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 13-Jul-2021 18:14:05 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/2_msa/Q8NI27_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27 --seed 2 --threads 9 --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 (9 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/2_msa/Q8NI27_trimmed_msa.fasta
[00:00:00] Loaded alignment with 451 taxa and 1234 sites

WARNING: Sequences tr_M3XQJ5_M3XQJ5_MUSPF_9669 and tr_J9PB31_J9PB31_CANLF_9615 are exactly identical!
WARNING: Sequences tr_M3XQJ5_M3XQJ5_MUSPF_9669 and tr_A0A2Y9KSF4_A0A2Y9KSF4_ENHLU_391180 are exactly identical!
WARNING: Sequences tr_A0A2J8WWI2_A0A2J8WWI2_PONAB_9601 and sp_Q8NI27_THOC2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_F6PLG3_F6PLG3_HORSE_9796 and tr_M3W9C3_M3W9C3_FELCA_9685 are exactly identical!
WARNING: Sequences sp_B0KWH8_THOC2_CALJA_9483 and tr_F7ESC3_F7ESC3_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G7Q3M2_G7Q3M2_MACFA_9541 and tr_A0A0D9S0F5_A0A0D9S0F5_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G7Q3M2_G7Q3M2_MACFA_9541 and tr_A0A2K5KKR6_A0A2K5KKR6_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G7Q3M2_G7Q3M2_MACFA_9541 and tr_A0A2K6C8F3_A0A2K6C8F3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G7Q3M2_G7Q3M2_MACFA_9541 and tr_A0A2K5Z1I8_A0A2K5Z1I8_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A015I2F6_A0A015I2F6_9GLOM_1432141 and tr_U9ST07_U9ST07_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A044V9M4_A0A044V9M4_ONCVO_6282 and tr_A0A182ECD5_A0A182ECD5_ONCOC_42157 are exactly identical!
WARNING: Duplicate sequences found: 11

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/Q8NI27/3_mltree/Q8NI27.raxml.reduced.phy

Alignment comprises 1 partitions and 1234 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1234 / 1234
Gaps: 16.90 %
Invariant sites: 0.16 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 9 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 451 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 138 / 11040
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -871116.599513] Initial branch length optimization
[00:00:02 -681572.544673] Model parameter optimization (eps = 10.000000)
[00:00:20 -679127.112435] AUTODETECT spr round 1 (radius: 5)
[00:00:54 -496463.481998] AUTODETECT spr round 2 (radius: 10)
[00:01:32 -368340.552373] AUTODETECT spr round 3 (radius: 15)
[00:02:16 -306535.050576] AUTODETECT spr round 4 (radius: 20)
[00:03:07 -294393.432159] AUTODETECT spr round 5 (radius: 25)
[00:04:17 -294001.922327] SPR radius for FAST iterations: 25 (autodetect)
[00:04:17 -294001.922327] Model parameter optimization (eps = 3.000000)
[00:04:29 -293738.844250] FAST spr round 1 (radius: 25)
[00:05:19 -270003.963691] FAST spr round 2 (radius: 25)
[00:05:57 -268654.602437] FAST spr round 3 (radius: 25)
[00:06:28 -268624.539300] FAST spr round 4 (radius: 25)
[00:06:55 -268624.525887] Model parameter optimization (eps = 1.000000)
[00:07:06 -268611.003932] SLOW spr round 1 (radius: 5)
[00:07:50 -268569.563520] SLOW spr round 2 (radius: 5)
[00:08:34 -268567.539419] SLOW spr round 3 (radius: 5)
[00:09:15 -268567.538049] SLOW spr round 4 (radius: 10)
[00:10:02 -268565.794536] SLOW spr round 5 (radius: 5)
[00:10:56 -268565.791093] SLOW spr round 6 (radius: 10)
[00:11:47 -268565.767137] SLOW spr round 7 (radius: 15)
[00:13:00 -268565.767053] SLOW spr round 8 (radius: 20)
[00:14:45 -268565.550608] SLOW spr round 9 (radius: 5)
[00:15:44 -268565.550550] SLOW spr round 10 (radius: 10)
[00:16:41 -268565.550545] SLOW spr round 11 (radius: 15)
[00:17:54 -268563.551271] SLOW spr round 12 (radius: 5)
[00:18:52 -268563.543698] SLOW spr round 13 (radius: 10)
[00:19:47 -268563.541396] SLOW spr round 14 (radius: 15)
[00:21:00 -268563.540704] SLOW spr round 15 (radius: 20)
[00:22:44 -268563.540497] SLOW spr round 16 (radius: 25)
[00:24:30 -268563.540434] Model parameter optimization (eps = 0.100000)

[00:24:35] ML tree search #1, logLikelihood: -268563.465665

[00:24:35 -870626.249215] Initial branch length optimization
[00:24:37 -683611.557474] Model parameter optimization (eps = 10.000000)
[00:24:53 -681138.127922] AUTODETECT spr round 1 (radius: 5)
[00:25:27 -478504.100793] AUTODETECT spr round 2 (radius: 10)
[00:26:04 -368205.088435] AUTODETECT spr round 3 (radius: 15)
[00:26:46 -325814.668948] AUTODETECT spr round 4 (radius: 20)
[00:27:34 -299861.442663] AUTODETECT spr round 5 (radius: 25)
[00:28:41 -297100.958973] SPR radius for FAST iterations: 25 (autodetect)
[00:28:41 -297100.958973] Model parameter optimization (eps = 3.000000)
[00:28:55 -296830.940107] FAST spr round 1 (radius: 25)
[00:29:45 -270708.286339] FAST spr round 2 (radius: 25)
[00:30:19 -269892.748681] FAST spr round 3 (radius: 25)
[00:30:51 -268785.020987] FAST spr round 4 (radius: 25)
[00:31:20 -268601.072681] FAST spr round 5 (radius: 25)
[00:31:48 -268596.745935] FAST spr round 6 (radius: 25)
[00:32:15 -268596.744617] Model parameter optimization (eps = 1.000000)
[00:32:23 -268587.138773] SLOW spr round 1 (radius: 5)
[00:33:05 -268570.655701] SLOW spr round 2 (radius: 5)
[00:33:46 -268570.655395] SLOW spr round 3 (radius: 10)
[00:34:31 -268570.021763] SLOW spr round 4 (radius: 5)
[00:35:24 -268570.021621] SLOW spr round 5 (radius: 10)
[00:36:15 -268569.994494] SLOW spr round 6 (radius: 15)
[00:37:25 -268569.994415] SLOW spr round 7 (radius: 20)
[00:39:02 -268569.994414] SLOW spr round 8 (radius: 25)
[00:40:44 -268569.994414] Model parameter optimization (eps = 0.100000)

[00:40:47] ML tree search #2, logLikelihood: -268569.957840

[00:40:47 -871829.229965] Initial branch length optimization
[00:40:49 -685713.530856] Model parameter optimization (eps = 10.000000)
[00:41:07 -683154.829650] AUTODETECT spr round 1 (radius: 5)
[00:41:42 -501511.107270] AUTODETECT spr round 2 (radius: 10)
[00:42:17 -416913.736866] AUTODETECT spr round 3 (radius: 15)
[00:43:02 -314422.367534] AUTODETECT spr round 4 (radius: 20)
[00:43:56 -303424.227233] AUTODETECT spr round 5 (radius: 25)
[00:44:56 -300639.377625] SPR radius for FAST iterations: 25 (autodetect)
[00:44:56 -300639.377625] Model parameter optimization (eps = 3.000000)
[00:45:09 -300338.986349] FAST spr round 1 (radius: 25)
[00:46:02 -270685.912216] FAST spr round 2 (radius: 25)
[00:46:45 -268703.178940] FAST spr round 3 (radius: 25)
[00:47:17 -268609.197437] FAST spr round 4 (radius: 25)
[00:47:45 -268603.615104] FAST spr round 5 (radius: 25)
[00:48:12 -268603.613319] Model parameter optimization (eps = 1.000000)
[00:48:20 -268593.361119] SLOW spr round 1 (radius: 5)
[00:49:06 -268567.883776] SLOW spr round 2 (radius: 5)
[00:49:49 -268565.457164] SLOW spr round 3 (radius: 5)
[00:50:30 -268565.455029] SLOW spr round 4 (radius: 10)
[00:51:17 -268564.822169] SLOW spr round 5 (radius: 5)
[00:52:10 -268564.821923] SLOW spr round 6 (radius: 10)
[00:53:01 -268564.791328] SLOW spr round 7 (radius: 15)
[00:54:12 -268564.791245] SLOW spr round 8 (radius: 20)
[00:55:53 -268564.791245] SLOW spr round 9 (radius: 25)
[00:57:38 -268564.791245] Model parameter optimization (eps = 0.100000)

[00:57:41] ML tree search #3, logLikelihood: -268564.687170

[00:57:41 -870706.891403] Initial branch length optimization
[00:57:44 -678283.226528] Model parameter optimization (eps = 10.000000)
[00:58:12 -675843.503087] AUTODETECT spr round 1 (radius: 5)
[00:58:47 -500021.645047] AUTODETECT spr round 2 (radius: 10)
[00:59:25 -370045.884066] AUTODETECT spr round 3 (radius: 15)
[01:00:07 -301944.013448] AUTODETECT spr round 4 (radius: 20)
[01:01:00 -289103.543210] AUTODETECT spr round 5 (radius: 25)
[01:01:55 -288440.865602] SPR radius for FAST iterations: 25 (autodetect)
[01:01:55 -288440.865602] Model parameter optimization (eps = 3.000000)
[01:02:08 -288156.383605] FAST spr round 1 (radius: 25)
[01:02:54 -269204.699069] FAST spr round 2 (radius: 25)
[01:03:28 -268697.938791] FAST spr round 3 (radius: 25)
[01:04:01 -268612.872333] FAST spr round 4 (radius: 25)
[01:04:29 -268612.023562] FAST spr round 5 (radius: 25)
[01:04:55 -268612.020352] Model parameter optimization (eps = 1.000000)
[01:05:01 -268609.394682] SLOW spr round 1 (radius: 5)
[01:05:43 -268571.905096] SLOW spr round 2 (radius: 5)
[01:06:28 -268564.206747] SLOW spr round 3 (radius: 5)
[01:07:12 -268556.470247] SLOW spr round 4 (radius: 5)
[01:07:54 -268556.467293] SLOW spr round 5 (radius: 10)
[01:08:41 -268556.466286] SLOW spr round 6 (radius: 15)
[01:09:54 -268556.465936] SLOW spr round 7 (radius: 20)
[01:11:33 -268556.465816] SLOW spr round 8 (radius: 25)
[01:13:17 -268556.465775] Model parameter optimization (eps = 0.100000)

[01:13:22] ML tree search #4, logLikelihood: -268555.930070

[01:13:22 -860310.581062] Initial branch length optimization
[01:13:24 -675848.880168] Model parameter optimization (eps = 10.000000)
[01:13:43 -673359.319763] AUTODETECT spr round 1 (radius: 5)
[01:14:18 -492013.292892] AUTODETECT spr round 2 (radius: 10)
[01:14:56 -399618.420749] AUTODETECT spr round 3 (radius: 15)
[01:15:40 -334441.536850] AUTODETECT spr round 4 (radius: 20)
[01:16:28 -316834.267916] AUTODETECT spr round 5 (radius: 25)
[01:17:24 -310490.270866] SPR radius for FAST iterations: 25 (autodetect)
[01:17:24 -310490.270866] Model parameter optimization (eps = 3.000000)
[01:17:36 -310212.039268] FAST spr round 1 (radius: 25)
[01:18:23 -272422.120107] FAST spr round 2 (radius: 25)
[01:18:58 -268846.076184] FAST spr round 3 (radius: 25)
[01:19:29 -268629.115961] FAST spr round 4 (radius: 25)
[01:19:57 -268610.720978] FAST spr round 5 (radius: 25)
[01:20:24 -268610.686396] Model parameter optimization (eps = 1.000000)
[01:20:31 -268607.610022] SLOW spr round 1 (radius: 5)
[01:21:13 -268583.157862] SLOW spr round 2 (radius: 5)
[01:21:55 -268575.464623] SLOW spr round 3 (radius: 5)
[01:22:35 -268575.464427] SLOW spr round 4 (radius: 10)
[01:23:22 -268568.627535] SLOW spr round 5 (radius: 5)
[01:24:17 -268561.961186] SLOW spr round 6 (radius: 5)
[01:25:03 -268561.961104] SLOW spr round 7 (radius: 10)
[01:25:51 -268561.930411] SLOW spr round 8 (radius: 15)
[01:27:02 -268561.930332] SLOW spr round 9 (radius: 20)
[01:28:40 -268561.930331] SLOW spr round 10 (radius: 25)
[01:30:21 -268561.930331] Model parameter optimization (eps = 0.100000)

[01:30:27] ML tree search #5, logLikelihood: -268561.561781

[01:30:27 -859670.190980] Initial branch length optimization
[01:30:29 -676564.815564] Model parameter optimization (eps = 10.000000)
[01:30:47 -673815.665720] AUTODETECT spr round 1 (radius: 5)
[01:31:22 -494155.791345] AUTODETECT spr round 2 (radius: 10)
[01:32:00 -384939.406462] AUTODETECT spr round 3 (radius: 15)
[01:32:43 -317577.743137] AUTODETECT spr round 4 (radius: 20)
[01:33:33 -299437.261792] AUTODETECT spr round 5 (radius: 25)
[01:34:28 -299171.265359] SPR radius for FAST iterations: 25 (autodetect)
[01:34:28 -299171.265359] Model parameter optimization (eps = 3.000000)
[01:34:39 -298898.495995] FAST spr round 1 (radius: 25)
[01:35:21 -270191.468186] FAST spr round 2 (radius: 25)
[01:35:56 -268701.677690] FAST spr round 3 (radius: 25)
[01:36:27 -268616.358067] FAST spr round 4 (radius: 25)
[01:36:56 -268608.392919] FAST spr round 5 (radius: 25)
[01:37:22 -268608.392186] Model parameter optimization (eps = 1.000000)
[01:37:29 -268600.902712] SLOW spr round 1 (radius: 5)
[01:38:11 -268559.323929] SLOW spr round 2 (radius: 5)
[01:38:53 -268558.689067] SLOW spr round 3 (radius: 5)
[01:39:35 -268558.688833] SLOW spr round 4 (radius: 10)
[01:40:21 -268558.660415] SLOW spr round 5 (radius: 15)
[01:41:38 -268558.660332] SLOW spr round 6 (radius: 20)
[01:43:21 -268558.660331] SLOW spr round 7 (radius: 25)
[01:45:02 -268558.660331] Model parameter optimization (eps = 0.100000)

[01:45:06] ML tree search #6, logLikelihood: -268558.637791

[01:45:06 -851278.255929] Initial branch length optimization
[01:45:09 -676348.221211] Model parameter optimization (eps = 10.000000)
[01:45:25 -673765.691930] AUTODETECT spr round 1 (radius: 5)
[01:46:00 -509708.518094] AUTODETECT spr round 2 (radius: 10)
[01:46:37 -394216.217968] AUTODETECT spr round 3 (radius: 15)
[01:47:20 -335043.027535] AUTODETECT spr round 4 (radius: 20)
[01:48:10 -310320.679944] AUTODETECT spr round 5 (radius: 25)
[01:49:12 -302291.590897] SPR radius for FAST iterations: 25 (autodetect)
[01:49:12 -302291.590897] Model parameter optimization (eps = 3.000000)
[01:49:22 -302082.377242] FAST spr round 1 (radius: 25)
[01:50:13 -270185.805283] FAST spr round 2 (radius: 25)
[01:50:55 -268829.663894] FAST spr round 3 (radius: 25)
[01:51:32 -268635.790659] FAST spr round 4 (radius: 25)
[01:52:01 -268624.026905] FAST spr round 5 (radius: 25)
[01:52:28 -268623.998614] Model parameter optimization (eps = 1.000000)
[01:52:35 -268612.583454] SLOW spr round 1 (radius: 5)
[01:53:18 -268583.959659] SLOW spr round 2 (radius: 5)
[01:54:03 -268575.197015] SLOW spr round 3 (radius: 5)
[01:54:44 -268575.195852] SLOW spr round 4 (radius: 10)
[01:55:33 -268561.903831] SLOW spr round 5 (radius: 5)
[01:56:27 -268561.903588] SLOW spr round 6 (radius: 10)
[01:57:20 -268561.876696] SLOW spr round 7 (radius: 15)
[01:58:35 -268561.876612] SLOW spr round 8 (radius: 20)
[02:00:20 -268561.876612] SLOW spr round 9 (radius: 25)
[02:02:07 -268561.876611] Model parameter optimization (eps = 0.100000)

[02:02:10] ML tree search #7, logLikelihood: -268561.843361

[02:02:10 -855937.538333] Initial branch length optimization
[02:02:13 -678913.895978] Model parameter optimization (eps = 10.000000)
[02:02:33 -676389.968179] AUTODETECT spr round 1 (radius: 5)
[02:03:08 -494200.174149] AUTODETECT spr round 2 (radius: 10)
[02:03:45 -383703.995628] AUTODETECT spr round 3 (radius: 15)
[02:04:28 -312022.664682] AUTODETECT spr round 4 (radius: 20)
[02:05:18 -295804.084133] AUTODETECT spr round 5 (radius: 25)
[02:06:15 -295600.766054] SPR radius for FAST iterations: 25 (autodetect)
[02:06:15 -295600.766054] Model parameter optimization (eps = 3.000000)
[02:06:27 -295308.371617] FAST spr round 1 (radius: 25)
[02:07:15 -269251.537666] FAST spr round 2 (radius: 25)
[02:07:57 -268679.297231] FAST spr round 3 (radius: 25)
[02:08:29 -268640.374359] FAST spr round 4 (radius: 25)
[02:08:57 -268629.090161] FAST spr round 5 (radius: 25)
[02:09:24 -268624.242138] FAST spr round 6 (radius: 25)
[02:09:51 -268624.238312] Model parameter optimization (eps = 1.000000)
[02:09:55 -268622.998060] SLOW spr round 1 (radius: 5)
[02:10:39 -268576.806540] SLOW spr round 2 (radius: 5)
[02:11:22 -268566.287486] SLOW spr round 3 (radius: 5)
[02:12:03 -268566.286973] SLOW spr round 4 (radius: 10)
[02:12:50 -268565.653694] SLOW spr round 5 (radius: 5)
[02:13:44 -268565.653534] SLOW spr round 6 (radius: 10)
[02:14:35 -268565.627167] SLOW spr round 7 (radius: 15)
[02:15:45 -268565.071371] SLOW spr round 8 (radius: 5)
[02:16:43 -268564.817092] SLOW spr round 9 (radius: 5)
[02:17:32 -268564.810910] SLOW spr round 10 (radius: 10)
[02:18:21 -268564.810898] SLOW spr round 11 (radius: 15)
[02:19:31 -268564.810894] SLOW spr round 12 (radius: 20)
[02:21:09 -268564.810893] SLOW spr round 13 (radius: 25)
[02:22:50 -268564.810892] Model parameter optimization (eps = 0.100000)

[02:22:56] ML tree search #8, logLikelihood: -268564.694644

[02:22:56 -864584.205051] Initial branch length optimization
[02:22:59 -676583.078742] Model parameter optimization (eps = 10.000000)
[02:23:14 -674147.170218] AUTODETECT spr round 1 (radius: 5)
[02:23:51 -488417.943276] AUTODETECT spr round 2 (radius: 10)
[02:24:27 -383705.544321] AUTODETECT spr round 3 (radius: 15)
[02:25:10 -328518.508859] AUTODETECT spr round 4 (radius: 20)
[02:26:04 -312603.866570] AUTODETECT spr round 5 (radius: 25)
[02:27:06 -306627.090267] SPR radius for FAST iterations: 25 (autodetect)
[02:27:06 -306627.090267] Model parameter optimization (eps = 3.000000)
[02:27:21 -305577.436203] FAST spr round 1 (radius: 25)
[02:28:08 -270415.126043] FAST spr round 2 (radius: 25)
[02:28:46 -268775.092763] FAST spr round 3 (radius: 25)
[02:29:20 -268629.288474] FAST spr round 4 (radius: 25)
[02:29:49 -268617.791182] FAST spr round 5 (radius: 25)
[02:30:15 -268617.788104] Model parameter optimization (eps = 1.000000)
[02:30:22 -268614.691066] SLOW spr round 1 (radius: 5)
[02:31:06 -268569.479327] SLOW spr round 2 (radius: 5)
[02:31:47 -268569.240077] SLOW spr round 3 (radius: 5)
[02:32:28 -268569.239865] SLOW spr round 4 (radius: 10)
[02:33:16 -268568.087892] SLOW spr round 5 (radius: 5)
[02:34:10 -268568.087860] SLOW spr round 6 (radius: 10)
[02:35:02 -268568.087859] SLOW spr round 7 (radius: 15)
[02:36:14 -268568.087858] SLOW spr round 8 (radius: 20)
[02:37:53 -268568.087858] SLOW spr round 9 (radius: 25)
[02:39:37 -268568.087857] Model parameter optimization (eps = 0.100000)

[02:39:40] ML tree search #9, logLikelihood: -268568.059860

[02:39:40 -861232.388945] Initial branch length optimization
[02:39:42 -684104.545754] Model parameter optimization (eps = 10.000000)
[02:40:06 -681603.850049] AUTODETECT spr round 1 (radius: 5)
[02:40:42 -483596.006480] AUTODETECT spr round 2 (radius: 10)
[02:41:21 -364270.209039] AUTODETECT spr round 3 (radius: 15)
[02:42:05 -308538.785866] AUTODETECT spr round 4 (radius: 20)
[02:42:56 -296431.161899] AUTODETECT spr round 5 (radius: 25)
[02:43:59 -295903.855756] SPR radius for FAST iterations: 25 (autodetect)
[02:43:59 -295903.855756] Model parameter optimization (eps = 3.000000)
[02:44:14 -295670.145399] FAST spr round 1 (radius: 25)
[02:45:03 -269642.117689] FAST spr round 2 (radius: 25)
[02:45:42 -268705.890514] FAST spr round 3 (radius: 25)
[02:46:17 -268630.797290] FAST spr round 4 (radius: 25)
[02:46:46 -268617.721750] FAST spr round 5 (radius: 25)
[02:47:13 -268615.998806] FAST spr round 6 (radius: 25)
[02:47:39 -268615.973756] Model parameter optimization (eps = 1.000000)
[02:47:47 -268611.064655] SLOW spr round 1 (radius: 5)
[02:48:31 -268576.951986] SLOW spr round 2 (radius: 5)
[02:49:14 -268568.015781] SLOW spr round 3 (radius: 5)
[02:49:55 -268568.015667] SLOW spr round 4 (radius: 10)
[02:50:40 -268568.015640] SLOW spr round 5 (radius: 15)
[02:51:53 -268568.015633] SLOW spr round 6 (radius: 20)
[02:53:28 -268568.015631] SLOW spr round 7 (radius: 25)
[02:55:09 -268568.015630] Model parameter optimization (eps = 0.100000)

[02:55:14] ML tree search #10, logLikelihood: -268567.434375

[02:55:14 -869739.207762] Initial branch length optimization
[02:55:16 -681753.428281] Model parameter optimization (eps = 10.000000)
[02:55:31 -679201.609918] AUTODETECT spr round 1 (radius: 5)
[02:56:07 -482216.273425] AUTODETECT spr round 2 (radius: 10)
[02:56:43 -373425.466059] AUTODETECT spr round 3 (radius: 15)
[02:57:24 -303552.029507] AUTODETECT spr round 4 (radius: 20)
[02:58:14 -295843.621987] AUTODETECT spr round 5 (radius: 25)
[02:59:12 -295836.496679] SPR radius for FAST iterations: 25 (autodetect)
[02:59:12 -295836.496679] Model parameter optimization (eps = 3.000000)
[02:59:25 -295531.430706] FAST spr round 1 (radius: 25)
[03:00:07 -269687.985177] FAST spr round 2 (radius: 25)
[03:00:41 -268732.683009] FAST spr round 3 (radius: 25)
[03:01:13 -268661.770716] FAST spr round 4 (radius: 25)
[03:01:41 -268655.520977] FAST spr round 5 (radius: 25)
[03:02:08 -268655.519603] Model parameter optimization (eps = 1.000000)
[03:02:15 -268649.819178] SLOW spr round 1 (radius: 5)
[03:02:58 -268560.576554] SLOW spr round 2 (radius: 5)
[03:03:41 -268560.260037] SLOW spr round 3 (radius: 5)
[03:04:22 -268560.259296] SLOW spr round 4 (radius: 10)
[03:05:09 -268559.625657] SLOW spr round 5 (radius: 5)
[03:06:03 -268559.624991] SLOW spr round 6 (radius: 10)
[03:06:55 -268559.597670] SLOW spr round 7 (radius: 15)
[03:08:09 -268559.597124] SLOW spr round 8 (radius: 20)
[03:09:54 -268559.596663] SLOW spr round 9 (radius: 25)
[03:11:43 -268559.596210] Model parameter optimization (eps = 0.100000)

[03:11:47] ML tree search #11, logLikelihood: -268559.382657

[03:11:47 -863237.770687] Initial branch length optimization
[03:11:49 -682711.540815] Model parameter optimization (eps = 10.000000)
[03:12:12 -680164.553960] AUTODETECT spr round 1 (radius: 5)
[03:12:49 -482391.338531] AUTODETECT spr round 2 (radius: 10)
[03:13:28 -381030.501731] AUTODETECT spr round 3 (radius: 15)
[03:14:13 -334245.875696] AUTODETECT spr round 4 (radius: 20)
[03:15:06 -324758.415070] AUTODETECT spr round 5 (radius: 25)
[03:16:12 -314719.589651] SPR radius for FAST iterations: 25 (autodetect)
[03:16:12 -314719.589651] Model parameter optimization (eps = 3.000000)
[03:16:23 -314435.089469] FAST spr round 1 (radius: 25)
[03:17:19 -270187.359569] FAST spr round 2 (radius: 25)
[03:17:56 -268721.133922] FAST spr round 3 (radius: 25)
[03:18:29 -268640.198052] FAST spr round 4 (radius: 25)
[03:18:59 -268619.454771] FAST spr round 5 (radius: 25)
[03:19:27 -268619.452712] Model parameter optimization (eps = 1.000000)
[03:19:35 -268616.808703] SLOW spr round 1 (radius: 5)
[03:20:19 -268575.929463] SLOW spr round 2 (radius: 5)
[03:21:01 -268575.928688] SLOW spr round 3 (radius: 10)
[03:21:48 -268575.266685] SLOW spr round 4 (radius: 5)
[03:22:43 -268575.266578] SLOW spr round 5 (radius: 10)
[03:23:36 -268575.266577] SLOW spr round 6 (radius: 15)
[03:24:50 -268575.266577] SLOW spr round 7 (radius: 20)
[03:26:36 -268575.266576] SLOW spr round 8 (radius: 25)
[03:28:24 -268575.266576] Model parameter optimization (eps = 0.100000)

[03:28:27] ML tree search #12, logLikelihood: -268575.220339

[03:28:27 -863834.320485] Initial branch length optimization
[03:28:29 -675707.426162] Model parameter optimization (eps = 10.000000)
[03:28:47 -673274.256575] AUTODETECT spr round 1 (radius: 5)
[03:29:22 -490450.315422] AUTODETECT spr round 2 (radius: 10)
[03:30:00 -397826.556418] AUTODETECT spr round 3 (radius: 15)
[03:30:44 -336501.949077] AUTODETECT spr round 4 (radius: 20)
[03:31:39 -302811.865661] AUTODETECT spr round 5 (radius: 25)
[03:32:34 -302598.052189] SPR radius for FAST iterations: 25 (autodetect)
[03:32:34 -302598.052189] Model parameter optimization (eps = 3.000000)
[03:32:45 -302316.480291] FAST spr round 1 (radius: 25)
[03:33:39 -269859.648705] FAST spr round 2 (radius: 25)
[03:34:14 -268649.119809] FAST spr round 3 (radius: 25)
[03:34:47 -268629.971082] FAST spr round 4 (radius: 25)
[03:35:16 -268624.688133] FAST spr round 5 (radius: 25)
[03:35:44 -268624.665086] Model parameter optimization (eps = 1.000000)
[03:35:53 -268618.442873] SLOW spr round 1 (radius: 5)
[03:36:37 -268555.653920] SLOW spr round 2 (radius: 5)
[03:37:20 -268555.652788] SLOW spr round 3 (radius: 10)
[03:38:09 -268555.019578] SLOW spr round 4 (radius: 5)
[03:39:05 -268555.019304] SLOW spr round 5 (radius: 10)
[03:40:00 -268554.992900] SLOW spr round 6 (radius: 15)
[03:41:17 -268554.992791] SLOW spr round 7 (radius: 20)
[03:43:08 -268554.992761] SLOW spr round 8 (radius: 25)
[03:44:59 -268554.992732] Model parameter optimization (eps = 0.100000)

[03:45:02] ML tree search #13, logLikelihood: -268554.918342

[03:45:02 -867554.592836] Initial branch length optimization
[03:45:05 -679435.818997] Model parameter optimization (eps = 10.000000)
[03:45:28 -676978.300719] AUTODETECT spr round 1 (radius: 5)
[03:46:04 -497518.303936] AUTODETECT spr round 2 (radius: 10)
[03:46:44 -376565.586333] AUTODETECT spr round 3 (radius: 15)
[03:47:29 -308731.579384] AUTODETECT spr round 4 (radius: 20)
[03:48:23 -294100.005312] AUTODETECT spr round 5 (radius: 25)
[03:49:28 -293221.191104] SPR radius for FAST iterations: 25 (autodetect)
[03:49:28 -293221.191104] Model parameter optimization (eps = 3.000000)
[03:49:41 -292938.697384] FAST spr round 1 (radius: 25)
[03:50:27 -269696.646684] FAST spr round 2 (radius: 25)
[03:51:01 -268729.226828] FAST spr round 3 (radius: 25)
[03:51:35 -268642.646377] FAST spr round 4 (radius: 25)
[03:52:04 -268633.793275] FAST spr round 5 (radius: 25)
[03:52:32 -268633.790549] Model parameter optimization (eps = 1.000000)
[03:52:42 -268624.187282] SLOW spr round 1 (radius: 5)
[03:53:26 -268567.261869] SLOW spr round 2 (radius: 5)
[03:54:09 -268567.256355] SLOW spr round 3 (radius: 10)
[03:54:57 -268566.598124] SLOW spr round 4 (radius: 5)
[03:55:54 -268566.597929] SLOW spr round 5 (radius: 10)
[03:56:47 -268566.597895] SLOW spr round 6 (radius: 15)
[03:58:06 -268566.597881] SLOW spr round 7 (radius: 20)
[03:59:54 -268566.597876] SLOW spr round 8 (radius: 25)
[04:01:47 -268566.597874] Model parameter optimization (eps = 0.100000)

[04:01:49] ML tree search #14, logLikelihood: -268566.543634

[04:01:50 -868728.757112] Initial branch length optimization
[04:01:52 -680157.942538] Model parameter optimization (eps = 10.000000)
[04:02:12 -677548.577057] AUTODETECT spr round 1 (radius: 5)
[04:02:48 -503763.615321] AUTODETECT spr round 2 (radius: 10)
[04:03:27 -394019.714151] AUTODETECT spr round 3 (radius: 15)
[04:04:10 -334793.498347] AUTODETECT spr round 4 (radius: 20)
[04:05:05 -309537.986785] AUTODETECT spr round 5 (radius: 25)
[04:06:00 -307050.858268] SPR radius for FAST iterations: 25 (autodetect)
[04:06:00 -307050.858268] Model parameter optimization (eps = 3.000000)
[04:06:14 -306801.202238] FAST spr round 1 (radius: 25)
[04:07:08 -269440.402572] FAST spr round 2 (radius: 25)
[04:07:48 -268710.507965] FAST spr round 3 (radius: 25)
[04:08:22 -268662.043328] FAST spr round 4 (radius: 25)
[04:08:52 -268615.260771] FAST spr round 5 (radius: 25)
[04:09:20 -268615.259404] Model parameter optimization (eps = 1.000000)
[04:09:28 -268609.797222] SLOW spr round 1 (radius: 5)
[04:10:12 -268558.198135] SLOW spr round 2 (radius: 5)
[04:10:56 -268558.167420] SLOW spr round 3 (radius: 10)
[04:11:44 -268557.531151] SLOW spr round 4 (radius: 5)
[04:12:41 -268557.530149] SLOW spr round 5 (radius: 10)
[04:13:35 -268557.508117] SLOW spr round 6 (radius: 15)
[04:14:53 -268557.508034] SLOW spr round 7 (radius: 20)
[04:16:40 -268557.508033] SLOW spr round 8 (radius: 25)
[04:18:26 -268557.508033] Model parameter optimization (eps = 0.100000)

[04:18:32] ML tree search #15, logLikelihood: -268556.946276

[04:18:32 -871205.737356] Initial branch length optimization
[04:18:35 -686748.990579] Model parameter optimization (eps = 10.000000)
[04:18:55 -684136.044324] AUTODETECT spr round 1 (radius: 5)
[04:19:30 -511703.618926] AUTODETECT spr round 2 (radius: 10)
[04:20:08 -387042.613891] AUTODETECT spr round 3 (radius: 15)
[04:20:49 -340478.236098] AUTODETECT spr round 4 (radius: 20)
[04:21:46 -301294.318707] AUTODETECT spr round 5 (radius: 25)
[04:22:52 -298152.873148] SPR radius for FAST iterations: 25 (autodetect)
[04:22:52 -298152.873148] Model parameter optimization (eps = 3.000000)
[04:23:05 -297827.652219] FAST spr round 1 (radius: 25)
[04:23:49 -271837.059016] FAST spr round 2 (radius: 25)
[04:24:27 -268716.214868] FAST spr round 3 (radius: 25)
[04:25:02 -268610.820852] FAST spr round 4 (radius: 25)
[04:25:32 -268602.780339] FAST spr round 5 (radius: 25)
[04:26:00 -268602.768047] Model parameter optimization (eps = 1.000000)
[04:26:06 -268596.900669] SLOW spr round 1 (radius: 5)
[04:26:52 -268562.939573] SLOW spr round 2 (radius: 5)
[04:27:38 -268558.116129] SLOW spr round 3 (radius: 5)
[04:28:21 -268558.114652] SLOW spr round 4 (radius: 10)
[04:29:10 -268557.056996] SLOW spr round 5 (radius: 5)
[04:30:06 -268557.054298] SLOW spr round 6 (radius: 10)
[04:30:59 -268557.029558] SLOW spr round 7 (radius: 15)
[04:32:14 -268557.029475] SLOW spr round 8 (radius: 20)
[04:33:56 -268557.029475] SLOW spr round 9 (radius: 25)
[04:35:45 -268557.029475] Model parameter optimization (eps = 0.100000)

[04:35:49] ML tree search #16, logLikelihood: -268556.996305

[04:35:49 -866385.911620] Initial branch length optimization
[04:35:51 -680134.649132] Model parameter optimization (eps = 10.000000)
[04:36:09 -677710.439236] AUTODETECT spr round 1 (radius: 5)
[04:36:46 -502579.163250] AUTODETECT spr round 2 (radius: 10)
[04:37:24 -402731.918393] AUTODETECT spr round 3 (radius: 15)
[04:38:11 -330057.575008] AUTODETECT spr round 4 (radius: 20)
[04:39:03 -305771.012038] AUTODETECT spr round 5 (radius: 25)
[04:39:58 -303705.032497] SPR radius for FAST iterations: 25 (autodetect)
[04:39:58 -303705.032497] Model parameter optimization (eps = 3.000000)
[04:40:12 -303421.803487] FAST spr round 1 (radius: 25)
[04:41:04 -271791.998110] FAST spr round 2 (radius: 25)
[04:41:45 -268673.030088] FAST spr round 3 (radius: 25)
[04:42:21 -268615.970770] FAST spr round 4 (radius: 25)
[04:42:50 -268612.754375] FAST spr round 5 (radius: 25)
[04:43:18 -268612.749204] Model parameter optimization (eps = 1.000000)
[04:43:26 -268608.104913] SLOW spr round 1 (radius: 5)
[04:44:10 -268571.815963] SLOW spr round 2 (radius: 5)
[04:44:55 -268570.599326] SLOW spr round 3 (radius: 5)
[04:45:38 -268570.596245] SLOW spr round 4 (radius: 10)
[04:46:28 -268569.941403] SLOW spr round 5 (radius: 5)
[04:47:25 -268569.941314] SLOW spr round 6 (radius: 10)
[04:48:20 -268569.941314] SLOW spr round 7 (radius: 15)
[04:49:39 -268569.941314] SLOW spr round 8 (radius: 20)
[04:51:30 -268569.941313] SLOW spr round 9 (radius: 25)
[04:53:23 -268569.941313] Model parameter optimization (eps = 0.100000)

[04:53:25] ML tree search #17, logLikelihood: -268569.899679

[04:53:25 -860844.691164] Initial branch length optimization
[04:53:28 -675251.388380] Model parameter optimization (eps = 10.000000)
[04:53:44 -672755.140511] AUTODETECT spr round 1 (radius: 5)
[04:54:20 -493830.331932] AUTODETECT spr round 2 (radius: 10)
[04:55:00 -373520.980579] AUTODETECT spr round 3 (radius: 15)
[04:55:49 -311851.187257] AUTODETECT spr round 4 (radius: 20)
[04:56:47 -295252.622980] AUTODETECT spr round 5 (radius: 25)
[04:57:55 -294367.702402] SPR radius for FAST iterations: 25 (autodetect)
[04:57:55 -294367.702402] Model parameter optimization (eps = 3.000000)
[04:58:07 -294107.142011] FAST spr round 1 (radius: 25)
[04:59:00 -269531.757312] FAST spr round 2 (radius: 25)
[04:59:42 -268645.822117] FAST spr round 3 (radius: 25)
[05:00:17 -268599.583819] FAST spr round 4 (radius: 25)
[05:00:46 -268592.522325] FAST spr round 5 (radius: 25)
[05:01:15 -268592.419164] FAST spr round 6 (radius: 25)
[05:01:42 -268592.416300] Model parameter optimization (eps = 1.000000)
[05:01:49 -268586.756312] SLOW spr round 1 (radius: 5)
[05:02:31 -268565.838033] SLOW spr round 2 (radius: 5)
[05:03:14 -268565.834566] SLOW spr round 3 (radius: 10)
[05:04:01 -268565.200641] SLOW spr round 4 (radius: 5)
[05:04:54 -268565.200054] SLOW spr round 5 (radius: 10)
[05:05:48 -268565.171044] SLOW spr round 6 (radius: 15)
[05:06:58 -268565.170944] SLOW spr round 7 (radius: 20)
[05:08:36 -268565.170937] SLOW spr round 8 (radius: 25)
[05:10:18 -268565.170934] Model parameter optimization (eps = 0.100000)

[05:10:22] ML tree search #18, logLikelihood: -268565.082164

[05:10:22 -861370.045047] Initial branch length optimization
[05:10:24 -676049.144985] Model parameter optimization (eps = 10.000000)
[05:10:47 -673651.989547] AUTODETECT spr round 1 (radius: 5)
[05:11:24 -476376.499185] AUTODETECT spr round 2 (radius: 10)
[05:12:03 -385742.337049] AUTODETECT spr round 3 (radius: 15)
[05:12:46 -323325.272783] AUTODETECT spr round 4 (radius: 20)
[05:13:30 -314639.931648] AUTODETECT spr round 5 (radius: 25)
[05:14:20 -314455.607661] SPR radius for FAST iterations: 25 (autodetect)
[05:14:20 -314455.607661] Model parameter optimization (eps = 3.000000)
[05:14:34 -314147.802952] FAST spr round 1 (radius: 25)
[05:15:21 -269917.895763] FAST spr round 2 (radius: 25)
[05:16:01 -268701.086542] FAST spr round 3 (radius: 25)
[05:16:36 -268624.952768] FAST spr round 4 (radius: 25)
[05:17:05 -268619.897132] FAST spr round 5 (radius: 25)
[05:17:32 -268619.861636] Model parameter optimization (eps = 1.000000)
[05:17:39 -268616.784159] SLOW spr round 1 (radius: 5)
[05:18:26 -268567.238784] SLOW spr round 2 (radius: 5)
[05:19:10 -268565.102454] SLOW spr round 3 (radius: 5)
[05:19:53 -268565.100725] SLOW spr round 4 (radius: 10)
[05:20:43 -268564.439416] SLOW spr round 5 (radius: 5)
[05:21:40 -268564.439317] SLOW spr round 6 (radius: 10)
[05:22:32 -268564.439314] SLOW spr round 7 (radius: 15)
[05:23:44 -268564.439313] SLOW spr round 8 (radius: 20)
[05:25:23 -268564.439313] SLOW spr round 9 (radius: 25)
[05:27:09 -268564.439313] Model parameter optimization (eps = 0.100000)

[05:27:11] ML tree search #19, logLikelihood: -268564.376837

[05:27:11 -857618.337605] Initial branch length optimization
[05:27:14 -665864.293666] Model parameter optimization (eps = 10.000000)
[05:27:30 -663328.958116] AUTODETECT spr round 1 (radius: 5)
[05:28:06 -510959.472684] AUTODETECT spr round 2 (radius: 10)
[05:28:44 -392627.850767] AUTODETECT spr round 3 (radius: 15)
[05:29:25 -349552.226782] AUTODETECT spr round 4 (radius: 20)
[05:30:17 -312230.457044] AUTODETECT spr round 5 (radius: 25)
[05:31:13 -307356.646508] SPR radius for FAST iterations: 25 (autodetect)
[05:31:13 -307356.646508] Model parameter optimization (eps = 3.000000)
[05:31:27 -306963.509036] FAST spr round 1 (radius: 25)
[05:32:12 -270605.759681] FAST spr round 2 (radius: 25)
[05:32:47 -268721.691083] FAST spr round 3 (radius: 25)
[05:33:20 -268618.740032] FAST spr round 4 (radius: 25)
[05:33:49 -268611.810383] FAST spr round 5 (radius: 25)
[05:34:18 -268611.808807] Model parameter optimization (eps = 1.000000)
[05:34:25 -268606.882472] SLOW spr round 1 (radius: 5)
[05:35:09 -268568.335776] SLOW spr round 2 (radius: 5)
[05:35:53 -268567.549015] SLOW spr round 3 (radius: 5)
[05:36:36 -268567.548537] SLOW spr round 4 (radius: 10)
[05:37:24 -268567.518996] SLOW spr round 5 (radius: 15)
[05:38:39 -268567.518913] SLOW spr round 6 (radius: 20)
[05:40:17 -268567.518912] SLOW spr round 7 (radius: 25)
[05:42:02 -268567.518912] Model parameter optimization (eps = 0.100000)

[05:42:08] ML tree search #20, logLikelihood: -268567.369789


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.180066,0.433255) (0.214535,0.506174) (0.312032,0.838020) (0.293367,1.881275) 
   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: -268554.918342

AIC score: 538919.836683 / AICc score: 543919.409854 / BIC score: 543551.641348
Free parameters (model + branch lengths): 905

Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q8NI27/3_mltree/Q8NI27.raxml.log

Analysis started: 13-Jul-2021 18:14:05 / finished: 13-Jul-2021 23:56:13

Elapsed time: 20528.715 seconds

Consumed energy: 1721.835 Wh (= 9 km in an electric car, or 43 km with an e-scooter!)