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 6140 CPU @ 2.30GHz, 36 cores, 251 GB RAM

RAxML-NG was called at 10-Jul-2021 05:21:41 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/2_msa/Q9BX59_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59 --seed 2 --threads 1 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), NONE/sequential

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/2_msa/Q9BX59_trimmed_msa.fasta
[00:00:00] Loaded alignment with 167 taxa and 65 sites

WARNING: Sequences tr_G3QPR2_G3QPR2_GORGO_9595 and tr_H2Q5A3_H2Q5A3_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QPR2_G3QPR2_GORGO_9595 and sp_Q9BX59_TPSNR_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G3QPR2_G3QPR2_GORGO_9595 and tr_A0A2R9BZX7_A0A2R9BZX7_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G3QUP3_G3QUP3_GORGO_9595 and tr_H2QST3_H2QST3_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QUP3_G3QUP3_GORGO_9595 and tr_A0A2R8ZML1_A0A2R8ZML1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2NG80_H2NG80_PONAB_9601 and sp_Q5R8H1_TPSNR_PONAB_9601 are exactly identical!
WARNING: Sequences tr_A0A1B8Y2A3_A0A1B8Y2A3_XENTR_8364 and tr_A0A1B8Y2N3_A0A1B8Y2N3_XENTR_8364 are exactly identical!
WARNING: Sequences tr_A0A1B8Y432_A0A1B8Y432_XENTR_8364 and tr_F7C0S8_F7C0S8_XENTR_8364 are exactly identical!
WARNING: Sequences tr_A0A096MZU0_A0A096MZU0_PAPAN_9555 and tr_A0A0D9RDY8_A0A0D9RDY8_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A096MZU0_A0A096MZU0_PAPAN_9555 and tr_A0A2K5P6R9_A0A2K5P6R9_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A096MZU0_A0A096MZU0_PAPAN_9555 and tr_A0A2K6AUG4_A0A2K6AUG4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A096MZU0_A0A096MZU0_PAPAN_9555 and tr_A0A2K5Y4G2_A0A2K5Y4G2_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A151MD09_A0A151MD09_ALLMI_8496 and tr_A0A1U8DB99_A0A1U8DB99_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_A0A226MCL6_A0A226MCL6_CALSU_9009 and tr_A0A226P3Y3_A0A226P3Y3_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2D0REQ1_A0A2D0REQ1_ICTPU_7998 and tr_A0A2D0RGK1_A0A2D0RGK1_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 15

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.reduced.phy

Alignment comprises 1 partitions and 65 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 65 / 65
Gaps: 5.27 %
Invariant sites: 4.62 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 1 thread(s)

Parallel reduction/worker buffer size: 1 KB  / 0 KB

[00:00:00] Generating 20 random starting tree(s) with 167 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 65 / 5200
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -19875.768738] Initial branch length optimization
[00:00:00 -16029.767653] Model parameter optimization (eps = 10.000000)
[00:00:03 -15976.537259] AUTODETECT spr round 1 (radius: 5)
[00:00:06 -12677.867654] AUTODETECT spr round 2 (radius: 10)
[00:00:11 -10621.085195] AUTODETECT spr round 3 (radius: 15)
[00:00:15 -9830.680307] AUTODETECT spr round 4 (radius: 20)
[00:00:20 -8579.418491] AUTODETECT spr round 5 (radius: 25)
[00:00:26 -8448.212302] SPR radius for FAST iterations: 25 (autodetect)
[00:00:26 -8448.212302] Model parameter optimization (eps = 3.000000)
[00:00:29 -8428.085872] FAST spr round 1 (radius: 25)
[00:00:33 -7709.146774] FAST spr round 2 (radius: 25)
[00:00:37 -7654.777105] FAST spr round 3 (radius: 25)
[00:00:41 -7646.609787] FAST spr round 4 (radius: 25)
[00:00:44 -7645.215989] FAST spr round 5 (radius: 25)
[00:00:47 -7645.026449] FAST spr round 6 (radius: 25)
[00:00:50 -7645.024046] Model parameter optimization (eps = 1.000000)
[00:00:52 -7643.941556] SLOW spr round 1 (radius: 5)
[00:00:58 -7638.653703] SLOW spr round 2 (radius: 5)
[00:01:04 -7637.547396] SLOW spr round 3 (radius: 5)
[00:01:09 -7637.547297] SLOW spr round 4 (radius: 10)
[00:01:15 -7636.892774] SLOW spr round 5 (radius: 5)
[00:01:23 -7634.948210] SLOW spr round 6 (radius: 5)
[00:01:30 -7634.947314] SLOW spr round 7 (radius: 10)
[00:01:36 -7634.947282] SLOW spr round 8 (radius: 15)
[00:01:46 -7634.947280] SLOW spr round 9 (radius: 20)
[00:01:56 -7634.947280] SLOW spr round 10 (radius: 25)
[00:02:02 -7634.947280] Model parameter optimization (eps = 0.100000)

[00:02:04] ML tree search #1, logLikelihood: -7634.718582

[00:02:04 -19891.690257] Initial branch length optimization
[00:02:04 -16207.394823] Model parameter optimization (eps = 10.000000)
[00:02:07 -16168.310348] AUTODETECT spr round 1 (radius: 5)
[00:02:10 -12324.108231] AUTODETECT spr round 2 (radius: 10)
[00:02:15 -10120.691811] AUTODETECT spr round 3 (radius: 15)
[00:02:21 -8753.625808] AUTODETECT spr round 4 (radius: 20)
[00:02:26 -8703.226121] AUTODETECT spr round 5 (radius: 25)
[00:02:32 -8701.304567] SPR radius for FAST iterations: 25 (autodetect)
[00:02:32 -8701.304567] Model parameter optimization (eps = 3.000000)
[00:02:34 -8679.502939] FAST spr round 1 (radius: 25)
[00:02:39 -7702.555721] FAST spr round 2 (radius: 25)
[00:02:43 -7664.119523] FAST spr round 3 (radius: 25)
[00:02:46 -7661.768085] FAST spr round 4 (radius: 25)
[00:02:49 -7661.767441] Model parameter optimization (eps = 1.000000)
[00:02:52 -7657.928884] SLOW spr round 1 (radius: 5)
[00:02:58 -7657.256350] SLOW spr round 2 (radius: 5)
[00:03:04 -7657.102350] SLOW spr round 3 (radius: 5)
[00:03:10 -7657.102219] SLOW spr round 4 (radius: 10)
[00:03:15 -7656.693110] SLOW spr round 5 (radius: 5)
[00:03:23 -7656.075176] SLOW spr round 6 (radius: 5)
[00:03:30 -7655.156242] SLOW spr round 7 (radius: 5)
[00:03:36 -7655.072140] SLOW spr round 8 (radius: 10)
[00:03:42 -7655.071889] SLOW spr round 9 (radius: 15)
[00:03:50 -7655.071878] SLOW spr round 10 (radius: 20)
[00:04:00 -7654.646470] SLOW spr round 11 (radius: 5)
[00:04:08 -7654.645091] SLOW spr round 12 (radius: 10)
[00:04:15 -7654.645033] SLOW spr round 13 (radius: 15)
[00:04:23 -7654.645031] SLOW spr round 14 (radius: 20)
[00:04:32 -7654.645031] SLOW spr round 15 (radius: 25)
[00:04:42 -7650.050282] SLOW spr round 16 (radius: 5)
[00:04:50 -7648.525111] SLOW spr round 17 (radius: 5)
[00:04:57 -7648.519878] SLOW spr round 18 (radius: 10)
[00:05:03 -7648.519396] SLOW spr round 19 (radius: 15)
[00:05:12 -7647.812150] SLOW spr round 20 (radius: 5)
[00:05:20 -7641.851107] SLOW spr round 21 (radius: 5)
[00:05:27 -7639.251143] SLOW spr round 22 (radius: 5)
[00:05:33 -7639.250572] SLOW spr round 23 (radius: 10)
[00:05:39 -7639.250556] SLOW spr round 24 (radius: 15)
[00:05:47 -7639.250555] SLOW spr round 25 (radius: 20)
[00:05:56 -7639.250555] SLOW spr round 26 (radius: 25)
[00:06:06 -7639.250555] Model parameter optimization (eps = 0.100000)

[00:06:07] ML tree search #2, logLikelihood: -7638.950062

[00:06:07 -19505.861508] Initial branch length optimization
[00:06:07 -15834.078166] Model parameter optimization (eps = 10.000000)
[00:06:10 -15804.695816] AUTODETECT spr round 1 (radius: 5)
[00:06:13 -11986.317394] AUTODETECT spr round 2 (radius: 10)
[00:06:18 -9225.028406] AUTODETECT spr round 3 (radius: 15)
[00:06:24 -8585.924621] AUTODETECT spr round 4 (radius: 20)
[00:06:29 -8567.538504] AUTODETECT spr round 5 (radius: 25)
[00:06:35 -8566.093838] SPR radius for FAST iterations: 25 (autodetect)
[00:06:35 -8566.093838] Model parameter optimization (eps = 3.000000)
[00:06:37 -8537.143397] FAST spr round 1 (radius: 25)
[00:06:42 -7735.513992] FAST spr round 2 (radius: 25)
[00:06:46 -7669.224178] FAST spr round 3 (radius: 25)
[00:06:50 -7663.259170] FAST spr round 4 (radius: 25)
[00:06:53 -7662.984797] FAST spr round 5 (radius: 25)
[00:06:56 -7659.817785] FAST spr round 6 (radius: 25)
[00:06:59 -7659.816451] Model parameter optimization (eps = 1.000000)
[00:07:00 -7659.428728] SLOW spr round 1 (radius: 5)
[00:07:07 -7658.377463] SLOW spr round 2 (radius: 5)
[00:07:12 -7658.377280] SLOW spr round 3 (radius: 10)
[00:07:18 -7655.323920] SLOW spr round 4 (radius: 5)
[00:07:26 -7642.907304] SLOW spr round 5 (radius: 5)
[00:07:33 -7642.906180] SLOW spr round 6 (radius: 10)
[00:07:38 -7642.161665] SLOW spr round 7 (radius: 5)
[00:07:46 -7642.161531] SLOW spr round 8 (radius: 10)
[00:07:52 -7642.161527] SLOW spr round 9 (radius: 15)
[00:08:01 -7642.161527] SLOW spr round 10 (radius: 20)
[00:08:11 -7639.710896] SLOW spr round 11 (radius: 5)
[00:08:19 -7639.660370] SLOW spr round 12 (radius: 10)
[00:08:26 -7639.136098] SLOW spr round 13 (radius: 5)
[00:08:33 -7639.135346] SLOW spr round 14 (radius: 10)
[00:08:39 -7639.135325] SLOW spr round 15 (radius: 15)
[00:08:48 -7639.135324] SLOW spr round 16 (radius: 20)
[00:08:58 -7639.135324] SLOW spr round 17 (radius: 25)
[00:09:06 -7639.135324] Model parameter optimization (eps = 0.100000)

[00:09:08] ML tree search #3, logLikelihood: -7639.015422

[00:09:08 -19674.000162] Initial branch length optimization
[00:09:08 -16252.825649] Model parameter optimization (eps = 10.000000)
[00:09:12 -16220.886128] AUTODETECT spr round 1 (radius: 5)
[00:09:15 -12216.186397] AUTODETECT spr round 2 (radius: 10)
[00:09:20 -9310.375636] AUTODETECT spr round 3 (radius: 15)
[00:09:26 -8453.398185] AUTODETECT spr round 4 (radius: 20)
[00:09:33 -8436.787735] AUTODETECT spr round 5 (radius: 25)
[00:09:36 -8436.774469] SPR radius for FAST iterations: 20 (autodetect)
[00:09:36 -8436.774469] Model parameter optimization (eps = 3.000000)
[00:09:39 -8415.724334] FAST spr round 1 (radius: 20)
[00:09:44 -7701.368122] FAST spr round 2 (radius: 20)
[00:09:48 -7644.017638] FAST spr round 3 (radius: 20)
[00:09:52 -7637.621254] FAST spr round 4 (radius: 20)
[00:09:55 -7637.617869] Model parameter optimization (eps = 1.000000)
[00:09:56 -7636.108682] SLOW spr round 1 (radius: 5)
[00:10:02 -7635.087145] SLOW spr round 2 (radius: 5)
[00:10:08 -7635.086556] SLOW spr round 3 (radius: 10)
[00:10:14 -7635.086263] SLOW spr round 4 (radius: 15)
[00:10:24 -7635.086111] SLOW spr round 5 (radius: 20)
[00:10:34 -7635.086031] SLOW spr round 6 (radius: 25)
[00:10:40 -7635.085989] Model parameter optimization (eps = 0.100000)

[00:10:40] ML tree search #4, logLikelihood: -7635.081778

[00:10:40 -20216.443834] Initial branch length optimization
[00:10:41 -16469.267780] Model parameter optimization (eps = 10.000000)
[00:10:44 -16425.439566] AUTODETECT spr round 1 (radius: 5)
[00:10:47 -12100.609929] AUTODETECT spr round 2 (radius: 10)
[00:10:52 -9708.147565] AUTODETECT spr round 3 (radius: 15)
[00:10:59 -8580.823510] AUTODETECT spr round 4 (radius: 20)
[00:11:04 -8571.040390] AUTODETECT spr round 5 (radius: 25)
[00:11:10 -8561.956594] SPR radius for FAST iterations: 25 (autodetect)
[00:11:10 -8561.956594] Model parameter optimization (eps = 3.000000)
[00:11:14 -8535.469436] FAST spr round 1 (radius: 25)
[00:11:18 -7713.514122] FAST spr round 2 (radius: 25)
[00:11:22 -7666.946301] FAST spr round 3 (radius: 25)
[00:11:26 -7662.305074] FAST spr round 4 (radius: 25)
[00:11:29 -7661.647694] FAST spr round 5 (radius: 25)
[00:11:32 -7660.555877] FAST spr round 6 (radius: 25)
[00:11:35 -7657.348717] FAST spr round 7 (radius: 25)
[00:11:38 -7657.348582] Model parameter optimization (eps = 1.000000)
[00:11:40 -7655.511409] SLOW spr round 1 (radius: 5)
[00:11:47 -7648.770880] SLOW spr round 2 (radius: 5)
[00:11:53 -7648.770777] SLOW spr round 3 (radius: 10)
[00:11:58 -7646.493735] SLOW spr round 4 (radius: 5)
[00:12:06 -7646.432646] SLOW spr round 5 (radius: 10)
[00:12:12 -7646.430856] SLOW spr round 6 (radius: 15)
[00:12:20 -7646.429890] SLOW spr round 7 (radius: 20)
[00:12:28 -7646.429386] SLOW spr round 8 (radius: 25)
[00:12:36 -7645.483330] SLOW spr round 9 (radius: 5)
[00:12:45 -7645.481449] SLOW spr round 10 (radius: 10)
[00:12:51 -7645.018613] SLOW spr round 11 (radius: 5)
[00:12:59 -7645.017903] SLOW spr round 12 (radius: 10)
[00:13:05 -7645.017854] SLOW spr round 13 (radius: 15)
[00:13:13 -7645.017850] SLOW spr round 14 (radius: 20)
[00:13:21 -7645.017849] SLOW spr round 15 (radius: 25)
[00:13:29 -7645.017849] Model parameter optimization (eps = 0.100000)

[00:13:30] ML tree search #5, logLikelihood: -7644.903366

[00:13:30 -19907.378683] Initial branch length optimization
[00:13:30 -16074.317821] Model parameter optimization (eps = 10.000000)
[00:13:34 -16044.383530] AUTODETECT spr round 1 (radius: 5)
[00:13:37 -12300.695005] AUTODETECT spr round 2 (radius: 10)
[00:13:42 -9256.702950] AUTODETECT spr round 3 (radius: 15)
[00:13:48 -8575.922426] AUTODETECT spr round 4 (radius: 20)
[00:13:55 -8407.116020] AUTODETECT spr round 5 (radius: 25)
[00:14:00 -8407.106448] SPR radius for FAST iterations: 20 (autodetect)
[00:14:00 -8407.106448] Model parameter optimization (eps = 3.000000)
[00:14:05 -8386.982849] FAST spr round 1 (radius: 20)
[00:14:10 -7687.954162] FAST spr round 2 (radius: 20)
[00:14:14 -7653.797542] FAST spr round 3 (radius: 20)
[00:14:17 -7645.456743] FAST spr round 4 (radius: 20)
[00:14:20 -7645.455727] Model parameter optimization (eps = 1.000000)
[00:14:22 -7641.527831] SLOW spr round 1 (radius: 5)
[00:14:28 -7639.273577] SLOW spr round 2 (radius: 5)
[00:14:34 -7639.273430] SLOW spr round 3 (radius: 10)
[00:14:39 -7639.273366] SLOW spr round 4 (radius: 15)
[00:14:49 -7636.087367] SLOW spr round 5 (radius: 5)
[00:14:57 -7635.014986] SLOW spr round 6 (radius: 5)
[00:15:04 -7635.014093] SLOW spr round 7 (radius: 10)
[00:15:10 -7635.014044] SLOW spr round 8 (radius: 15)
[00:15:19 -7635.014041] SLOW spr round 9 (radius: 20)
[00:15:29 -7635.014041] SLOW spr round 10 (radius: 25)
[00:15:36 -7635.014041] Model parameter optimization (eps = 0.100000)

[00:15:37] ML tree search #6, logLikelihood: -7634.829621

[00:15:37 -19769.061228] Initial branch length optimization
[00:15:38 -15812.121511] Model parameter optimization (eps = 10.000000)
[00:15:43 -15758.316789] AUTODETECT spr round 1 (radius: 5)
[00:15:46 -11844.260028] AUTODETECT spr round 2 (radius: 10)
[00:15:51 -9749.146060] AUTODETECT spr round 3 (radius: 15)
[00:15:57 -8574.110372] AUTODETECT spr round 4 (radius: 20)
[00:16:04 -8301.505517] AUTODETECT spr round 5 (radius: 25)
[00:16:09 -8297.466249] SPR radius for FAST iterations: 25 (autodetect)
[00:16:09 -8297.466249] Model parameter optimization (eps = 3.000000)
[00:16:12 -8279.126399] FAST spr round 1 (radius: 25)
[00:16:17 -7698.614154] FAST spr round 2 (radius: 25)
[00:16:21 -7658.216141] FAST spr round 3 (radius: 25)
[00:16:24 -7645.735301] FAST spr round 4 (radius: 25)
[00:16:28 -7643.704994] FAST spr round 5 (radius: 25)
[00:16:31 -7643.704621] Model parameter optimization (eps = 1.000000)
[00:16:32 -7642.279643] SLOW spr round 1 (radius: 5)
[00:16:38 -7640.793402] SLOW spr round 2 (radius: 5)
[00:16:44 -7640.744065] SLOW spr round 3 (radius: 10)
[00:16:50 -7639.901635] SLOW spr round 4 (radius: 5)
[00:16:58 -7637.561967] SLOW spr round 5 (radius: 5)
[00:17:05 -7637.561065] SLOW spr round 6 (radius: 10)
[00:17:10 -7637.560644] SLOW spr round 7 (radius: 15)
[00:17:20 -7637.560373] SLOW spr round 8 (radius: 20)
[00:17:30 -7637.560196] SLOW spr round 9 (radius: 25)
[00:17:37 -7637.560080] Model parameter optimization (eps = 0.100000)

[00:17:37] ML tree search #7, logLikelihood: -7637.518412

[00:17:37 -19828.998356] Initial branch length optimization
[00:17:38 -16068.047413] Model parameter optimization (eps = 10.000000)
[00:17:41 -16041.786853] AUTODETECT spr round 1 (radius: 5)
[00:17:44 -12090.568366] AUTODETECT spr round 2 (radius: 10)
[00:17:48 -9813.989221] AUTODETECT spr round 3 (radius: 15)
[00:17:54 -8469.318775] AUTODETECT spr round 4 (radius: 20)
[00:18:00 -8357.889676] AUTODETECT spr round 5 (radius: 25)
[00:18:05 -8357.843508] SPR radius for FAST iterations: 20 (autodetect)
[00:18:05 -8357.843508] Model parameter optimization (eps = 3.000000)
[00:18:08 -8326.238481] FAST spr round 1 (radius: 20)
[00:18:13 -7733.293961] FAST spr round 2 (radius: 20)
[00:18:17 -7661.210962] FAST spr round 3 (radius: 20)
[00:18:20 -7653.334194] FAST spr round 4 (radius: 20)
[00:18:23 -7652.290768] FAST spr round 5 (radius: 20)
[00:18:26 -7648.759976] FAST spr round 6 (radius: 20)
[00:18:30 -7643.930412] FAST spr round 7 (radius: 20)
[00:18:33 -7643.929853] Model parameter optimization (eps = 1.000000)
[00:18:34 -7642.373675] SLOW spr round 1 (radius: 5)
[00:18:40 -7640.460118] SLOW spr round 2 (radius: 5)
[00:18:46 -7640.457203] SLOW spr round 3 (radius: 10)
[00:18:52 -7639.940430] SLOW spr round 4 (radius: 5)
[00:19:00 -7638.377730] SLOW spr round 5 (radius: 5)
[00:19:07 -7638.377304] SLOW spr round 6 (radius: 10)
[00:19:13 -7637.639962] SLOW spr round 7 (radius: 5)
[00:19:21 -7634.881665] SLOW spr round 8 (radius: 5)
[00:19:28 -7634.880942] SLOW spr round 9 (radius: 10)
[00:19:34 -7634.880845] SLOW spr round 10 (radius: 15)
[00:19:44 -7634.880801] SLOW spr round 11 (radius: 20)
[00:19:54 -7634.880777] SLOW spr round 12 (radius: 25)
[00:20:00 -7634.880764] Model parameter optimization (eps = 0.100000)

[00:20:02] ML tree search #8, logLikelihood: -7634.538470

[00:20:02 -19516.366713] Initial branch length optimization
[00:20:02 -15831.980136] Model parameter optimization (eps = 10.000000)
[00:20:06 -15759.731059] AUTODETECT spr round 1 (radius: 5)
[00:20:09 -12189.364148] AUTODETECT spr round 2 (radius: 10)
[00:20:13 -10065.487043] AUTODETECT spr round 3 (radius: 15)
[00:20:19 -8728.420960] AUTODETECT spr round 4 (radius: 20)
[00:20:25 -8443.652088] AUTODETECT spr round 5 (radius: 25)
[00:20:30 -8407.691995] SPR radius for FAST iterations: 25 (autodetect)
[00:20:30 -8407.691995] Model parameter optimization (eps = 3.000000)
[00:20:32 -8392.612367] FAST spr round 1 (radius: 25)
[00:20:37 -7697.257273] FAST spr round 2 (radius: 25)
[00:20:41 -7656.202129] FAST spr round 3 (radius: 25)
[00:20:45 -7645.317570] FAST spr round 4 (radius: 25)
[00:20:48 -7641.219486] FAST spr round 5 (radius: 25)
[00:20:51 -7640.469539] FAST spr round 6 (radius: 25)
[00:20:54 -7640.252636] FAST spr round 7 (radius: 25)
[00:20:57 -7639.298676] FAST spr round 8 (radius: 25)
[00:21:00 -7639.298587] Model parameter optimization (eps = 1.000000)
[00:21:02 -7638.078927] SLOW spr round 1 (radius: 5)
[00:21:09 -7636.699429] SLOW spr round 2 (radius: 5)
[00:21:14 -7636.693995] SLOW spr round 3 (radius: 10)
[00:21:20 -7636.328402] SLOW spr round 4 (radius: 5)
[00:21:28 -7632.580014] SLOW spr round 5 (radius: 5)
[00:21:35 -7632.579445] SLOW spr round 6 (radius: 10)
[00:21:40 -7632.579432] SLOW spr round 7 (radius: 15)
[00:21:49 -7632.579432] SLOW spr round 8 (radius: 20)
[00:22:00 -7632.579432] SLOW spr round 9 (radius: 25)
[00:22:07 -7632.579432] Model parameter optimization (eps = 0.100000)

[00:22:08] ML tree search #9, logLikelihood: -7632.548659

[00:22:08 -19889.192037] Initial branch length optimization
[00:22:08 -16088.717306] Model parameter optimization (eps = 10.000000)
[00:22:12 -16055.164696] AUTODETECT spr round 1 (radius: 5)
[00:22:15 -11719.214896] AUTODETECT spr round 2 (radius: 10)
[00:22:20 -9888.034209] AUTODETECT spr round 3 (radius: 15)
[00:22:26 -8962.484337] AUTODETECT spr round 4 (radius: 20)
[00:22:32 -8750.436771] AUTODETECT spr round 5 (radius: 25)
[00:22:36 -8750.397769] SPR radius for FAST iterations: 20 (autodetect)
[00:22:36 -8750.397769] Model parameter optimization (eps = 3.000000)
[00:22:39 -8737.266365] FAST spr round 1 (radius: 20)
[00:22:44 -7704.525886] FAST spr round 2 (radius: 20)
[00:22:48 -7661.852725] FAST spr round 3 (radius: 20)
[00:22:51 -7647.182145] FAST spr round 4 (radius: 20)
[00:22:54 -7643.279705] FAST spr round 5 (radius: 20)
[00:22:58 -7639.079898] FAST spr round 6 (radius: 20)
[00:23:01 -7635.299635] FAST spr round 7 (radius: 20)
[00:23:04 -7635.296077] Model parameter optimization (eps = 1.000000)
[00:23:05 -7634.484836] SLOW spr round 1 (radius: 5)
[00:23:11 -7633.397237] SLOW spr round 2 (radius: 5)
[00:23:17 -7633.395747] SLOW spr round 3 (radius: 10)
[00:23:22 -7633.395177] SLOW spr round 4 (radius: 15)
[00:23:32 -7633.394884] SLOW spr round 5 (radius: 20)
[00:23:42 -7633.394728] SLOW spr round 6 (radius: 25)
[00:23:49 -7633.394646] Model parameter optimization (eps = 0.100000)

[00:23:49] ML tree search #10, logLikelihood: -7633.391800

[00:23:49 -19659.886233] Initial branch length optimization
[00:23:50 -16118.374955] Model parameter optimization (eps = 10.000000)
[00:23:53 -16085.202737] AUTODETECT spr round 1 (radius: 5)
[00:23:56 -12413.178282] AUTODETECT spr round 2 (radius: 10)
[00:24:01 -9080.291394] AUTODETECT spr round 3 (radius: 15)
[00:24:07 -8473.373374] AUTODETECT spr round 4 (radius: 20)
[00:24:13 -8433.289079] AUTODETECT spr round 5 (radius: 25)
[00:24:18 -8433.150823] SPR radius for FAST iterations: 25 (autodetect)
[00:24:18 -8433.150823] Model parameter optimization (eps = 3.000000)
[00:24:22 -8397.976533] FAST spr round 1 (radius: 25)
[00:24:26 -7703.665067] FAST spr round 2 (radius: 25)
[00:24:30 -7660.767319] FAST spr round 3 (radius: 25)
[00:24:34 -7649.738565] FAST spr round 4 (radius: 25)
[00:24:37 -7649.039243] FAST spr round 5 (radius: 25)
[00:24:40 -7648.382079] FAST spr round 6 (radius: 25)
[00:24:43 -7648.381648] Model parameter optimization (eps = 1.000000)
[00:24:45 -7646.219728] SLOW spr round 1 (radius: 5)
[00:24:51 -7643.866916] SLOW spr round 2 (radius: 5)
[00:24:56 -7643.866868] SLOW spr round 3 (radius: 10)
[00:25:02 -7643.737682] SLOW spr round 4 (radius: 5)
[00:25:10 -7643.734982] SLOW spr round 5 (radius: 10)
[00:25:17 -7643.734391] SLOW spr round 6 (radius: 15)
[00:25:27 -7642.328772] SLOW spr round 7 (radius: 5)
[00:25:36 -7642.327791] SLOW spr round 8 (radius: 10)
[00:25:43 -7642.327677] SLOW spr round 9 (radius: 15)
[00:25:53 -7642.327632] SLOW spr round 10 (radius: 20)
[00:26:03 -7642.327606] SLOW spr round 11 (radius: 25)
[00:26:09 -7642.327590] Model parameter optimization (eps = 0.100000)

[00:26:10] ML tree search #11, logLikelihood: -7642.238098

[00:26:10 -19992.761496] Initial branch length optimization
[00:26:10 -16256.883505] Model parameter optimization (eps = 10.000000)
[00:26:13 -16223.536219] AUTODETECT spr round 1 (radius: 5)
[00:26:16 -12601.679214] AUTODETECT spr round 2 (radius: 10)
[00:26:21 -9479.610585] AUTODETECT spr round 3 (radius: 15)
[00:26:28 -8485.893056] AUTODETECT spr round 4 (radius: 20)
[00:26:34 -8458.817247] AUTODETECT spr round 5 (radius: 25)
[00:26:39 -8452.152818] SPR radius for FAST iterations: 25 (autodetect)
[00:26:39 -8452.152818] Model parameter optimization (eps = 3.000000)
[00:26:41 -8436.747839] FAST spr round 1 (radius: 25)
[00:26:46 -7734.457751] FAST spr round 2 (radius: 25)
[00:26:50 -7649.864024] FAST spr round 3 (radius: 25)
[00:26:54 -7643.601846] FAST spr round 4 (radius: 25)
[00:26:57 -7643.601585] Model parameter optimization (eps = 1.000000)
[00:26:58 -7641.167995] SLOW spr round 1 (radius: 5)
[00:27:04 -7639.652102] SLOW spr round 2 (radius: 5)
[00:27:10 -7639.651648] SLOW spr round 3 (radius: 10)
[00:27:16 -7639.651629] SLOW spr round 4 (radius: 15)
[00:27:25 -7639.604906] SLOW spr round 5 (radius: 20)
[00:27:35 -7638.667475] SLOW spr round 6 (radius: 5)
[00:27:43 -7638.667032] SLOW spr round 7 (radius: 10)
[00:27:50 -7636.559806] SLOW spr round 8 (radius: 5)
[00:27:58 -7635.403548] SLOW spr round 9 (radius: 5)
[00:28:04 -7635.402471] SLOW spr round 10 (radius: 10)
[00:28:10 -7633.677734] SLOW spr round 11 (radius: 5)
[00:28:18 -7633.677572] SLOW spr round 12 (radius: 10)
[00:28:24 -7633.677565] SLOW spr round 13 (radius: 15)
[00:28:33 -7633.677564] SLOW spr round 14 (radius: 20)
[00:28:43 -7633.677564] SLOW spr round 15 (radius: 25)
[00:28:50 -7633.677564] Model parameter optimization (eps = 0.100000)

[00:28:52] ML tree search #12, logLikelihood: -7633.435999

[00:28:52 -19496.004431] Initial branch length optimization
[00:28:52 -15779.027454] Model parameter optimization (eps = 10.000000)
[00:28:55 -15750.383158] AUTODETECT spr round 1 (radius: 5)
[00:28:59 -12589.911716] AUTODETECT spr round 2 (radius: 10)
[00:29:03 -10123.415060] AUTODETECT spr round 3 (radius: 15)
[00:29:10 -8826.070048] AUTODETECT spr round 4 (radius: 20)
[00:29:14 -8715.000623] AUTODETECT spr round 5 (radius: 25)
[00:29:19 -8714.097100] SPR radius for FAST iterations: 25 (autodetect)
[00:29:19 -8714.097100] Model parameter optimization (eps = 3.000000)
[00:29:23 -8674.263522] FAST spr round 1 (radius: 25)
[00:29:27 -7749.877252] FAST spr round 2 (radius: 25)
[00:29:31 -7660.081086] FAST spr round 3 (radius: 25)
[00:29:34 -7646.693493] FAST spr round 4 (radius: 25)
[00:29:37 -7645.831284] FAST spr round 5 (radius: 25)
[00:29:40 -7645.434888] FAST spr round 6 (radius: 25)
[00:29:44 -7645.434539] Model parameter optimization (eps = 1.000000)
[00:29:45 -7645.126022] SLOW spr round 1 (radius: 5)
[00:29:51 -7642.543769] SLOW spr round 2 (radius: 5)
[00:29:57 -7641.897232] SLOW spr round 3 (radius: 5)
[00:30:03 -7641.896070] SLOW spr round 4 (radius: 10)
[00:30:08 -7641.195685] SLOW spr round 5 (radius: 5)
[00:30:16 -7641.195566] SLOW spr round 6 (radius: 10)
[00:30:22 -7641.195563] SLOW spr round 7 (radius: 15)
[00:30:30 -7641.195563] SLOW spr round 8 (radius: 20)
[00:30:40 -7641.195563] SLOW spr round 9 (radius: 25)
[00:30:48 -7638.834659] SLOW spr round 10 (radius: 5)
[00:30:57 -7638.786872] SLOW spr round 11 (radius: 10)
[00:31:04 -7638.330004] SLOW spr round 12 (radius: 5)
[00:31:11 -7638.329549] SLOW spr round 13 (radius: 10)
[00:31:17 -7638.329532] SLOW spr round 14 (radius: 15)
[00:31:25 -7638.329531] SLOW spr round 15 (radius: 20)
[00:31:35 -7638.329531] SLOW spr round 16 (radius: 25)
[00:31:44 -7638.329531] Model parameter optimization (eps = 0.100000)

[00:31:45] ML tree search #13, logLikelihood: -7638.134390

[00:31:45 -19616.767033] Initial branch length optimization
[00:31:45 -15931.526014] Model parameter optimization (eps = 10.000000)
[00:31:48 -15896.370581] AUTODETECT spr round 1 (radius: 5)
[00:31:52 -12003.519800] AUTODETECT spr round 2 (radius: 10)
[00:31:56 -9787.316249] AUTODETECT spr round 3 (radius: 15)
[00:32:02 -9342.242787] AUTODETECT spr round 4 (radius: 20)
[00:32:08 -8802.831590] AUTODETECT spr round 5 (radius: 25)
[00:32:13 -8798.191840] SPR radius for FAST iterations: 25 (autodetect)
[00:32:13 -8798.191840] Model parameter optimization (eps = 3.000000)
[00:32:16 -8782.980133] FAST spr round 1 (radius: 25)
[00:32:21 -7839.672961] FAST spr round 2 (radius: 25)
[00:32:25 -7786.872090] FAST spr round 3 (radius: 25)
[00:32:29 -7765.634349] FAST spr round 4 (radius: 25)
[00:32:33 -7762.247984] FAST spr round 5 (radius: 25)
[00:32:36 -7761.665828] FAST spr round 6 (radius: 25)
[00:32:40 -7642.810270] FAST spr round 7 (radius: 25)
[00:32:43 -7641.704328] FAST spr round 8 (radius: 25)
[00:32:46 -7641.704233] Model parameter optimization (eps = 1.000000)
[00:32:48 -7636.065490] SLOW spr round 1 (radius: 5)
[00:32:54 -7635.130139] SLOW spr round 2 (radius: 5)
[00:32:59 -7635.130021] SLOW spr round 3 (radius: 10)
[00:33:05 -7635.129960] SLOW spr round 4 (radius: 15)
[00:33:15 -7635.129928] SLOW spr round 5 (radius: 20)
[00:33:25 -7635.129911] SLOW spr round 6 (radius: 25)
[00:33:32 -7635.129902] Model parameter optimization (eps = 0.100000)

[00:33:32] ML tree search #14, logLikelihood: -7635.127209

[00:33:32 -19679.196732] Initial branch length optimization
[00:33:32 -16135.251176] Model parameter optimization (eps = 10.000000)
[00:33:35 -16096.881087] AUTODETECT spr round 1 (radius: 5)
[00:33:39 -12201.876357] AUTODETECT spr round 2 (radius: 10)
[00:33:44 -9655.769368] AUTODETECT spr round 3 (radius: 15)
[00:33:49 -8884.157781] AUTODETECT spr round 4 (radius: 20)
[00:33:56 -8491.736919] AUTODETECT spr round 5 (radius: 25)
[00:34:01 -8346.245062] SPR radius for FAST iterations: 25 (autodetect)
[00:34:01 -8346.245062] Model parameter optimization (eps = 3.000000)
[00:34:04 -8317.186705] FAST spr round 1 (radius: 25)
[00:34:09 -7688.018734] FAST spr round 2 (radius: 25)
[00:34:13 -7665.410196] FAST spr round 3 (radius: 25)
[00:34:16 -7655.849730] FAST spr round 4 (radius: 25)
[00:34:19 -7653.994354] FAST spr round 5 (radius: 25)
[00:34:23 -7653.470681] FAST spr round 6 (radius: 25)
[00:34:26 -7653.469973] Model parameter optimization (eps = 1.000000)
[00:34:28 -7648.284871] SLOW spr round 1 (radius: 5)
[00:34:34 -7643.388236] SLOW spr round 2 (radius: 5)
[00:34:40 -7642.292195] SLOW spr round 3 (radius: 5)
[00:34:46 -7642.292015] SLOW spr round 4 (radius: 10)
[00:34:51 -7640.766640] SLOW spr round 5 (radius: 5)
[00:34:59 -7639.226351] SLOW spr round 6 (radius: 5)
[00:35:06 -7639.225748] SLOW spr round 7 (radius: 10)
[00:35:12 -7637.780162] SLOW spr round 8 (radius: 5)
[00:35:20 -7636.144720] SLOW spr round 9 (radius: 5)
[00:35:26 -7636.144714] SLOW spr round 10 (radius: 10)
[00:35:32 -7636.144714] SLOW spr round 11 (radius: 15)
[00:35:41 -7633.561236] SLOW spr round 12 (radius: 5)
[00:35:49 -7632.549483] SLOW spr round 13 (radius: 5)
[00:35:56 -7632.546809] SLOW spr round 14 (radius: 10)
[00:36:02 -7632.546697] SLOW spr round 15 (radius: 15)
[00:36:10 -7632.546689] SLOW spr round 16 (radius: 20)
[00:36:20 -7632.546689] SLOW spr round 17 (radius: 25)
[00:36:28 -7632.546689] Model parameter optimization (eps = 0.100000)

[00:36:29] ML tree search #15, logLikelihood: -7632.328412

[00:36:29 -20011.561625] Initial branch length optimization
[00:36:29 -16050.464330] Model parameter optimization (eps = 10.000000)
[00:36:33 -16009.192809] AUTODETECT spr round 1 (radius: 5)
[00:36:36 -11804.119258] AUTODETECT spr round 2 (radius: 10)
[00:36:41 -9090.816743] AUTODETECT spr round 3 (radius: 15)
[00:36:47 -8280.012399] AUTODETECT spr round 4 (radius: 20)
[00:36:54 -8190.917524] AUTODETECT spr round 5 (radius: 25)
[00:36:58 -8190.906264] SPR radius for FAST iterations: 20 (autodetect)
[00:36:58 -8190.906264] Model parameter optimization (eps = 3.000000)
[00:37:00 -8175.897483] FAST spr round 1 (radius: 20)
[00:37:05 -7689.154885] FAST spr round 2 (radius: 20)
[00:37:08 -7665.322878] FAST spr round 3 (radius: 20)
[00:37:11 -7650.429877] FAST spr round 4 (radius: 20)
[00:37:15 -7650.426644] Model parameter optimization (eps = 1.000000)
[00:37:16 -7650.201563] SLOW spr round 1 (radius: 5)
[00:37:22 -7648.299537] SLOW spr round 2 (radius: 5)
[00:37:28 -7646.756356] SLOW spr round 3 (radius: 5)
[00:37:34 -7646.755458] SLOW spr round 4 (radius: 10)
[00:37:39 -7646.679469] SLOW spr round 5 (radius: 15)
[00:37:49 -7646.670369] SLOW spr round 6 (radius: 20)
[00:37:59 -7646.669161] SLOW spr round 7 (radius: 25)
[00:38:06 -7646.669035] Model parameter optimization (eps = 0.100000)

[00:38:07] ML tree search #16, logLikelihood: -7646.596338

[00:38:07 -19623.172415] Initial branch length optimization
[00:38:07 -16066.490670] Model parameter optimization (eps = 10.000000)
[00:38:10 -16030.539310] AUTODETECT spr round 1 (radius: 5)
[00:38:13 -12333.588466] AUTODETECT spr round 2 (radius: 10)
[00:38:18 -10191.453749] AUTODETECT spr round 3 (radius: 15)
[00:38:23 -9269.595374] AUTODETECT spr round 4 (radius: 20)
[00:38:29 -8640.458847] AUTODETECT spr round 5 (radius: 25)
[00:38:35 -8618.553612] SPR radius for FAST iterations: 25 (autodetect)
[00:38:35 -8618.553612] Model parameter optimization (eps = 3.000000)
[00:38:38 -8599.621590] FAST spr round 1 (radius: 25)
[00:38:43 -7806.965844] FAST spr round 2 (radius: 25)
[00:38:47 -7659.636797] FAST spr round 3 (radius: 25)
[00:38:51 -7650.480272] FAST spr round 4 (radius: 25)
[00:38:54 -7649.144372] FAST spr round 5 (radius: 25)
[00:38:57 -7647.087890] FAST spr round 6 (radius: 25)
[00:39:00 -7647.086209] Model parameter optimization (eps = 1.000000)
[00:39:02 -7645.395786] SLOW spr round 1 (radius: 5)
[00:39:08 -7645.180577] SLOW spr round 2 (radius: 5)
[00:39:14 -7645.179714] SLOW spr round 3 (radius: 10)
[00:39:19 -7645.179461] SLOW spr round 4 (radius: 15)
[00:39:28 -7645.179366] SLOW spr round 5 (radius: 20)
[00:39:36 -7642.338119] SLOW spr round 6 (radius: 5)
[00:39:44 -7642.332350] SLOW spr round 7 (radius: 10)
[00:39:51 -7642.075147] SLOW spr round 8 (radius: 5)
[00:39:59 -7641.768685] SLOW spr round 9 (radius: 5)
[00:40:05 -7641.766876] SLOW spr round 10 (radius: 10)
[00:40:11 -7641.765887] SLOW spr round 11 (radius: 15)
[00:40:19 -7641.765363] SLOW spr round 12 (radius: 20)
[00:40:27 -7641.765091] SLOW spr round 13 (radius: 25)
[00:40:35 -7641.764953] Model parameter optimization (eps = 0.100000)

[00:40:36] ML tree search #17, logLikelihood: -7641.576576

[00:40:36 -19978.667316] Initial branch length optimization
[00:40:37 -16206.231111] Model parameter optimization (eps = 10.000000)
[00:40:40 -16153.978300] AUTODETECT spr round 1 (radius: 5)
[00:40:43 -12431.779211] AUTODETECT spr round 2 (radius: 10)
[00:40:48 -9996.226345] AUTODETECT spr round 3 (radius: 15)
[00:40:54 -8956.529161] AUTODETECT spr round 4 (radius: 20)
[00:40:59 -8833.093891] AUTODETECT spr round 5 (radius: 25)
[00:41:03 -8702.335659] SPR radius for FAST iterations: 25 (autodetect)
[00:41:03 -8702.335659] Model parameter optimization (eps = 3.000000)
[00:41:06 -8688.303227] FAST spr round 1 (radius: 25)
[00:41:10 -7732.773722] FAST spr round 2 (radius: 25)
[00:41:14 -7661.461844] FAST spr round 3 (radius: 25)
[00:41:17 -7654.167586] FAST spr round 4 (radius: 25)
[00:41:20 -7653.886233] FAST spr round 5 (radius: 25)
[00:41:23 -7653.281869] FAST spr round 6 (radius: 25)
[00:41:26 -7653.281555] Model parameter optimization (eps = 1.000000)
[00:41:29 -7651.622843] SLOW spr round 1 (radius: 5)
[00:41:35 -7644.285339] SLOW spr round 2 (radius: 5)
[00:41:41 -7639.301008] SLOW spr round 3 (radius: 5)
[00:41:47 -7637.130780] SLOW spr round 4 (radius: 5)
[00:41:52 -7637.130616] SLOW spr round 5 (radius: 10)
[00:41:58 -7634.744264] SLOW spr round 6 (radius: 5)
[00:42:06 -7634.743111] SLOW spr round 7 (radius: 10)
[00:42:12 -7634.742600] SLOW spr round 8 (radius: 15)
[00:42:22 -7634.742329] SLOW spr round 9 (radius: 20)
[00:42:32 -7634.742180] SLOW spr round 10 (radius: 25)
[00:42:39 -7634.742098] Model parameter optimization (eps = 0.100000)

[00:42:40] ML tree search #18, logLikelihood: -7633.876503

[00:42:40 -20180.120273] Initial branch length optimization
[00:42:41 -16345.543791] Model parameter optimization (eps = 10.000000)
[00:42:44 -16293.060460] AUTODETECT spr round 1 (radius: 5)
[00:42:47 -12376.992904] AUTODETECT spr round 2 (radius: 10)
[00:42:52 -9610.718258] AUTODETECT spr round 3 (radius: 15)
[00:42:57 -8862.803265] AUTODETECT spr round 4 (radius: 20)
[00:43:02 -8517.093218] AUTODETECT spr round 5 (radius: 25)
[00:43:07 -8517.017245] SPR radius for FAST iterations: 20 (autodetect)
[00:43:07 -8517.017245] Model parameter optimization (eps = 3.000000)
[00:43:10 -8486.240813] FAST spr round 1 (radius: 20)
[00:43:14 -7702.047807] FAST spr round 2 (radius: 20)
[00:43:18 -7659.542703] FAST spr round 3 (radius: 20)
[00:43:22 -7649.440230] FAST spr round 4 (radius: 20)
[00:43:25 -7649.247203] FAST spr round 5 (radius: 20)
[00:43:28 -7649.245614] Model parameter optimization (eps = 1.000000)
[00:43:30 -7643.575061] SLOW spr round 1 (radius: 5)
[00:43:36 -7641.035289] SLOW spr round 2 (radius: 5)
[00:43:42 -7639.836910] SLOW spr round 3 (radius: 5)
[00:43:48 -7638.336874] SLOW spr round 4 (radius: 5)
[00:43:53 -7638.336160] SLOW spr round 5 (radius: 10)
[00:43:59 -7635.595350] SLOW spr round 6 (radius: 5)
[00:44:07 -7632.851762] SLOW spr round 7 (radius: 5)
[00:44:14 -7632.851121] SLOW spr round 8 (radius: 10)
[00:44:20 -7632.851081] SLOW spr round 9 (radius: 15)
[00:44:29 -7632.851072] SLOW spr round 10 (radius: 20)
[00:44:40 -7632.851068] SLOW spr round 11 (radius: 25)
[00:44:46 -7632.851066] Model parameter optimization (eps = 0.100000)

[00:44:48] ML tree search #19, logLikelihood: -7632.693063

[00:44:48 -19563.162332] Initial branch length optimization
[00:44:48 -15825.185512] Model parameter optimization (eps = 10.000000)
[00:44:52 -15785.761062] AUTODETECT spr round 1 (radius: 5)
[00:44:55 -12291.980756] AUTODETECT spr round 2 (radius: 10)
[00:45:00 -9220.625081] AUTODETECT spr round 3 (radius: 15)
[00:45:05 -8473.882372] AUTODETECT spr round 4 (radius: 20)
[00:45:12 -8406.824073] AUTODETECT spr round 5 (radius: 25)
[00:45:16 -8402.756779] SPR radius for FAST iterations: 25 (autodetect)
[00:45:16 -8402.756779] Model parameter optimization (eps = 3.000000)
[00:45:19 -8397.139499] FAST spr round 1 (radius: 25)
[00:45:24 -7720.332107] FAST spr round 2 (radius: 25)
[00:45:28 -7665.864746] FAST spr round 3 (radius: 25)
[00:45:32 -7660.641435] FAST spr round 4 (radius: 25)
[00:45:35 -7660.640582] Model parameter optimization (eps = 1.000000)
[00:45:37 -7659.261500] SLOW spr round 1 (radius: 5)
[00:45:43 -7653.872251] SLOW spr round 2 (radius: 5)
[00:45:49 -7652.089425] SLOW spr round 3 (radius: 5)
[00:45:55 -7652.088872] SLOW spr round 4 (radius: 10)
[00:46:00 -7651.686755] SLOW spr round 5 (radius: 5)
[00:46:08 -7651.686664] SLOW spr round 6 (radius: 10)
[00:46:14 -7651.686605] SLOW spr round 7 (radius: 15)
[00:46:21 -7651.571263] SLOW spr round 8 (radius: 5)
[00:46:29 -7651.571106] SLOW spr round 9 (radius: 10)
[00:46:35 -7651.571071] SLOW spr round 10 (radius: 15)
[00:46:43 -7651.571048] SLOW spr round 11 (radius: 20)
[00:46:52 -7651.571031] SLOW spr round 12 (radius: 25)
[00:47:00 -7648.934714] SLOW spr round 13 (radius: 5)
[00:47:08 -7648.903998] SLOW spr round 14 (radius: 10)
[00:47:15 -7648.740036] SLOW spr round 15 (radius: 5)
[00:47:23 -7646.529122] SLOW spr round 16 (radius: 5)
[00:47:29 -7646.527522] SLOW spr round 17 (radius: 10)
[00:47:34 -7646.526727] SLOW spr round 18 (radius: 15)
[00:47:42 -7646.526331] SLOW spr round 19 (radius: 20)
[00:47:51 -7646.526139] SLOW spr round 20 (radius: 25)
[00:47:59 -7646.526047] Model parameter optimization (eps = 0.100000)

[00:48:01] ML tree search #20, logLikelihood: -7645.820526


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.219147,0.438971) (0.163786,0.596131) (0.416349,1.009532) (0.200718,1.922324) 
   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: -7632.328412

AIC score: 15938.656824 / AICc score: 243750.656824 / BIC score: 16671.425334
Free parameters (model + branch lengths): 337

WARNING: Number of free parameters (K=337) is larger than alignment size (n=65).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9BX59/3_mltree/Q9BX59.raxml.log

Analysis started: 10-Jul-2021 05:21:41 / finished: 10-Jul-2021 06:09:42

Elapsed time: 2881.329 seconds