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 03-Jul-2021 15:20:14 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/2_msa/Q9Y4B5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/3_mltree/Q9Y4B5 --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/Q9Y4B5/2_msa/Q9Y4B5_trimmed_msa.fasta
[00:00:00] Loaded alignment with 391 taxa and 477 sites

WARNING: Sequences tr_A0A2I2YSN5_A0A2I2YSN5_GORGO_9595 and tr_H2P1U2_H2P1U2_PONAB_9601 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_H2PKA5_H2PKA5_PONAB_9601 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_H2QTQ1_H2QTQ1_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and sp_Q5TF21_SOGA3_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_F7BRJ0_F7BRJ0_MACMU_9544 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_A0A2R8ND74_A0A2R8ND74_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_A0A0D9RV41_A0A0D9RV41_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_A0A2K5MW80_A0A2K5MW80_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_A0A2K6BUY0_A0A2K6BUY0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G3QCT0_G3QCT0_GORGO_9595 and tr_A0A2K5ZK89_A0A2K5ZK89_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A0R3P1D2_A0A0R3P1D2_DROPS_46245 and tr_B4GKZ6_B4GKZ6_DROPE_7234 are exactly identical!
WARNING: Sequences tr_G1M7Z7_G1M7Z7_AILME_9646 and tr_A0A2U3X3M5_A0A2U3X3M5_ODORO_9708 are exactly identical!
WARNING: Sequences tr_A0A096N862_A0A096N862_PAPAN_9555 and tr_A0A2K5N297_A0A2K5N297_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A096NX06_A0A096NX06_PAPAN_9555 and tr_A0A0D9RC62_A0A0D9RC62_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A096NX06_A0A096NX06_PAPAN_9555 and tr_A0A2K5LZJ8_A0A2K5LZJ8_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A091UTC6_A0A091UTC6_NIPNI_128390 and tr_A0A087R6F9_A0A087R6F9_APTFO_9233 are exactly identical!
WARNING: Sequences tr_A0A091UTC6_A0A091UTC6_NIPNI_128390 and tr_A0A0A0A5F4_A0A0A0A5F4_CHAVO_50402 are exactly identical!
WARNING: Sequences tr_A0A2I0MV44_A0A2I0MV44_COLLI_8932 and tr_A0A1V4JMX0_A0A1V4JMX0_PATFA_372326 are exactly identical!
WARNING: Sequences tr_A0A0V1CKX9_A0A0V1CKX9_TRIBR_45882 and tr_A0A0V1PEI7_A0A0V1PEI7_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V0XBV8_A0A0V0XBV8_9BILA_92179 and tr_A0A0V1L1I0_A0A0V1L1I0_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A226NGX0_A0A226NGX0_CALSU_9009 and tr_A0A226P1I7_A0A226P1I7_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2D0RQT6_A0A2D0RQT6_ICTPU_7998 and tr_A0A2D0RQU7_A0A2D0RQU7_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0T900_A0A2D0T900_ICTPU_7998 and tr_A0A2D0T9L0_A0A2D0T9L0_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 23

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/Q9Y4B5/3_mltree/Q9Y4B5.raxml.reduced.phy

Alignment comprises 1 partitions and 477 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 477 / 477
Gaps: 15.22 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/3_mltree/Q9Y4B5.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 391 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 69 / 5520
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -233054.197215] Initial branch length optimization
[00:00:00 -177244.478810] Model parameter optimization (eps = 10.000000)
[00:00:19 -176647.320450] AUTODETECT spr round 1 (radius: 5)
[00:00:35 -109615.009258] AUTODETECT spr round 2 (radius: 10)
[00:00:55 -84727.415469] AUTODETECT spr round 3 (radius: 15)
[00:01:19 -66759.077756] AUTODETECT spr round 4 (radius: 20)
[00:01:44 -63757.847170] AUTODETECT spr round 5 (radius: 25)
[00:02:16 -63656.799238] SPR radius for FAST iterations: 25 (autodetect)
[00:02:16 -63656.799238] Model parameter optimization (eps = 3.000000)
[00:02:34 -63294.418916] FAST spr round 1 (radius: 25)
[00:02:58 -55140.544000] FAST spr round 2 (radius: 25)
[00:03:17 -54966.001945] FAST spr round 3 (radius: 25)
[00:03:33 -54946.913258] FAST spr round 4 (radius: 25)
[00:03:48 -54945.676454] FAST spr round 5 (radius: 25)
[00:04:02 -54945.652162] Model parameter optimization (eps = 1.000000)
[00:04:11 -54933.465063] SLOW spr round 1 (radius: 5)
[00:04:32 -54924.578696] SLOW spr round 2 (radius: 5)
[00:04:52 -54924.576118] SLOW spr round 3 (radius: 10)
[00:05:13 -54922.770667] SLOW spr round 4 (radius: 5)
[00:05:41 -54921.623046] SLOW spr round 5 (radius: 5)
[00:06:05 -54921.621566] SLOW spr round 6 (radius: 10)
[00:06:28 -54921.621422] SLOW spr round 7 (radius: 15)
[00:07:03 -54921.621345] SLOW spr round 8 (radius: 20)
[00:07:55 -54919.755166] SLOW spr round 9 (radius: 5)
[00:08:26 -54918.434318] SLOW spr round 10 (radius: 5)
[00:08:52 -54918.433319] SLOW spr round 11 (radius: 10)
[00:09:15 -54918.433172] SLOW spr round 12 (radius: 15)
[00:09:52 -54918.433110] SLOW spr round 13 (radius: 20)
[00:10:48 -54918.433060] SLOW spr round 14 (radius: 25)
[00:11:46 -54918.433006] Model parameter optimization (eps = 0.100000)

[00:11:51] ML tree search #1, logLikelihood: -54917.621814

[00:11:51 -235193.406120] Initial branch length optimization
[00:11:52 -177103.718801] Model parameter optimization (eps = 10.000000)
[00:12:08 -176527.649110] AUTODETECT spr round 1 (radius: 5)
[00:12:24 -113313.259579] AUTODETECT spr round 2 (radius: 10)
[00:12:42 -85770.099602] AUTODETECT spr round 3 (radius: 15)
[00:13:05 -70358.825239] AUTODETECT spr round 4 (radius: 20)
[00:13:31 -66203.951308] AUTODETECT spr round 5 (radius: 25)
[00:14:00 -64867.245311] SPR radius for FAST iterations: 25 (autodetect)
[00:14:00 -64867.245311] Model parameter optimization (eps = 3.000000)
[00:14:23 -64475.887564] FAST spr round 1 (radius: 25)
[00:14:46 -55445.807999] FAST spr round 2 (radius: 25)
[00:15:06 -55039.531834] FAST spr round 3 (radius: 25)
[00:15:24 -54967.159719] FAST spr round 4 (radius: 25)
[00:15:39 -54966.941632] FAST spr round 5 (radius: 25)
[00:15:52 -54966.425335] FAST spr round 6 (radius: 25)
[00:16:06 -54966.424279] Model parameter optimization (eps = 1.000000)
[00:16:17 -54944.369995] SLOW spr round 1 (radius: 5)
[00:16:39 -54931.678530] SLOW spr round 2 (radius: 5)
[00:16:59 -54931.661534] SLOW spr round 3 (radius: 10)
[00:17:21 -54928.223487] SLOW spr round 4 (radius: 5)
[00:17:49 -54924.727055] SLOW spr round 5 (radius: 5)
[00:18:13 -54924.726928] SLOW spr round 6 (radius: 10)
[00:18:35 -54924.726872] SLOW spr round 7 (radius: 15)
[00:19:11 -54924.726820] SLOW spr round 8 (radius: 20)
[00:20:06 -54922.656114] SLOW spr round 9 (radius: 5)
[00:20:36 -54922.653893] SLOW spr round 10 (radius: 10)
[00:21:04 -54922.653472] SLOW spr round 11 (radius: 15)
[00:21:40 -54922.653357] SLOW spr round 12 (radius: 20)
[00:22:36 -54922.653296] SLOW spr round 13 (radius: 25)
[00:23:34 -54922.653238] Model parameter optimization (eps = 0.100000)

[00:23:39] ML tree search #2, logLikelihood: -54921.896316

[00:23:39 -229477.911420] Initial branch length optimization
[00:23:39 -175007.828859] Model parameter optimization (eps = 10.000000)
[00:23:58 -174546.916542] AUTODETECT spr round 1 (radius: 5)
[00:24:13 -117679.388911] AUTODETECT spr round 2 (radius: 10)
[00:24:32 -87264.896685] AUTODETECT spr round 3 (radius: 15)
[00:24:55 -68036.232050] AUTODETECT spr round 4 (radius: 20)
[00:25:26 -63667.277060] AUTODETECT spr round 5 (radius: 25)
[00:25:57 -63625.963504] SPR radius for FAST iterations: 25 (autodetect)
[00:25:57 -63625.963504] Model parameter optimization (eps = 3.000000)
[00:26:08 -63244.744890] FAST spr round 1 (radius: 25)
[00:26:28 -55453.325395] FAST spr round 2 (radius: 25)
[00:26:45 -55094.497091] FAST spr round 3 (radius: 25)
[00:27:01 -55043.143246] FAST spr round 4 (radius: 25)
[00:27:17 -55038.870603] FAST spr round 5 (radius: 25)
[00:27:31 -55036.269373] FAST spr round 6 (radius: 25)
[00:27:45 -55036.269232] Model parameter optimization (eps = 1.000000)
[00:28:00 -54961.157093] SLOW spr round 1 (radius: 5)
[00:28:21 -54930.958696] SLOW spr round 2 (radius: 5)
[00:28:43 -54923.707364] SLOW spr round 3 (radius: 5)
[00:29:04 -54917.306196] SLOW spr round 4 (radius: 5)
[00:29:24 -54917.303961] SLOW spr round 5 (radius: 10)
[00:29:47 -54912.392205] SLOW spr round 6 (radius: 5)
[00:30:15 -54911.694158] SLOW spr round 7 (radius: 5)
[00:30:38 -54911.692571] SLOW spr round 8 (radius: 10)
[00:31:01 -54911.692404] SLOW spr round 9 (radius: 15)
[00:31:41 -54911.692341] SLOW spr round 10 (radius: 20)
[00:32:39 -54911.692288] SLOW spr round 11 (radius: 25)
[00:33:38 -54911.692243] Model parameter optimization (eps = 0.100000)

[00:33:45] ML tree search #3, logLikelihood: -54910.563276

[00:33:45 -231703.939457] Initial branch length optimization
[00:33:45 -175592.214403] Model parameter optimization (eps = 10.000000)
[00:34:02 -175204.739143] AUTODETECT spr round 1 (radius: 5)
[00:34:17 -115741.757204] AUTODETECT spr round 2 (radius: 10)
[00:34:35 -89575.115603] AUTODETECT spr round 3 (radius: 15)
[00:34:56 -72357.642833] AUTODETECT spr round 4 (radius: 20)
[00:35:20 -65301.080264] AUTODETECT spr round 5 (radius: 25)
[00:35:47 -62549.437068] SPR radius for FAST iterations: 25 (autodetect)
[00:35:47 -62549.437068] Model parameter optimization (eps = 3.000000)
[00:35:57 -62226.883561] FAST spr round 1 (radius: 25)
[00:36:18 -55288.858581] FAST spr round 2 (radius: 25)
[00:36:36 -55128.039279] FAST spr round 3 (radius: 25)
[00:36:52 -55051.556161] FAST spr round 4 (radius: 25)
[00:37:08 -55047.526117] FAST spr round 5 (radius: 25)
[00:37:22 -55046.536580] FAST spr round 6 (radius: 25)
[00:37:36 -55046.536529] Model parameter optimization (eps = 1.000000)
[00:37:45 -55028.505287] SLOW spr round 1 (radius: 5)
[00:38:06 -55008.197145] SLOW spr round 2 (radius: 5)
[00:38:26 -55008.194092] SLOW spr round 3 (radius: 10)
[00:38:48 -55007.320241] SLOW spr round 4 (radius: 5)
[00:39:15 -55007.319488] SLOW spr round 5 (radius: 10)
[00:39:40 -55007.319053] SLOW spr round 6 (radius: 15)
[00:40:15 -55007.318784] SLOW spr round 7 (radius: 20)
[00:41:09 -55007.318608] SLOW spr round 8 (radius: 25)
[00:42:08 -55007.318481] Model parameter optimization (eps = 0.100000)

[00:42:13] ML tree search #4, logLikelihood: -55007.093237

[00:42:13 -233962.080099] Initial branch length optimization
[00:42:13 -176396.067801] Model parameter optimization (eps = 10.000000)
[00:42:34 -175934.989124] AUTODETECT spr round 1 (radius: 5)
[00:42:49 -114934.073109] AUTODETECT spr round 2 (radius: 10)
[00:43:08 -80212.294815] AUTODETECT spr round 3 (radius: 15)
[00:43:30 -68805.727803] AUTODETECT spr round 4 (radius: 20)
[00:44:00 -63862.377186] AUTODETECT spr round 5 (radius: 25)
[00:44:31 -63402.171476] SPR radius for FAST iterations: 25 (autodetect)
[00:44:31 -63402.171476] Model parameter optimization (eps = 3.000000)
[00:44:41 -63087.264473] FAST spr round 1 (radius: 25)
[00:45:03 -55305.196511] FAST spr round 2 (radius: 25)
[00:45:22 -55071.375638] FAST spr round 3 (radius: 25)
[00:45:38 -55053.093737] FAST spr round 4 (radius: 25)
[00:45:53 -55048.464781] FAST spr round 5 (radius: 25)
[00:46:07 -55048.463235] Model parameter optimization (eps = 1.000000)
[00:46:15 -55026.608077] SLOW spr round 1 (radius: 5)
[00:46:36 -55010.272003] SLOW spr round 2 (radius: 5)
[00:46:57 -55010.093254] SLOW spr round 3 (radius: 5)
[00:47:18 -55010.093069] SLOW spr round 4 (radius: 10)
[00:47:41 -55005.304943] SLOW spr round 5 (radius: 5)
[00:48:11 -55005.265185] SLOW spr round 6 (radius: 10)
[00:48:37 -55005.264952] SLOW spr round 7 (radius: 15)
[00:49:13 -55004.481979] SLOW spr round 8 (radius: 5)
[00:49:43 -55004.440066] SLOW spr round 9 (radius: 10)
[00:50:11 -55004.439817] SLOW spr round 10 (radius: 15)
[00:50:47 -55004.439661] SLOW spr round 11 (radius: 20)
[00:51:44 -55004.439558] SLOW spr round 12 (radius: 25)
[00:52:42 -55004.439495] Model parameter optimization (eps = 0.100000)

[00:52:48] ML tree search #5, logLikelihood: -55003.055422

[00:52:48 -234854.512270] Initial branch length optimization
[00:52:48 -177480.640338] Model parameter optimization (eps = 10.000000)
[00:53:07 -177063.603661] AUTODETECT spr round 1 (radius: 5)
[00:53:24 -116935.767398] AUTODETECT spr round 2 (radius: 10)
[00:53:44 -87611.919533] AUTODETECT spr round 3 (radius: 15)
[00:54:08 -74306.374360] AUTODETECT spr round 4 (radius: 20)
[00:54:37 -65047.313915] AUTODETECT spr round 5 (radius: 25)
[00:55:06 -64971.735811] SPR radius for FAST iterations: 25 (autodetect)
[00:55:06 -64971.735811] Model parameter optimization (eps = 3.000000)
[00:55:23 -64638.819006] FAST spr round 1 (radius: 25)
[00:55:45 -55844.499758] FAST spr round 2 (radius: 25)
[00:56:05 -55057.093086] FAST spr round 3 (radius: 25)
[00:56:22 -55046.006593] FAST spr round 4 (radius: 25)
[00:56:38 -55042.618638] FAST spr round 5 (radius: 25)
[00:56:53 -55042.606498] Model parameter optimization (eps = 1.000000)
[00:57:03 -55022.137582] SLOW spr round 1 (radius: 5)
[00:57:25 -55011.607492] SLOW spr round 2 (radius: 5)
[00:57:47 -55011.002158] SLOW spr round 3 (radius: 5)
[00:58:08 -55010.999100] SLOW spr round 4 (radius: 10)
[00:58:31 -55009.349044] SLOW spr round 5 (radius: 5)
[00:58:59 -55007.954189] SLOW spr round 6 (radius: 5)
[00:59:23 -55007.953666] SLOW spr round 7 (radius: 10)
[00:59:45 -55007.953302] SLOW spr round 8 (radius: 15)
[01:00:19 -55006.501594] SLOW spr round 9 (radius: 5)
[01:00:48 -55006.501221] SLOW spr round 10 (radius: 10)
[01:01:15 -55006.501060] SLOW spr round 11 (radius: 15)
[01:01:51 -55006.500939] SLOW spr round 12 (radius: 20)
[01:02:48 -55006.500836] SLOW spr round 13 (radius: 25)
[01:03:48 -55006.500744] Model parameter optimization (eps = 0.100000)

[01:03:53] ML tree search #6, logLikelihood: -55004.317628

[01:03:53 -233633.892447] Initial branch length optimization
[01:03:54 -177050.006418] Model parameter optimization (eps = 10.000000)
[01:04:11 -176657.870285] AUTODETECT spr round 1 (radius: 5)
[01:04:28 -115480.174229] AUTODETECT spr round 2 (radius: 10)
[01:04:47 -86246.897607] AUTODETECT spr round 3 (radius: 15)
[01:05:09 -69805.904201] AUTODETECT spr round 4 (radius: 20)
[01:05:33 -64531.379001] AUTODETECT spr round 5 (radius: 25)
[01:06:02 -62597.245598] SPR radius for FAST iterations: 25 (autodetect)
[01:06:02 -62597.245598] Model parameter optimization (eps = 3.000000)
[01:06:23 -62202.278476] FAST spr round 1 (radius: 25)
[01:06:46 -55298.302296] FAST spr round 2 (radius: 25)
[01:07:05 -54988.356611] FAST spr round 3 (radius: 25)
[01:07:22 -54957.089601] FAST spr round 4 (radius: 25)
[01:07:37 -54956.847562] FAST spr round 5 (radius: 25)
[01:07:52 -54956.844953] Model parameter optimization (eps = 1.000000)
[01:08:03 -54938.086612] SLOW spr round 1 (radius: 5)
[01:08:25 -54915.963112] SLOW spr round 2 (radius: 5)
[01:08:47 -54915.962226] SLOW spr round 3 (radius: 10)
[01:09:10 -54915.962142] SLOW spr round 4 (radius: 15)
[01:09:48 -54915.962089] SLOW spr round 5 (radius: 20)
[01:10:47 -54915.859907] SLOW spr round 6 (radius: 5)
[01:11:18 -54915.853499] SLOW spr round 7 (radius: 10)
[01:11:49 -54915.088749] SLOW spr round 8 (radius: 5)
[01:12:17 -54913.814426] SLOW spr round 9 (radius: 5)
[01:12:41 -54913.814172] SLOW spr round 10 (radius: 10)
[01:13:05 -54913.814104] SLOW spr round 11 (radius: 15)
[01:13:43 -54913.814051] SLOW spr round 12 (radius: 20)
[01:14:41 -54913.814000] SLOW spr round 13 (radius: 25)
[01:15:39 -54913.813950] Model parameter optimization (eps = 0.100000)

[01:15:45] ML tree search #7, logLikelihood: -54913.187505

[01:15:45 -229064.841980] Initial branch length optimization
[01:15:46 -172140.387654] Model parameter optimization (eps = 10.000000)
[01:16:05 -171741.403506] AUTODETECT spr round 1 (radius: 5)
[01:16:21 -123411.173380] AUTODETECT spr round 2 (radius: 10)
[01:16:41 -91996.246029] AUTODETECT spr round 3 (radius: 15)
[01:17:04 -80891.355629] AUTODETECT spr round 4 (radius: 20)
[01:17:32 -65585.574587] AUTODETECT spr round 5 (radius: 25)
[01:18:04 -64351.845030] SPR radius for FAST iterations: 25 (autodetect)
[01:18:04 -64351.845030] Model parameter optimization (eps = 3.000000)
[01:18:16 -64059.448686] FAST spr round 1 (radius: 25)
[01:18:37 -55324.742669] FAST spr round 2 (radius: 25)
[01:18:56 -55057.493741] FAST spr round 3 (radius: 25)
[01:19:13 -55046.484005] FAST spr round 4 (radius: 25)
[01:19:28 -55046.480392] Model parameter optimization (eps = 1.000000)
[01:19:38 -55016.812971] SLOW spr round 1 (radius: 5)
[01:20:00 -55003.622756] SLOW spr round 2 (radius: 5)
[01:20:22 -55002.368915] SLOW spr round 3 (radius: 5)
[01:20:43 -55002.342071] SLOW spr round 4 (radius: 10)
[01:21:05 -54999.954061] SLOW spr round 5 (radius: 5)
[01:21:34 -54999.953628] SLOW spr round 6 (radius: 10)
[01:22:00 -54999.953551] SLOW spr round 7 (radius: 15)
[01:22:37 -54999.953497] SLOW spr round 8 (radius: 20)
[01:23:32 -54999.953448] SLOW spr round 9 (radius: 25)
[01:24:31 -54999.953402] Model parameter optimization (eps = 0.100000)

[01:24:37] ML tree search #8, logLikelihood: -54998.860531

[01:24:37 -230802.390935] Initial branch length optimization
[01:24:38 -175759.908170] Model parameter optimization (eps = 10.000000)
[01:25:02 -175295.289041] AUTODETECT spr round 1 (radius: 5)
[01:25:18 -112181.990160] AUTODETECT spr round 2 (radius: 10)
[01:25:38 -82533.044490] AUTODETECT spr round 3 (radius: 15)
[01:26:03 -68374.587618] AUTODETECT spr round 4 (radius: 20)
[01:26:28 -67326.796711] AUTODETECT spr round 5 (radius: 25)
[01:26:59 -67178.636261] SPR radius for FAST iterations: 25 (autodetect)
[01:26:59 -67178.636261] Model parameter optimization (eps = 3.000000)
[01:27:13 -66817.142386] FAST spr round 1 (radius: 25)
[01:27:38 -55270.951203] FAST spr round 2 (radius: 25)
[01:27:55 -55039.677807] FAST spr round 3 (radius: 25)
[01:28:11 -55028.658820] FAST spr round 4 (radius: 25)
[01:28:25 -55028.093453] FAST spr round 5 (radius: 25)
[01:28:39 -55028.091968] Model parameter optimization (eps = 1.000000)
[01:28:46 -55014.338077] SLOW spr round 1 (radius: 5)
[01:29:08 -55003.458951] SLOW spr round 2 (radius: 5)
[01:29:29 -54996.463640] SLOW spr round 3 (radius: 5)
[01:29:50 -54995.914770] SLOW spr round 4 (radius: 5)
[01:30:10 -54995.914754] SLOW spr round 5 (radius: 10)
[01:30:32 -54995.451446] SLOW spr round 6 (radius: 5)
[01:31:01 -54995.440155] SLOW spr round 7 (radius: 10)
[01:31:27 -54995.439471] SLOW spr round 8 (radius: 15)
[01:32:05 -54995.439109] SLOW spr round 9 (radius: 20)
[01:33:03 -54995.438867] SLOW spr round 10 (radius: 25)
[01:34:05 -54995.438702] Model parameter optimization (eps = 0.100000)

[01:34:12] ML tree search #9, logLikelihood: -54994.502702

[01:34:12 -230564.670496] Initial branch length optimization
[01:34:12 -174070.250300] Model parameter optimization (eps = 10.000000)
[01:34:30 -173582.569283] AUTODETECT spr round 1 (radius: 5)
[01:34:46 -113899.926833] AUTODETECT spr round 2 (radius: 10)
[01:35:06 -81217.742548] AUTODETECT spr round 3 (radius: 15)
[01:35:28 -70142.089458] AUTODETECT spr round 4 (radius: 20)
[01:35:53 -65152.001780] AUTODETECT spr round 5 (radius: 25)
[01:36:24 -64132.830376] SPR radius for FAST iterations: 25 (autodetect)
[01:36:24 -64132.830376] Model parameter optimization (eps = 3.000000)
[01:36:42 -63655.485594] FAST spr round 1 (radius: 25)
[01:37:08 -55449.351408] FAST spr round 2 (radius: 25)
[01:37:28 -54985.216845] FAST spr round 3 (radius: 25)
[01:37:47 -54949.858553] FAST spr round 4 (radius: 25)
[01:38:02 -54949.856724] Model parameter optimization (eps = 1.000000)
[01:38:12 -54939.569813] SLOW spr round 1 (radius: 5)
[01:38:35 -54930.735502] SLOW spr round 2 (radius: 5)
[01:38:57 -54930.606639] SLOW spr round 3 (radius: 5)
[01:39:19 -54930.605249] SLOW spr round 4 (radius: 10)
[01:39:42 -54928.805285] SLOW spr round 5 (radius: 5)
[01:40:11 -54928.002128] SLOW spr round 6 (radius: 5)
[01:40:35 -54928.001972] SLOW spr round 7 (radius: 10)
[01:40:58 -54926.214921] SLOW spr round 8 (radius: 5)
[01:41:25 -54926.196991] SLOW spr round 9 (radius: 10)
[01:41:49 -54923.366472] SLOW spr round 10 (radius: 5)
[01:42:16 -54923.365980] SLOW spr round 11 (radius: 10)
[01:42:40 -54921.871324] SLOW spr round 12 (radius: 5)
[01:43:08 -54921.870554] SLOW spr round 13 (radius: 10)
[01:43:33 -54921.870323] SLOW spr round 14 (radius: 15)
[01:44:11 -54921.870149] SLOW spr round 15 (radius: 20)
[01:45:07 -54921.870004] SLOW spr round 16 (radius: 25)
[01:46:08 -54921.869889] Model parameter optimization (eps = 0.100000)

[01:46:14] ML tree search #10, logLikelihood: -54921.066115

[01:46:14 -233780.375742] Initial branch length optimization
[01:46:15 -177645.992397] Model parameter optimization (eps = 10.000000)
[01:46:34 -177187.411177] AUTODETECT spr round 1 (radius: 5)
[01:46:50 -115046.308329] AUTODETECT spr round 2 (radius: 10)
[01:47:09 -86099.794918] AUTODETECT spr round 3 (radius: 15)
[01:47:33 -74134.898244] AUTODETECT spr round 4 (radius: 20)
[01:48:01 -69442.975238] AUTODETECT spr round 5 (radius: 25)
[01:48:32 -65655.531557] SPR radius for FAST iterations: 25 (autodetect)
[01:48:32 -65655.531557] Model parameter optimization (eps = 3.000000)
[01:48:47 -65322.929904] FAST spr round 1 (radius: 25)
[01:49:10 -55944.305446] FAST spr round 2 (radius: 25)
[01:49:29 -55069.099864] FAST spr round 3 (radius: 25)
[01:49:46 -55048.200670] FAST spr round 4 (radius: 25)
[01:50:01 -55047.549925] FAST spr round 5 (radius: 25)
[01:50:16 -55047.549774] Model parameter optimization (eps = 1.000000)
[01:50:24 -55028.422445] SLOW spr round 1 (radius: 5)
[01:50:46 -55010.441131] SLOW spr round 2 (radius: 5)
[01:51:08 -55005.769057] SLOW spr round 3 (radius: 5)
[01:51:29 -55005.767901] SLOW spr round 4 (radius: 10)
[01:51:52 -55001.506362] SLOW spr round 5 (radius: 5)
[01:52:21 -55001.504870] SLOW spr round 6 (radius: 10)
[01:52:47 -55001.504427] SLOW spr round 7 (radius: 15)
[01:53:24 -55001.504117] SLOW spr round 8 (radius: 20)
[01:54:19 -55001.503873] SLOW spr round 9 (radius: 25)
[01:55:19 -55001.503666] Model parameter optimization (eps = 0.100000)

[01:55:25] ML tree search #11, logLikelihood: -55000.436810

[01:55:25 -231441.278706] Initial branch length optimization
[01:55:26 -176466.421827] Model parameter optimization (eps = 10.000000)
[01:55:58 -176034.962224] AUTODETECT spr round 1 (radius: 5)
[01:56:15 -115878.725913] AUTODETECT spr round 2 (radius: 10)
[01:56:35 -83818.333187] AUTODETECT spr round 3 (radius: 15)
[01:57:00 -66347.129532] AUTODETECT spr round 4 (radius: 20)
[01:57:29 -63868.426173] AUTODETECT spr round 5 (radius: 25)
[01:58:10 -63700.312319] SPR radius for FAST iterations: 25 (autodetect)
[01:58:10 -63700.312319] Model parameter optimization (eps = 3.000000)
[01:58:33 -63276.137260] FAST spr round 1 (radius: 25)
[01:59:00 -55285.748659] FAST spr round 2 (radius: 25)
[01:59:23 -54985.332284] FAST spr round 3 (radius: 25)
[01:59:42 -54975.760574] FAST spr round 4 (radius: 25)
[02:00:00 -54964.764109] FAST spr round 5 (radius: 25)
[02:00:17 -54951.020579] FAST spr round 6 (radius: 25)
[02:00:33 -54951.020234] Model parameter optimization (eps = 1.000000)
[02:00:46 -54933.166038] SLOW spr round 1 (radius: 5)
[02:01:09 -54919.127817] SLOW spr round 2 (radius: 5)
[02:01:30 -54919.125624] SLOW spr round 3 (radius: 10)
[02:01:52 -54918.607853] SLOW spr round 4 (radius: 5)
[02:02:21 -54918.607601] SLOW spr round 5 (radius: 10)
[02:02:47 -54918.607122] SLOW spr round 6 (radius: 15)
[02:03:26 -54916.974073] SLOW spr round 7 (radius: 5)
[02:03:57 -54916.790498] SLOW spr round 8 (radius: 5)
[02:04:24 -54916.789503] SLOW spr round 9 (radius: 10)
[02:04:48 -54916.789463] SLOW spr round 10 (radius: 15)
[02:05:28 -54916.789460] SLOW spr round 11 (radius: 20)
[02:06:28 -54916.789453] SLOW spr round 12 (radius: 25)
[02:07:29 -54916.789452] Model parameter optimization (eps = 0.100000)

[02:07:32] ML tree search #12, logLikelihood: -54916.741488

[02:07:32 -235238.086912] Initial branch length optimization
[02:07:33 -177806.081170] Model parameter optimization (eps = 10.000000)
[02:07:52 -177453.311392] AUTODETECT spr round 1 (radius: 5)
[02:08:09 -114027.045114] AUTODETECT spr round 2 (radius: 10)
[02:08:28 -87744.058911] AUTODETECT spr round 3 (radius: 15)
[02:08:51 -73613.571956] AUTODETECT spr round 4 (radius: 20)
[02:09:21 -65789.036508] AUTODETECT spr round 5 (radius: 25)
[02:09:53 -65302.900143] SPR radius for FAST iterations: 25 (autodetect)
[02:09:53 -65302.900143] Model parameter optimization (eps = 3.000000)
[02:10:04 -64951.834994] FAST spr round 1 (radius: 25)
[02:10:25 -55642.015311] FAST spr round 2 (radius: 25)
[02:10:43 -55087.019491] FAST spr round 3 (radius: 25)
[02:11:01 -55035.202509] FAST spr round 4 (radius: 25)
[02:11:17 -55032.994342] FAST spr round 5 (radius: 25)
[02:11:32 -55032.992885] Model parameter optimization (eps = 1.000000)
[02:11:43 -54957.028473] SLOW spr round 1 (radius: 5)
[02:12:05 -54931.266196] SLOW spr round 2 (radius: 5)
[02:12:28 -54927.983410] SLOW spr round 3 (radius: 5)
[02:12:49 -54927.981594] SLOW spr round 4 (radius: 10)
[02:13:11 -54926.320416] SLOW spr round 5 (radius: 5)
[02:13:40 -54926.316772] SLOW spr round 6 (radius: 10)
[02:14:06 -54926.316506] SLOW spr round 7 (radius: 15)
[02:14:43 -54925.718530] SLOW spr round 8 (radius: 5)
[02:15:14 -54924.304143] SLOW spr round 9 (radius: 5)
[02:15:40 -54924.304127] SLOW spr round 10 (radius: 10)
[02:16:04 -54924.304125] SLOW spr round 11 (radius: 15)
[02:16:42 -54924.304123] SLOW spr round 12 (radius: 20)
[02:17:39 -54924.304122] SLOW spr round 13 (radius: 25)
[02:18:37 -54920.835053] SLOW spr round 14 (radius: 5)
[02:19:09 -54920.829706] SLOW spr round 15 (radius: 10)
[02:19:38 -54920.829483] SLOW spr round 16 (radius: 15)
[02:20:16 -54918.675442] SLOW spr round 17 (radius: 5)
[02:20:47 -54918.675272] SLOW spr round 18 (radius: 10)
[02:21:16 -54918.675196] SLOW spr round 19 (radius: 15)
[02:21:53 -54918.675146] SLOW spr round 20 (radius: 20)
[02:22:52 -54918.675112] SLOW spr round 21 (radius: 25)
[02:23:50 -54918.675082] Model parameter optimization (eps = 0.100000)

[02:24:00] ML tree search #13, logLikelihood: -54915.789274

[02:24:00 -232464.663548] Initial branch length optimization
[02:24:01 -177108.044070] Model parameter optimization (eps = 10.000000)
[02:24:22 -176588.159778] AUTODETECT spr round 1 (radius: 5)
[02:24:38 -117556.375435] AUTODETECT spr round 2 (radius: 10)
[02:24:56 -88427.652626] AUTODETECT spr round 3 (radius: 15)
[02:25:18 -68596.812188] AUTODETECT spr round 4 (radius: 20)
[02:25:44 -64244.673800] AUTODETECT spr round 5 (radius: 25)
[02:26:14 -64240.736820] SPR radius for FAST iterations: 25 (autodetect)
[02:26:14 -64240.736820] Model parameter optimization (eps = 3.000000)
[02:26:31 -63871.070820] FAST spr round 1 (radius: 25)
[02:26:54 -55279.706826] FAST spr round 2 (radius: 25)
[02:27:14 -55022.991908] FAST spr round 3 (radius: 25)
[02:27:31 -54997.551229] FAST spr round 4 (radius: 25)
[02:27:46 -54997.515247] Model parameter optimization (eps = 1.000000)
[02:27:58 -54951.492167] SLOW spr round 1 (radius: 5)
[02:28:20 -54926.337931] SLOW spr round 2 (radius: 5)
[02:28:42 -54926.336035] SLOW spr round 3 (radius: 10)
[02:29:05 -54925.808942] SLOW spr round 4 (radius: 5)
[02:29:33 -54925.807936] SLOW spr round 5 (radius: 10)
[02:30:00 -54925.807292] SLOW spr round 6 (radius: 15)
[02:30:39 -54923.694117] SLOW spr round 7 (radius: 5)
[02:31:10 -54923.693729] SLOW spr round 8 (radius: 10)
[02:31:38 -54923.693473] SLOW spr round 9 (radius: 15)
[02:32:17 -54923.693282] SLOW spr round 10 (radius: 20)
[02:33:17 -54923.693133] SLOW spr round 11 (radius: 25)
[02:34:17 -54923.693007] Model parameter optimization (eps = 0.100000)

[02:34:25] ML tree search #14, logLikelihood: -54921.126289

[02:34:26 -231316.488675] Initial branch length optimization
[02:34:26 -176376.953216] Model parameter optimization (eps = 10.000000)
[02:34:44 -175868.380925] AUTODETECT spr round 1 (radius: 5)
[02:35:01 -116039.288631] AUTODETECT spr round 2 (radius: 10)
[02:35:21 -85759.000959] AUTODETECT spr round 3 (radius: 15)
[02:35:45 -75470.196187] AUTODETECT spr round 4 (radius: 20)
[02:36:13 -64888.544517] AUTODETECT spr round 5 (radius: 25)
[02:36:41 -63300.168694] SPR radius for FAST iterations: 25 (autodetect)
[02:36:41 -63300.168694] Model parameter optimization (eps = 3.000000)
[02:36:59 -62831.518686] FAST spr round 1 (radius: 25)
[02:37:21 -55403.786815] FAST spr round 2 (radius: 25)
[02:37:40 -55004.774676] FAST spr round 3 (radius: 25)
[02:37:58 -54985.044642] FAST spr round 4 (radius: 25)
[02:38:14 -54985.042568] Model parameter optimization (eps = 1.000000)
[02:38:25 -54974.816968] SLOW spr round 1 (radius: 5)
[02:38:47 -54953.361644] SLOW spr round 2 (radius: 5)
[02:39:08 -54953.361240] SLOW spr round 3 (radius: 10)
[02:39:29 -54947.786902] SLOW spr round 4 (radius: 5)
[02:39:58 -54922.183590] SLOW spr round 5 (radius: 5)
[02:40:21 -54922.182995] SLOW spr round 6 (radius: 10)
[02:40:44 -54922.182942] SLOW spr round 7 (radius: 15)
[02:41:25 -54922.182888] SLOW spr round 8 (radius: 20)
[02:42:24 -54922.182835] SLOW spr round 9 (radius: 25)
[02:43:22 -54922.182777] Model parameter optimization (eps = 0.100000)

[02:43:29] ML tree search #15, logLikelihood: -54921.371091

[02:43:29 -235737.151403] Initial branch length optimization
[02:43:30 -178944.350458] Model parameter optimization (eps = 10.000000)
[02:43:48 -178440.447524] AUTODETECT spr round 1 (radius: 5)
[02:44:04 -117827.722448] AUTODETECT spr round 2 (radius: 10)
[02:44:24 -83645.232478] AUTODETECT spr round 3 (radius: 15)
[02:44:46 -70468.683831] AUTODETECT spr round 4 (radius: 20)
[02:45:12 -64657.193816] AUTODETECT spr round 5 (radius: 25)
[02:45:41 -64622.805450] SPR radius for FAST iterations: 25 (autodetect)
[02:45:41 -64622.805450] Model parameter optimization (eps = 3.000000)
[02:46:00 -64177.500150] FAST spr round 1 (radius: 25)
[02:46:24 -56105.101285] FAST spr round 2 (radius: 25)
[02:46:43 -55456.357519] FAST spr round 3 (radius: 25)
[02:47:00 -55012.027032] FAST spr round 4 (radius: 25)
[02:47:17 -54977.888201] FAST spr round 5 (radius: 25)
[02:47:32 -54977.118915] FAST spr round 6 (radius: 25)
[02:47:47 -54977.118594] Model parameter optimization (eps = 1.000000)
[02:47:58 -54943.327773] SLOW spr round 1 (radius: 5)
[02:48:20 -54930.089682] SLOW spr round 2 (radius: 5)
[02:48:41 -54930.089389] SLOW spr round 3 (radius: 10)
[02:49:04 -54929.981498] SLOW spr round 4 (radius: 5)
[02:49:33 -54929.981420] SLOW spr round 5 (radius: 10)
[02:50:00 -54929.981360] SLOW spr round 6 (radius: 15)
[02:50:38 -54929.981302] SLOW spr round 7 (radius: 20)
[02:51:34 -54929.981243] SLOW spr round 8 (radius: 25)
[02:52:32 -54929.981179] Model parameter optimization (eps = 0.100000)

[02:52:38] ML tree search #16, logLikelihood: -54929.551422

[02:52:38 -232179.347007] Initial branch length optimization
[02:52:39 -175510.536885] Model parameter optimization (eps = 10.000000)
[02:53:00 -174982.720245] AUTODETECT spr round 1 (radius: 5)
[02:53:16 -109059.243607] AUTODETECT spr round 2 (radius: 10)
[02:53:35 -86409.160297] AUTODETECT spr round 3 (radius: 15)
[02:53:58 -72236.064898] AUTODETECT spr round 4 (radius: 20)
[02:54:23 -70280.586603] AUTODETECT spr round 5 (radius: 25)
[02:54:56 -69927.859679] SPR radius for FAST iterations: 25 (autodetect)
[02:54:56 -69927.859679] Model parameter optimization (eps = 3.000000)
[02:55:08 -69587.133190] FAST spr round 1 (radius: 25)
[02:55:30 -55824.869102] FAST spr round 2 (radius: 25)
[02:55:49 -55094.577443] FAST spr round 3 (radius: 25)
[02:56:05 -55050.406732] FAST spr round 4 (radius: 25)
[02:56:20 -55050.404654] Model parameter optimization (eps = 1.000000)
[02:56:31 -55023.337063] SLOW spr round 1 (radius: 5)
[02:56:53 -55000.816279] SLOW spr round 2 (radius: 5)
[02:57:14 -55000.339316] SLOW spr round 3 (radius: 5)
[02:57:35 -55000.214660] SLOW spr round 4 (radius: 5)
[02:57:56 -54999.008160] SLOW spr round 5 (radius: 5)
[02:58:17 -54998.606664] SLOW spr round 6 (radius: 5)
[02:58:37 -54998.363783] SLOW spr round 7 (radius: 5)
[02:58:58 -54998.363718] SLOW spr round 8 (radius: 10)
[02:59:20 -54998.363660] SLOW spr round 9 (radius: 15)
[02:59:58 -54998.363605] SLOW spr round 10 (radius: 20)
[03:00:53 -54998.363545] SLOW spr round 11 (radius: 25)
[03:01:51 -54998.363493] Model parameter optimization (eps = 0.100000)

[03:01:57] ML tree search #17, logLikelihood: -54996.757022

[03:01:57 -232550.889248] Initial branch length optimization
[03:01:58 -176977.745903] Model parameter optimization (eps = 10.000000)
[03:02:16 -176500.859595] AUTODETECT spr round 1 (radius: 5)
[03:02:32 -112433.035466] AUTODETECT spr round 2 (radius: 10)
[03:02:51 -87077.805105] AUTODETECT spr round 3 (radius: 15)
[03:03:15 -73811.797586] AUTODETECT spr round 4 (radius: 20)
[03:03:43 -66292.716901] AUTODETECT spr round 5 (radius: 25)
[03:04:17 -66109.805194] SPR radius for FAST iterations: 25 (autodetect)
[03:04:17 -66109.805194] Model parameter optimization (eps = 3.000000)
[03:04:34 -65778.353325] FAST spr round 1 (radius: 25)
[03:04:54 -55442.458037] FAST spr round 2 (radius: 25)
[03:05:13 -55086.663094] FAST spr round 3 (radius: 25)
[03:05:30 -55051.598519] FAST spr round 4 (radius: 25)
[03:05:45 -55044.440711] FAST spr round 5 (radius: 25)
[03:06:00 -55044.439333] Model parameter optimization (eps = 1.000000)
[03:06:10 -55015.894273] SLOW spr round 1 (radius: 5)
[03:06:31 -55001.483644] SLOW spr round 2 (radius: 5)
[03:06:50 -55001.481375] SLOW spr round 3 (radius: 10)
[03:07:11 -55001.204983] SLOW spr round 4 (radius: 5)
[03:07:38 -55001.204068] SLOW spr round 5 (radius: 10)
[03:08:02 -55001.203487] SLOW spr round 6 (radius: 15)
[03:08:37 -55001.203106] SLOW spr round 7 (radius: 20)
[03:09:31 -55001.202853] SLOW spr round 8 (radius: 25)
[03:10:29 -55001.202678] Model parameter optimization (eps = 0.100000)

[03:10:33] ML tree search #18, logLikelihood: -55001.051453

[03:10:33 -230978.865489] Initial branch length optimization
[03:10:33 -176955.293070] Model parameter optimization (eps = 10.000000)
[03:10:53 -176498.647394] AUTODETECT spr round 1 (radius: 5)
[03:11:09 -109109.839896] AUTODETECT spr round 2 (radius: 10)
[03:11:28 -83180.135897] AUTODETECT spr round 3 (radius: 15)
[03:11:52 -71090.037792] AUTODETECT spr round 4 (radius: 20)
[03:12:20 -65262.827504] AUTODETECT spr round 5 (radius: 25)
[03:12:53 -64606.325008] SPR radius for FAST iterations: 25 (autodetect)
[03:12:53 -64606.325008] Model parameter optimization (eps = 3.000000)
[03:13:09 -64261.830335] FAST spr round 1 (radius: 25)
[03:13:33 -55514.551327] FAST spr round 2 (radius: 25)
[03:13:52 -55108.039814] FAST spr round 3 (radius: 25)
[03:14:08 -55048.834572] FAST spr round 4 (radius: 25)
[03:14:24 -55048.731284] FAST spr round 5 (radius: 25)
[03:14:39 -55048.730874] Model parameter optimization (eps = 1.000000)
[03:14:51 -54968.609364] SLOW spr round 1 (radius: 5)
[03:15:13 -54940.871709] SLOW spr round 2 (radius: 5)
[03:15:35 -54938.804768] SLOW spr round 3 (radius: 5)
[03:15:56 -54938.802800] SLOW spr round 4 (radius: 10)
[03:16:18 -54937.917390] SLOW spr round 5 (radius: 5)
[03:16:47 -54934.889074] SLOW spr round 6 (radius: 5)
[03:17:12 -54934.888579] SLOW spr round 7 (radius: 10)
[03:17:36 -54934.888229] SLOW spr round 8 (radius: 15)
[03:18:14 -54934.887973] SLOW spr round 9 (radius: 20)
[03:19:09 -54934.887780] SLOW spr round 10 (radius: 25)
[03:20:07 -54932.765334] SLOW spr round 11 (radius: 5)
[03:20:39 -54932.760220] SLOW spr round 12 (radius: 10)
[03:21:09 -54931.301571] SLOW spr round 13 (radius: 5)
[03:21:37 -54931.300999] SLOW spr round 14 (radius: 10)
[03:22:02 -54931.300801] SLOW spr round 15 (radius: 15)
[03:22:39 -54929.146938] SLOW spr round 16 (radius: 5)
[03:23:07 -54929.146748] SLOW spr round 17 (radius: 10)
[03:23:34 -54929.146634] SLOW spr round 18 (radius: 15)
[03:24:09 -54929.146537] SLOW spr round 19 (radius: 20)
[03:25:03 -54929.146452] SLOW spr round 20 (radius: 25)
[03:26:00 -54929.146367] Model parameter optimization (eps = 0.100000)

[03:26:06] ML tree search #19, logLikelihood: -54928.463595

[03:26:06 -235592.416419] Initial branch length optimization
[03:26:07 -176700.270853] Model parameter optimization (eps = 10.000000)
[03:26:26 -176229.961285] AUTODETECT spr round 1 (radius: 5)
[03:26:42 -121265.875557] AUTODETECT spr round 2 (radius: 10)
[03:27:01 -86366.915895] AUTODETECT spr round 3 (radius: 15)
[03:27:24 -66124.486404] AUTODETECT spr round 4 (radius: 20)
[03:27:54 -64413.395813] AUTODETECT spr round 5 (radius: 25)
[03:28:28 -64314.430444] SPR radius for FAST iterations: 25 (autodetect)
[03:28:28 -64314.430444] Model parameter optimization (eps = 3.000000)
[03:28:47 -63867.990117] FAST spr round 1 (radius: 25)
[03:29:11 -55487.227222] FAST spr round 2 (radius: 25)
[03:29:30 -54993.383124] FAST spr round 3 (radius: 25)
[03:29:47 -54958.352904] FAST spr round 4 (radius: 25)
[03:30:03 -54956.556203] FAST spr round 5 (radius: 25)
[03:30:18 -54956.554976] Model parameter optimization (eps = 1.000000)
[03:30:27 -54942.276546] SLOW spr round 1 (radius: 5)
[03:30:49 -54924.991072] SLOW spr round 2 (radius: 5)
[03:31:10 -54924.988398] SLOW spr round 3 (radius: 10)
[03:31:33 -54924.987681] SLOW spr round 4 (radius: 15)
[03:32:12 -54924.987215] SLOW spr round 5 (radius: 20)
[03:33:13 -54924.986866] SLOW spr round 6 (radius: 25)
[03:34:13 -54924.986591] Model parameter optimization (eps = 0.100000)

[03:34:19] ML tree search #20, logLikelihood: -54924.784594


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.150143,0.669357) (0.100139,2.321360) (0.489642,0.591249) (0.260076,1.451657) 
   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: -54910.563276

AIC score: 111391.126552 / AICc score: 1345411.126552 / BIC score: 114662.626997
Free parameters (model + branch lengths): 785

WARNING: Number of free parameters (K=785) is larger than alignment size (n=477).
         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/Q9Y4B5/3_mltree/Q9Y4B5.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/3_mltree/Q9Y4B5.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/3_mltree/Q9Y4B5.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9Y4B5/3_mltree/Q9Y4B5.raxml.log

Analysis started: 03-Jul-2021 15:20:14 / finished: 03-Jul-2021 18:54:34

Elapsed time: 12859.480 seconds

Consumed energy: 1201.408 Wh (= 6 km in an electric car, or 30 km with an e-scooter!)