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 04:06:30 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/2_msa/P04259_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/3_mltree/P04259 --seed 2 --threads 7 --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 (7 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/2_msa/P04259_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 596 sites

WARNING: Sequences sp_Q9DCV7_K2C7_MOUSE_10090 and sp_Q6IG12_K2C7_RAT_10116 are exactly identical!
WARNING: Sequences tr_G3QJY7_G3QJY7_GORGO_9595 and tr_H2Q5Z3_H2Q5Z3_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QLP7_G3QLP7_GORGO_9595 and sp_P04264_K2C1_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G1SY72_G1SY72_RABIT_9986 and sp_Q29426_K2C3_RABIT_9986 are exactly identical!
WARNING: Sequences tr_A0A2J8KDC3_A0A2J8KDC3_PANTR_9598 and tr_A0A2R9A6T6_A0A2R9A6T6_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2RGY7_H2RGY7_PANTR_9598 and tr_A0A2R9AZS5_A0A2R9AZS5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F7AEK9_F7AEK9_MACMU_9544 and tr_G7PID3_G7PID3_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7AEK9_F7AEK9_MACMU_9544 and tr_A0A2K6E1L5_A0A2K6E1L5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7HME7_F7HME7_MACMU_9544 and tr_A0A2K5N2V1_A0A2K5N2V1_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A5D7M6_A5D7M6_BOVIN_9913 and sp_Q5XQN5_K2C5_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_A0A096MVH8_A0A096MVH8_PAPAN_9555 and tr_A0A2K5ZK75_A0A2K5ZK75_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A096N7Y8_A0A096N7Y8_PAPAN_9555 and tr_A0A2K5NJ30_A0A2K5NJ30_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A096N7Y8_A0A096N7Y8_PAPAN_9555 and tr_A0A2K6E7G3_A0A2K6E7G3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A096N7Y8_A0A096N7Y8_PAPAN_9555 and tr_A0A2K5XF23_A0A2K5XF23_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 14

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/P04259/3_mltree/P04259.raxml.reduced.phy

Alignment comprises 1 partitions and 596 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 596 / 596
Gaps: 14.98 %
Invariant sites: 0.67 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/3_mltree/P04259.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 7 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 / 86 / 6880
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -601491.895027] Initial branch length optimization
[00:00:04 -536108.161625] Model parameter optimization (eps = 10.000000)
[00:00:31 -532603.093691] AUTODETECT spr round 1 (radius: 5)
[00:02:25 -380269.513073] AUTODETECT spr round 2 (radius: 10)
[00:04:21 -255072.424585] AUTODETECT spr round 3 (radius: 15)
[00:06:26 -212954.274341] AUTODETECT spr round 4 (radius: 20)
[00:09:19 -202824.828442] AUTODETECT spr round 5 (radius: 25)
[00:13:20 -202049.961690] SPR radius for FAST iterations: 25 (autodetect)
[00:13:20 -202049.961690] Model parameter optimization (eps = 3.000000)
[00:13:39 -201830.803891] FAST spr round 1 (radius: 25)
[00:15:42 -183704.859744] FAST spr round 2 (radius: 25)
[00:17:26 -182885.153063] FAST spr round 3 (radius: 25)
[00:19:01 -182822.081986] FAST spr round 4 (radius: 25)
[00:20:30 -182822.081813] Model parameter optimization (eps = 1.000000)
[00:20:42 -182819.959417] SLOW spr round 1 (radius: 5)
[00:22:43 -182760.282047] SLOW spr round 2 (radius: 5)
[00:24:36 -182757.348388] SLOW spr round 3 (radius: 5)
[00:26:25 -182753.694364] SLOW spr round 4 (radius: 5)
[00:28:15 -182753.694351] SLOW spr round 5 (radius: 10)
[00:30:03 -182741.057229] SLOW spr round 6 (radius: 5)
[00:32:16 -182733.429682] SLOW spr round 7 (radius: 5)
[00:34:18 -182727.062247] SLOW spr round 8 (radius: 5)
[00:36:11 -182727.062226] SLOW spr round 9 (radius: 10)
[00:38:01 -182727.062226] SLOW spr round 10 (radius: 15)
[00:40:48 -182726.701163] SLOW spr round 11 (radius: 5)
[00:43:06 -182725.715078] SLOW spr round 12 (radius: 5)
[00:45:09 -182725.715072] SLOW spr round 13 (radius: 10)
[00:46:58 -182725.715072] SLOW spr round 14 (radius: 15)
[00:49:42 -182725.715072] SLOW spr round 15 (radius: 20)
[00:54:39 -182725.715072] SLOW spr round 16 (radius: 25)
[01:01:20 -182725.715072] Model parameter optimization (eps = 0.100000)

[01:01:28] ML tree search #1, logLikelihood: -182725.611132

[01:01:28 -606549.083286] Initial branch length optimization
[01:01:31 -538245.374784] Model parameter optimization (eps = 10.000000)
[01:01:59 -534790.630395] AUTODETECT spr round 1 (radius: 5)
[01:03:50 -388375.209430] AUTODETECT spr round 2 (radius: 10)
[01:05:52 -260508.105542] AUTODETECT spr round 3 (radius: 15)
[01:08:07 -218162.420574] AUTODETECT spr round 4 (radius: 20)
[01:10:58 -207350.334821] AUTODETECT spr round 5 (radius: 25)
[01:14:25 -206760.217578] SPR radius for FAST iterations: 25 (autodetect)
[01:14:25 -206760.217578] Model parameter optimization (eps = 3.000000)
[01:14:52 -206527.106499] FAST spr round 1 (radius: 25)
[01:16:54 -183952.669981] FAST spr round 2 (radius: 25)
[01:18:39 -182936.437625] FAST spr round 3 (radius: 25)
[01:20:19 -182806.372961] FAST spr round 4 (radius: 25)
[01:21:53 -182790.123398] FAST spr round 5 (radius: 25)
[01:23:21 -182787.779469] FAST spr round 6 (radius: 25)
[01:24:47 -182787.779305] Model parameter optimization (eps = 1.000000)
[01:24:59 -182782.362424] SLOW spr round 1 (radius: 5)
[01:26:55 -182741.165193] SLOW spr round 2 (radius: 5)
[01:28:49 -182737.004561] SLOW spr round 3 (radius: 5)
[01:30:40 -182733.383225] SLOW spr round 4 (radius: 5)
[01:32:29 -182733.383167] SLOW spr round 5 (radius: 10)
[01:34:16 -182733.383166] SLOW spr round 6 (radius: 15)
[01:37:01 -182733.383166] SLOW spr round 7 (radius: 20)
[01:41:44 -182732.991154] SLOW spr round 8 (radius: 5)
[01:44:05 -182728.453282] SLOW spr round 9 (radius: 5)
[01:46:09 -182728.297117] SLOW spr round 10 (radius: 5)
[01:48:02 -182728.297107] SLOW spr round 11 (radius: 10)
[01:49:52 -182728.297107] SLOW spr round 12 (radius: 15)
[01:52:37 -182728.297107] SLOW spr round 13 (radius: 20)
[01:57:23 -182728.297107] SLOW spr round 14 (radius: 25)
[02:03:43 -182728.297107] Model parameter optimization (eps = 0.100000)

[02:03:48] ML tree search #2, logLikelihood: -182728.238830

[02:03:48 -602714.624661] Initial branch length optimization
[02:03:52 -536736.964031] Model parameter optimization (eps = 10.000000)
[02:04:20 -533336.094239] AUTODETECT spr round 1 (radius: 5)
[02:06:14 -382187.466512] AUTODETECT spr round 2 (radius: 10)
[02:08:09 -261795.666115] AUTODETECT spr round 3 (radius: 15)
[02:10:19 -211022.032450] AUTODETECT spr round 4 (radius: 20)
[02:13:06 -205101.257709] AUTODETECT spr round 5 (radius: 25)
[02:17:01 -205063.749410] SPR radius for FAST iterations: 25 (autodetect)
[02:17:01 -205063.749410] Model parameter optimization (eps = 3.000000)
[02:17:27 -204790.005572] FAST spr round 1 (radius: 25)
[02:19:33 -183490.460961] FAST spr round 2 (radius: 25)
[02:21:20 -182859.284476] FAST spr round 3 (radius: 25)
[02:22:59 -182782.351590] FAST spr round 4 (radius: 25)
[02:24:31 -182765.513895] FAST spr round 5 (radius: 25)
[02:26:02 -182751.490450] FAST spr round 6 (radius: 25)
[02:27:29 -182751.490437] Model parameter optimization (eps = 1.000000)
[02:27:44 -182744.579545] SLOW spr round 1 (radius: 5)
[02:29:41 -182706.396894] SLOW spr round 2 (radius: 5)
[02:31:35 -182694.892175] SLOW spr round 3 (radius: 5)
[02:33:26 -182694.892075] SLOW spr round 4 (radius: 10)
[02:35:14 -182690.799061] SLOW spr round 5 (radius: 5)
[02:37:25 -182683.555174] SLOW spr round 6 (radius: 5)
[02:39:25 -182683.555164] SLOW spr round 7 (radius: 10)
[02:41:16 -182683.555164] SLOW spr round 8 (radius: 15)
[02:44:05 -182683.555164] SLOW spr round 9 (radius: 20)
[02:49:10 -182683.555164] SLOW spr round 10 (radius: 25)
[02:55:47 -182683.555164] Model parameter optimization (eps = 0.100000)

[02:55:56] ML tree search #3, logLikelihood: -182683.366174

[02:55:56 -605845.142949] Initial branch length optimization
[02:55:59 -538441.765797] Model parameter optimization (eps = 10.000000)
[02:56:30 -534944.666244] AUTODETECT spr round 1 (radius: 5)
[02:58:21 -396327.672873] AUTODETECT spr round 2 (radius: 10)
[03:00:26 -258994.919850] AUTODETECT spr round 3 (radius: 15)
[03:02:35 -209571.740820] AUTODETECT spr round 4 (radius: 20)
[03:05:41 -201191.751169] AUTODETECT spr round 5 (radius: 25)
[03:10:01 -200923.597373] SPR radius for FAST iterations: 25 (autodetect)
[03:10:01 -200923.597373] Model parameter optimization (eps = 3.000000)
[03:10:29 -200710.427828] FAST spr round 1 (radius: 25)
[03:12:28 -183551.487612] FAST spr round 2 (radius: 25)
[03:14:13 -182808.658022] FAST spr round 3 (radius: 25)
[03:15:52 -182762.705786] FAST spr round 4 (radius: 25)
[03:17:24 -182749.897180] FAST spr round 5 (radius: 25)
[03:18:51 -182749.896988] Model parameter optimization (eps = 1.000000)
[03:19:10 -182742.913392] SLOW spr round 1 (radius: 5)
[03:21:12 -182720.034274] SLOW spr round 2 (radius: 5)
[03:23:04 -182718.905842] SLOW spr round 3 (radius: 5)
[03:24:55 -182718.905838] SLOW spr round 4 (radius: 10)
[03:26:44 -182716.731922] SLOW spr round 5 (radius: 5)
[03:28:58 -182715.630510] SLOW spr round 6 (radius: 5)
[03:30:58 -182715.629935] SLOW spr round 7 (radius: 10)
[03:32:49 -182715.604119] SLOW spr round 8 (radius: 15)
[03:35:33 -182715.604100] SLOW spr round 9 (radius: 20)
[03:40:21 -182715.604100] SLOW spr round 10 (radius: 25)
[03:46:53 -182715.604100] Model parameter optimization (eps = 0.100000)

[03:46:59] ML tree search #4, logLikelihood: -182715.525487

[03:46:59 -601877.239148] Initial branch length optimization
[03:47:02 -536175.655028] Model parameter optimization (eps = 10.000000)
[03:47:27 -532756.549277] AUTODETECT spr round 1 (radius: 5)
[03:49:21 -386276.137778] AUTODETECT spr round 2 (radius: 10)
[03:51:16 -258604.473393] AUTODETECT spr round 3 (radius: 15)
[03:53:22 -221658.851084] AUTODETECT spr round 4 (radius: 20)
[03:56:01 -209213.775994] AUTODETECT spr round 5 (radius: 25)
[03:59:17 -206569.058894] SPR radius for FAST iterations: 25 (autodetect)
[03:59:17 -206569.058894] Model parameter optimization (eps = 3.000000)
[03:59:44 -206328.064033] FAST spr round 1 (radius: 25)
[04:01:51 -183765.627838] FAST spr round 2 (radius: 25)
[04:03:37 -182835.890930] FAST spr round 3 (radius: 25)
[04:05:17 -182779.426214] FAST spr round 4 (radius: 25)
[04:06:47 -182774.865042] FAST spr round 5 (radius: 25)
[04:08:15 -182774.865042] Model parameter optimization (eps = 1.000000)
[04:08:31 -182765.594221] SLOW spr round 1 (radius: 5)
[04:10:28 -182720.431197] SLOW spr round 2 (radius: 5)
[04:12:26 -182713.177104] SLOW spr round 3 (radius: 5)
[04:14:20 -182710.246939] SLOW spr round 4 (radius: 5)
[04:16:08 -182710.246919] SLOW spr round 5 (radius: 10)
[04:17:59 -182707.962050] SLOW spr round 6 (radius: 5)
[04:20:13 -182704.507745] SLOW spr round 7 (radius: 5)
[04:22:15 -182704.507730] SLOW spr round 8 (radius: 10)
[04:24:07 -182704.283994] SLOW spr round 9 (radius: 5)
[04:26:17 -182704.283394] SLOW spr round 10 (radius: 10)
[04:28:14 -182704.283378] SLOW spr round 11 (radius: 15)
[04:30:54 -182704.283377] SLOW spr round 12 (radius: 20)
[04:35:44 -182704.283377] SLOW spr round 13 (radius: 25)
[04:42:16 -182704.283377] Model parameter optimization (eps = 0.100000)

[04:42:22] ML tree search #5, logLikelihood: -182704.212318

[04:42:22 -603418.419942] Initial branch length optimization
[04:42:26 -537668.468561] Model parameter optimization (eps = 10.000000)
[04:43:00 -534090.545046] AUTODETECT spr round 1 (radius: 5)
[04:44:52 -381340.765174] AUTODETECT spr round 2 (radius: 10)
[04:46:49 -252508.897827] AUTODETECT spr round 3 (radius: 15)
[04:49:07 -212570.886317] AUTODETECT spr round 4 (radius: 20)
[04:52:08 -203718.741158] AUTODETECT spr round 5 (radius: 25)
[04:56:06 -202379.210366] SPR radius for FAST iterations: 25 (autodetect)
[04:56:06 -202379.210366] Model parameter optimization (eps = 3.000000)
[04:56:29 -202188.748681] FAST spr round 1 (radius: 25)
[04:58:37 -183633.692354] FAST spr round 2 (radius: 25)
[05:00:22 -182857.644512] FAST spr round 3 (radius: 25)
[05:02:00 -182802.891189] FAST spr round 4 (radius: 25)
[05:03:31 -182800.194445] FAST spr round 5 (radius: 25)
[05:05:00 -182800.194337] Model parameter optimization (eps = 1.000000)
[05:05:14 -182795.012467] SLOW spr round 1 (radius: 5)
[05:07:17 -182729.008699] SLOW spr round 2 (radius: 5)
[05:09:12 -182718.342913] SLOW spr round 3 (radius: 5)
[05:11:02 -182718.342881] SLOW spr round 4 (radius: 10)
[05:12:51 -182716.173944] SLOW spr round 5 (radius: 5)
[05:15:07 -182715.073315] SLOW spr round 6 (radius: 5)
[05:17:09 -182715.071650] SLOW spr round 7 (radius: 10)
[05:19:00 -182715.071605] SLOW spr round 8 (radius: 15)
[05:21:47 -182715.071603] SLOW spr round 9 (radius: 20)
[05:26:47 -182715.071603] SLOW spr round 10 (radius: 25)
[05:33:17 -182715.071603] Model parameter optimization (eps = 0.100000)

[05:33:27] ML tree search #6, logLikelihood: -182714.966135

[05:33:27 -607636.301214] Initial branch length optimization
[05:33:31 -539487.639897] Model parameter optimization (eps = 10.000000)
[05:34:00 -535993.897118] AUTODETECT spr round 1 (radius: 5)
[05:35:54 -387637.705479] AUTODETECT spr round 2 (radius: 10)
[05:37:53 -247741.777733] AUTODETECT spr round 3 (radius: 15)
[05:40:05 -213097.356157] AUTODETECT spr round 4 (radius: 20)
[05:43:17 -205199.287499] AUTODETECT spr round 5 (radius: 25)
[05:47:30 -205042.284253] SPR radius for FAST iterations: 25 (autodetect)
[05:47:30 -205042.284253] Model parameter optimization (eps = 3.000000)
[05:48:01 -204865.598904] FAST spr round 1 (radius: 25)
[05:50:05 -183621.781759] FAST spr round 2 (radius: 25)
[05:51:51 -182883.995834] FAST spr round 3 (radius: 25)
[05:53:31 -182812.481286] FAST spr round 4 (radius: 25)
[05:55:00 -182804.849784] FAST spr round 5 (radius: 25)
[05:56:30 -182804.849784] Model parameter optimization (eps = 1.000000)
[05:56:43 -182802.431105] SLOW spr round 1 (radius: 5)
[05:58:43 -182740.622746] SLOW spr round 2 (radius: 5)
[06:00:41 -182731.895066] SLOW spr round 3 (radius: 5)
[06:02:34 -182728.431928] SLOW spr round 4 (radius: 5)
[06:04:25 -182727.868621] SLOW spr round 5 (radius: 5)
[06:06:13 -182727.868617] SLOW spr round 6 (radius: 10)
[06:08:04 -182725.614707] SLOW spr round 7 (radius: 5)
[06:10:18 -182723.690264] SLOW spr round 8 (radius: 5)
[06:12:20 -182723.690118] SLOW spr round 9 (radius: 10)
[06:14:11 -182723.690118] SLOW spr round 10 (radius: 15)
[06:16:54 -182723.690118] SLOW spr round 11 (radius: 20)
[06:21:54 -182723.690118] SLOW spr round 12 (radius: 25)
[06:28:52 -182723.690118] Model parameter optimization (eps = 0.100000)

[06:28:58] ML tree search #7, logLikelihood: -182723.666689

[06:28:58 -603161.922737] Initial branch length optimization
[06:29:02 -537472.116353] Model parameter optimization (eps = 10.000000)
[06:29:28 -533972.797589] AUTODETECT spr round 1 (radius: 5)
[06:31:22 -381201.115193] AUTODETECT spr round 2 (radius: 10)
[06:33:22 -249451.731691] AUTODETECT spr round 3 (radius: 15)
[06:35:33 -208529.298459] AUTODETECT spr round 4 (radius: 20)
[06:38:26 -202476.672886] AUTODETECT spr round 5 (radius: 25)
[06:41:48 -202170.750074] SPR radius for FAST iterations: 25 (autodetect)
[06:41:48 -202170.750074] Model parameter optimization (eps = 3.000000)
[06:42:10 -201979.881258] FAST spr round 1 (radius: 25)
[06:44:14 -183419.456819] FAST spr round 2 (radius: 25)
[06:46:01 -182849.954904] FAST spr round 3 (radius: 25)
[06:47:42 -182784.163842] FAST spr round 4 (radius: 25)
[06:49:11 -182777.909025] FAST spr round 5 (radius: 25)
[06:50:41 -182775.429034] FAST spr round 6 (radius: 25)
[06:52:09 -182770.610800] FAST spr round 7 (radius: 25)
[06:53:36 -182770.610797] Model parameter optimization (eps = 1.000000)
[06:53:43 -182770.191215] SLOW spr round 1 (radius: 5)
[06:55:41 -182731.567702] SLOW spr round 2 (radius: 5)
[06:57:32 -182730.692199] SLOW spr round 3 (radius: 5)
[06:59:21 -182730.692179] SLOW spr round 4 (radius: 10)
[07:01:08 -182726.967778] SLOW spr round 5 (radius: 5)
[07:03:20 -182726.967760] SLOW spr round 6 (radius: 10)
[07:05:14 -182726.967760] SLOW spr round 7 (radius: 15)
[07:07:52 -182726.967760] SLOW spr round 8 (radius: 20)
[07:12:35 -182726.967760] SLOW spr round 9 (radius: 25)
[07:18:53 -182726.967760] Model parameter optimization (eps = 0.100000)

[07:18:58] ML tree search #8, logLikelihood: -182726.879873

[07:18:58 -603502.332362] Initial branch length optimization
[07:19:02 -536144.303136] Model parameter optimization (eps = 10.000000)
[07:19:29 -532639.462199] AUTODETECT spr round 1 (radius: 5)
[07:21:21 -388924.869614] AUTODETECT spr round 2 (radius: 10)
[07:23:21 -255931.357673] AUTODETECT spr round 3 (radius: 15)
[07:25:34 -211912.294186] AUTODETECT spr round 4 (radius: 20)
[07:28:39 -205119.691210] AUTODETECT spr round 5 (radius: 25)
[07:32:29 -204564.336134] SPR radius for FAST iterations: 25 (autodetect)
[07:32:29 -204564.336134] Model parameter optimization (eps = 3.000000)
[07:32:53 -204326.272149] FAST spr round 1 (radius: 25)
[07:35:00 -183555.277064] FAST spr round 2 (radius: 25)
[07:36:45 -182868.128106] FAST spr round 3 (radius: 25)
[07:38:22 -182801.950257] FAST spr round 4 (radius: 25)
[07:39:55 -182792.054142] FAST spr round 5 (radius: 25)
[07:41:21 -182790.279294] FAST spr round 6 (radius: 25)
[07:42:50 -182790.279290] Model parameter optimization (eps = 1.000000)
[07:43:04 -182782.374751] SLOW spr round 1 (radius: 5)
[07:45:01 -182741.871914] SLOW spr round 2 (radius: 5)
[07:46:54 -182732.159399] SLOW spr round 3 (radius: 5)
[07:48:43 -182732.159393] SLOW spr round 4 (radius: 10)
[07:50:32 -182729.267480] SLOW spr round 5 (radius: 5)
[07:52:45 -182729.267439] SLOW spr round 6 (radius: 10)
[07:54:41 -182729.267439] SLOW spr round 7 (radius: 15)
[07:57:22 -182729.267439] SLOW spr round 8 (radius: 20)
[08:02:31 -182729.267439] SLOW spr round 9 (radius: 25)
[08:09:27 -182729.267439] Model parameter optimization (eps = 0.100000)

[08:09:35] ML tree search #9, logLikelihood: -182729.146234

[08:09:35 -605193.564799] Initial branch length optimization
[08:09:38 -538160.491404] Model parameter optimization (eps = 10.000000)
[08:10:06 -534738.564800] AUTODETECT spr round 1 (radius: 5)
[08:11:59 -389644.444425] AUTODETECT spr round 2 (radius: 10)
[08:14:02 -259872.268634] AUTODETECT spr round 3 (radius: 15)
[08:16:11 -216546.704136] AUTODETECT spr round 4 (radius: 20)
[08:19:12 -206113.223373] AUTODETECT spr round 5 (radius: 25)
[08:23:10 -205533.224142] SPR radius for FAST iterations: 25 (autodetect)
[08:23:10 -205533.224142] Model parameter optimization (eps = 3.000000)
[08:23:33 -205306.772418] FAST spr round 1 (radius: 25)
[08:25:37 -183646.083825] FAST spr round 2 (radius: 25)
[08:27:22 -182958.065031] FAST spr round 3 (radius: 25)
[08:29:02 -182883.550724] FAST spr round 4 (radius: 25)
[08:30:34 -182861.885600] FAST spr round 5 (radius: 25)
[08:32:05 -182860.017253] FAST spr round 6 (radius: 25)
[08:33:32 -182860.017250] Model parameter optimization (eps = 1.000000)
[08:33:46 -182846.680760] SLOW spr round 1 (radius: 5)
[08:35:44 -182756.366687] SLOW spr round 2 (radius: 5)
[08:37:37 -182747.612129] SLOW spr round 3 (radius: 5)
[08:39:26 -182747.612106] SLOW spr round 4 (radius: 10)
[08:41:15 -182746.071214] SLOW spr round 5 (radius: 5)
[08:43:29 -182744.258593] SLOW spr round 6 (radius: 5)
[08:45:34 -182741.831529] SLOW spr round 7 (radius: 5)
[08:47:27 -182741.831483] SLOW spr round 8 (radius: 10)
[08:49:17 -182740.118743] SLOW spr round 9 (radius: 5)
[08:51:29 -182734.893380] SLOW spr round 10 (radius: 5)
[08:53:30 -182734.025792] SLOW spr round 11 (radius: 5)
[08:55:24 -182734.025791] SLOW spr round 12 (radius: 10)
[08:57:14 -182734.025791] SLOW spr round 13 (radius: 15)
[09:00:02 -182734.025791] SLOW spr round 14 (radius: 20)
[09:05:00 -182734.025791] SLOW spr round 15 (radius: 25)
[09:11:46 -182734.025791] Model parameter optimization (eps = 0.100000)

[09:11:54] ML tree search #10, logLikelihood: -182733.311139

[09:11:54 -605692.209286] Initial branch length optimization
[09:11:58 -537853.885064] Model parameter optimization (eps = 10.000000)
[09:12:23 -534412.088578] AUTODETECT spr round 1 (radius: 5)
[09:14:23 -388872.780544] AUTODETECT spr round 2 (radius: 10)
[09:16:26 -257590.524300] AUTODETECT spr round 3 (radius: 15)
[09:18:42 -213415.924580] AUTODETECT spr round 4 (radius: 20)
[09:21:35 -207547.003291] AUTODETECT spr round 5 (radius: 25)
[09:25:23 -207259.333710] SPR radius for FAST iterations: 25 (autodetect)
[09:25:23 -207259.333710] Model parameter optimization (eps = 3.000000)
[09:25:50 -207116.795870] FAST spr round 1 (radius: 25)
[09:27:57 -184070.769569] FAST spr round 2 (radius: 25)
[09:29:45 -182921.480355] FAST spr round 3 (radius: 25)
[09:31:27 -182809.593282] FAST spr round 4 (radius: 25)
[09:32:59 -182800.010472] FAST spr round 5 (radius: 25)
[09:34:27 -182800.010445] Model parameter optimization (eps = 1.000000)
[09:34:40 -182792.288505] SLOW spr round 1 (radius: 5)
[09:36:43 -182712.705914] SLOW spr round 2 (radius: 5)
[09:38:38 -182706.610632] SLOW spr round 3 (radius: 5)
[09:40:29 -182703.602913] SLOW spr round 4 (radius: 5)
[09:42:18 -182703.602902] SLOW spr round 5 (radius: 10)
[09:44:07 -182699.537489] SLOW spr round 6 (radius: 5)
[09:46:22 -182692.236294] SLOW spr round 7 (radius: 5)
[09:48:23 -182692.236270] SLOW spr round 8 (radius: 10)
[09:50:14 -182691.759114] SLOW spr round 9 (radius: 5)
[09:52:29 -182686.209877] SLOW spr round 10 (radius: 5)
[09:54:31 -182686.209751] SLOW spr round 11 (radius: 10)
[09:56:23 -182686.209749] SLOW spr round 12 (radius: 15)
[09:59:07 -182686.209749] SLOW spr round 13 (radius: 20)
[10:05:20 -182686.209749] SLOW spr round 14 (radius: 25)
[10:11:43 -182686.209749] Model parameter optimization (eps = 0.100000)

[10:11:53] ML tree search #11, logLikelihood: -182685.897684

[10:11:53 -604287.045296] Initial branch length optimization
[10:11:57 -538079.688226] Model parameter optimization (eps = 10.000000)
[10:12:25 -534570.251217] AUTODETECT spr round 1 (radius: 5)
[10:14:18 -384414.324558] AUTODETECT spr round 2 (radius: 10)
[10:16:17 -259464.789276] AUTODETECT spr round 3 (radius: 15)
[10:18:29 -216433.300696] AUTODETECT spr round 4 (radius: 20)
[10:21:13 -205401.399902] AUTODETECT spr round 5 (radius: 25)
[10:24:37 -204622.068249] SPR radius for FAST iterations: 25 (autodetect)
[10:24:37 -204622.068249] Model parameter optimization (eps = 3.000000)
[10:25:03 -204432.416010] FAST spr round 1 (radius: 25)
[10:27:08 -183733.089401] FAST spr round 2 (radius: 25)
[10:28:53 -182922.496552] FAST spr round 3 (radius: 25)
[10:30:33 -182821.958234] FAST spr round 4 (radius: 25)
[10:32:05 -182802.057383] FAST spr round 5 (radius: 25)
[10:33:34 -182802.057356] Model parameter optimization (eps = 1.000000)
[10:33:45 -182801.013441] SLOW spr round 1 (radius: 5)
[10:35:45 -182723.765010] SLOW spr round 2 (radius: 5)
[10:37:40 -182710.803751] SLOW spr round 3 (radius: 5)
[10:39:31 -182710.317416] SLOW spr round 4 (radius: 5)
[10:41:20 -182710.317409] SLOW spr round 5 (radius: 10)
[10:43:10 -182708.457061] SLOW spr round 6 (radius: 5)
[10:45:25 -182706.916057] SLOW spr round 7 (radius: 5)
[10:47:27 -182702.420213] SLOW spr round 8 (radius: 5)
[10:49:20 -182702.420211] SLOW spr round 9 (radius: 10)
[10:51:11 -182702.420211] SLOW spr round 10 (radius: 15)
[10:54:02 -182702.420211] SLOW spr round 11 (radius: 20)
[10:58:58 -182702.420211] SLOW spr round 12 (radius: 25)
[11:05:33 -182702.420211] Model parameter optimization (eps = 0.100000)

[11:05:40] ML tree search #12, logLikelihood: -182702.346493

[11:05:40 -604579.009371] Initial branch length optimization
[11:05:45 -537145.616920] Model parameter optimization (eps = 10.000000)
[11:06:13 -533702.667842] AUTODETECT spr round 1 (radius: 5)
[11:08:08 -385345.747506] AUTODETECT spr round 2 (radius: 10)
[11:10:10 -258798.165981] AUTODETECT spr round 3 (radius: 15)
[11:12:20 -215526.977982] AUTODETECT spr round 4 (radius: 20)
[11:14:52 -203584.757822] AUTODETECT spr round 5 (radius: 25)
[11:18:21 -203312.866986] SPR radius for FAST iterations: 25 (autodetect)
[11:18:22 -203312.866986] Model parameter optimization (eps = 3.000000)
[11:18:39 -203191.549395] FAST spr round 1 (radius: 25)
[11:20:17 -183812.870607] FAST spr round 2 (radius: 25)
[11:21:48 -182884.634815] FAST spr round 3 (radius: 25)
[11:23:20 -182819.624901] FAST spr round 4 (radius: 25)
[11:24:45 -182811.763301] FAST spr round 5 (radius: 25)
[11:26:08 -182809.836895] FAST spr round 6 (radius: 25)
[11:27:29 -182809.836885] Model parameter optimization (eps = 1.000000)
[11:27:42 -182804.489629] SLOW spr round 1 (radius: 5)
[11:29:19 -182743.532490] SLOW spr round 2 (radius: 5)
[11:30:50 -182737.728219] SLOW spr round 3 (radius: 5)
[11:32:16 -182737.728195] SLOW spr round 4 (radius: 10)
[11:33:43 -182733.708559] SLOW spr round 5 (radius: 5)
[11:35:36 -182730.694230] SLOW spr round 6 (radius: 5)
[11:37:17 -182730.693688] SLOW spr round 7 (radius: 10)
[11:38:46 -182730.693683] SLOW spr round 8 (radius: 15)
[11:41:05 -182730.693683] SLOW spr round 9 (radius: 20)
[11:45:29 -182730.693683] SLOW spr round 10 (radius: 25)
[11:51:46 -182730.693683] Model parameter optimization (eps = 0.100000)

[11:51:54] ML tree search #13, logLikelihood: -182730.503752

[11:51:55 -605454.843215] Initial branch length optimization
[11:51:58 -537997.841915] Model parameter optimization (eps = 10.000000)
[11:52:28 -534475.155166] AUTODETECT spr round 1 (radius: 5)
[11:54:16 -391314.008929] AUTODETECT spr round 2 (radius: 10)
[11:56:07 -259141.826597] AUTODETECT spr round 3 (radius: 15)
[11:58:14 -213710.387384] AUTODETECT spr round 4 (radius: 20)
[12:01:07 -205325.433192] AUTODETECT spr round 5 (radius: 25)
[12:04:33 -204215.476671] SPR radius for FAST iterations: 25 (autodetect)
[12:04:33 -204215.476671] Model parameter optimization (eps = 3.000000)
[12:04:55 -204052.820539] FAST spr round 1 (radius: 25)
[12:06:52 -184217.065040] FAST spr round 2 (radius: 25)
[12:08:32 -182967.067350] FAST spr round 3 (radius: 25)
[12:10:06 -182855.126815] FAST spr round 4 (radius: 25)
[12:11:33 -182841.901049] FAST spr round 5 (radius: 25)
[12:12:58 -182836.950591] FAST spr round 6 (radius: 25)
[12:14:21 -182836.950034] Model parameter optimization (eps = 1.000000)
[12:14:35 -182829.182442] SLOW spr round 1 (radius: 5)
[12:16:30 -182738.894712] SLOW spr round 2 (radius: 5)
[12:18:16 -182709.922936] SLOW spr round 3 (radius: 5)
[12:20:02 -182708.756843] SLOW spr round 4 (radius: 5)
[12:21:46 -182708.756811] SLOW spr round 5 (radius: 10)
[12:23:28 -182704.707464] SLOW spr round 6 (radius: 5)
[12:25:38 -182700.651443] SLOW spr round 7 (radius: 5)
[12:27:33 -182699.562523] SLOW spr round 8 (radius: 5)
[12:29:22 -182699.562506] SLOW spr round 9 (radius: 10)
[12:31:06 -182699.562506] SLOW spr round 10 (radius: 15)
[12:33:51 -182699.373362] SLOW spr round 11 (radius: 5)
[12:36:02 -182699.373344] SLOW spr round 12 (radius: 10)
[12:37:57 -182699.373344] SLOW spr round 13 (radius: 15)
[12:40:36 -182699.373344] SLOW spr round 14 (radius: 20)
[12:45:53 -182699.373344] SLOW spr round 15 (radius: 25)
[12:52:40 -182699.373344] Model parameter optimization (eps = 0.100000)

[12:52:51] ML tree search #14, logLikelihood: -182698.941439

[12:52:51 -606856.027575] Initial branch length optimization
[12:52:54 -538375.174099] Model parameter optimization (eps = 10.000000)
[12:53:17 -534905.107047] AUTODETECT spr round 1 (radius: 5)
[12:55:05 -391781.774886] AUTODETECT spr round 2 (radius: 10)
[12:56:56 -254675.242568] AUTODETECT spr round 3 (radius: 15)
[12:59:08 -213532.178077] AUTODETECT spr round 4 (radius: 20)
[13:02:10 -205295.698529] AUTODETECT spr round 5 (radius: 25)
[13:06:07 -204057.815968] SPR radius for FAST iterations: 25 (autodetect)
[13:06:07 -204057.815968] Model parameter optimization (eps = 3.000000)
[13:06:28 -203817.864694] FAST spr round 1 (radius: 25)
[13:08:26 -183873.487280] FAST spr round 2 (radius: 25)
[13:10:07 -182898.952620] FAST spr round 3 (radius: 25)
[13:11:39 -182840.293240] FAST spr round 4 (radius: 25)
[13:13:06 -182830.493027] FAST spr round 5 (radius: 25)
[13:14:28 -182830.492862] Model parameter optimization (eps = 1.000000)
[13:14:46 -182823.368091] SLOW spr round 1 (radius: 5)
[13:16:42 -182755.210368] SLOW spr round 2 (radius: 5)
[13:18:32 -182739.356433] SLOW spr round 3 (radius: 5)
[13:20:17 -182739.356394] SLOW spr round 4 (radius: 10)
[13:21:59 -182739.356394] SLOW spr round 5 (radius: 15)
[13:24:42 -182739.356393] SLOW spr round 6 (radius: 20)
[13:29:35 -182739.356393] SLOW spr round 7 (radius: 25)
[13:36:16 -182739.356393] Model parameter optimization (eps = 0.100000)

[13:36:22] ML tree search #15, logLikelihood: -182739.273149

[13:36:22 -600550.355628] Initial branch length optimization
[13:36:26 -534483.761677] Model parameter optimization (eps = 10.000000)
[13:36:51 -531114.891989] AUTODETECT spr round 1 (radius: 5)
[13:38:37 -379784.548082] AUTODETECT spr round 2 (radius: 10)
[13:40:29 -250610.283665] AUTODETECT spr round 3 (radius: 15)
[13:42:39 -205065.886584] AUTODETECT spr round 4 (radius: 20)
[13:45:32 -201373.527443] AUTODETECT spr round 5 (radius: 25)
[13:49:24 -200725.209512] SPR radius for FAST iterations: 25 (autodetect)
[13:49:24 -200725.209512] Model parameter optimization (eps = 3.000000)
[13:49:48 -200497.137784] FAST spr round 1 (radius: 25)
[13:51:48 -183571.203021] FAST spr round 2 (radius: 25)
[13:53:31 -182913.070437] FAST spr round 3 (radius: 25)
[13:55:07 -182860.485622] FAST spr round 4 (radius: 25)
[13:56:35 -182844.847242] FAST spr round 5 (radius: 25)
[13:57:58 -182844.847239] Model parameter optimization (eps = 1.000000)
[13:58:14 -182840.229565] SLOW spr round 1 (radius: 5)
[14:00:11 -182798.542332] SLOW spr round 2 (radius: 5)
[14:01:59 -182793.224829] SLOW spr round 3 (radius: 5)
[14:03:44 -182793.224760] SLOW spr round 4 (radius: 10)
[14:05:27 -182770.559617] SLOW spr round 5 (radius: 5)
[14:07:38 -182757.358133] SLOW spr round 6 (radius: 5)
[14:09:33 -182757.358041] SLOW spr round 7 (radius: 10)
[14:11:18 -182755.246537] SLOW spr round 8 (radius: 5)
[14:13:24 -182754.069504] SLOW spr round 9 (radius: 5)
[14:15:19 -182754.068929] SLOW spr round 10 (radius: 10)
[14:17:04 -182753.392271] SLOW spr round 11 (radius: 5)
[14:19:12 -182748.254590] SLOW spr round 12 (radius: 5)
[14:21:07 -182748.254573] SLOW spr round 13 (radius: 10)
[14:22:52 -182748.254573] SLOW spr round 14 (radius: 15)
[14:25:35 -182748.254573] SLOW spr round 15 (radius: 20)
[14:30:36 -182748.254573] SLOW spr round 16 (radius: 25)
[14:37:05 -182748.254573] Model parameter optimization (eps = 0.100000)

[14:37:12] ML tree search #16, logLikelihood: -182748.195342

[14:37:12 -605944.331728] Initial branch length optimization
[14:37:16 -537793.718777] Model parameter optimization (eps = 10.000000)
[14:37:44 -534316.568720] AUTODETECT spr round 1 (radius: 5)
[14:39:33 -393065.743284] AUTODETECT spr round 2 (radius: 10)
[14:41:30 -251737.444742] AUTODETECT spr round 3 (radius: 15)
[14:43:37 -210820.253552] AUTODETECT spr round 4 (radius: 20)
[14:46:53 -204611.266439] AUTODETECT spr round 5 (radius: 25)
[14:50:48 -203408.855261] SPR radius for FAST iterations: 25 (autodetect)
[14:50:48 -203408.855261] Model parameter optimization (eps = 3.000000)
[14:51:17 -203207.472201] FAST spr round 1 (radius: 25)
[14:53:18 -183444.641743] FAST spr round 2 (radius: 25)
[14:54:56 -182947.592301] FAST spr round 3 (radius: 25)
[14:56:31 -182867.921404] FAST spr round 4 (radius: 25)
[14:57:56 -182864.594732] FAST spr round 5 (radius: 25)
[14:59:20 -182857.238907] FAST spr round 6 (radius: 25)
[15:00:43 -182857.238870] Model parameter optimization (eps = 1.000000)
[15:00:54 -182855.259454] SLOW spr round 1 (radius: 5)
[15:02:47 -182753.481806] SLOW spr round 2 (radius: 5)
[15:04:37 -182745.488905] SLOW spr round 3 (radius: 5)
[15:06:22 -182744.515654] SLOW spr round 4 (radius: 5)
[15:08:05 -182744.515653] SLOW spr round 5 (radius: 10)
[15:09:50 -182741.069589] SLOW spr round 6 (radius: 5)
[15:11:59 -182738.052609] SLOW spr round 7 (radius: 5)
[15:13:54 -182738.052598] SLOW spr round 8 (radius: 10)
[15:15:40 -182738.052598] SLOW spr round 9 (radius: 15)
[15:18:16 -182738.052598] SLOW spr round 10 (radius: 20)
[15:22:55 -182738.052598] SLOW spr round 11 (radius: 25)
[15:29:22 -182738.052598] Model parameter optimization (eps = 0.100000)

[15:29:32] ML tree search #17, logLikelihood: -182736.044193

[15:29:32 -605109.373850] Initial branch length optimization
[15:29:36 -537493.749993] Model parameter optimization (eps = 10.000000)
[15:30:05 -534041.438529] AUTODETECT spr round 1 (radius: 5)
[15:31:48 -381500.685552] AUTODETECT spr round 2 (radius: 10)
[15:33:34 -262982.103766] AUTODETECT spr round 3 (radius: 15)
[15:35:38 -215061.883049] AUTODETECT spr round 4 (radius: 20)
[15:38:18 -208298.322345] AUTODETECT spr round 5 (radius: 25)
[15:41:53 -207174.860513] SPR radius for FAST iterations: 25 (autodetect)
[15:41:53 -207174.860513] Model parameter optimization (eps = 3.000000)
[15:42:17 -206980.243389] FAST spr round 1 (radius: 25)
[15:44:14 -183854.704122] FAST spr round 2 (radius: 25)
[15:45:56 -182858.236652] FAST spr round 3 (radius: 25)
[15:47:29 -182810.524383] FAST spr round 4 (radius: 25)
[15:48:57 -182802.449923] FAST spr round 5 (radius: 25)
[15:50:20 -182802.173315] FAST spr round 6 (radius: 25)
[15:51:41 -182802.173313] Model parameter optimization (eps = 1.000000)
[15:51:55 -182794.103153] SLOW spr round 1 (radius: 5)
[15:53:48 -182729.980692] SLOW spr round 2 (radius: 5)
[15:55:36 -182715.332598] SLOW spr round 3 (radius: 5)
[15:57:21 -182715.241052] SLOW spr round 4 (radius: 10)
[15:59:04 -182713.930655] SLOW spr round 5 (radius: 5)
[16:01:12 -182710.752265] SLOW spr round 6 (radius: 5)
[16:03:06 -182710.752259] SLOW spr round 7 (radius: 10)
[16:04:50 -182710.752259] SLOW spr round 8 (radius: 15)
[16:07:36 -182710.752259] SLOW spr round 9 (radius: 20)
[16:12:34 -182710.752259] SLOW spr round 10 (radius: 25)
[16:19:01 -182710.752259] Model parameter optimization (eps = 0.100000)

[16:19:10] ML tree search #18, logLikelihood: -182710.477875

[16:19:10 -603287.112646] Initial branch length optimization
[16:19:14 -536314.264932] Model parameter optimization (eps = 10.000000)
[16:19:41 -532925.088582] AUTODETECT spr round 1 (radius: 5)
[16:21:30 -391119.639779] AUTODETECT spr round 2 (radius: 10)
[16:23:21 -255475.398753] AUTODETECT spr round 3 (radius: 15)
[16:25:25 -210642.807750] AUTODETECT spr round 4 (radius: 20)
[16:28:16 -203429.820515] AUTODETECT spr round 5 (radius: 25)
[16:31:41 -203099.146617] SPR radius for FAST iterations: 25 (autodetect)
[16:31:41 -203099.146617] Model parameter optimization (eps = 3.000000)
[16:32:08 -202926.403209] FAST spr round 1 (radius: 25)
[16:34:10 -183560.585159] FAST spr round 2 (radius: 25)
[16:35:50 -182872.936916] FAST spr round 3 (radius: 25)
[16:37:23 -182841.697643] FAST spr round 4 (radius: 25)
[16:38:48 -182840.717581] FAST spr round 5 (radius: 25)
[16:40:12 -182840.717483] Model parameter optimization (eps = 1.000000)
[16:40:28 -182835.384459] SLOW spr round 1 (radius: 5)
[16:42:20 -182769.192983] SLOW spr round 2 (radius: 5)
[16:44:08 -182754.595466] SLOW spr round 3 (radius: 5)
[16:45:53 -182752.261642] SLOW spr round 4 (radius: 5)
[16:47:37 -182750.829309] SLOW spr round 5 (radius: 5)
[16:49:20 -182750.829306] SLOW spr round 6 (radius: 10)
[16:51:03 -182748.652864] SLOW spr round 7 (radius: 5)
[16:53:10 -182747.551290] SLOW spr round 8 (radius: 5)
[16:55:04 -182747.550714] SLOW spr round 9 (radius: 10)
[16:56:49 -182747.550714] SLOW spr round 10 (radius: 15)
[16:59:27 -182747.550714] SLOW spr round 11 (radius: 20)
[17:04:09 -182747.550714] SLOW spr round 12 (radius: 25)
[17:10:25 -182747.550714] Model parameter optimization (eps = 0.100000)

[17:10:30] ML tree search #19, logLikelihood: -182747.524404

[17:10:30 -603718.321789] Initial branch length optimization
[17:10:34 -536606.032544] Model parameter optimization (eps = 10.000000)
[17:11:02 -533142.525710] AUTODETECT spr round 1 (radius: 5)
[17:12:50 -384614.975722] AUTODETECT spr round 2 (radius: 10)
[17:14:42 -259381.421339] AUTODETECT spr round 3 (radius: 15)
[17:16:42 -213333.478006] AUTODETECT spr round 4 (radius: 20)
[17:19:19 -205487.344741] AUTODETECT spr round 5 (radius: 25)
[17:22:42 -203203.759549] SPR radius for FAST iterations: 25 (autodetect)
[17:22:42 -203203.759549] Model parameter optimization (eps = 3.000000)
[17:23:10 -203008.788879] FAST spr round 1 (radius: 25)
[17:25:11 -184247.022024] FAST spr round 2 (radius: 25)
[17:26:51 -182878.694450] FAST spr round 3 (radius: 25)
[17:28:25 -182819.395000] FAST spr round 4 (radius: 25)
[17:29:50 -182819.394960] Model parameter optimization (eps = 1.000000)
[17:30:06 -182811.263169] SLOW spr round 1 (radius: 5)
[17:32:02 -182765.425677] SLOW spr round 2 (radius: 5)
[17:33:53 -182758.336374] SLOW spr round 3 (radius: 5)
[17:35:39 -182758.336233] SLOW spr round 4 (radius: 10)
[17:37:25 -182741.811831] SLOW spr round 5 (radius: 5)
[17:39:37 -182729.038976] SLOW spr round 6 (radius: 5)
[17:41:34 -182727.061494] SLOW spr round 7 (radius: 5)
[17:43:23 -182727.061397] SLOW spr round 8 (radius: 10)
[17:45:09 -182727.061396] SLOW spr round 9 (radius: 15)
[17:47:52 -182727.061396] SLOW spr round 10 (radius: 20)
[17:52:51 -182727.061396] SLOW spr round 11 (radius: 25)
[17:59:32 -182727.061396] Model parameter optimization (eps = 0.100000)

[17:59:44] ML tree search #20, logLikelihood: -182725.441768


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.237783,0.299575) (0.182595,0.432595) (0.414127,1.291738) (0.165495,1.902368) 
   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: -182683.366174

AIC score: 369376.732347 / AICc score: 8413436.732347 / BIC score: 378179.164884
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=596).
         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/P04259/3_mltree/P04259.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/3_mltree/P04259.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/3_mltree/P04259.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P04259/3_mltree/P04259.raxml.log

Analysis started: 01-Jul-2021 04:06:30 / finished: 01-Jul-2021 22:06:14

Elapsed time: 64784.505 seconds

Consumed energy: 5808.223 Wh (= 29 km in an electric car, or 145 km with an e-scooter!)