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 06-Jul-2021 15:54:33 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/2_msa/A0A087WSX0_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0 --seed 2 --threads 2 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (2 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/2_msa/A0A087WSX0_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 104 sites

WARNING: Sequences sp_P04210_LV1_CHICK_9031 and tr_R9PXM5_R9PXM5_CHICK_9031 are exactly identical!
WARNING: Sequences tr_A0A2I2YJC5_A0A2I2YJC5_GORGO_9595 and tr_A0A2I3RV96_A0A2I3RV96_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3RK08_G3RK08_GORGO_9595 and tr_A0A2I3S3B0_A0A2I3S3B0_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3RK08_G3RK08_GORGO_9595 and sp_P12018_VPREB_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G3RK08_G3RK08_GORGO_9595 and tr_A0A2R9BNT9_A0A2R9BNT9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G3SDJ0_G3SDJ0_GORGO_9595 and tr_H2QLC7_H2QLC7_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3SDJ0_G3SDJ0_GORGO_9595 and tr_A0A2R9ALJ8_A0A2R9ALJ8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2P3Q5_H2P3Q5_PONAB_9601 and tr_F7DFA6_F7DFA6_MACMU_9544 are exactly identical!
WARNING: Sequences tr_H2P3Q5_H2P3Q5_PONAB_9601 and tr_G8F424_G8F424_MACFA_9541 are exactly identical!
WARNING: Sequences tr_H2P3Q5_H2P3Q5_PONAB_9601 and tr_A0A0D9RMS9_A0A0D9RMS9_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_J9P8P3_J9P8P3_CANLF_9615 and tr_J9PAD4_J9PAD4_CANLF_9615 are exactly identical!
WARNING: Sequences tr_A0A2I3SR69_A0A2I3SR69_PANTR_9598 and tr_A0A2R8ZB48_A0A2R8ZB48_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3T0N1_A0A2I3T0N1_PANTR_9598 and tr_A0A2R8ZDA9_A0A2R8ZDA9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TQF9_A0A2I3TQF9_PANTR_9598 and tr_A0A2R8ZQY1_A0A2R8ZQY1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TUR2_A0A2I3TUR2_PANTR_9598 and tr_A0A2R8ZX92_A0A2R8ZX92_PANPA_9597 are exactly identical!
WARNING: Sequences sp_A0A0B4J1Y8_LV949_HUMAN_9606 and tr_A0A2R9A2R6_A0A2R9A2R6_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5QR47_A0A1D5QR47_MACMU_9544 and tr_G8F2W8_G8F2W8_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F6SWU6_F6SWU6_MACMU_9544 and tr_G8F5L7_G8F5L7_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7F215_F7F215_MACMU_9544 and tr_A0A2K6ARQ7_A0A2K6ARQ7_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_G8F609_G8F609_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A0D9RG94_A0A0D9RG94_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K5M4Y2_A0A2K5M4Y2_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K6BRF2_A0A2K6BRF2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G8F1D9_G8F1D9_MACMU_9544 and tr_A0A2K5Y552_A0A2K5Y552_MANLE_9568 are exactly identical!
WARNING: Sequences tr_H9H4S2_H9H4S2_MACMU_9544 and tr_H9H5B4_H9H5B4_MACMU_9544 are exactly identical!
WARNING: Sequences tr_A0A2R8MJT0_A0A2R8MJT0_CALJA_9483 and tr_A0A2R8P774_A0A2R8P774_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G7PHB9_G7PHB9_MACFA_9541 and tr_A0A096NSB1_A0A096NSB1_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G7PHB9_G7PHB9_MACFA_9541 and tr_A0A2K5XPA3_A0A2K5XPA3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A096NRF9_A0A096NRF9_PAPAN_9555 and tr_A0A2K6ADQ1_A0A2K6ADQ1_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A0D9RN59_A0A0D9RN59_CHLSB_60711 and tr_A0A0D9RN85_A0A0D9RN85_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A2K5KMJ7_A0A2K5KMJ7_CERAT_9531 and tr_A0A2K5XYB4_A0A2K5XYB4_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 31

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/A0A087WSX0/3_mltree/A0A087WSX0.raxml.reduced.phy

Alignment comprises 1 partitions and 104 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 104 / 104
Gaps: 4.34 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 1 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 104 / 8320
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -152380.461911] Initial branch length optimization
[00:00:02 -134307.788996] Model parameter optimization (eps = 10.000000)
[00:00:30 -134076.973408] AUTODETECT spr round 1 (radius: 5)
[00:02:17 -95017.892126] AUTODETECT spr round 2 (radius: 10)
[00:04:08 -72665.426378] AUTODETECT spr round 3 (radius: 15)
[00:06:13 -64038.121399] AUTODETECT spr round 4 (radius: 20)
[00:08:43 -59200.348475] AUTODETECT spr round 5 (radius: 25)
[00:11:23 -57710.222377] SPR radius for FAST iterations: 25 (autodetect)
[00:11:23 -57710.222377] Model parameter optimization (eps = 3.000000)
[00:11:41 -57430.556818] FAST spr round 1 (radius: 25)
[00:13:52 -50242.923607] FAST spr round 2 (radius: 25)
[00:15:38 -49747.739228] FAST spr round 3 (radius: 25)
[00:17:11 -49690.022218] FAST spr round 4 (radius: 25)
[00:18:38 -49674.842586] FAST spr round 5 (radius: 25)
[00:20:01 -49674.842417] Model parameter optimization (eps = 1.000000)
[00:20:11 -49672.675617] SLOW spr round 1 (radius: 5)
[00:22:01 -49660.671098] SLOW spr round 2 (radius: 5)
[00:23:48 -49656.170484] SLOW spr round 3 (radius: 5)
[00:25:30 -49655.701347] SLOW spr round 4 (radius: 5)
[00:27:09 -49655.701285] SLOW spr round 5 (radius: 10)
[00:28:51 -49654.758468] SLOW spr round 6 (radius: 5)
[00:30:55 -49652.583157] SLOW spr round 7 (radius: 5)
[00:32:46 -49652.583077] SLOW spr round 8 (radius: 10)
[00:34:28 -49651.697294] SLOW spr round 9 (radius: 5)
[00:36:29 -49651.697264] SLOW spr round 10 (radius: 10)
[00:38:18 -49651.697235] SLOW spr round 11 (radius: 15)
[00:40:48 -49651.181873] SLOW spr round 12 (radius: 5)
[00:42:56 -49650.432930] SLOW spr round 13 (radius: 5)
[00:44:49 -49650.432921] SLOW spr round 14 (radius: 10)
[00:46:34 -49650.286114] SLOW spr round 15 (radius: 5)
[00:48:36 -49650.286076] SLOW spr round 16 (radius: 10)
[00:50:24 -49650.286072] SLOW spr round 17 (radius: 15)
[00:52:55 -49650.286068] SLOW spr round 18 (radius: 20)
[00:56:40 -49650.286063] SLOW spr round 19 (radius: 25)
[01:01:12 -49650.286059] Model parameter optimization (eps = 0.100000)

[01:01:16] [worker #0] ML tree search #1, logLikelihood: -49650.256194

[01:01:17 -152148.351240] Initial branch length optimization
[01:01:19 -134043.588104] Model parameter optimization (eps = 10.000000)
[01:01:49 -133847.699095] AUTODETECT spr round 1 (radius: 5)
[01:03:37 -98360.481393] AUTODETECT spr round 2 (radius: 10)
[01:05:28 -76275.266302] AUTODETECT spr round 3 (radius: 15)
[01:07:39 -64377.334443] AUTODETECT spr round 4 (radius: 20)
[01:10:11 -60648.070549] AUTODETECT spr round 5 (radius: 25)
[01:11:02] [worker #1] ML tree search #2, logLikelihood: -49651.548140
[01:13:01 -59063.911037] SPR radius for FAST iterations: 25 (autodetect)
[01:13:01 -59063.911037] Model parameter optimization (eps = 3.000000)
[01:13:08 -59060.177359] FAST spr round 1 (radius: 25)
[01:15:25 -50663.515658] FAST spr round 2 (radius: 25)
[01:17:13 -50068.708291] FAST spr round 3 (radius: 25)
[01:18:50 -50024.367513] FAST spr round 4 (radius: 25)
[01:20:19 -50017.538161] FAST spr round 5 (radius: 25)
[01:21:43 -50017.537670] Model parameter optimization (eps = 1.000000)
[01:22:03 -49799.102199] SLOW spr round 1 (radius: 5)
[01:23:54 -49771.841659] SLOW spr round 2 (radius: 5)
[01:25:42 -49767.744643] SLOW spr round 3 (radius: 5)
[01:27:28 -49758.743623] SLOW spr round 4 (radius: 5)
[01:29:10 -49757.408738] SLOW spr round 5 (radius: 5)
[01:30:51 -49757.408593] SLOW spr round 6 (radius: 10)
[01:32:34 -49754.139928] SLOW spr round 7 (radius: 5)
[01:34:38 -49751.551410] SLOW spr round 8 (radius: 5)
[01:36:30 -49751.367540] SLOW spr round 9 (radius: 5)
[01:38:14 -49751.367372] SLOW spr round 10 (radius: 10)
[01:39:56 -49751.097862] SLOW spr round 11 (radius: 5)
[01:41:57 -49751.097632] SLOW spr round 12 (radius: 10)
[01:43:47 -49751.097621] SLOW spr round 13 (radius: 15)
[01:46:09 -49750.486699] SLOW spr round 14 (radius: 5)
[01:48:17 -49748.779578] SLOW spr round 15 (radius: 5)
[01:50:11 -49748.779386] SLOW spr round 16 (radius: 10)
[01:51:57 -49747.948291] SLOW spr round 17 (radius: 5)
[01:54:02 -49746.162083] SLOW spr round 18 (radius: 5)
[01:55:52 -49746.161954] SLOW spr round 19 (radius: 10)
[01:57:37 -49746.161948] SLOW spr round 20 (radius: 15)
[02:00:03 -49745.875964] SLOW spr round 21 (radius: 5)
[02:02:11 -49744.668335] SLOW spr round 22 (radius: 5)
[02:04:06 -49743.199065] SLOW spr round 23 (radius: 5)
[02:05:54 -49743.197557] SLOW spr round 24 (radius: 10)
[02:07:38 -49742.885751] SLOW spr round 25 (radius: 5)
[02:09:43 -49740.474972] SLOW spr round 26 (radius: 5)
[02:11:33 -49740.474953] SLOW spr round 27 (radius: 10)
[02:13:18 -49740.474936] SLOW spr round 28 (radius: 15)
[02:15:47 -49740.030446] SLOW spr round 29 (radius: 5)
[02:17:53 -49740.030417] SLOW spr round 30 (radius: 10)
[02:19:47 -49740.030401] SLOW spr round 31 (radius: 15)
[02:22:09 -49740.030385] SLOW spr round 32 (radius: 20)
[02:25:32 -49739.376065] SLOW spr round 33 (radius: 5)
[02:27:40 -49739.376050] SLOW spr round 34 (radius: 10)
[02:29:37 -49739.376034] SLOW spr round 35 (radius: 15)
[02:31:59 -49739.376019] SLOW spr round 36 (radius: 20)
[02:35:23 -49739.376004] SLOW spr round 37 (radius: 25)
[02:39:51 -49739.312030] Model parameter optimization (eps = 0.100000)

[02:39:56] [worker #0] ML tree search #3, logLikelihood: -49739.237871

[02:39:56 -152494.628602] Initial branch length optimization
[02:39:58 -134357.039481] Model parameter optimization (eps = 10.000000)
[02:40:22 -134155.442375] AUTODETECT spr round 1 (radius: 5)
[02:42:10 -96402.588555] AUTODETECT spr round 2 (radius: 10)
[02:44:06 -72316.376345] AUTODETECT spr round 3 (radius: 15)
[02:46:18 -62001.193789] AUTODETECT spr round 4 (radius: 20)
[02:48:50 -57886.458039] AUTODETECT spr round 5 (radius: 25)
[02:51:35 -57368.838266] SPR radius for FAST iterations: 25 (autodetect)
[02:51:35 -57368.838266] Model parameter optimization (eps = 3.000000)
[02:51:53 -57134.566830] FAST spr round 1 (radius: 25)
[02:52:04] [worker #1] ML tree search #4, logLikelihood: -49663.607709
[02:54:11 -50225.974876] FAST spr round 2 (radius: 25)
[02:55:59 -49758.715158] FAST spr round 3 (radius: 25)
[02:57:37 -49677.134860] FAST spr round 4 (radius: 25)
[02:59:08 -49666.427559] FAST spr round 5 (radius: 25)
[03:00:33 -49665.255259] FAST spr round 6 (radius: 25)
[03:01:57 -49665.254152] Model parameter optimization (eps = 1.000000)
[03:02:06 -49663.354199] SLOW spr round 1 (radius: 5)
[03:03:55 -49658.419518] SLOW spr round 2 (radius: 5)
[03:05:39 -49658.419356] SLOW spr round 3 (radius: 10)
[03:07:23 -49657.995519] SLOW spr round 4 (radius: 5)
[03:09:28 -49657.834927] SLOW spr round 5 (radius: 5)
[03:11:20 -49657.834911] SLOW spr round 6 (radius: 10)
[03:13:06 -49657.427755] SLOW spr round 7 (radius: 5)
[03:15:08 -49657.427669] SLOW spr round 8 (radius: 10)
[03:16:59 -49657.038555] SLOW spr round 9 (radius: 5)
[03:19:00 -49657.038074] SLOW spr round 10 (radius: 10)
[03:20:49 -49657.038051] SLOW spr round 11 (radius: 15)
[03:23:18 -49657.038036] SLOW spr round 12 (radius: 20)
[03:26:57 -49657.038022] SLOW spr round 13 (radius: 25)
[03:31:44 -49657.038008] Model parameter optimization (eps = 0.100000)

[03:31:52] [worker #0] ML tree search #5, logLikelihood: -49656.744706

[03:31:52 -151835.759212] Initial branch length optimization
[03:31:54 -133915.807015] Model parameter optimization (eps = 10.000000)
[03:32:26 -133781.835869] AUTODETECT spr round 1 (radius: 5)
[03:34:12 -97732.335720] AUTODETECT spr round 2 (radius: 10)
[03:36:08 -73298.916933] AUTODETECT spr round 3 (radius: 15)
[03:38:17 -61702.603701] AUTODETECT spr round 4 (radius: 20)
[03:40:43 -57703.503427] AUTODETECT spr round 5 (radius: 25)
[03:43:33 -57018.267020] SPR radius for FAST iterations: 25 (autodetect)
[03:43:33 -57018.267020] Model parameter optimization (eps = 3.000000)
[03:43:56 -56785.287021] FAST spr round 1 (radius: 25)
[03:46:08 -50165.623081] FAST spr round 2 (radius: 25)
[03:47:52 -49772.414127] FAST spr round 3 (radius: 25)
[03:49:29 -49695.831666] FAST spr round 4 (radius: 25)
[03:50:56 -49686.652945] FAST spr round 5 (radius: 25)
[03:52:20 -49686.214920] FAST spr round 6 (radius: 25)
[03:53:42 -49686.214776] Model parameter optimization (eps = 1.000000)
[03:53:57 -49667.812129] SLOW spr round 1 (radius: 5)
[03:55:46 -49645.811904] SLOW spr round 2 (radius: 5)
[03:57:30 -49643.795904] SLOW spr round 3 (radius: 5)
[03:59:10 -49643.795712] SLOW spr round 4 (radius: 10)
[04:00:54 -49640.311907] SLOW spr round 5 (radius: 5)
[04:02:55 -49640.311712] SLOW spr round 6 (radius: 10)
[04:04:46 -49640.311606] SLOW spr round 7 (radius: 15)
[04:07:10 -49639.069510] SLOW spr round 8 (radius: 5)
[04:09:15 -49639.069375] SLOW spr round 9 (radius: 10)
[04:11:10 -49639.069257] SLOW spr round 10 (radius: 15)
[04:13:32 -49639.069134] SLOW spr round 11 (radius: 20)
[04:16:48 -49639.069002] SLOW spr round 12 (radius: 25)
[04:18:14] [worker #1] ML tree search #6, logLikelihood: -49671.371545
[04:20:59 -49638.336278] SLOW spr round 13 (radius: 5)
[04:23:06 -49638.336055] SLOW spr round 14 (radius: 10)
[04:25:05 -49638.335848] SLOW spr round 15 (radius: 15)
[04:27:26 -49638.335585] SLOW spr round 16 (radius: 20)
[04:30:43 -49638.335227] SLOW spr round 17 (radius: 25)
[04:34:55 -49638.334935] Model parameter optimization (eps = 0.100000)

[04:34:59] [worker #0] ML tree search #7, logLikelihood: -49638.295392

[04:34:59 -151306.670322] Initial branch length optimization
[04:35:01 -133503.202773] Model parameter optimization (eps = 10.000000)
[04:35:26 -133304.525309] AUTODETECT spr round 1 (radius: 5)
[04:37:10 -95902.305165] AUTODETECT spr round 2 (radius: 10)
[04:39:04 -73200.319114] AUTODETECT spr round 3 (radius: 15)
[04:41:12 -60062.977703] AUTODETECT spr round 4 (radius: 20)
[04:43:45 -57042.920271] AUTODETECT spr round 5 (radius: 25)
[04:46:40 -56752.660023] SPR radius for FAST iterations: 25 (autodetect)
[04:46:40 -56752.660023] Model parameter optimization (eps = 3.000000)
[04:46:59 -56506.538489] FAST spr round 1 (radius: 25)
[04:49:09 -50212.274653] FAST spr round 2 (radius: 25)
[04:50:54 -49780.099192] FAST spr round 3 (radius: 25)
[04:52:29 -49743.906079] FAST spr round 4 (radius: 25)
[04:53:59 -49731.533064] FAST spr round 5 (radius: 25)
[04:55:24 -49727.452088] FAST spr round 6 (radius: 25)
[04:56:46 -49726.903016] FAST spr round 7 (radius: 25)
[04:58:07 -49726.902835] Model parameter optimization (eps = 1.000000)
[04:58:26 -49713.988343] SLOW spr round 1 (radius: 5)
[05:00:14 -49696.137961] SLOW spr round 2 (radius: 5)
[05:01:58 -49690.730547] SLOW spr round 3 (radius: 5)
[05:03:38 -49690.730323] SLOW spr round 4 (radius: 10)
[05:05:21 -49688.508792] SLOW spr round 5 (radius: 5)
[05:07:24 -49686.979242] SLOW spr round 6 (radius: 5)
[05:09:15 -49686.536077] SLOW spr round 7 (radius: 5)
[05:10:59 -49686.536001] SLOW spr round 8 (radius: 10)
[05:12:43 -49683.448431] SLOW spr round 9 (radius: 5)
[05:14:45 -49681.183821] SLOW spr round 10 (radius: 5)
[05:16:36 -49678.880380] SLOW spr round 11 (radius: 5)
[05:18:21 -49678.880301] SLOW spr round 12 (radius: 10)
[05:20:04 -49678.312488] SLOW spr round 13 (radius: 5)
[05:22:06 -49677.610037] SLOW spr round 14 (radius: 5)
[05:23:56 -49677.609929] SLOW spr round 15 (radius: 10)
[05:25:41 -49677.098493] SLOW spr round 16 (radius: 5)
[05:27:42 -49677.098381] SLOW spr round 17 (radius: 10)
[05:29:32 -49676.859847] SLOW spr round 18 (radius: 5)
[05:31:31 -49676.835344] SLOW spr round 19 (radius: 10)
[05:33:21 -49676.835231] SLOW spr round 20 (radius: 15)
[05:35:52 -49673.795601] SLOW spr round 21 (radius: 5)
[05:37:56 -49673.795544] SLOW spr round 22 (radius: 10)
[05:39:52 -49673.795490] SLOW spr round 23 (radius: 15)
[05:42:20 -49673.371725] SLOW spr round 24 (radius: 5)
[05:43:37] [worker #1] ML tree search #8, logLikelihood: -49672.956062
[05:44:26 -49671.349155] SLOW spr round 25 (radius: 5)
[05:46:19 -49670.361537] SLOW spr round 26 (radius: 5)
[05:48:04 -49670.361498] SLOW spr round 27 (radius: 10)
[05:49:47 -49670.361473] SLOW spr round 28 (radius: 15)
[05:52:25 -49670.361449] SLOW spr round 29 (radius: 20)
[05:56:00 -49670.361424] SLOW spr round 30 (radius: 25)
[06:00:35 -49670.361400] Model parameter optimization (eps = 0.100000)

[06:00:41] [worker #0] ML tree search #9, logLikelihood: -49670.334007

[06:00:41 -151989.629322] Initial branch length optimization
[06:00:43 -133484.105416] Model parameter optimization (eps = 10.000000)
[06:01:19 -133375.927840] AUTODETECT spr round 1 (radius: 5)
[06:03:06 -96377.378497] AUTODETECT spr round 2 (radius: 10)
[06:04:59 -75998.364533] AUTODETECT spr round 3 (radius: 15)
[06:07:19 -61485.018907] AUTODETECT spr round 4 (radius: 20)
[06:09:55 -57613.614682] AUTODETECT spr round 5 (radius: 25)
[06:12:49 -57176.016389] SPR radius for FAST iterations: 25 (autodetect)
[06:12:50 -57176.016389] Model parameter optimization (eps = 3.000000)
[06:12:56 -57171.901703] FAST spr round 1 (radius: 25)
[06:15:10 -50512.121363] FAST spr round 2 (radius: 25)
[06:16:56 -50049.321640] FAST spr round 3 (radius: 25)
[06:18:34 -49992.925565] FAST spr round 4 (radius: 25)
[06:20:03 -49988.944761] FAST spr round 5 (radius: 25)
[06:21:27 -49988.944452] Model parameter optimization (eps = 1.000000)
[06:21:33 -49987.899698] SLOW spr round 1 (radius: 5)
[06:23:24 -49961.120057] SLOW spr round 2 (radius: 5)
[06:25:13 -49951.224002] SLOW spr round 3 (radius: 5)
[06:26:57 -49951.221680] SLOW spr round 4 (radius: 10)
[06:28:42 -49951.154361] SLOW spr round 5 (radius: 15)
[06:31:23 -49950.789635] SLOW spr round 6 (radius: 5)
[06:33:33 -49949.835550] SLOW spr round 7 (radius: 5)
[06:35:26 -49949.835451] SLOW spr round 8 (radius: 10)
[06:37:15 -49949.778935] SLOW spr round 9 (radius: 15)
[06:39:52 -49949.179709] SLOW spr round 10 (radius: 5)
[06:42:05 -49939.507386] SLOW spr round 11 (radius: 5)
[06:44:02 -49938.177247] SLOW spr round 12 (radius: 5)
[06:45:49 -49938.176807] SLOW spr round 13 (radius: 10)
[06:47:34 -49938.176749] SLOW spr round 14 (radius: 15)
[06:50:13 -49938.176713] SLOW spr round 15 (radius: 20)
[06:53:55 -49938.176678] SLOW spr round 16 (radius: 25)
[06:58:57 -49938.176644] Model parameter optimization (eps = 0.100000)

[06:59:00] [worker #0] ML tree search #11, logLikelihood: -49938.174697

[06:59:00 -152062.738019] Initial branch length optimization
[06:59:02 -133480.665672] Model parameter optimization (eps = 10.000000)
[06:59:29 -133354.634413] AUTODETECT spr round 1 (radius: 5)
[07:01:15 -95175.241092] AUTODETECT spr round 2 (radius: 10)
[07:03:07 -71874.519497] AUTODETECT spr round 3 (radius: 15)
[07:05:13 -61175.415400] AUTODETECT spr round 4 (radius: 20)
[07:07:46 -57690.567723] AUTODETECT spr round 5 (radius: 25)
[07:09:00] [worker #1] ML tree search #10, logLikelihood: -49910.327389
[07:10:28 -57089.010153] SPR radius for FAST iterations: 25 (autodetect)
[07:10:28 -57089.010153] Model parameter optimization (eps = 3.000000)
[07:10:47 -56863.522520] FAST spr round 1 (radius: 25)
[07:13:02 -50174.785269] FAST spr round 2 (radius: 25)
[07:14:49 -49784.158406] FAST spr round 3 (radius: 25)
[07:16:27 -49727.238148] FAST spr round 4 (radius: 25)
[07:17:58 -49705.826986] FAST spr round 5 (radius: 25)
[07:19:22 -49703.309369] FAST spr round 6 (radius: 25)
[07:20:44 -49703.309361] Model parameter optimization (eps = 1.000000)
[07:20:48 -49702.742000] SLOW spr round 1 (radius: 5)
[07:22:38 -49681.989891] SLOW spr round 2 (radius: 5)
[07:24:25 -49678.151527] SLOW spr round 3 (radius: 5)
[07:26:07 -49678.149461] SLOW spr round 4 (radius: 10)
[07:27:52 -49675.260492] SLOW spr round 5 (radius: 5)
[07:29:57 -49674.288430] SLOW spr round 6 (radius: 5)
[07:31:48 -49674.287881] SLOW spr round 7 (radius: 10)
[07:33:33 -49671.834442] SLOW spr round 8 (radius: 5)
[07:35:36 -49670.260069] SLOW spr round 9 (radius: 5)
[07:37:26 -49670.259833] SLOW spr round 10 (radius: 10)
[07:39:09 -49670.138844] SLOW spr round 11 (radius: 5)
[07:41:11 -49669.646744] SLOW spr round 12 (radius: 5)
[07:43:01 -49669.646716] SLOW spr round 13 (radius: 10)
[07:44:44 -49669.586355] SLOW spr round 14 (radius: 15)
[07:47:15 -49669.585987] SLOW spr round 15 (radius: 20)
[07:50:58 -49667.882644] SLOW spr round 16 (radius: 5)
[07:53:10 -49663.490693] SLOW spr round 17 (radius: 5)
[07:55:05 -49662.723001] SLOW spr round 18 (radius: 5)
[07:56:51 -49662.722774] SLOW spr round 19 (radius: 10)
[07:58:35 -49662.722706] SLOW spr round 20 (radius: 15)
[08:01:08 -49662.722669] SLOW spr round 21 (radius: 20)
[08:04:50 -49662.722639] SLOW spr round 22 (radius: 25)
[08:09:42 -49662.417730] SLOW spr round 23 (radius: 5)
[08:11:53 -49662.412781] SLOW spr round 24 (radius: 10)
[08:13:52 -49662.412604] SLOW spr round 25 (radius: 15)
[08:16:18 -49662.412570] SLOW spr round 26 (radius: 20)
[08:20:07 -49662.412542] SLOW spr round 27 (radius: 25)
[08:24:55 -49662.412513] Model parameter optimization (eps = 0.100000)

[08:24:58] [worker #0] ML tree search #13, logLikelihood: -49662.409410

[08:24:58 -151560.069214] Initial branch length optimization
[08:25:01 -133673.238725] Model parameter optimization (eps = 10.000000)
[08:25:31 -133458.207891] AUTODETECT spr round 1 (radius: 5)
[08:27:17 -96058.454999] AUTODETECT spr round 2 (radius: 10)
[08:29:11 -71979.157202] AUTODETECT spr round 3 (radius: 15)
[08:31:28 -59071.094491] AUTODETECT spr round 4 (radius: 20)
[08:34:30 -56940.652938] AUTODETECT spr round 5 (radius: 25)
[08:37:53 -56447.793894] SPR radius for FAST iterations: 25 (autodetect)
[08:37:53 -56447.793894] Model parameter optimization (eps = 3.000000)
[08:38:00 -56442.998146] FAST spr round 1 (radius: 25)
[08:40:10 -50376.824243] FAST spr round 2 (radius: 25)
[08:41:57 -50019.294275] FAST spr round 3 (radius: 25)
[08:43:32 -49967.503545] FAST spr round 4 (radius: 25)
[08:45:01 -49960.263229] FAST spr round 5 (radius: 25)
[08:46:26 -49960.122568] FAST spr round 6 (radius: 25)
[08:47:50 -49960.122522] Model parameter optimization (eps = 1.000000)
[08:48:12 -49738.884298] SLOW spr round 1 (radius: 5)
[08:50:02 -49704.745724] SLOW spr round 2 (radius: 5)
[08:51:50 -49697.889428] SLOW spr round 3 (radius: 5)
[08:52:11] [worker #1] ML tree search #12, logLikelihood: -49649.126156
[08:53:32 -49697.888720] SLOW spr round 4 (radius: 10)
[08:55:17 -49696.317907] SLOW spr round 5 (radius: 5)
[08:57:22 -49687.485305] SLOW spr round 6 (radius: 5)
[08:59:13 -49686.754090] SLOW spr round 7 (radius: 5)
[09:00:58 -49686.753957] SLOW spr round 8 (radius: 10)
[09:02:41 -49685.716515] SLOW spr round 9 (radius: 5)
[09:04:42 -49685.716436] SLOW spr round 10 (radius: 10)
[09:06:33 -49685.502852] SLOW spr round 11 (radius: 5)
[09:08:35 -49685.502398] SLOW spr round 12 (radius: 10)
[09:10:25 -49685.502315] SLOW spr round 13 (radius: 15)
[09:12:51 -49685.502234] SLOW spr round 14 (radius: 20)
[09:16:17 -49684.467104] SLOW spr round 15 (radius: 5)
[09:18:28 -49684.298660] SLOW spr round 16 (radius: 5)
[09:20:23 -49684.298091] SLOW spr round 17 (radius: 10)
[09:22:10 -49684.298002] SLOW spr round 18 (radius: 15)
[09:24:39 -49684.297917] SLOW spr round 19 (radius: 20)
[09:28:02 -49684.297832] SLOW spr round 20 (radius: 25)
[09:31:58 -49684.297747] Model parameter optimization (eps = 0.100000)

[09:32:25] [worker #0] ML tree search #15, logLikelihood: -49682.227227

[09:32:25 -151680.880641] Initial branch length optimization
[09:32:27 -133903.944842] Model parameter optimization (eps = 10.000000)
[09:32:59 -133760.797520] AUTODETECT spr round 1 (radius: 5)
[09:34:47 -96360.030782] AUTODETECT spr round 2 (radius: 10)
[09:36:40 -72154.813578] AUTODETECT spr round 3 (radius: 15)
[09:38:20] [worker #1] ML tree search #14, logLikelihood: -49666.660536
[09:38:51 -63842.920295] AUTODETECT spr round 4 (radius: 20)
[09:41:10 -60797.981106] AUTODETECT spr round 5 (radius: 25)
[09:44:08 -57968.864924] SPR radius for FAST iterations: 25 (autodetect)
[09:44:08 -57968.864924] Model parameter optimization (eps = 3.000000)
[09:44:26 -57692.451293] FAST spr round 1 (radius: 25)
[09:46:39 -50151.895133] FAST spr round 2 (radius: 25)
[09:48:22 -49755.004860] FAST spr round 3 (radius: 25)
[09:49:56 -49719.986801] FAST spr round 4 (radius: 25)
[09:51:23 -49717.195463] FAST spr round 5 (radius: 25)
[09:52:47 -49715.502584] FAST spr round 6 (radius: 25)
[09:54:11 -49715.502528] Model parameter optimization (eps = 1.000000)
[09:54:24 -49712.415453] SLOW spr round 1 (radius: 5)
[09:56:16 -49685.534476] SLOW spr round 2 (radius: 5)
[09:58:02 -49680.532365] SLOW spr round 3 (radius: 5)
[09:59:47 -49674.023587] SLOW spr round 4 (radius: 5)
[10:01:31 -49669.994367] SLOW spr round 5 (radius: 5)
[10:03:12 -49667.313385] SLOW spr round 6 (radius: 5)
[10:04:54 -49664.579718] SLOW spr round 7 (radius: 5)
[10:06:36 -49663.401483] SLOW spr round 8 (radius: 5)
[10:08:16 -49663.401422] SLOW spr round 9 (radius: 10)
[10:10:01 -49650.625183] SLOW spr round 10 (radius: 5)
[10:12:04 -49650.625048] SLOW spr round 11 (radius: 10)
[10:13:57 -49647.663174] SLOW spr round 12 (radius: 5)
[10:15:59 -49647.470229] SLOW spr round 13 (radius: 5)
[10:17:50 -49647.470148] SLOW spr round 14 (radius: 10)
[10:19:37 -49646.706441] SLOW spr round 15 (radius: 5)
[10:21:42 -49645.732463] SLOW spr round 16 (radius: 5)
[10:23:33 -49645.732432] SLOW spr round 17 (radius: 10)
[10:25:20 -49642.604657] SLOW spr round 18 (radius: 5)
[10:27:26 -49640.591154] SLOW spr round 19 (radius: 5)
[10:29:19 -49639.723825] SLOW spr round 20 (radius: 5)
[10:31:05 -49639.118941] SLOW spr round 21 (radius: 5)
[10:32:48 -49639.118855] SLOW spr round 22 (radius: 10)
[10:34:32 -49638.930053] SLOW spr round 23 (radius: 5)
[10:36:36 -49638.348173] SLOW spr round 24 (radius: 5)
[10:38:27 -49638.348146] SLOW spr round 25 (radius: 10)
[10:40:14 -49638.348128] SLOW spr round 26 (radius: 15)
[10:42:52 -49638.348110] SLOW spr round 27 (radius: 20)
[10:46:33 -49638.348093] SLOW spr round 28 (radius: 25)
[10:51:02 -49638.348075] Model parameter optimization (eps = 0.100000)

[10:51:06] [worker #0] ML tree search #17, logLikelihood: -49638.343506

[10:51:06 -151718.865078] Initial branch length optimization
[10:51:08 -133634.731607] Model parameter optimization (eps = 10.000000)
[10:51:33 -133480.229729] AUTODETECT spr round 1 (radius: 5)
[10:53:22 -97201.412060] AUTODETECT spr round 2 (radius: 10)
[10:55:17 -73156.125156] AUTODETECT spr round 3 (radius: 15)
[10:57:27 -61526.467534] AUTODETECT spr round 4 (radius: 20)
[11:00:05 -57668.527081] AUTODETECT spr round 5 (radius: 25)
[11:03:28 -57042.048492] SPR radius for FAST iterations: 25 (autodetect)
[11:03:28 -57042.048492] Model parameter optimization (eps = 3.000000)
[11:03:45 -56775.518615] FAST spr round 1 (radius: 25)
[11:05:56 -50188.957746] FAST spr round 2 (radius: 25)
[11:07:42 -49813.857923] FAST spr round 3 (radius: 25)
[11:09:20 -49759.562018] FAST spr round 4 (radius: 25)
[11:10:14] [worker #1] ML tree search #16, logLikelihood: -49638.873414
[11:10:48 -49755.768666] FAST spr round 5 (radius: 25)
[11:12:14 -49754.631019] FAST spr round 6 (radius: 25)
[11:13:40 -49754.610713] Model parameter optimization (eps = 1.000000)
[11:13:52 -49750.784042] SLOW spr round 1 (radius: 5)
[11:15:50 -49717.104765] SLOW spr round 2 (radius: 5)
[11:17:40 -49707.325793] SLOW spr round 3 (radius: 5)
[11:19:25 -49707.220971] SLOW spr round 4 (radius: 5)
[11:21:09 -49707.219893] SLOW spr round 5 (radius: 10)
[11:22:58 -49705.820582] SLOW spr round 6 (radius: 5)
[11:25:06 -49702.170427] SLOW spr round 7 (radius: 5)
[11:27:03 -49702.170378] SLOW spr round 8 (radius: 10)
[11:28:51 -49696.469663] SLOW spr round 9 (radius: 5)
[11:31:04 -49683.749591] SLOW spr round 10 (radius: 5)
[11:33:01 -49681.094605] SLOW spr round 11 (radius: 5)
[11:34:52 -49681.094552] SLOW spr round 12 (radius: 10)
[11:36:41 -49681.094522] SLOW spr round 13 (radius: 15)
[11:39:23 -49680.739378] SLOW spr round 14 (radius: 5)
[11:41:35 -49680.612944] SLOW spr round 15 (radius: 5)
[11:43:33 -49680.612921] SLOW spr round 16 (radius: 10)
[11:45:22 -49680.612901] SLOW spr round 17 (radius: 15)
[11:48:03 -49680.373980] SLOW spr round 18 (radius: 5)
[11:50:16 -49680.373937] SLOW spr round 19 (radius: 10)
[11:52:18 -49680.373917] SLOW spr round 20 (radius: 15)
[11:54:51 -49680.373897] SLOW spr round 21 (radius: 20)
[11:58:24 -49679.084373] SLOW spr round 22 (radius: 5)
[12:00:36 -49679.084351] SLOW spr round 23 (radius: 10)
[12:02:42 -49676.539684] SLOW spr round 24 (radius: 5)
[12:04:47 -49674.256740] SLOW spr round 25 (radius: 5)
[12:06:38 -49674.256693] SLOW spr round 26 (radius: 10)
[12:08:27 -49670.831458] SLOW spr round 27 (radius: 5)
[12:10:35 -49670.831353] SLOW spr round 28 (radius: 10)
[12:12:29 -49670.831332] SLOW spr round 29 (radius: 15)
[12:13:01] [worker #1] ML tree search #18, logLikelihood: -49643.523339
[12:15:00 -49669.426534] SLOW spr round 30 (radius: 5)
[12:17:09 -49669.426513] SLOW spr round 31 (radius: 10)
[12:19:05 -49669.426493] SLOW spr round 32 (radius: 15)
[12:21:32 -49669.426472] SLOW spr round 33 (radius: 20)
[12:24:55 -49669.426451] SLOW spr round 34 (radius: 25)
[12:29:08 -49669.426430] Model parameter optimization (eps = 0.100000)

[12:29:19] [worker #0] ML tree search #19, logLikelihood: -49668.439305

[13:26:06] [worker #1] ML tree search #20, logLikelihood: -49654.154876

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.222006,0.428510) (0.152879,0.442172) (0.461651,0.968358) (0.163463,2.387235) 
   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: -49638.295392

AIC score: 103286.590784 / AICc score: 8147346.590784 / BIC score: 108588.594537
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=104).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 108 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A0A087WSX0/3_mltree/A0A087WSX0.raxml.log

Analysis started: 06-Jul-2021 15:54:33 / finished: 07-Jul-2021 05:20:40

Elapsed time: 48367.148 seconds

Consumed energy: 3759.222 Wh (= 19 km in an electric car, or 94 km with an e-scooter!)