAST iterations: 20 (autodetect)
[00:06:57 -14501.334998] Model parameter optimization (eps = 3.000000)
[00:07:01 -14485.361061] FAST spr round 1 (radius: 20)
[00:07:08 -13432.303412] FAST spr round 2 (radius: 20)
[00:07:14 -13382.235376] FAST spr round 3 (radius: 20)
[00:07:18 -13377.354133] FAST spr round 4 (radius: 20)
[00:07:23 -13377.352702] Model parameter optimization (eps = 1.000000)
[00:07:26 -13373.844294] SLOW spr round 1 (radius: 5)
[00:07:34 -13371.464005] SLOW spr round 2 (radius: 5)
[00:07:42 -13371.463574] SLOW spr round 3 (radius: 10)
[00:07:50 -13371.463568] SLOW spr round 4 (radius: 15)
[00:07:56] [worker #1] ML tree search #6, logLikelihood: -13375.319611
[00:08:04 -13371.463568] SLOW spr round 5 (radius: 20)
[00:08:18 -13371.463568] SLOW spr round 6 (radius: 25)
[00:08:30 -13371.463568] Model parameter optimization (eps = 0.100000)

[00:08:31] [worker #0] ML tree search #5, logLikelihood: -13371.457542

[00:08:31 -32710.521499] Initial branch length optimization
[00:08:31 -27311.783970] Model parameter optimization (eps = 10.000000)
[00:08:36 -27247.729797] AUTODETECT spr round 1 (radius: 5)
[00:08:41 -20112.620177] AUTODETECT spr round 2 (radius: 10)
[00:08:48 -15740.017801] AUTODETECT spr round 3 (radius: 15)
[00:08:57 -14523.369423] AUTODETECT spr round 4 (radius: 20)
[00:09:07 -14498.177493] AUTODETECT spr round 5 (radius: 25)
[00:09:16 -14487.965405] SPR radius for FAST iterations: 25 (autodetect)
[00:09:16 -14487.965405] Model parameter optimization (eps = 3.000000)
[00:09:19 -14475.652289] FAST spr round 1 (radius: 25)
[00:09:26 -13441.683294] FAST spr round 2 (radius: 25)
[00:09:32 -13388.312881] FAST spr round 3 (radius: 25)
[00:09:38 -13385.146195] FAST spr round 4 (radius: 25)
[00:09:42 -13382.464741] FAST spr round 5 (radius: 25)
[00:09:46 -13381.460490] FAST spr round 6 (radius: 25)
[00:09:51 -13381.440283] Model parameter optimization (eps = 1.000000)
[00:09:53 -13379.529242] SLOW spr round 1 (radius: 5)
[00:10:01 -13376.833802] SLOW spr round 2 (radius: 5)
[00:10:09 -13376.832756] SLOW spr round 3 (radius: 10)
[00:10:17 -13376.832505] SLOW spr round 4 (radius: 15)
[00:10:28] [worker #1] ML tree search #8, logLikelihood: -13369.645931
[00:10:32 -13376.832277] SLOW spr round 5 (radius: 20)
[00:10:46 -13376.832050] SLOW spr round 6 (radius: 25)
[00:10:57 -13376.831822] Model parameter optimization (eps = 0.100000)

[00:10:58] [worker #0] ML tree search #7, logLikelihood: -13376.810100

[00:10:58 -32956.072713] Initial branch length optimization
[00:10:59 -27448.964886] Model parameter optimization (eps = 10.000000)
[00:11:05 -27331.057276] AUTODETECT spr round 1 (radius: 5)
[00:11:10 -19714.118827] AUTODETECT spr round 2 (radius: 10)
[00:11:17 -15250.130352] AUTODETECT spr round 3 (radius: 15)
[00:11:26 -14506.039581] AUTODETECT spr round 4 (radius: 20)
[00:11:36 -14487.688125] AUTODETECT spr round 5 (radius: 25)
[00:11:45 -14487.678298] SPR radius for FAST iterations: 20 (autodetect)
[00:11:45 -14487.678298] Model parameter optimization (eps = 3.000000)
[00:11:49 -14466.973088] FAST spr round 1 (radius: 20)
[00:11:56 -13458.067847] FAST spr round 2 (radius: 20)
[00:12:02 -13383.140325] FAST spr round 3 (radius: 20)
[00:12:06 -13381.318899] FAST spr round 4 (radius: 20)
[00:12:10 -13381.318734] Model parameter optimization (eps = 1.000000)
[00:12:13 -13379.500214] SLOW spr round 1 (radius: 5)
[00:12:22 -13371.840778] SLOW spr round 2 (radius: 5)
[00:12:29 -13370.599917] SLOW spr round 3 (radius: 5)
[00:12:37 -13370.515404] SLOW spr round 4 (radius: 10)
[00:12:45 -13370.515237] SLOW spr round 5 (radius: 15)
[00:12:59 -13370.515235] SLOW spr round 6 (radius: 20)
[00:13:01] [worker #1] ML tree search #10, logLikelihood: -13365.336786
[00:13:13 -13370.515235] SLOW spr round 7 (radius: 25)
[00:13:25 -13370.515235] Model parameter optimization (eps = 0.100000)

[00:13:26] [worker #0] ML tree search #9, logLikelihood: -13370.466824

[00:13:26 -32870.023242] Initial branch length optimization
[00:13:26 -27499.247884] Model parameter optimization (eps = 10.000000)
[00:13:32 -27353.933884] AUTODETECT spr round 1 (radius: 5)
[00:13:37 -18747.891363] AUTODETECT spr round 2 (radius: 10)
[00:13:44 -15640.436147] AUTODETECT spr round 3 (radius: 15)
[00:13:52 -14925.799645] AUTODETECT spr round 4 (radius: 20)
[00:14:03 -14766.549080] AUTODETECT spr round 5 (radius: 25)
[00:14:10 -14756.840686] SPR radius for FAST iterations: 25 (autodetect)
[00:14:11 -14756.840686] Model parameter optimization (eps = 3.000000)
[00:14:14 -14729.516725] FAST spr round 1 (radius: 25)
[00:14:21 -13523.080096] FAST spr round 2 (radius: 25)
[00:14:27 -13390.334259] FAST spr round 3 (radius: 25)
[00:14:32 -13384.898049] FAST spr round 4 (radius: 25)
[00:14:37 -13382.743822] FAST spr round 5 (radius: 25)
[00:14:41 -13382.711880] Model parameter optimization (eps = 1.000000)
[00:14:44 -13382.296398] SLOW spr round 1 (radius: 5)
[00:14:52 -13380.120497] SLOW spr round 2 (radius: 5)
[00:15:00 -13380.119408] SLOW spr round 3 (radius: 10)
[00:15:08 -13380.119401] SLOW spr round 4 (radius: 15)
[00:15:22 -13380.119401] SLOW spr round 5 (radius: 20)
[00:15:36 -13380.119401] SLOW spr round 6 (radius: 25)
[00:15:42] [worker #1] ML tree search #12, logLikelihood: -13376.462604
[00:15:47 -13380.119400] Model parameter optimization (eps = 0.100000)

[00:15:48] [worker #0] ML tree search #11, logLikelihood: -13380.104182

[00:15:48 -33182.499628] Initial branch length optimization
[00:15:48 -27739.443825] Model parameter optimization (eps = 10.000000)
[00:15:53 -27644.157654] AUTODETECT spr round 1 (radius: 5)
[00:15:58 -19912.734293] AUTODETECT spr round 2 (radius: 10)
[00:16:05 -15873.407764] AUTODETECT spr round 3 (radius: 15)
[00:16:14 -14707.604748] AUTODETECT spr round 4 (radius: 20)
[00:16:24 -14644.527902] AUTODETECT spr round 5 (radius: 25)
[00:16:32 -14644.525927] SPR radius for FAST iterations: 20 (autodetect)
[00:16:32 -14644.525927] Model parameter optimization (eps = 3.000000)
[00:16:36 -14601.768032] FAST spr round 1 (radius: 20)
[00:16:42 -13479.506181] FAST spr round 2 (radius: 20)
[00:16:49 -13384.114936] FAST spr round 3 (radius: 20)
[00:16:54 -13377.387797] FAST spr round 4 (radius: 20)
[00:16:58 -13373.857466] FAST spr round 5 (radius: 20)
[00:17:03 -13373.857424] Model parameter optimization (eps = 1.000000)
[00:17:04 -13373.198088] SLOW spr round 1 (radius: 5)
[00:17:13 -13369.707583] SLOW spr round 2 (radius: 5)
[00:17:21 -13369.707346] SLOW spr round 3 (radius: 10)
[00:17:29 -13368.388533] SLOW spr round 4 (radius: 5)
[00:17:41 -13368.388180] SLOW spr round 5 (radius: 10)
[00:17:50 -13367.990908] SLOW spr round 6 (radius: 5)
[00:18:02 -13367.351498] SLOW spr round 7 (radius: 5)
[00:18:08] [worker #1] ML tree search #14, logLikelihood: -13377.296517
[00:18:11 -13366.164081] SLOW spr round 8 (radius: 5)
[00:18:19 -13366.163817] SLOW spr round 9 (radius: 10)
[00:18:28 -13366.163814] SLOW spr round 10 (radius: 15)
[00:18:42 -13366.163814] SLOW spr round 11 (radius: 20)
[00:18:56 -13366.163813] SLOW spr round 12 (radius: 25)
[00:19:08 -13366.163812] Model parameter optimization (eps = 0.100000)

[00:19:09] [worker #0] ML tree search #13, logLikelihood: -13366.096008

[00:19:09 -32531.249678] Initial branch length optimization
[00:19:09 -27183.258222] Model parameter optimization (eps = 10.000000)
[00:19:14 -27046.151295] AUTODETECT spr round 1 (radius: 5)
[00:19:19 -19416.839968] AUTODETECT spr round 2 (radius: 10)
[00:19:26 -15196.504085] AUTODETECT spr round 3 (radius: 15)
[00:19:35 -14300.026981] AUTODETECT spr round 4 (radius: 20)
[00:19:44 -14298.161378] AUTODETECT spr round 5 (radius: 25)
[00:19:52 -14298.159681] SPR radius for FAST iterations: 20 (autodetect)
[00:19:52 -14298.159681] Model parameter optimization (eps = 3.000000)
[00:19:56 -14271.750909] FAST spr round 1 (radius: 20)
[00:20:03 -13424.025497] FAST spr round 2 (radius: 20)
[00:20:09 -13396.032938] FAST spr round 3 (radius: 20)
[00:20:13 -13396.032747] Model parameter optimization (eps = 1.000000)
[00:20:16 -13394.357113] SLOW spr round 1 (radius: 5)
[00:20:25 -13389.814469] SLOW spr round 2 (radius: 5)
[00:20:32 -13389.158393] SLOW spr round 3 (radius: 5)
[00:20:39] [worker #1] ML tree search #16, logLikelihood: -13365.274501
[00:20:40 -13389.158388] SLOW spr round 4 (radius: 10)
[00:20:48 -13385.228735] SLOW spr round 5 (radius: 5)
[00:21:01 -13382.776791] SLOW spr round 6 (radius: 5)
[00:21:10 -13382.776791] SLOW spr round 7 (radius: 10)
[00:21:19 -13382.776791] SLOW spr round 8 (radius: 15)
[00:21:33 -13382.695304] SLOW spr round 9 (radius: 20)
[00:21:48 -13382.695276] SLOW spr round 10 (radius: 25)
[00:21:59 -13382.695276] Model parameter optimization (eps = 0.100000)

[00:22:01] [worker #0] ML tree search #15, logLikelihood: -13382.663885

[00:22:01 -32295.468082] Initial branch length optimization
[00:22:01 -27284.014384] Model parameter optimization (eps = 10.000000)
[00:22:08 -27167.143152] AUTODETECT spr round 1 (radius: 5)
[00:22:12 -19372.252152] AUTODETECT spr round 2 (radius: 10)
[00:22:19 -16556.782213] AUTODETECT spr round 3 (radius: 15)
[00:22:27 -15658.360859] AUTODETECT spr round 4 (radius: 20)
[00:22:37 -15215.657725] AUTODETECT spr round 5 (radius: 25)
[00:22:44 -15208.579502] SPR radius for FAST iterations: 25 (autodetect)
[00:22:44 -15208.579502] Model parameter optimization (eps = 3.000000)
[00:22:48 -15190.043918] FAST spr round 1 (radius: 25)
[00:22:55 -13503.839513] FAST spr round 2 (radius: 25)
[00:23:01 -13417.412069] FAST spr round 3 (radius: 25)
[00:23:07 -13411.523283] FAST spr round 4 (radius: 25)
[00:23:11 -13410.495587] FAST spr round 5 (radius: 25)
[00:23:16 -13409.839477] FAST spr round 6 (radius: 25)
[00:23:20 -13409.807700] Model parameter optimization (eps = 1.000000)
[00:23:24 -13389.305585] SLOW spr round 1 (radius: 5)
[00:23:33 -13373.129901] SLOW spr round 2 (radius: 5)
[00:23:41 -13370.696961] SLOW spr round 3 (radius: 5)
[00:23:48 -13370.696622] SLOW spr round 4 (radius: 10)
[00:23:54] [worker #1] ML tree search #18, logLikelihood: -13370.385926
[00:23:56 -13370.696616] SLOW spr round 5 (radius: 15)
[00:24:09 -13370.485406] SLOW spr round 6 (radius: 5)
[00:24:22 -13369.373345] SLOW spr round 7 (radius: 5)
[00:24:32 -13369.373279] SLOW spr round 8 (radius: 10)
[00:24:40 -13369.373277] SLOW spr round 9 (radius: 15)
[00:24:52 -13369.373275] SLOW spr round 10 (radius: 20)
[00:25:07 -13369.373274] SLOW spr round 11 (radius: 25)
[00:25:19 -13369.373272] Model parameter optimization (eps = 0.100000)

[00:25:21] [worker #0] ML tree search #17, logLikelihood: -13369.197127

[00:25:21 -33197.803471] Initial branch length optimization
[00:25:21 -27393.154004] Model parameter optimization (eps = 10.000000)
[00:25:26 -27305.667639] AUTODETECT spr round 1 (radius: 5)
[00:25:31 -19241.023610] AUTODETECT spr round 2 (radius: 10)
[00:25:38 -15030.091724] AUTODETECT spr round 3 (radius: 15)
[00:25:48 -14455.258781] AUTODETECT spr round 4 (radius: 20)
[00:25:57 -14447.445902] AUTODETECT spr round 5 (radius: 25)
[00:26:04 -14447.439252] SPR radius for FAST iterations: 20 (autodetect)
[00:26:04 -14447.439252] Model parameter optimization (eps = 3.000000)
[00:26:07 -14433.329199] FAST spr round 1 (radius: 20)
[00:26:14 -13436.829486] FAST spr round 2 (radius: 20)
[00:26:20 -13379.896568] FAST spr round 3 (radius: 20)
[00:26:25 -13375.193378] FAST spr round 4 (radius: 20)
[00:26:30 -13375.193357] Model parameter optimization (eps = 1.000000)
[00:26:31 -13374.640809] SLOW spr round 1 (radius: 5)
[00:26:33] [worker #1] ML tree search #20, logLikelihood: -13374.075583
[00:26:40 -13370.967829] SLOW spr round 2 (radius: 5)
[00:26:48 -13367.085974] SLOW spr round 3 (radius: 5)
[00:26:56 -13366.537633] SLOW spr round 4 (radius: 5)
[00:27:03 -13366.537602] SLOW spr round 5 (radius: 10)
[00:27:11 -13366.537602] SLOW spr round 6 (radius: 15)
[00:27:25 -13366.537602] SLOW spr round 7 (radius: 20)
[00:27:40 -13366.537602] SLOW spr round 8 (radius: 25)
[00:27:51 -13366.537602] Model parameter optimization (eps = 0.100000)

[00:27:53] [worker #0] ML tree search #19, logLikelihood: -13366.425326


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.050138,0.159064) (0.165689,0.493933) (0.365573,0.768354) (0.418600,1.503337) 
   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: -13365.274501

AIC score: 27516.549002 / AICc score: 337200.549002 / BIC score: 28467.153360
Free parameters (model + branch lengths): 393

WARNING: Number of free parameters (K=393) is larger than alignment size (n=83).
         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/A0A0C4DH28/3_mltree/A0A0C4DH28.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/3_mltree/A0A0C4DH28.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/3_mltree/A0A0C4DH28.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A0C4DH28/3_mltree/A0A0C4DH28.raxml.log

Analysis started: 05-Jul-2021 06:10:15 / finished: 05-Jul-2021 06:38:08

Elapsed time: 1673.239 seconds

Consumed energy: 153.951 Wh