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 15-Jul-2021 11:02:42 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/2_msa/Q5XG99_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/3_mltree/Q5XG99 --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: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/2_msa/Q5XG99_trimmed_msa.fasta
[00:00:00] Loaded alignment with 286 taxa and 545 sites

WARNING: Sequences tr_A0A2I3TLK8_A0A2I3TLK8_PANTR_9598 and tr_A0A2R9B8N1_A0A2R9B8N1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_I1PEM6_I1PEM6_ORYGL_4538 and tr_A0A0D3FMU5_A0A0D3FMU5_9ORYZ_65489 are exactly identical!
WARNING: Sequences tr_B3RSC9_B3RSC9_TRIAD_10228 and tr_A0A369SHQ3_A0A369SHQ3_9METZ_287889 are exactly identical!
WARNING: Sequences tr_G7P9J1_G7P9J1_MACFA_9541 and tr_A0A2K6DGQ2_A0A2K6DGQ2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A096NNE3_A0A096NNE3_PAPAN_9555 and tr_A0A2K5P7K3_A0A2K5P7K3_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A1U8FGC1_A0A1U8FGC1_CAPAN_4072 and tr_A0A2G3BUK5_A0A2G3BUK5_CAPCH_80379 are exactly identical!
WARNING: Sequences tr_A0A2K5L9J2_A0A2K5L9J2_CERAT_9531 and tr_A0A2K5ZWB9_A0A2K5ZWB9_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 7

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/Q5XG99/3_mltree/Q5XG99.raxml.reduced.phy

Alignment comprises 1 partitions and 545 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 545 / 545
Gaps: 48.72 %
Invariant sites: 0.37 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/3_mltree/Q5XG99.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 286 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 78 / 6240
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -170591.532719] Initial branch length optimization
[00:00:00 -138379.461309] Model parameter optimization (eps = 10.000000)
[00:00:16 -137835.616121] AUTODETECT spr round 1 (radius: 5)
[00:00:26 -102823.377446] AUTODETECT spr round 2 (radius: 10)
[00:00:39 -78620.888604] AUTODETECT spr round 3 (radius: 15)
[00:00:55 -70796.214307] AUTODETECT spr round 4 (radius: 20)
[00:01:14 -68753.002720] AUTODETECT spr round 5 (radius: 25)
[00:01:30 -68752.058530] SPR radius for FAST iterations: 25 (autodetect)
[00:01:30 -68752.058530] Model parameter optimization (eps = 3.000000)
[00:01:39 -68385.820932] FAST spr round 1 (radius: 25)
[00:01:53 -61644.409840] FAST spr round 2 (radius: 25)
[00:02:05 -61342.350137] FAST spr round 3 (radius: 25)
[00:02:14 -61337.471323] FAST spr round 4 (radius: 25)
[00:02:23 -61337.187134] FAST spr round 5 (radius: 25)
[00:02:32 -61337.186854] Model parameter optimization (eps = 1.000000)
[00:02:38 -61327.619791] SLOW spr round 1 (radius: 5)
[00:02:56 -61314.986738] SLOW spr round 2 (radius: 5)
[00:03:11 -61314.986583] SLOW spr round 3 (radius: 10)
[00:03:28 -61314.986577] SLOW spr round 4 (radius: 15)
[00:03:58 -61314.986577] SLOW spr round 5 (radius: 20)
[00:04:32 -61314.986576] SLOW spr round 6 (radius: 25)
[00:05:04 -61314.986576] Model parameter optimization (eps = 0.100000)

[00:05:06] ML tree search #1, logLikelihood: -61314.963237

[00:05:06 -168142.547174] Initial branch length optimization
[00:05:06 -138308.479462] Model parameter optimization (eps = 10.000000)
[00:05:17 -137948.752045] AUTODETECT spr round 1 (radius: 5)
[00:05:27 -103050.246044] AUTODETECT spr round 2 (radius: 10)
[00:05:41 -77679.309900] AUTODETECT spr round 3 (radius: 15)
[00:05:57 -66972.765030] AUTODETECT spr round 4 (radius: 20)
[00:06:15 -66773.159605] AUTODETECT spr round 5 (radius: 25)
[00:06:34 -66765.783073] SPR radius for FAST iterations: 25 (autodetect)
[00:06:34 -66765.783073] Model parameter optimization (eps = 3.000000)
[00:06:47 -66505.493785] FAST spr round 1 (radius: 25)
[00:07:02 -61576.510747] FAST spr round 2 (radius: 25)
[00:07:15 -61367.113650] FAST spr round 3 (radius: 25)
[00:07:27 -61339.048642] FAST spr round 4 (radius: 25)
[00:07:36 -61332.285418] FAST spr round 5 (radius: 25)
[00:07:45 -61332.282083] Model parameter optimization (eps = 1.000000)
[00:07:52 -61327.575571] SLOW spr round 1 (radius: 5)
[00:08:09 -61320.176430] SLOW spr round 2 (radius: 5)
[00:08:25 -61319.897366] SLOW spr round 3 (radius: 5)
[00:08:41 -61319.896836] SLOW spr round 4 (radius: 10)
[00:08:58 -61319.896828] SLOW spr round 5 (radius: 15)
[00:09:28 -61319.896827] SLOW spr round 6 (radius: 20)
[00:10:03 -61319.896827] SLOW spr round 7 (radius: 25)
[00:10:35 -61319.896827] Model parameter optimization (eps = 0.100000)

[00:10:36] ML tree search #2, logLikelihood: -61319.892593

[00:10:36 -168724.450316] Initial branch length optimization
[00:10:37 -138012.055607] Model parameter optimization (eps = 10.000000)
[00:10:44 -137665.035500] AUTODETECT spr round 1 (radius: 5)
[00:10:55 -99336.622951] AUTODETECT spr round 2 (radius: 10)
[00:11:08 -75008.259004] AUTODETECT spr round 3 (radius: 15)
[00:11:23 -67490.111336] AUTODETECT spr round 4 (radius: 20)
[00:11:48 -66231.276164] AUTODETECT spr round 5 (radius: 25)
[00:12:09 -66231.237020] SPR radius for FAST iterations: 20 (autodetect)
[00:12:10 -66231.237020] Model parameter optimization (eps = 3.000000)
[00:12:19 -66022.891383] FAST spr round 1 (radius: 20)
[00:12:34 -61625.293235] FAST spr round 2 (radius: 20)
[00:12:47 -61440.107032] FAST spr round 3 (radius: 20)
[00:12:58 -61412.430731] FAST spr round 4 (radius: 20)
[00:13:06 -61412.423817] Model parameter optimization (eps = 1.000000)
[00:13:11 -61407.759216] SLOW spr round 1 (radius: 5)
[00:13:30 -61394.221997] SLOW spr round 2 (radius: 5)
[00:13:46 -61390.495892] SLOW spr round 3 (radius: 5)
[00:14:01 -61390.495033] SLOW spr round 4 (radius: 10)
[00:14:17 -61390.057473] SLOW spr round 5 (radius: 5)
[00:14:39 -61390.057450] SLOW spr round 6 (radius: 10)
[00:14:58 -61390.057450] SLOW spr round 7 (radius: 15)
[00:15:24 -61390.057450] SLOW spr round 8 (radius: 20)
[00:15:57 -61390.057450] SLOW spr round 9 (radius: 25)
[00:16:30 -61390.057450] Model parameter optimization (eps = 0.100000)

[00:16:34] ML tree search #3, logLikelihood: -61389.683300

[00:16:34 -170622.486017] Initial branch length optimization
[00:16:34 -137218.506827] Model parameter optimization (eps = 10.000000)
[00:16:43 -136861.142881] AUTODETECT spr round 1 (radius: 5)
[00:16:53 -104147.966735] AUTODETECT spr round 2 (radius: 10)
[00:17:06 -83028.175798] AUTODETECT spr round 3 (radius: 15)
[00:17:22 -74134.539677] AUTODETECT spr round 4 (radius: 20)
[00:17:42 -71391.999720] AUTODETECT spr round 5 (radius: 25)
[00:18:03 -71391.923429] SPR radius for FAST iterations: 20 (autodetect)
[00:18:03 -71391.923429] Model parameter optimization (eps = 3.000000)
[00:18:13 -71114.777113] FAST spr round 1 (radius: 20)
[00:18:29 -62110.933771] FAST spr round 2 (radius: 20)
[00:18:42 -61377.185034] FAST spr round 3 (radius: 20)
[00:18:53 -61355.261278] FAST spr round 4 (radius: 20)
[00:19:02 -61346.776558] FAST spr round 5 (radius: 20)
[00:19:11 -61342.116404] FAST spr round 6 (radius: 20)
[00:19:20 -61340.328716] FAST spr round 7 (radius: 20)
[00:19:29 -61337.491556] FAST spr round 8 (radius: 20)
[00:19:38 -61337.491510] Model parameter optimization (eps = 1.000000)
[00:19:44 -61325.846417] SLOW spr round 1 (radius: 5)
[00:20:00 -61319.075509] SLOW spr round 2 (radius: 5)
[00:20:16 -61319.075402] SLOW spr round 3 (radius: 10)
[00:20:33 -61319.075401] SLOW spr round 4 (radius: 15)
[00:21:03 -61319.075401] SLOW spr round 5 (radius: 20)
[00:21:38 -61319.075401] SLOW spr round 6 (radius: 25)
[00:22:10 -61319.075401] Model parameter optimization (eps = 0.100000)

[00:22:11] ML tree search #4, logLikelihood: -61319.068720

[00:22:11 -170725.400558] Initial branch length optimization
[00:22:12 -139294.537665] Model parameter optimization (eps = 10.000000)
[00:22:21 -138882.554743] AUTODETECT spr round 1 (radius: 5)
[00:22:31 -104504.207390] AUTODETECT spr round 2 (radius: 10)
[00:22:44 -81662.767653] AUTODETECT spr round 3 (radius: 15)
[00:22:58 -73625.679228] AUTODETECT spr round 4 (radius: 20)
[00:23:14 -68436.292001] AUTODETECT spr round 5 (radius: 25)
[00:23:34 -68436.258332] SPR radius for FAST iterations: 20 (autodetect)
[00:23:34 -68436.258332] Model parameter optimization (eps = 3.000000)
[00:23:52 -68117.984061] FAST spr round 1 (radius: 20)
[00:24:09 -61781.603307] FAST spr round 2 (radius: 20)
[00:24:20 -61380.355723] FAST spr round 3 (radius: 20)
[00:24:30 -61371.691279] FAST spr round 4 (radius: 20)
[00:24:40 -61366.410990] FAST spr round 5 (radius: 20)
[00:24:49 -61366.410731] Model parameter optimization (eps = 1.000000)
[00:24:58 -61356.687671] SLOW spr round 1 (radius: 5)
[00:25:16 -61318.064126] SLOW spr round 2 (radius: 5)
[00:25:32 -61317.040605] SLOW spr round 3 (radius: 5)
[00:25:47 -61317.039814] SLOW spr round 4 (radius: 10)
[00:26:04 -61313.607472] SLOW spr round 5 (radius: 5)
[00:26:26 -61313.607154] SLOW spr round 6 (radius: 10)
[00:26:45 -61313.607154] SLOW spr round 7 (radius: 15)
[00:27:13 -61313.607154] SLOW spr round 8 (radius: 20)
[00:27:48 -61313.607154] SLOW spr round 9 (radius: 25)
[00:28:20 -61313.607154] Model parameter optimization (eps = 0.100000)

[00:28:24] ML tree search #5, logLikelihood: -61313.279247

[00:28:24 -170374.354340] Initial branch length optimization
[00:28:25 -139005.951684] Model parameter optimization (eps = 10.000000)
[00:28:35 -138567.085780] AUTODETECT spr round 1 (radius: 5)
[00:28:46 -100183.424614] AUTODETECT spr round 2 (radius: 10)
[00:28:59 -74279.838353] AUTODETECT spr round 3 (radius: 15)
[00:29:15 -67616.844391] AUTODETECT spr round 4 (radius: 20)
[00:29:35 -67562.636176] AUTODETECT spr round 5 (radius: 25)
[00:29:57 -67562.609165] SPR radius for FAST iterations: 20 (autodetect)
[00:29:57 -67562.609165] Model parameter optimization (eps = 3.000000)
[00:30:08 -67194.267774] FAST spr round 1 (radius: 20)
[00:30:23 -61459.257158] FAST spr round 2 (radius: 20)
[00:30:35 -61339.352043] FAST spr round 3 (radius: 20)
[00:30:44 -61333.866983] FAST spr round 4 (radius: 20)
[00:30:54 -61330.247585] FAST spr round 5 (radius: 20)
[00:31:02 -61327.989818] FAST spr round 6 (radius: 20)
[00:31:11 -61326.946597] FAST spr round 7 (radius: 20)
[00:31:20 -61326.946371] Model parameter optimization (eps = 1.000000)
[00:31:25 -61323.092985] SLOW spr round 1 (radius: 5)
[00:31:42 -61317.726240] SLOW spr round 2 (radius: 5)
[00:31:58 -61317.163593] SLOW spr round 3 (radius: 5)
[00:32:13 -61317.163485] SLOW spr round 4 (radius: 10)
[00:32:30 -61313.695645] SLOW spr round 5 (radius: 5)
[00:32:52 -61313.695329] SLOW spr round 6 (radius: 10)
[00:33:11 -61313.695329] SLOW spr round 7 (radius: 15)
[00:33:39 -61313.695329] SLOW spr round 8 (radius: 20)
[00:34:14 -61313.695329] SLOW spr round 9 (radius: 25)
[00:34:46 -61313.695329] Model parameter optimization (eps = 0.100000)

[00:34:48] ML tree search #6, logLikelihood: -61313.650611

[00:34:48 -170277.813118] Initial branch length optimization
[00:34:48 -140781.582134] Model parameter optimization (eps = 10.000000)
[00:35:03 -140245.120310] AUTODETECT spr round 1 (radius: 5)
[00:35:13 -101412.427366] AUTODETECT spr round 2 (radius: 10)
[00:35:27 -78110.283489] AUTODETECT spr round 3 (radius: 15)
[00:35:46 -67413.976677] AUTODETECT spr round 4 (radius: 20)
[00:36:04 -67208.790215] AUTODETECT spr round 5 (radius: 25)
[00:36:26 -67208.750674] SPR radius for FAST iterations: 20 (autodetect)
[00:36:26 -67208.750674] Model parameter optimization (eps = 3.000000)
[00:36:35 -66840.675010] FAST spr round 1 (radius: 20)
[00:36:50 -61609.080680] FAST spr round 2 (radius: 20)
[00:37:03 -61367.472327] FAST spr round 3 (radius: 20)
[00:37:14 -61340.260392] FAST spr round 4 (radius: 20)
[00:37:24 -61333.683282] FAST spr round 5 (radius: 20)
[00:37:33 -61333.683125] Model parameter optimization (eps = 1.000000)
[00:37:38 -61330.003182] SLOW spr round 1 (radius: 5)
[00:37:56 -61320.468774] SLOW spr round 2 (radius: 5)
[00:38:11 -61320.468754] SLOW spr round 3 (radius: 10)
[00:38:28 -61320.468754] SLOW spr round 4 (radius: 15)
[00:38:56 -61320.468754] SLOW spr round 5 (radius: 20)
[00:39:30 -61320.468754] SLOW spr round 6 (radius: 25)
[00:40:03 -61320.468754] Model parameter optimization (eps = 0.100000)

[00:40:05] ML tree search #7, logLikelihood: -61320.432988

[00:40:05 -167286.708948] Initial branch length optimization
[00:40:06 -136513.057050] Model parameter optimization (eps = 10.000000)
[00:40:15 -136160.349389] AUTODETECT spr round 1 (radius: 5)
[00:40:25 -98879.117959] AUTODETECT spr round 2 (radius: 10)
[00:40:38 -76628.397476] AUTODETECT spr round 3 (radius: 15)
[00:40:53 -71381.510502] AUTODETECT spr round 4 (radius: 20)
[00:41:11 -68891.450944] AUTODETECT spr round 5 (radius: 25)
[00:41:29 -68695.097325] SPR radius for FAST iterations: 25 (autodetect)
[00:41:29 -68695.097325] Model parameter optimization (eps = 3.000000)
[00:41:40 -68454.959902] FAST spr round 1 (radius: 25)
[00:41:56 -61671.425136] FAST spr round 2 (radius: 25)
[00:42:09 -61420.448644] FAST spr round 3 (radius: 25)
[00:42:20 -61391.148974] FAST spr round 4 (radius: 25)
[00:42:29 -61390.552773] FAST spr round 5 (radius: 25)
[00:42:37 -61390.552535] Model parameter optimization (eps = 1.000000)
[00:42:47 -61329.044864] SLOW spr round 1 (radius: 5)
[00:43:05 -61320.089412] SLOW spr round 2 (radius: 5)
[00:43:20 -61320.087627] SLOW spr round 3 (radius: 10)
[00:43:37 -61320.087579] SLOW spr round 4 (radius: 15)
[00:44:06 -61320.087577] SLOW spr round 5 (radius: 20)
[00:44:41 -61320.087577] SLOW spr round 6 (radius: 25)
[00:45:13 -61320.087577] Model parameter optimization (eps = 0.100000)

[00:45:15] ML tree search #8, logLikelihood: -61320.036242

[00:45:15 -171532.615499] Initial branch length optimization
[00:45:15 -140182.100562] Model parameter optimization (eps = 10.000000)
[00:45:24 -139729.567277] AUTODETECT spr round 1 (radius: 5)
[00:45:34 -103906.302837] AUTODETECT spr round 2 (radius: 10)
[00:45:47 -79478.274672] AUTODETECT spr round 3 (radius: 15)
[00:46:04 -68560.337708] AUTODETECT spr round 4 (radius: 20)
[00:46:25 -68195.463148] AUTODETECT spr round 5 (radius: 25)
[00:46:45 -68130.305867] SPR radius for FAST iterations: 25 (autodetect)
[00:46:45 -68130.305867] Model parameter optimization (eps = 3.000000)
[00:46:57 -67803.712237] FAST spr round 1 (radius: 25)
[00:47:12 -61600.453351] FAST spr round 2 (radius: 25)
[00:47:24 -61411.933015] FAST spr round 3 (radius: 25)
[00:47:35 -61402.226931] FAST spr round 4 (radius: 25)
[00:47:44 -61398.883900] FAST spr round 5 (radius: 25)
[00:47:53 -61397.676649] FAST spr round 6 (radius: 25)
[00:48:01 -61397.676616] Model parameter optimization (eps = 1.000000)
[00:48:08 -61394.353253] SLOW spr round 1 (radius: 5)
[00:48:26 -61379.189469] SLOW spr round 2 (radius: 5)
[00:48:42 -61379.189261] SLOW spr round 3 (radius: 10)
[00:48:58 -61379.189255] SLOW spr round 4 (radius: 15)
[00:49:28 -61379.189255] SLOW spr round 5 (radius: 20)
[00:50:02 -61379.189255] SLOW spr round 6 (radius: 25)
[00:50:34 -61379.189255] Model parameter optimization (eps = 0.100000)

[00:50:41] ML tree search #9, logLikelihood: -61320.588702

[00:50:41 -168431.893121] Initial branch length optimization
[00:50:42 -138155.709922] Model parameter optimization (eps = 10.000000)
[00:50:50 -137771.909384] AUTODETECT spr round 1 (radius: 5)
[00:51:00 -102488.147812] AUTODETECT spr round 2 (radius: 10)
[00:51:14 -78541.162424] AUTODETECT spr round 3 (radius: 15)
[00:51:31 -70081.255511] AUTODETECT spr round 4 (radius: 20)
[00:51:51 -69926.588936] AUTODETECT spr round 5 (radius: 25)
[00:52:09 -69925.654469] SPR radius for FAST iterations: 25 (autodetect)
[00:52:09 -69925.654469] Model parameter optimization (eps = 3.000000)
[00:52:22 -69655.983259] FAST spr round 1 (radius: 25)
[00:52:37 -61577.807387] FAST spr round 2 (radius: 25)
[00:52:50 -61348.891164] FAST spr round 3 (radius: 25)
[00:53:00 -61342.244726] FAST spr round 4 (radius: 25)
[00:53:09 -61341.504066] FAST spr round 5 (radius: 25)
[00:53:17 -61341.504024] Model parameter optimization (eps = 1.000000)
[00:53:24 -61333.007595] SLOW spr round 1 (radius: 5)
[00:53:42 -61325.537438] SLOW spr round 2 (radius: 5)
[00:53:57 -61325.537224] SLOW spr round 3 (radius: 10)
[00:54:14 -61325.537223] SLOW spr round 4 (radius: 15)
[00:54:44 -61325.537223] SLOW spr round 5 (radius: 20)
[00:55:23 -61325.537223] SLOW spr round 6 (radius: 25)
[00:55:54 -61325.537223] Model parameter optimization (eps = 0.100000)

[00:55:58] ML tree search #10, logLikelihood: -61325.421754

[00:55:58 -168665.643286] Initial branch length optimization
[00:55:58 -137960.305505] Model parameter optimization (eps = 10.000000)
[00:56:07 -137511.912050] AUTODETECT spr round 1 (radius: 5)
[00:56:17 -102174.839087] AUTODETECT spr round 2 (radius: 10)
[00:56:30 -78536.626684] AUTODETECT spr round 3 (radius: 15)
[00:56:47 -71588.383157] AUTODETECT spr round 4 (radius: 20)
[00:57:05 -69469.864004] AUTODETECT spr round 5 (radius: 25)
[00:57:22 -69467.534553] SPR radius for FAST iterations: 25 (autodetect)
[00:57:22 -69467.534553] Model parameter optimization (eps = 3.000000)
[00:57:32 -69129.153142] FAST spr round 1 (radius: 25)
[00:57:46 -61668.243411] FAST spr round 2 (radius: 25)
[00:57:59 -61362.329520] FAST spr round 3 (radius: 25)
[00:58:11 -61338.803257] FAST spr round 4 (radius: 25)
[00:58:20 -61338.802029] Model parameter optimization (eps = 1.000000)
[00:58:25 -61333.300659] SLOW spr round 1 (radius: 5)
[00:58:42 -61327.285300] SLOW spr round 2 (radius: 5)
[00:58:58 -61327.285241] SLOW spr round 3 (radius: 10)
[00:59:14 -61327.285240] SLOW spr round 4 (radius: 15)
[00:59:44 -61327.285240] SLOW spr round 5 (radius: 20)
[01:00:19 -61327.285240] SLOW spr round 6 (radius: 25)
[01:00:51 -61327.285240] Model parameter optimization (eps = 0.100000)

[01:00:53] ML tree search #11, logLikelihood: -61327.276244

[01:00:53 -170773.089205] Initial branch length optimization
[01:00:53 -138494.978397] Model parameter optimization (eps = 10.000000)
[01:01:02 -138097.451490] AUTODETECT spr round 1 (radius: 5)
[01:01:13 -100483.123230] AUTODETECT spr round 2 (radius: 10)
[01:01:26 -76934.075529] AUTODETECT spr round 3 (radius: 15)
[01:01:43 -67840.168675] AUTODETECT spr round 4 (radius: 20)
[01:02:03 -67548.342383] AUTODETECT spr round 5 (radius: 25)
[01:02:22 -67548.314984] SPR radius for FAST iterations: 20 (autodetect)
[01:02:22 -67548.314984] Model parameter optimization (eps = 3.000000)
[01:02:32 -67145.003514] FAST spr round 1 (radius: 20)
[01:02:46 -61571.741464] FAST spr round 2 (radius: 20)
[01:02:58 -61420.137051] FAST spr round 3 (radius: 20)
[01:03:09 -61403.131232] FAST spr round 4 (radius: 20)
[01:03:18 -61400.457796] FAST spr round 5 (radius: 20)
[01:03:27 -61400.457662] Model parameter optimization (eps = 1.000000)
[01:03:37 -61394.707832] SLOW spr round 1 (radius: 5)
[01:03:55 -61381.948435] SLOW spr round 2 (radius: 5)
[01:04:11 -61381.640120] SLOW spr round 3 (radius: 5)
[01:04:26 -61381.640075] SLOW spr round 4 (radius: 10)
[01:04:43 -61379.412357] SLOW spr round 5 (radius: 5)
[01:05:05 -61379.412322] SLOW spr round 6 (radius: 10)
[01:05:25 -61379.412321] SLOW spr round 7 (radius: 15)
[01:05:53 -61379.412321] SLOW spr round 8 (radius: 20)
[01:06:27 -61379.412321] SLOW spr round 9 (radius: 25)
[01:06:59 -61379.412321] Model parameter optimization (eps = 0.100000)

[01:07:06] ML tree search #12, logLikelihood: -61318.393097

[01:07:06 -169540.079759] Initial branch length optimization
[01:07:07 -139500.129313] Model parameter optimization (eps = 10.000000)
[01:07:17 -138932.563191] AUTODETECT spr round 1 (radius: 5)
[01:07:27 -101028.649079] AUTODETECT spr round 2 (radius: 10)
[01:07:40 -79025.802589] AUTODETECT spr round 3 (radius: 15)
[01:07:57 -71067.429040] AUTODETECT spr round 4 (radius: 20)
[01:08:16 -69871.520175] AUTODETECT spr round 5 (radius: 25)
[01:08:36 -69583.022881] SPR radius for FAST iterations: 25 (autodetect)
[01:08:36 -69583.022881] Model parameter optimization (eps = 3.000000)
[01:08:44 -69257.003984] FAST spr round 1 (radius: 25)
[01:09:01 -61637.630535] FAST spr round 2 (radius: 25)
[01:09:13 -61449.093903] FAST spr round 3 (radius: 25)
[01:09:24 -61405.182136] FAST spr round 4 (radius: 25)
[01:09:33 -61405.181099] Model parameter optimization (eps = 1.000000)
[01:09:48 -61347.603651] SLOW spr round 1 (radius: 5)
[01:10:06 -61329.557526] SLOW spr round 2 (radius: 5)
[01:10:22 -61327.770095] SLOW spr round 3 (radius: 5)
[01:10:38 -61324.830144] SLOW spr round 4 (radius: 5)
[01:10:53 -61324.829521] SLOW spr round 5 (radius: 10)
[01:11:09 -61321.412126] SLOW spr round 6 (radius: 5)
[01:11:31 -61321.411900] SLOW spr round 7 (radius: 10)
[01:11:51 -61321.411900] SLOW spr round 8 (radius: 15)
[01:12:19 -61321.411900] SLOW spr round 9 (radius: 20)
[01:12:55 -61321.411900] SLOW spr round 10 (radius: 25)
[01:13:27 -61321.411900] Model parameter optimization (eps = 0.100000)

[01:13:32] ML tree search #13, logLikelihood: -61320.534782

[01:13:32 -170313.216856] Initial branch length optimization
[01:13:33 -138890.787237] Model parameter optimization (eps = 10.000000)
[01:13:40 -138520.991998] AUTODETECT spr round 1 (radius: 5)
[01:13:51 -102269.286392] AUTODETECT spr round 2 (radius: 10)
[01:14:04 -80626.454732] AUTODETECT spr round 3 (radius: 15)
[01:14:21 -69048.884358] AUTODETECT spr round 4 (radius: 20)
[01:14:40 -68313.157099] AUTODETECT spr round 5 (radius: 25)
[01:14:59 -68304.246885] SPR radius for FAST iterations: 25 (autodetect)
[01:14:59 -68304.246885] Model parameter optimization (eps = 3.000000)
[01:15:08 -68077.292619] FAST spr round 1 (radius: 25)
[01:15:22 -61841.130089] FAST spr round 2 (radius: 25)
[01:15:35 -61419.577156] FAST spr round 3 (radius: 25)
[01:15:45 -61409.632227] FAST spr round 4 (radius: 25)
[01:15:54 -61408.531287] FAST spr round 5 (radius: 25)
[01:16:04 -61401.665550] FAST spr round 6 (radius: 25)
[01:16:13 -61401.665482] Model parameter optimization (eps = 1.000000)
[01:16:17 -61398.177642] SLOW spr round 1 (radius: 5)
[01:16:36 -61391.072972] SLOW spr round 2 (radius: 5)
[01:16:51 -61390.215644] SLOW spr round 3 (radius: 5)
[01:17:06 -61390.215037] SLOW spr round 4 (radius: 10)
[01:17:23 -61389.689684] SLOW spr round 5 (radius: 5)
[01:17:44 -61389.689667] SLOW spr round 6 (radius: 10)
[01:18:04 -61389.325496] SLOW spr round 7 (radius: 5)
[01:18:25 -61389.325493] SLOW spr round 8 (radius: 10)
[01:18:43 -61389.325493] SLOW spr round 9 (radius: 15)
[01:19:10 -61389.325493] SLOW spr round 10 (radius: 20)
[01:19:43 -61389.325493] SLOW spr round 11 (radius: 25)
[01:20:15 -61389.325493] Model parameter optimization (eps = 0.100000)

[01:20:18] ML tree search #14, logLikelihood: -61389.297297

[01:20:18 -169050.033347] Initial branch length optimization
[01:20:18 -138080.744553] Model parameter optimization (eps = 10.000000)
[01:20:27 -137613.119008] AUTODETECT spr round 1 (radius: 5)
[01:20:38 -99472.708884] AUTODETECT spr round 2 (radius: 10)
[01:20:51 -78237.984455] AUTODETECT spr round 3 (radius: 15)
[01:21:07 -67502.740280] AUTODETECT spr round 4 (radius: 20)
[01:21:24 -66910.529623] AUTODETECT spr round 5 (radius: 25)
[01:21:44 -66910.501322] SPR radius for FAST iterations: 20 (autodetect)
[01:21:44 -66910.501322] Model parameter optimization (eps = 3.000000)
[01:21:53 -66579.591191] FAST spr round 1 (radius: 20)
[01:22:07 -61542.135455] FAST spr round 2 (radius: 20)
[01:22:19 -61358.961811] FAST spr round 3 (radius: 20)
[01:22:29 -61347.836949] FAST spr round 4 (radius: 20)
[01:22:38 -61344.675392] FAST spr round 5 (radius: 20)
[01:22:47 -61344.675380] Model parameter optimization (eps = 1.000000)
[01:22:54 -61341.556398] SLOW spr round 1 (radius: 5)
[01:23:11 -61322.132454] SLOW spr round 2 (radius: 5)
[01:23:27 -61321.244249] SLOW spr round 3 (radius: 5)
[01:23:43 -61321.244108] SLOW spr round 4 (radius: 10)
[01:23:59 -61321.244104] SLOW spr round 5 (radius: 15)
[01:24:27 -61321.244103] SLOW spr round 6 (radius: 20)
[01:25:00 -61321.244103] SLOW spr round 7 (radius: 25)
[01:25:33 -61321.244103] Model parameter optimization (eps = 0.100000)

[01:25:36] ML tree search #15, logLikelihood: -61320.913093

[01:25:36 -169016.650024] Initial branch length optimization
[01:25:37 -137409.049082] Model parameter optimization (eps = 10.000000)
[01:25:47 -136979.898993] AUTODETECT spr round 1 (radius: 5)
[01:25:57 -104111.354644] AUTODETECT spr round 2 (radius: 10)
[01:26:10 -75289.905160] AUTODETECT spr round 3 (radius: 15)
[01:26:29 -68139.028062] AUTODETECT spr round 4 (radius: 20)
[01:26:54 -68007.258421] AUTODETECT spr round 5 (radius: 25)
[01:27:14 -68007.229704] SPR radius for FAST iterations: 20 (autodetect)
[01:27:14 -68007.229704] Model parameter optimization (eps = 3.000000)
[01:27:25 -67620.619736] FAST spr round 1 (radius: 20)
[01:27:42 -61507.796115] FAST spr round 2 (radius: 20)
[01:27:54 -61366.837383] FAST spr round 3 (radius: 20)
[01:28:04 -61356.709000] FAST spr round 4 (radius: 20)
[01:28:13 -61356.708974] Model parameter optimization (eps = 1.000000)
[01:28:20 -61343.916072] SLOW spr round 1 (radius: 5)
[01:28:37 -61325.503245] SLOW spr round 2 (radius: 5)
[01:28:53 -61325.061322] SLOW spr round 3 (radius: 5)
[01:29:08 -61325.060727] SLOW spr round 4 (radius: 10)
[01:29:24 -61325.060708] SLOW spr round 5 (radius: 15)
[01:29:54 -61320.585226] SLOW spr round 6 (radius: 5)
[01:30:17 -61320.344022] SLOW spr round 7 (radius: 5)
[01:30:36 -61319.732477] SLOW spr round 8 (radius: 5)
[01:30:53 -61319.732374] SLOW spr round 9 (radius: 10)
[01:31:10 -61319.732372] SLOW spr round 10 (radius: 15)
[01:31:39 -61319.732372] SLOW spr round 11 (radius: 20)
[01:32:13 -61319.732372] SLOW spr round 12 (radius: 25)
[01:32:45 -61319.732372] Model parameter optimization (eps = 0.100000)

[01:32:48] ML tree search #16, logLikelihood: -61319.594951

[01:32:48 -169540.556301] Initial branch length optimization
[01:32:49 -139753.773156] Model parameter optimization (eps = 10.000000)
[01:32:58 -139108.347190] AUTODETECT spr round 1 (radius: 5)
[01:33:08 -100018.589198] AUTODETECT spr round 2 (radius: 10)
[01:33:21 -79056.558922] AUTODETECT spr round 3 (radius: 15)
[01:33:39 -70073.649902] AUTODETECT spr round 4 (radius: 20)
[01:33:58 -69375.288271] AUTODETECT spr round 5 (radius: 25)
[01:34:19 -69370.680600] SPR radius for FAST iterations: 25 (autodetect)
[01:34:19 -69370.680600] Model parameter optimization (eps = 3.000000)
[01:34:27 -69102.979378] FAST spr round 1 (radius: 25)
[01:34:41 -61568.808587] FAST spr round 2 (radius: 25)
[01:34:52 -61368.735762] FAST spr round 3 (radius: 25)
[01:35:02 -61362.881170] FAST spr round 4 (radius: 25)
[01:35:11 -61359.868904] FAST spr round 5 (radius: 25)
[01:35:20 -61359.868638] Model parameter optimization (eps = 1.000000)
[01:35:27 -61339.149600] SLOW spr round 1 (radius: 5)
[01:35:44 -61322.235912] SLOW spr round 2 (radius: 5)
[01:36:00 -61318.798877] SLOW spr round 3 (radius: 5)
[01:36:16 -61314.645359] SLOW spr round 4 (radius: 5)
[01:36:31 -61314.645111] SLOW spr round 5 (radius: 10)
[01:36:48 -61314.645108] SLOW spr round 6 (radius: 15)
[01:37:16 -61314.645108] SLOW spr round 7 (radius: 20)
[01:37:49 -61314.645108] SLOW spr round 8 (radius: 25)
[01:38:21 -61314.645108] Model parameter optimization (eps = 0.100000)

[01:38:23] ML tree search #17, logLikelihood: -61314.631240

[01:38:23 -170690.865520] Initial branch length optimization
[01:38:23 -139878.859431] Model parameter optimization (eps = 10.000000)
[01:38:35 -139325.717677] AUTODETECT spr round 1 (radius: 5)
[01:38:45 -103397.507533] AUTODETECT spr round 2 (radius: 10)
[01:38:59 -76050.779651] AUTODETECT spr round 3 (radius: 15)
[01:39:15 -68152.037972] AUTODETECT spr round 4 (radius: 20)
[01:39:33 -67909.866714] AUTODETECT spr round 5 (radius: 25)
[01:39:54 -67909.856686] SPR radius for FAST iterations: 20 (autodetect)
[01:39:54 -67909.856686] Model parameter optimization (eps = 3.000000)
[01:40:16 -67353.475643] FAST spr round 1 (radius: 20)
[01:40:30 -61483.403614] FAST spr round 2 (radius: 20)
[01:40:41 -61342.645555] FAST spr round 3 (radius: 20)
[01:40:51 -61338.716333] FAST spr round 4 (radius: 20)
[01:41:00 -61338.715856] Model parameter optimization (eps = 1.000000)
[01:41:05 -61330.583163] SLOW spr round 1 (radius: 5)
[01:41:23 -61321.651614] SLOW spr round 2 (radius: 5)
[01:41:39 -61318.109136] SLOW spr round 3 (radius: 5)
[01:41:54 -61318.105498] SLOW spr round 4 (radius: 10)
[01:42:11 -61318.105498] SLOW spr round 5 (radius: 15)
[01:42:41 -61318.105498] SLOW spr round 6 (radius: 20)
[01:43:16 -61318.105498] SLOW spr round 7 (radius: 25)
[01:43:47 -61318.105498] Model parameter optimization (eps = 0.100000)

[01:43:49] ML tree search #18, logLikelihood: -61318.087485

[01:43:49 -169503.733848] Initial branch length optimization
[01:43:49 -138130.128400] Model parameter optimization (eps = 10.000000)
[01:43:59 -137783.344589] AUTODETECT spr round 1 (radius: 5)
[01:44:09 -102062.786082] AUTODETECT spr round 2 (radius: 10)
[01:44:22 -80904.521116] AUTODETECT spr round 3 (radius: 15)
[01:44:38 -70114.612091] AUTODETECT spr round 4 (radius: 20)
[01:44:55 -68307.256823] AUTODETECT spr round 5 (radius: 25)
[01:45:13 -68297.820443] SPR radius for FAST iterations: 25 (autodetect)
[01:45:13 -68297.820443] Model parameter optimization (eps = 3.000000)
[01:45:23 -67887.729777] FAST spr round 1 (radius: 25)
[01:45:38 -61590.018203] FAST spr round 2 (radius: 25)
[01:45:51 -61372.770931] FAST spr round 3 (radius: 25)
[01:46:01 -61362.711287] FAST spr round 4 (radius: 25)
[01:46:10 -61361.449595] FAST spr round 5 (radius: 25)
[01:46:19 -61361.440118] Model parameter optimization (eps = 1.000000)
[01:46:30 -61341.673836] SLOW spr round 1 (radius: 5)
[01:46:48 -61321.015171] SLOW spr round 2 (radius: 5)
[01:47:04 -61318.662523] SLOW spr round 3 (radius: 5)
[01:47:19 -61318.662420] SLOW spr round 4 (radius: 10)
[01:47:36 -61318.662420] SLOW spr round 5 (radius: 15)
[01:48:05 -61318.662420] SLOW spr round 6 (radius: 20)
[01:48:38 -61318.662420] SLOW spr round 7 (radius: 25)
[01:49:10 -61318.662420] Model parameter optimization (eps = 0.100000)

[01:49:13] ML tree search #19, logLikelihood: -61318.505421

[01:49:13 -170494.447887] Initial branch length optimization
[01:49:13 -140659.825548] Model parameter optimization (eps = 10.000000)
[01:49:26 -140097.067294] AUTODETECT spr round 1 (radius: 5)
[01:49:36 -101397.668563] AUTODETECT spr round 2 (radius: 10)
[01:49:49 -75109.790513] AUTODETECT spr round 3 (radius: 15)
[01:50:05 -68826.341930] AUTODETECT spr round 4 (radius: 20)
[01:50:25 -68686.089021] AUTODETECT spr round 5 (radius: 25)
[01:50:43 -68683.840397] SPR radius for FAST iterations: 25 (autodetect)
[01:50:43 -68683.840397] Model parameter optimization (eps = 3.000000)
[01:50:54 -68343.938382] FAST spr round 1 (radius: 25)
[01:51:08 -61571.791942] FAST spr round 2 (radius: 25)
[01:51:20 -61354.325978] FAST spr round 3 (radius: 25)
[01:51:31 -61330.935082] FAST spr round 4 (radius: 25)
[01:51:40 -61324.210772] FAST spr round 5 (radius: 25)
[01:51:49 -61324.210756] Model parameter optimization (eps = 1.000000)
[01:51:53 -61322.890918] SLOW spr round 1 (radius: 5)
[01:52:09 -61321.976804] SLOW spr round 2 (radius: 5)
[01:52:24 -61321.976782] SLOW spr round 3 (radius: 10)
[01:52:41 -61321.227938] SLOW spr round 4 (radius: 5)
[01:53:03 -61321.226924] SLOW spr round 5 (radius: 10)
[01:53:23 -61321.226903] SLOW spr round 6 (radius: 15)
[01:53:51 -61321.226903] SLOW spr round 7 (radius: 20)
[01:54:27 -61321.226903] SLOW spr round 8 (radius: 25)
[01:54:59 -61321.226902] Model parameter optimization (eps = 0.100000)

[01:55:01] ML tree search #20, logLikelihood: -61321.133134


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.143306,0.523871) (0.100036,1.291460) (0.242434,0.571665) (0.514224,1.277931) 
   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: -61313.279247

AIC score: 123776.558494 / AICc score: 786176.558494 / BIC score: 126249.510326
Free parameters (model + branch lengths): 575

WARNING: Number of free parameters (K=575) is larger than alignment size (n=545).
         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/Q5XG99/3_mltree/Q5XG99.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/3_mltree/Q5XG99.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/3_mltree/Q5XG99.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5XG99/3_mltree/Q5XG99.raxml.log

Analysis started: 15-Jul-2021 11:02:42 / finished: 15-Jul-2021 12:57:43

Elapsed time: 6901.784 seconds