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 14-Jul-2021 14:51:35 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/2_msa/Q96J65_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65 --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/Q96J65/2_msa/Q96J65_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 1223 sites

WARNING: Sequences tr_B5DJ61_B5DJ61_DROPS_46245 and tr_B4G834_B4G834_DROPE_7234 are exactly identical!
WARNING: Sequences tr_F1PRX6_F1PRX6_CANLF_9615 and sp_Q6UR05_MRP1_CANLF_9615 are exactly identical!
WARNING: Sequences tr_K7AN90_K7AN90_PANTR_9598 and sp_O15440_MRP5_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_K7AN90_K7AN90_PANTR_9598 and tr_A0A2R9AB62_A0A2R9AB62_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F7FL20_F7FL20_MACMU_9544 and tr_G7NZ07_G7NZ07_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7FL20_F7FL20_MACMU_9544 and tr_A0A0D9RM21_A0A0D9RM21_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_F7FL20_F7FL20_MACMU_9544 and tr_A0A2K5LB23_A0A2K5LB23_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F4NRK4_F4NRK4_BATDJ_684364 and tr_A0A177W839_A0A177W839_BATDE_403673 are exactly identical!
WARNING: Sequences tr_F4P102_F4P102_BATDJ_684364 and tr_A0A177WDX7_A0A177WDX7_BATDE_403673 are exactly identical!
WARNING: Sequences tr_M8ANV9_M8ANV9_TRIUA_4572 and tr_A0A3B6B5F5_A0A3B6B5F5_WHEAT_4565 are exactly identical!
WARNING: Sequences tr_M8ANV9_M8ANV9_TRIUA_4572 and tr_A0A3B6DKM1_A0A3B6DKM1_WHEAT_4565 are exactly identical!
WARNING: Sequences tr_W2PWQ0_W2PWQ0_PHYPN_761204 and tr_W2KR63_W2KR63_PHYPR_4792 are exactly identical!
WARNING: Sequences tr_A0A015KCR6_A0A015KCR6_9GLOM_1432141 and tr_A0A2H5SSS0_A0A2H5SSS0_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A078FGE1_A0A078FGE1_BRANA_3708 and tr_A0A0D3BJ45_A0A0D3BJ45_BRAOL_109376 are exactly identical!
WARNING: Sequences tr_A0A226N3N4_A0A226N3N4_CALSU_9009 and tr_A0A226PSH4_A0A226PSH4_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2D0SD46_A0A2D0SD46_ICTPU_7998 and tr_A0A2D0SDR3_A0A2D0SDR3_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 16

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/Q96J65/3_mltree/Q96J65.raxml.reduced.phy

Alignment comprises 1 partitions and 1223 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1223 / 1223
Gaps: 2.61 %
Invariant sites: 0.33 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.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 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 136 / 10880
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -2249389.640619] Initial branch length optimization
[00:00:05 -1909358.964450] Model parameter optimization (eps = 10.000000)
[00:01:02 -1904786.074711] AUTODETECT spr round 1 (radius: 5)
[00:03:35 -1382924.998874] AUTODETECT spr round 2 (radius: 10)
[00:06:27 -986685.284294] AUTODETECT spr round 3 (radius: 15)
[00:09:34 -840949.638885] AUTODETECT spr round 4 (radius: 20)
[00:13:22 -779189.551645] AUTODETECT spr round 5 (radius: 25)
[00:18:17 -778186.607799] SPR radius for FAST iterations: 25 (autodetect)
[00:18:17 -778186.607799] Model parameter optimization (eps = 3.000000)
[00:18:37 -777305.558916] FAST spr round 1 (radius: 25)
[00:21:57 -692476.058680] FAST spr round 2 (radius: 25)
[00:24:29 -689927.250865] FAST spr round 3 (radius: 25)
[00:26:38 -689846.790750] FAST spr round 4 (radius: 25)
[00:28:28 -689840.361161] FAST spr round 5 (radius: 25)
[00:30:15 -689840.361154] Model parameter optimization (eps = 1.000000)
[00:30:26 -689836.344713] SLOW spr round 1 (radius: 5)
[00:33:12 -689719.561139] SLOW spr round 2 (radius: 5)
[00:35:38 -689715.713452] SLOW spr round 3 (radius: 5)
[00:38:02 -689715.713443] SLOW spr round 4 (radius: 10)
[00:40:24 -689715.713443] SLOW spr round 5 (radius: 15)
[00:44:34 -689715.713443] SLOW spr round 6 (radius: 20)
[00:50:59 -689715.713443] SLOW spr round 7 (radius: 25)
[00:59:10 -689715.713443] Model parameter optimization (eps = 0.100000)

[00:59:15] ML tree search #1, logLikelihood: -689715.660550

[00:59:15 -2258850.734906] Initial branch length optimization
[00:59:19 -1917267.244262] Model parameter optimization (eps = 10.000000)
[01:00:05 -1912439.070491] AUTODETECT spr round 1 (radius: 5)
[01:02:39 -1391359.167664] AUTODETECT spr round 2 (radius: 10)
[01:05:36 -990300.891215] AUTODETECT spr round 3 (radius: 15)
[01:08:41 -849712.659215] AUTODETECT spr round 4 (radius: 20)
[01:12:18 -803581.540003] AUTODETECT spr round 5 (radius: 25)
[01:16:18 -784152.547662] SPR radius for FAST iterations: 25 (autodetect)
[01:16:18 -784152.547662] Model parameter optimization (eps = 3.000000)
[01:16:37 -783414.682449] FAST spr round 1 (radius: 25)
[01:19:57 -693151.260960] FAST spr round 2 (radius: 25)
[01:22:21 -690077.792020] FAST spr round 3 (radius: 25)
[01:24:30 -689864.444068] FAST spr round 4 (radius: 25)
[01:26:21 -689847.087611] FAST spr round 5 (radius: 25)
[01:28:10 -689847.087559] Model parameter optimization (eps = 1.000000)
[01:28:26 -689812.765129] SLOW spr round 1 (radius: 5)
[01:31:11 -689725.195423] SLOW spr round 2 (radius: 5)
[01:33:42 -689722.171180] SLOW spr round 3 (radius: 5)
[01:36:07 -689722.171061] SLOW spr round 4 (radius: 10)
[01:38:30 -689722.171061] SLOW spr round 5 (radius: 15)
[01:42:43 -689722.171061] SLOW spr round 6 (radius: 20)
[01:49:00 -689722.171061] SLOW spr round 7 (radius: 25)
[01:57:09 -689722.171061] Model parameter optimization (eps = 0.100000)

[01:57:19] ML tree search #2, logLikelihood: -689721.911050

[01:57:19 -2251705.104955] Initial branch length optimization
[01:57:26 -1917552.209707] Model parameter optimization (eps = 10.000000)
[01:58:21 -1912737.882289] AUTODETECT spr round 1 (radius: 5)
[02:00:56 -1382095.917799] AUTODETECT spr round 2 (radius: 10)
[02:03:53 -995584.289199] AUTODETECT spr round 3 (radius: 15)
[02:08:44 -800176.190178] AUTODETECT spr round 4 (radius: 20)
[02:11:55 -777984.529013] AUTODETECT spr round 5 (radius: 25)
[02:15:59 -772067.478332] SPR radius for FAST iterations: 25 (autodetect)
[02:15:59 -772067.478332] Model parameter optimization (eps = 3.000000)
[02:16:29 -771201.193021] FAST spr round 1 (radius: 25)
[02:19:51 -692618.597121] FAST spr round 2 (radius: 25)
[02:22:27 -690099.985555] FAST spr round 3 (radius: 25)
[02:24:42 -689907.360699] FAST spr round 4 (radius: 25)
[02:26:38 -689894.712710] FAST spr round 5 (radius: 25)
[02:28:29 -689893.760310] FAST spr round 6 (radius: 25)
[02:30:16 -689893.760306] Model parameter optimization (eps = 1.000000)
[02:30:32 -689886.072464] SLOW spr round 1 (radius: 5)
[02:33:16 -689738.487545] SLOW spr round 2 (radius: 5)
[02:35:43 -689734.559172] SLOW spr round 3 (radius: 5)
[02:38:07 -689734.558663] SLOW spr round 4 (radius: 10)
[02:40:30 -689730.583330] SLOW spr round 5 (radius: 5)
[02:43:34 -689722.086717] SLOW spr round 6 (radius: 5)
[02:46:11 -689722.086688] SLOW spr round 7 (radius: 10)
[02:48:38 -689722.086687] SLOW spr round 8 (radius: 15)
[02:52:38 -689722.086687] SLOW spr round 9 (radius: 20)
[02:58:57 -689722.086687] SLOW spr round 10 (radius: 25)
[03:06:53 -689722.086687] Model parameter optimization (eps = 0.100000)

[03:07:01] ML tree search #3, logLikelihood: -689722.057875

[03:07:01 -2248047.122811] Initial branch length optimization
[03:07:08 -1917483.641116] Model parameter optimization (eps = 10.000000)
[03:07:49 -1912408.656930] AUTODETECT spr round 1 (radius: 5)
[03:10:25 -1381000.756813] AUTODETECT spr round 2 (radius: 10)
[03:13:20 -1038637.298096] AUTODETECT spr round 3 (radius: 15)
[03:16:28 -866595.494269] AUTODETECT spr round 4 (radius: 20)
[03:19:47 -804022.208703] AUTODETECT spr round 5 (radius: 25)
[03:23:45 -799289.064403] SPR radius for FAST iterations: 25 (autodetect)
[03:23:45 -799289.064403] Model parameter optimization (eps = 3.000000)
[03:24:02 -798491.963890] FAST spr round 1 (radius: 25)
[03:27:26 -693226.500756] FAST spr round 2 (radius: 25)
[03:29:57 -690055.674873] FAST spr round 3 (radius: 25)
[03:32:13 -689894.020711] FAST spr round 4 (radius: 25)
[03:34:08 -689884.939958] FAST spr round 5 (radius: 25)
[03:35:59 -689884.939868] Model parameter optimization (eps = 1.000000)
[03:36:15 -689855.876609] SLOW spr round 1 (radius: 5)
[03:39:00 -689740.246733] SLOW spr round 2 (radius: 5)
[03:41:34 -689712.654127] SLOW spr round 3 (radius: 5)
[03:43:59 -689712.654105] SLOW spr round 4 (radius: 10)
[03:46:24 -689712.654105] SLOW spr round 5 (radius: 15)
[03:50:37 -689712.654105] SLOW spr round 6 (radius: 20)
[03:56:48 -689712.654105] SLOW spr round 7 (radius: 25)
[04:04:46 -689712.654105] Model parameter optimization (eps = 0.100000)

[04:04:51] ML tree search #4, logLikelihood: -689712.594538

[04:04:52 -2261732.433665] Initial branch length optimization
[04:04:58 -1922203.665226] Model parameter optimization (eps = 10.000000)
[04:05:58 -1917291.775486] AUTODETECT spr round 1 (radius: 5)
[04:08:38 -1388535.473867] AUTODETECT spr round 2 (radius: 10)
[04:11:54 -1027433.992092] AUTODETECT spr round 3 (radius: 15)
[04:15:11 -865762.904478] AUTODETECT spr round 4 (radius: 20)
[04:19:03 -798587.263175] AUTODETECT spr round 5 (radius: 25)
[04:23:18 -776672.230269] SPR radius for FAST iterations: 25 (autodetect)
[04:23:18 -776672.230269] Model parameter optimization (eps = 3.000000)
[04:23:43 -775890.591481] FAST spr round 1 (radius: 25)
[04:27:28 -693599.973895] FAST spr round 2 (radius: 25)
[04:30:08 -690228.711737] FAST spr round 3 (radius: 25)
[04:32:28 -690045.056717] FAST spr round 4 (radius: 25)
[04:34:31 -689924.682161] FAST spr round 5 (radius: 25)
[04:36:22 -689924.682104] Model parameter optimization (eps = 1.000000)
[04:36:38 -689907.214228] SLOW spr round 1 (radius: 5)
[04:39:26 -689723.735412] SLOW spr round 2 (radius: 5)
[04:42:01 -689711.445701] SLOW spr round 3 (radius: 5)
[04:44:27 -689711.445679] SLOW spr round 4 (radius: 10)
[04:46:53 -689711.445679] SLOW spr round 5 (radius: 15)
[04:51:06 -689711.445679] SLOW spr round 6 (radius: 20)
[04:57:25 -689711.445679] SLOW spr round 7 (radius: 25)
[05:05:34 -689711.445679] Model parameter optimization (eps = 0.100000)

[05:05:43] ML tree search #5, logLikelihood: -689711.199917

[05:05:43 -2256797.316276] Initial branch length optimization
[05:05:51 -1923789.153942] Model parameter optimization (eps = 10.000000)
[05:06:37 -1918731.127501] AUTODETECT spr round 1 (radius: 5)
[05:09:12 -1388590.538099] AUTODETECT spr round 2 (radius: 10)
[05:12:14 -995657.242867] AUTODETECT spr round 3 (radius: 15)
[05:15:17 -841625.041720] AUTODETECT spr round 4 (radius: 20)
[05:18:48 -797391.792314] AUTODETECT spr round 5 (radius: 25)
[05:23:22 -780642.238587] SPR radius for FAST iterations: 25 (autodetect)
[05:23:22 -780642.238587] Model parameter optimization (eps = 3.000000)
[05:23:39 -779828.377859] FAST spr round 1 (radius: 25)
[05:27:03 -693213.594996] FAST spr round 2 (radius: 25)
[05:29:35 -690177.252570] FAST spr round 3 (radius: 25)
[05:31:50 -689989.556228] FAST spr round 4 (radius: 25)
[05:33:46 -689972.765999] FAST spr round 5 (radius: 25)
[05:35:37 -689972.765730] Model parameter optimization (eps = 1.000000)
[05:35:54 -689935.638386] SLOW spr round 1 (radius: 5)
[05:38:39 -689763.177243] SLOW spr round 2 (radius: 5)
[05:41:09 -689757.311526] SLOW spr round 3 (radius: 5)
[05:43:35 -689756.284028] SLOW spr round 4 (radius: 5)
[05:46:00 -689756.218472] SLOW spr round 5 (radius: 10)
[05:48:25 -689749.301905] SLOW spr round 6 (radius: 5)
[05:51:29 -689736.462916] SLOW spr round 7 (radius: 5)
[05:54:11 -689736.462771] SLOW spr round 8 (radius: 10)
[05:56:39 -689732.894292] SLOW spr round 9 (radius: 5)
[05:59:41 -689730.276506] SLOW spr round 10 (radius: 5)
[06:02:22 -689730.276413] SLOW spr round 11 (radius: 10)
[06:04:49 -689730.276412] SLOW spr round 12 (radius: 15)
[06:08:55 -689730.276412] SLOW spr round 13 (radius: 20)
[06:15:28 -689730.276412] SLOW spr round 14 (radius: 25)
[06:23:50 -689730.276412] Model parameter optimization (eps = 0.100000)

[06:24:01] ML tree search #6, logLikelihood: -689730.165237

[06:24:01 -2261206.607184] Initial branch length optimization
[06:24:06 -1924756.705713] Model parameter optimization (eps = 10.000000)
[06:24:46 -1920036.150424] AUTODETECT spr round 1 (radius: 5)
[06:27:24 -1393327.235208] AUTODETECT spr round 2 (radius: 10)
[06:30:23 -1032082.574777] AUTODETECT spr round 3 (radius: 15)
[06:33:24 -836517.874118] AUTODETECT spr round 4 (radius: 20)
[06:36:48 -803148.282281] AUTODETECT spr round 5 (radius: 25)
[06:40:50 -786546.487795] SPR radius for FAST iterations: 25 (autodetect)
[06:40:50 -786546.487795] Model parameter optimization (eps = 3.000000)
[06:41:14 -785729.266563] FAST spr round 1 (radius: 25)
[06:44:35 -693159.710226] FAST spr round 2 (radius: 25)
[06:47:07 -690088.057664] FAST spr round 3 (radius: 25)
[06:49:26 -689898.944289] FAST spr round 4 (radius: 25)
[06:51:23 -689886.196800] FAST spr round 5 (radius: 25)
[06:53:16 -689879.509736] FAST spr round 6 (radius: 25)
[06:55:06 -689879.509360] Model parameter optimization (eps = 1.000000)
[06:55:22 -689861.670603] SLOW spr round 1 (radius: 5)
[06:58:08 -689704.165111] SLOW spr round 2 (radius: 5)
[07:00:38 -689696.690726] SLOW spr round 3 (radius: 5)
[07:03:03 -689696.690685] SLOW spr round 4 (radius: 10)
[07:05:29 -689696.690678] SLOW spr round 5 (radius: 15)
[07:09:42 -689696.690676] SLOW spr round 6 (radius: 20)
[07:16:03 -689696.690676] SLOW spr round 7 (radius: 25)
[07:24:12 -689696.690676] Model parameter optimization (eps = 0.100000)

[07:24:19] ML tree search #7, logLikelihood: -689696.600762

[07:24:19 -2262739.208511] Initial branch length optimization
[07:24:25 -1920647.835503] Model parameter optimization (eps = 10.000000)
[07:25:07 -1915944.253018] AUTODETECT spr round 1 (radius: 5)
[07:27:44 -1400040.187227] AUTODETECT spr round 2 (radius: 10)
[07:30:41 -1049544.122257] AUTODETECT spr round 3 (radius: 15)
[07:33:49 -824174.832203] AUTODETECT spr round 4 (radius: 20)
[07:37:11 -782874.577855] AUTODETECT spr round 5 (radius: 25)
[07:41:15 -781091.692979] SPR radius for FAST iterations: 25 (autodetect)
[07:41:15 -781091.692979] Model parameter optimization (eps = 3.000000)
[07:41:21 -781091.351243] FAST spr round 1 (radius: 25)
[07:44:48 -694037.668954] FAST spr round 2 (radius: 25)
[07:47:25 -690764.721140] FAST spr round 3 (radius: 25)
[07:49:40 -690642.569428] FAST spr round 4 (radius: 25)
[07:51:44 -690604.174457] FAST spr round 5 (radius: 25)
[07:53:36 -690604.174373] Model parameter optimization (eps = 1.000000)
[07:53:55 -689825.722109] SLOW spr round 1 (radius: 5)
[07:56:46 -689724.417175] SLOW spr round 2 (radius: 5)
[07:59:22 -689719.148464] SLOW spr round 3 (radius: 5)
[08:01:48 -689719.148433] SLOW spr round 4 (radius: 10)
[08:04:14 -689719.148433] SLOW spr round 5 (radius: 15)
[08:08:26 -689719.148433] SLOW spr round 6 (radius: 20)
[08:14:36 -689719.148433] SLOW spr round 7 (radius: 25)
[08:22:34 -689719.148433] Model parameter optimization (eps = 0.100000)

[08:22:46] ML tree search #8, logLikelihood: -689718.964057

[08:22:46 -2243063.806074] Initial branch length optimization
[08:22:51 -1905545.481253] Model parameter optimization (eps = 10.000000)
[08:23:44 -1900756.958538] AUTODETECT spr round 1 (radius: 5)
[08:26:17 -1381827.898430] AUTODETECT spr round 2 (radius: 10)
[08:29:13 -1042894.234997] AUTODETECT spr round 3 (radius: 15)
[08:32:26 -860127.205321] AUTODETECT spr round 4 (radius: 20)
[08:36:02 -794310.443770] AUTODETECT spr round 5 (radius: 25)
[08:39:56 -792553.238747] SPR radius for FAST iterations: 25 (autodetect)
[08:39:56 -792553.238747] Model parameter optimization (eps = 3.000000)
[08:40:15 -791869.354513] FAST spr round 1 (radius: 25)
[08:43:43 -693266.467213] FAST spr round 2 (radius: 25)
[08:46:13 -690191.107962] FAST spr round 3 (radius: 25)
[08:48:27 -689988.847646] FAST spr round 4 (radius: 25)
[08:50:29 -689961.599625] FAST spr round 5 (radius: 25)
[08:52:22 -689948.076110] FAST spr round 6 (radius: 25)
[08:54:11 -689948.075999] Model parameter optimization (eps = 1.000000)
[08:54:26 -689920.923451] SLOW spr round 1 (radius: 5)
[08:57:15 -689775.661846] SLOW spr round 2 (radius: 5)
[08:59:51 -689750.005831] SLOW spr round 3 (radius: 5)
[09:02:25 -689739.569456] SLOW spr round 4 (radius: 5)
[09:04:50 -689735.701117] SLOW spr round 5 (radius: 5)
[09:07:12 -689735.701097] SLOW spr round 6 (radius: 10)
[09:09:37 -689735.701097] SLOW spr round 7 (radius: 15)
[09:13:45 -689735.701097] SLOW spr round 8 (radius: 20)
[09:19:57 -689735.701097] SLOW spr round 9 (radius: 25)
[09:27:59 -689735.701097] Model parameter optimization (eps = 0.100000)

[09:28:05] ML tree search #9, logLikelihood: -689735.673564

[09:28:05 -2255974.888901] Initial branch length optimization
[09:28:12 -1921379.890891] Model parameter optimization (eps = 10.000000)
[09:29:05 -1916336.711300] AUTODETECT spr round 1 (radius: 5)
[09:31:38 -1386489.572370] AUTODETECT spr round 2 (radius: 10)
[09:34:35 -1037596.738719] AUTODETECT spr round 3 (radius: 15)
[09:37:38 -933136.382009] AUTODETECT spr round 4 (radius: 20)
[09:41:59 -788838.599713] AUTODETECT spr round 5 (radius: 25)
[09:46:33 -777480.624964] SPR radius for FAST iterations: 25 (autodetect)
[09:46:33 -777480.624964] Model parameter optimization (eps = 3.000000)
[09:46:55 -776758.402404] FAST spr round 1 (radius: 25)
[09:50:18 -693151.747242] FAST spr round 2 (radius: 25)
[09:52:54 -690312.795036] FAST spr round 3 (radius: 25)
[09:55:11 -689928.641555] FAST spr round 4 (radius: 25)
[09:57:12 -689878.354544] FAST spr round 5 (radius: 25)
[09:59:03 -689877.036553] FAST spr round 6 (radius: 25)
[10:00:51 -689877.036441] Model parameter optimization (eps = 1.000000)
[10:01:03 -689870.048371] SLOW spr round 1 (radius: 5)
[10:03:50 -689729.559024] SLOW spr round 2 (radius: 5)
[10:06:20 -689722.843663] SLOW spr round 3 (radius: 5)
[10:08:45 -689722.842811] SLOW spr round 4 (radius: 10)
[10:11:12 -689722.842638] SLOW spr round 5 (radius: 15)
[10:15:21 -689722.842603] SLOW spr round 6 (radius: 20)
[10:21:30 -689722.842596] SLOW spr round 7 (radius: 25)
[10:29:26 -689722.842594] Model parameter optimization (eps = 0.100000)

[10:29:35] ML tree search #10, logLikelihood: -689722.731128

[10:29:35 -2245983.349658] Initial branch length optimization
[10:29:41 -1910165.862586] Model parameter optimization (eps = 10.000000)
[10:30:36 -1905307.516370] AUTODETECT spr round 1 (radius: 5)
[10:33:14 -1384184.784367] AUTODETECT spr round 2 (radius: 10)
[10:36:05 -1060875.164114] AUTODETECT spr round 3 (radius: 15)
[10:39:18 -858530.543103] AUTODETECT spr round 4 (radius: 20)
[10:42:39 -802155.479444] AUTODETECT spr round 5 (radius: 25)
[10:46:44 -783595.619677] SPR radius for FAST iterations: 25 (autodetect)
[10:46:44 -783595.619677] Model parameter optimization (eps = 3.000000)
[10:47:05 -782718.800803] FAST spr round 1 (radius: 25)
[10:50:27 -693205.017155] FAST spr round 2 (radius: 25)
[10:53:02 -690651.446412] FAST spr round 3 (radius: 25)
[10:55:19 -690000.556668] FAST spr round 4 (radius: 25)
[10:57:20 -689935.163318] FAST spr round 5 (radius: 25)
[10:59:10 -689927.256481] FAST spr round 6 (radius: 25)
[11:01:00 -689927.256427] Model parameter optimization (eps = 1.000000)
[11:01:15 -689909.684711] SLOW spr round 1 (radius: 5)
[11:04:02 -689772.474507] SLOW spr round 2 (radius: 5)
[11:06:38 -689748.672680] SLOW spr round 3 (radius: 5)
[11:09:09 -689734.209365] SLOW spr round 4 (radius: 5)
[11:11:33 -689734.209338] SLOW spr round 5 (radius: 10)
[11:13:57 -689734.209338] SLOW spr round 6 (radius: 15)
[11:18:10 -689734.209338] SLOW spr round 7 (radius: 20)
[11:24:28 -689734.209338] SLOW spr round 8 (radius: 25)
[11:32:27 -689734.209338] Model parameter optimization (eps = 0.100000)

[11:32:33] ML tree search #11, logLikelihood: -689734.168969

[11:32:33 -2252812.827222] Initial branch length optimization
[11:32:40 -1920912.970357] Model parameter optimization (eps = 10.000000)
[11:33:20 -1915888.188064] AUTODETECT spr round 1 (radius: 5)
[11:35:55 -1403742.161701] AUTODETECT spr round 2 (radius: 10)
[11:38:56 -1053261.794108] AUTODETECT spr round 3 (radius: 15)
[11:42:06 -935341.411654] AUTODETECT spr round 4 (radius: 20)
[11:46:13 -876113.253912] AUTODETECT spr round 5 (radius: 25)
[11:50:27 -825141.273318] SPR radius for FAST iterations: 25 (autodetect)
[11:50:27 -825141.273318] Model parameter optimization (eps = 3.000000)
[11:50:43 -824296.573321] FAST spr round 1 (radius: 25)
[11:54:22 -695398.633405] FAST spr round 2 (radius: 25)
[11:56:57 -690493.905376] FAST spr round 3 (radius: 25)
[11:59:08 -690005.242920] FAST spr round 4 (radius: 25)
[12:01:07 -689967.100577] FAST spr round 5 (radius: 25)
[12:02:59 -689964.882654] FAST spr round 6 (radius: 25)
[12:04:49 -689964.882654] Model parameter optimization (eps = 1.000000)
[12:05:05 -689946.130842] SLOW spr round 1 (radius: 5)
[12:07:53 -689767.714742] SLOW spr round 2 (radius: 5)
[12:10:28 -689718.538719] SLOW spr round 3 (radius: 5)
[12:12:52 -689718.538659] SLOW spr round 4 (radius: 10)
[12:15:14 -689718.538659] SLOW spr round 5 (radius: 15)
[12:19:23 -689718.538659] SLOW spr round 6 (radius: 20)
[12:25:45 -689718.538659] SLOW spr round 7 (radius: 25)
[12:33:54 -689718.538659] Model parameter optimization (eps = 0.100000)

[12:34:04] ML tree search #12, logLikelihood: -689718.021205

[12:34:04 -2256385.424036] Initial branch length optimization
[12:34:10 -1914177.184711] Model parameter optimization (eps = 10.000000)
[12:34:57 -1909345.113422] AUTODETECT spr round 1 (radius: 5)
[12:37:32 -1385826.229054] AUTODETECT spr round 2 (radius: 10)
[12:40:26 -1049735.550020] AUTODETECT spr round 3 (radius: 15)
[12:43:24 -866126.443036] AUTODETECT spr round 4 (radius: 20)
[12:46:42 -800294.278434] AUTODETECT spr round 5 (radius: 25)
[12:50:32 -783697.908101] SPR radius for FAST iterations: 25 (autodetect)
[12:50:32 -783697.908101] Model parameter optimization (eps = 3.000000)
[12:50:53 -782898.649216] FAST spr round 1 (radius: 25)
[12:54:18 -693559.134037] FAST spr round 2 (radius: 25)
[12:56:53 -690056.246282] FAST spr round 3 (radius: 25)
[12:59:08 -689940.491546] FAST spr round 4 (radius: 25)
[13:01:05 -689926.400301] FAST spr round 5 (radius: 25)
[13:02:55 -689926.400279] Model parameter optimization (eps = 1.000000)
[13:03:11 -689871.746966] SLOW spr round 1 (radius: 5)
[13:06:00 -689749.185913] SLOW spr round 2 (radius: 5)
[13:08:38 -689724.841825] SLOW spr round 3 (radius: 5)
[13:11:05 -689724.212892] SLOW spr round 4 (radius: 5)
[13:13:30 -689724.212175] SLOW spr round 5 (radius: 10)
[13:15:54 -689724.212175] SLOW spr round 6 (radius: 15)
[13:20:09 -689724.212175] SLOW spr round 7 (radius: 20)
[13:26:36 -689724.212175] SLOW spr round 8 (radius: 25)
[13:34:53 -689724.212175] Model parameter optimization (eps = 0.100000)

[13:35:04] ML tree search #13, logLikelihood: -689724.053213

[13:35:04 -2253070.213195] Initial branch length optimization
[13:35:09 -1914869.616039] Model parameter optimization (eps = 10.000000)
[13:36:09 -1910293.251672] AUTODETECT spr round 1 (radius: 5)
[13:38:44 -1389368.050738] AUTODETECT spr round 2 (radius: 10)
[13:41:40 -1000208.443814] AUTODETECT spr round 3 (radius: 15)
[13:44:53 -827578.681625] AUTODETECT spr round 4 (radius: 20)
[13:48:28 -779930.685190] AUTODETECT spr round 5 (radius: 25)
[13:52:35 -772488.016197] SPR radius for FAST iterations: 25 (autodetect)
[13:52:35 -772488.016197] Model parameter optimization (eps = 3.000000)
[13:53:00 -771751.764929] FAST spr round 1 (radius: 25)
[13:56:18 -692947.768484] FAST spr round 2 (radius: 25)
[13:58:47 -690180.627293] FAST spr round 3 (radius: 25)
[14:01:01 -689921.572424] FAST spr round 4 (radius: 25)
[14:02:57 -689906.885688] FAST spr round 5 (radius: 25)
[14:04:52 -689896.297872] FAST spr round 6 (radius: 25)
[14:06:40 -689896.297865] Model parameter optimization (eps = 1.000000)
[14:06:55 -689872.806262] SLOW spr round 1 (radius: 5)
[14:09:37 -689750.202967] SLOW spr round 2 (radius: 5)
[14:12:08 -689725.825458] SLOW spr round 3 (radius: 5)
[14:14:32 -689720.551333] SLOW spr round 4 (radius: 5)
[14:16:54 -689716.237526] SLOW spr round 5 (radius: 5)
[14:19:16 -689716.237332] SLOW spr round 6 (radius: 10)
[14:21:38 -689716.237332] SLOW spr round 7 (radius: 15)
[14:25:48 -689716.237332] SLOW spr round 8 (radius: 20)
[14:32:05 -689716.237332] SLOW spr round 9 (radius: 25)
[14:40:08 -689716.237332] Model parameter optimization (eps = 0.100000)

[14:40:19] ML tree search #14, logLikelihood: -689715.891238

[14:40:20 -2257432.209435] Initial branch length optimization
[14:40:24 -1921799.043336] Model parameter optimization (eps = 10.000000)
[14:41:03 -1917026.303254] AUTODETECT spr round 1 (radius: 5)
[14:43:37 -1363835.830987] AUTODETECT spr round 2 (radius: 10)
[14:46:31 -1003662.686271] AUTODETECT spr round 3 (radius: 15)
[14:49:37 -826846.404204] AUTODETECT spr round 4 (radius: 20)
[14:53:00 -798210.902768] AUTODETECT spr round 5 (radius: 25)
[14:56:52 -785644.402759] SPR radius for FAST iterations: 25 (autodetect)
[14:56:52 -785644.402759] Model parameter optimization (eps = 3.000000)
[14:57:11 -784738.145045] FAST spr round 1 (radius: 25)
[15:00:24 -692721.110736] FAST spr round 2 (radius: 25)
[15:02:48 -690049.144000] FAST spr round 3 (radius: 25)
[15:04:57 -689973.388804] FAST spr round 4 (radius: 25)
[15:06:53 -689955.004013] FAST spr round 5 (radius: 25)
[15:08:44 -689950.110664] FAST spr round 6 (radius: 25)
[15:10:31 -689950.110664] Model parameter optimization (eps = 1.000000)
[15:10:48 -689929.278255] SLOW spr round 1 (radius: 5)
[15:13:26 -689749.296036] SLOW spr round 2 (radius: 5)
[15:15:56 -689710.817320] SLOW spr round 3 (radius: 5)
[15:18:22 -689708.196283] SLOW spr round 4 (radius: 5)
[15:20:45 -689708.195563] SLOW spr round 5 (radius: 10)
[15:23:08 -689708.195563] SLOW spr round 6 (radius: 15)
[15:27:23 -689708.195562] SLOW spr round 7 (radius: 20)
[15:33:51 -689708.195562] SLOW spr round 8 (radius: 25)
[15:42:07 -689708.195562] Model parameter optimization (eps = 0.100000)

[15:42:18] ML tree search #15, logLikelihood: -689707.265764

[15:42:19 -2262655.710769] Initial branch length optimization
[15:42:24 -1925370.343770] Model parameter optimization (eps = 10.000000)
[15:43:17 -1920401.627158] AUTODETECT spr round 1 (radius: 5)
[15:45:48 -1399843.799952] AUTODETECT spr round 2 (radius: 10)
[15:48:43 -1011299.982043] AUTODETECT spr round 3 (radius: 15)
[15:51:41 -837676.051663] AUTODETECT spr round 4 (radius: 20)
[15:55:16 -786220.645556] AUTODETECT spr round 5 (radius: 25)
[15:59:42 -778503.213193] SPR radius for FAST iterations: 25 (autodetect)
[15:59:42 -778503.213193] Model parameter optimization (eps = 3.000000)
[15:59:47 -778502.980121] FAST spr round 1 (radius: 25)
[16:03:12 -693560.174297] FAST spr round 2 (radius: 25)
[16:05:45 -690764.740713] FAST spr round 3 (radius: 25)
[16:07:58 -690659.937985] FAST spr round 4 (radius: 25)
[16:09:52 -690639.235631] FAST spr round 5 (radius: 25)
[16:11:41 -690639.235446] Model parameter optimization (eps = 1.000000)
[16:12:04 -689922.765057] SLOW spr round 1 (radius: 5)
[16:14:48 -689751.630756] SLOW spr round 2 (radius: 5)
[16:17:21 -689736.996165] SLOW spr round 3 (radius: 5)
[16:19:46 -689735.152904] SLOW spr round 4 (radius: 5)
[16:22:08 -689735.152847] SLOW spr round 5 (radius: 10)
[16:24:31 -689735.152845] SLOW spr round 6 (radius: 15)
[16:28:39 -689735.152845] SLOW spr round 7 (radius: 20)
[16:34:49 -689735.152845] SLOW spr round 8 (radius: 25)
[16:42:44 -689735.152845] Model parameter optimization (eps = 0.100000)

[16:42:56] ML tree search #16, logLikelihood: -689735.018386

[16:42:56 -2259714.147093] Initial branch length optimization
[16:43:02 -1925595.192933] Model parameter optimization (eps = 10.000000)
[16:43:56 -1920672.268602] AUTODETECT spr round 1 (radius: 5)
[16:46:29 -1400359.092925] AUTODETECT spr round 2 (radius: 10)
[16:49:20 -1059130.300622] AUTODETECT spr round 3 (radius: 15)
[16:52:24 -865469.967507] AUTODETECT spr round 4 (radius: 20)
[16:55:49 -805232.780164] AUTODETECT spr round 5 (radius: 25)
[16:59:57 -793005.615276] SPR radius for FAST iterations: 25 (autodetect)
[16:59:57 -793005.615276] Model parameter optimization (eps = 3.000000)
[17:00:18 -792219.744344] FAST spr round 1 (radius: 25)
[17:03:30 -694045.223072] FAST spr round 2 (radius: 25)
[17:05:57 -690149.122206] FAST spr round 3 (radius: 25)
[17:08:09 -689963.386409] FAST spr round 4 (radius: 25)
[17:10:04 -689928.744966] FAST spr round 5 (radius: 25)
[17:11:53 -689928.744735] Model parameter optimization (eps = 1.000000)
[17:12:09 -689904.198726] SLOW spr round 1 (radius: 5)
[17:14:48 -689756.046816] SLOW spr round 2 (radius: 5)
[17:17:15 -689748.049537] SLOW spr round 3 (radius: 5)
[17:19:37 -689748.049534] SLOW spr round 4 (radius: 10)
[17:21:57 -689748.049534] SLOW spr round 5 (radius: 15)
[17:26:01 -689748.049534] SLOW spr round 6 (radius: 20)
[17:32:01 -689748.049534] SLOW spr round 7 (radius: 25)
[17:39:42 -689748.049534] Model parameter optimization (eps = 0.100000)

[17:39:48] ML tree search #17, logLikelihood: -689748.006308

[17:39:48 -2254798.019494] Initial branch length optimization
[17:39:54 -1919659.645574] Model parameter optimization (eps = 10.000000)
[17:40:30 -1914713.229333] AUTODETECT spr round 1 (radius: 5)
[17:42:59 -1402024.511058] AUTODETECT spr round 2 (radius: 10)
[17:45:51 -998693.887240] AUTODETECT spr round 3 (radius: 15)
[17:48:50 -834814.126570] AUTODETECT spr round 4 (radius: 20)
[17:52:02 -800795.457816] AUTODETECT spr round 5 (radius: 25)
[17:56:03 -779166.211621] SPR radius for FAST iterations: 25 (autodetect)
[17:56:03 -779166.211621] Model parameter optimization (eps = 3.000000)
[17:56:08 -779165.638112] FAST spr round 1 (radius: 25)
[17:59:31 -695005.822129] FAST spr round 2 (radius: 25)
[18:01:58 -691091.526323] FAST spr round 3 (radius: 25)
[18:04:12 -690632.502533] FAST spr round 4 (radius: 25)
[18:06:08 -690595.270533] FAST spr round 5 (radius: 25)
[18:07:56 -690577.391945] FAST spr round 6 (radius: 25)
[18:09:40 -690577.391941] Model parameter optimization (eps = 1.000000)
[18:10:01 -689810.607456] SLOW spr round 1 (radius: 5)
[18:12:40 -689714.543579] SLOW spr round 2 (radius: 5)
[18:15:05 -689703.335917] SLOW spr round 3 (radius: 5)
[18:17:24 -689703.335286] SLOW spr round 4 (radius: 10)
[18:19:42 -689703.189430] SLOW spr round 5 (radius: 5)
[18:22:39 -689699.276506] SLOW spr round 6 (radius: 5)
[18:25:14 -689699.276506] SLOW spr round 7 (radius: 10)
[18:27:37 -689699.276506] SLOW spr round 8 (radius: 15)
[18:31:29 -689699.276506] SLOW spr round 9 (radius: 20)
[18:37:34 -689699.276506] SLOW spr round 10 (radius: 25)
[18:45:13 -689699.276506] Model parameter optimization (eps = 0.100000)

[18:45:23] ML tree search #18, logLikelihood: -689699.058966

[18:45:23 -2263135.554848] Initial branch length optimization
[18:45:28 -1928867.575012] Model parameter optimization (eps = 10.000000)
[18:46:19 -1923829.640645] AUTODETECT spr round 1 (radius: 5)
[18:48:50 -1408534.336322] AUTODETECT spr round 2 (radius: 10)
[18:51:44 -1047388.112152] AUTODETECT spr round 3 (radius: 15)
[18:54:41 -851302.182238] AUTODETECT spr round 4 (radius: 20)
[18:58:00 -806283.201722] AUTODETECT spr round 5 (radius: 25)
[19:02:09 -792204.337365] SPR radius for FAST iterations: 25 (autodetect)
[19:02:09 -792204.337365] Model parameter optimization (eps = 3.000000)
[19:02:26 -791534.741567] FAST spr round 1 (radius: 25)
[19:05:39 -694657.555094] FAST spr round 2 (radius: 25)
[19:07:58 -690105.633732] FAST spr round 3 (radius: 25)
[19:10:07 -689930.853416] FAST spr round 4 (radius: 25)
[19:12:04 -689897.714631] FAST spr round 5 (radius: 25)
[19:13:52 -689895.583607] FAST spr round 6 (radius: 25)
[19:15:36 -689895.583597] Model parameter optimization (eps = 1.000000)
[19:15:52 -689852.577305] SLOW spr round 1 (radius: 5)
[19:18:30 -689733.877076] SLOW spr round 2 (radius: 5)
[19:20:56 -689726.216278] SLOW spr round 3 (radius: 5)
[19:23:18 -689725.376104] SLOW spr round 4 (radius: 5)
[19:25:38 -689725.376044] SLOW spr round 5 (radius: 10)
[19:27:59 -689725.376041] SLOW spr round 6 (radius: 15)
[19:32:04 -689725.376041] SLOW spr round 7 (radius: 20)
[19:38:14 -689725.376041] SLOW spr round 8 (radius: 25)
[19:46:08 -689725.376041] Model parameter optimization (eps = 0.100000)

[19:46:20] ML tree search #19, logLikelihood: -689725.283259

[19:46:20 -2249006.476480] Initial branch length optimization
[19:46:25 -1914446.056443] Model parameter optimization (eps = 10.000000)
[19:47:10 -1909415.709156] AUTODETECT spr round 1 (radius: 5)
[19:49:42 -1362285.183432] AUTODETECT spr round 2 (radius: 10)
[19:52:31 -1025524.169730] AUTODETECT spr round 3 (radius: 15)
[19:55:31 -882648.619498] AUTODETECT spr round 4 (radius: 20)
[19:58:53 -821333.913017] AUTODETECT spr round 5 (radius: 25)
[20:02:48 -793879.803493] SPR radius for FAST iterations: 25 (autodetect)
[20:02:48 -793879.803493] Model parameter optimization (eps = 3.000000)
[20:03:08 -793125.832371] FAST spr round 1 (radius: 25)
[20:06:39 -694812.375505] FAST spr round 2 (radius: 25)
[20:09:14 -690213.482707] FAST spr round 3 (radius: 25)
[20:11:24 -689935.726153] FAST spr round 4 (radius: 25)
[20:13:22 -689903.947662] FAST spr round 5 (radius: 25)
[20:15:12 -689903.947662] Model parameter optimization (eps = 1.000000)
[20:15:27 -689873.590361] SLOW spr round 1 (radius: 5)
[20:18:07 -689724.878482] SLOW spr round 2 (radius: 5)
[20:20:37 -689717.074126] SLOW spr round 3 (radius: 5)
[20:22:59 -689717.074108] SLOW spr round 4 (radius: 10)
[20:25:22 -689717.074108] SLOW spr round 5 (radius: 15)
[20:29:30 -689717.074108] SLOW spr round 6 (radius: 20)
[20:35:45 -689717.074108] SLOW spr round 7 (radius: 25)
[20:43:48 -689717.074108] Model parameter optimization (eps = 0.100000)

[20:43:50] ML tree search #20, logLikelihood: -689717.073370


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.199575,0.392512) (0.313191,0.506294) (0.329464,1.222823) (0.157770,2.283208) 
   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: -689696.600762

AIC score: 1383403.201524 / AICc score: 9427463.201524 / BIC score: 1393646.871106
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=1223).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 25 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96J65/3_mltree/Q96J65.raxml.log

Analysis started: 14-Jul-2021 14:51:35 / finished: 15-Jul-2021 11:35:26

Elapsed time: 74630.679 seconds

Consumed energy: 5317.756 Wh (= 27 km in an electric car, or 133 km with an e-scooter!)