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 03-Jul-2021 19:35:25 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/2_msa/P19823_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823 --seed 2 --threads 8 --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 (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/2_msa/P19823_trimmed_msa.fasta
[00:00:00] Loaded alignment with 707 taxa and 908 sites

WARNING: Sequences tr_A0A2I3SNF6_A0A2I3SNF6_PANTR_9598 and tr_A0A2R8Z603_A0A2R8Z603_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1U7Q227_A0A1U7Q227_MESAU_10036 and sp_P97280_ITIH3_MESAU_10036 are exactly identical!
WARNING: Sequences tr_A0A1U7Q2C1_A0A1U7Q2C1_MESAU_10036 and sp_P97279_ITIH2_MESAU_10036 are exactly identical!
WARNING: Sequences tr_A0A2D0PI61_A0A2D0PI61_ICTPU_7998 and tr_A0A2D0PKE7_A0A2D0PKE7_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0T491_A0A2D0T491_ICTPU_7998 and tr_A0A2D0T499_A0A2D0T499_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0T4I4_A0A2D0T4I4_ICTPU_7998 and tr_A0A2D0T544_A0A2D0T544_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2G2ZR38_A0A2G2ZR38_CAPAN_4072 and tr_A0A2G3CPD4_A0A2G3CPD4_CAPCH_80379 are exactly identical!
WARNING: Duplicate sequences found: 7

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/P19823/3_mltree/P19823.raxml.reduced.phy

Alignment comprises 1 partitions and 908 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 908 / 908
Gaps: 22.01 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 707 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 227 / 18160
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1000950.950044] Initial branch length optimization
[00:00:08 -848577.449673] Model parameter optimization (eps = 10.000000)
[00:01:44 -846351.963409] AUTODETECT spr round 1 (radius: 5)
[00:04:45 -586086.841589] AUTODETECT spr round 2 (radius: 10)
[00:08:06 -445061.530705] AUTODETECT spr round 3 (radius: 15)
[00:12:06 -399258.407027] AUTODETECT spr round 4 (radius: 20)
[00:17:42 -348393.911105] AUTODETECT spr round 5 (radius: 25)
[00:23:48 -343773.725264] SPR radius for FAST iterations: 25 (autodetect)
[00:23:48 -343773.725264] Model parameter optimization (eps = 3.000000)
[00:24:28 -343547.795807] FAST spr round 1 (radius: 25)
[00:28:25 -310157.142520] FAST spr round 2 (radius: 25)
[00:31:37 -308637.824043] FAST spr round 3 (radius: 25)
[00:34:25 -308552.364477] FAST spr round 4 (radius: 25)
[00:36:48 -308526.110984] FAST spr round 5 (radius: 25)
[00:38:56 -308526.101962] Model parameter optimization (eps = 1.000000)
[00:39:20 -308524.371688] SLOW spr round 1 (radius: 5)
[00:42:53 -308481.332850] SLOW spr round 2 (radius: 5)
[00:46:07 -308479.517955] SLOW spr round 3 (radius: 5)
[00:49:19 -308476.450854] SLOW spr round 4 (radius: 5)
[00:52:26 -308476.449616] SLOW spr round 5 (radius: 10)
[00:55:49 -308476.125187] SLOW spr round 6 (radius: 5)
[01:00:01 -308476.119970] SLOW spr round 7 (radius: 10)
[01:03:54 -308476.118894] SLOW spr round 8 (radius: 15)
[01:09:51 -308476.118684] SLOW spr round 9 (radius: 20)
[01:20:58 -308476.118631] SLOW spr round 10 (radius: 25)
[01:22:32] [worker #1] ML tree search #2, logLikelihood: -308452.255032
[01:35:40 -308476.118608] Model parameter optimization (eps = 0.100000)

[01:35:57] [worker #0] ML tree search #1, logLikelihood: -308475.476942

[01:35:57 -1010839.949904] Initial branch length optimization
[01:36:06 -855950.837711] Model parameter optimization (eps = 10.000000)
[01:38:04 -853602.692461] AUTODETECT spr round 1 (radius: 5)
[01:41:11 -591941.046437] AUTODETECT spr round 2 (radius: 10)
[01:44:37 -448306.656998] AUTODETECT spr round 3 (radius: 15)
[01:48:34 -382544.339216] AUTODETECT spr round 4 (radius: 20)
[01:53:54 -350867.520869] AUTODETECT spr round 5 (radius: 25)
[02:00:58 -347560.333772] SPR radius for FAST iterations: 25 (autodetect)
[02:00:58 -347560.333772] Model parameter optimization (eps = 3.000000)
[02:01:35 -347340.806801] FAST spr round 1 (radius: 25)
[02:05:57 -309613.115639] FAST spr round 2 (radius: 25)
[02:09:23 -308633.030025] FAST spr round 3 (radius: 25)
[02:12:14 -308590.710704] FAST spr round 4 (radius: 25)
[02:14:52 -308558.621180] FAST spr round 5 (radius: 25)
[02:17:20 -308549.140016] FAST spr round 6 (radius: 25)
[02:19:36 -308549.035950] FAST spr round 7 (radius: 25)
[02:21:48 -308549.035770] Model parameter optimization (eps = 1.000000)
[02:22:16 -308543.589504] SLOW spr round 1 (radius: 5)
[02:26:00 -308457.227616] SLOW spr round 2 (radius: 5)
[02:29:23 -308450.620313] SLOW spr round 3 (radius: 5)
[02:32:40 -308450.616626] SLOW spr round 4 (radius: 10)
[02:36:15 -308450.615546] SLOW spr round 5 (radius: 15)
[02:43:10 -308450.614974] SLOW spr round 6 (radius: 20)
[02:49:17] [worker #1] ML tree search #4, logLikelihood: -308453.181170
[02:54:51 -308450.614625] SLOW spr round 7 (radius: 25)
[03:08:34 -308450.614403] Model parameter optimization (eps = 0.100000)

[03:08:55] [worker #0] ML tree search #3, logLikelihood: -308449.967993

[03:08:55 -1005708.598302] Initial branch length optimization
[03:09:03 -855335.505688] Model parameter optimization (eps = 10.000000)
[03:10:56 -853257.644608] AUTODETECT spr round 1 (radius: 5)
[03:13:59 -596397.451368] AUTODETECT spr round 2 (radius: 10)
[03:17:19 -445024.704604] AUTODETECT spr round 3 (radius: 15)
[03:21:11 -390322.293739] AUTODETECT spr round 4 (radius: 20)
[03:26:17 -353086.916713] AUTODETECT spr round 5 (radius: 25)
[03:33:11 -349961.175525] SPR radius for FAST iterations: 25 (autodetect)
[03:33:11 -349961.175525] Model parameter optimization (eps = 3.000000)
[03:33:53 -349608.542350] FAST spr round 1 (radius: 25)
[03:38:14 -310889.428357] FAST spr round 2 (radius: 25)
[03:41:27 -308642.697105] FAST spr round 3 (radius: 25)
[03:44:10 -308556.509502] FAST spr round 4 (radius: 25)
[03:46:38 -308542.597968] FAST spr round 5 (radius: 25)
[03:48:46 -308540.813945] FAST spr round 6 (radius: 25)
[03:50:51 -308540.813933] Model parameter optimization (eps = 1.000000)
[03:51:09 -308538.608475] SLOW spr round 1 (radius: 5)
[03:54:42 -308481.819477] SLOW spr round 2 (radius: 5)
[03:57:58 -308466.410765] SLOW spr round 3 (radius: 5)
[04:01:05 -308466.409145] SLOW spr round 4 (radius: 10)
[04:04:25 -308466.408992] SLOW spr round 5 (radius: 15)
[04:10:44 -308466.408935] SLOW spr round 6 (radius: 20)
[04:21:29 -308466.408902] SLOW spr round 7 (radius: 25)
[04:22:06] [worker #1] ML tree search #6, logLikelihood: -308449.877711
[04:36:01 -308466.408881] Model parameter optimization (eps = 0.100000)

[04:36:18] [worker #0] ML tree search #5, logLikelihood: -308466.193204

[04:36:18 -1010094.501430] Initial branch length optimization
[04:36:26 -854879.129181] Model parameter optimization (eps = 10.000000)
[04:38:11 -852600.772709] AUTODETECT spr round 1 (radius: 5)
[04:41:16 -595864.145344] AUTODETECT spr round 2 (radius: 10)
[04:44:51 -440064.403505] AUTODETECT spr round 3 (radius: 15)
[04:48:44 -371525.120929] AUTODETECT spr round 4 (radius: 20)
[04:53:16 -350899.406171] AUTODETECT spr round 5 (radius: 25)
[05:00:24 -348661.552086] SPR radius for FAST iterations: 25 (autodetect)
[05:00:24 -348661.552086] Model parameter optimization (eps = 3.000000)
[05:01:15 -348429.516297] FAST spr round 1 (radius: 25)
[05:05:28 -310049.871367] FAST spr round 2 (radius: 25)
[05:08:37 -308612.113834] FAST spr round 3 (radius: 25)
[05:11:24 -308532.254384] FAST spr round 4 (radius: 25)
[05:13:46 -308520.926751] FAST spr round 5 (radius: 25)
[05:15:55 -308520.926486] Model parameter optimization (eps = 1.000000)
[05:16:16 -308514.450256] SLOW spr round 1 (radius: 5)
[05:19:50 -308458.458720] SLOW spr round 2 (radius: 5)
[05:23:01 -308457.951327] SLOW spr round 3 (radius: 5)
[05:26:11 -308457.951117] SLOW spr round 4 (radius: 10)
[05:29:33 -308457.950971] SLOW spr round 5 (radius: 15)
[05:35:45 -308457.950870] SLOW spr round 6 (radius: 20)
[05:46:26 -308457.950801] SLOW spr round 7 (radius: 25)
[05:56:00] [worker #1] ML tree search #8, logLikelihood: -308456.698291
[06:01:15 -308457.950753] Model parameter optimization (eps = 0.100000)

[06:01:44] [worker #0] ML tree search #7, logLikelihood: -308457.091141

[06:01:44 -1011855.702751] Initial branch length optimization
[06:01:51 -855825.862183] Model parameter optimization (eps = 10.000000)
[06:03:17 -853553.594417] AUTODETECT spr round 1 (radius: 5)
[06:06:24 -591536.555544] AUTODETECT spr round 2 (radius: 10)
[06:09:53 -437707.650734] AUTODETECT spr round 3 (radius: 15)
[06:13:53 -384554.174357] AUTODETECT spr round 4 (radius: 20)
[06:19:06 -362731.258591] AUTODETECT spr round 5 (radius: 25)
[06:25:46 -358548.918512] SPR radius for FAST iterations: 25 (autodetect)
[06:25:46 -358548.918512] Model parameter optimization (eps = 3.000000)
[06:26:44 -358292.672108] FAST spr round 1 (radius: 25)
[06:31:22 -309912.751450] FAST spr round 2 (radius: 25)
[06:34:34 -308600.971828] FAST spr round 3 (radius: 25)
[06:37:24 -308531.411126] FAST spr round 4 (radius: 25)
[06:39:48 -308522.064912] FAST spr round 5 (radius: 25)
[06:42:03 -308517.192456] FAST spr round 6 (radius: 25)
[06:44:10 -308517.192215] Model parameter optimization (eps = 1.000000)
[06:44:27 -308515.780139] SLOW spr round 1 (radius: 5)
[06:48:02 -308475.971110] SLOW spr round 2 (radius: 5)
[06:51:21 -308468.245784] SLOW spr round 3 (radius: 5)
[06:54:29 -308467.011424] SLOW spr round 4 (radius: 5)
[06:57:36 -308467.010569] SLOW spr round 5 (radius: 10)
[07:00:58 -308465.932433] SLOW spr round 6 (radius: 5)
[07:05:13 -308464.990863] SLOW spr round 7 (radius: 5)
[07:08:49 -308464.990842] SLOW spr round 8 (radius: 10)
[07:12:19 -308464.820397] SLOW spr round 9 (radius: 5)
[07:16:31 -308464.579326] SLOW spr round 10 (radius: 5)
[07:20:05 -308464.577135] SLOW spr round 11 (radius: 10)
[07:22:48] [worker #1] ML tree search #10, logLikelihood: -308461.170126
[07:23:37 -308464.420073] SLOW spr round 12 (radius: 5)
[07:27:53 -308464.415475] SLOW spr round 13 (radius: 10)
[07:31:47 -308464.414573] SLOW spr round 14 (radius: 15)
[07:37:57 -308464.414426] SLOW spr round 15 (radius: 20)
[07:49:53 -308464.414405] SLOW spr round 16 (radius: 25)
[08:04:41 -308464.414402] Model parameter optimization (eps = 0.100000)

[08:05:07] [worker #0] ML tree search #9, logLikelihood: -308463.572640

[08:05:07 -1012690.423568] Initial branch length optimization
[08:05:14 -861289.120073] Model parameter optimization (eps = 10.000000)
[08:07:06 -858889.193413] AUTODETECT spr round 1 (radius: 5)
[08:10:07 -583144.530182] AUTODETECT spr round 2 (radius: 10)
[08:13:28 -437815.892593] AUTODETECT spr round 3 (radius: 15)
[08:17:23 -388387.623297] AUTODETECT spr round 4 (radius: 20)
[08:22:09 -348564.604209] AUTODETECT spr round 5 (radius: 25)
[08:27:29 -343571.870599] SPR radius for FAST iterations: 25 (autodetect)
[08:27:29 -343571.870599] Model parameter optimization (eps = 3.000000)
[08:28:09 -343356.354677] FAST spr round 1 (radius: 25)
[08:32:37 -309845.172803] FAST spr round 2 (radius: 25)
[08:35:53 -308589.002493] FAST spr round 3 (radius: 25)
[08:38:34 -308539.184795] FAST spr round 4 (radius: 25)
[08:40:43 -308539.182451] Model parameter optimization (eps = 1.000000)
[08:41:07 -308534.624006] SLOW spr round 1 (radius: 5)
[08:44:40 -308469.160393] SLOW spr round 2 (radius: 5)
[08:48:00 -308460.241981] SLOW spr round 3 (radius: 5)
[08:49:09] [worker #1] ML tree search #12, logLikelihood: -308451.071679
[08:51:11 -308460.241022] SLOW spr round 4 (radius: 10)
[08:54:36 -308460.198179] SLOW spr round 5 (radius: 15)
[09:00:58 -308460.191819] SLOW spr round 6 (radius: 20)
[09:12:19 -308460.190766] SLOW spr round 7 (radius: 25)
[09:26:54 -308460.190544] Model parameter optimization (eps = 0.100000)

[09:27:21] [worker #0] ML tree search #11, logLikelihood: -308458.709640

[09:27:21 -1016130.090604] Initial branch length optimization
[09:27:29 -862386.692615] Model parameter optimization (eps = 10.000000)
[09:29:16 -860069.287577] AUTODETECT spr round 1 (radius: 5)
[09:32:17 -605630.987595] AUTODETECT spr round 2 (radius: 10)
[09:35:42 -432699.236607] AUTODETECT spr round 3 (radius: 15)
[09:39:53 -365682.345286] AUTODETECT spr round 4 (radius: 20)
[09:45:36 -349951.687974] AUTODETECT spr round 5 (radius: 25)
[09:52:45 -347691.996782] SPR radius for FAST iterations: 25 (autodetect)
[09:52:45 -347691.996782] Model parameter optimization (eps = 3.000000)
[09:53:25 -347446.625367] FAST spr round 1 (radius: 25)
[09:57:43 -309920.507989] FAST spr round 2 (radius: 25)
[10:00:51 -308603.472434] FAST spr round 3 (radius: 25)
[10:03:37 -308536.977639] FAST spr round 4 (radius: 25)
[10:05:48 -308536.977365] Model parameter optimization (eps = 1.000000)
[10:06:07 -308535.985385] SLOW spr round 1 (radius: 5)
[10:09:37 -308476.879942] SLOW spr round 2 (radius: 5)
[10:12:54 -308466.785864] SLOW spr round 3 (radius: 5)
[10:16:07 -308463.351323] SLOW spr round 4 (radius: 5)
[10:19:03] [worker #1] ML tree search #14, logLikelihood: -308472.979275
[10:19:15 -308463.351034] SLOW spr round 5 (radius: 10)
[10:22:39 -308463.350979] SLOW spr round 6 (radius: 15)
[10:28:56 -308463.350954] SLOW spr round 7 (radius: 20)
[10:39:50 -308463.350940] SLOW spr round 8 (radius: 25)
[10:54:41 -308463.350931] Model parameter optimization (eps = 0.100000)

[10:55:07] [worker #0] ML tree search #13, logLikelihood: -308462.685880

[10:55:07 -1009956.684100] Initial branch length optimization
[10:55:16 -859298.138493] Model parameter optimization (eps = 10.000000)
[10:56:41 -857178.422358] AUTODETECT spr round 1 (radius: 5)
[10:59:40 -580277.042722] AUTODETECT spr round 2 (radius: 10)
[11:03:01 -444145.457014] AUTODETECT spr round 3 (radius: 15)
[11:06:57 -381968.468104] AUTODETECT spr round 4 (radius: 20)
[11:12:26 -356969.115518] AUTODETECT spr round 5 (radius: 25)
[11:19:12 -352265.012934] SPR radius for FAST iterations: 25 (autodetect)
[11:19:12 -352265.012934] Model parameter optimization (eps = 3.000000)
[11:19:50 -352049.361610] FAST spr round 1 (radius: 25)
[11:24:08 -310412.270831] FAST spr round 2 (radius: 25)
[11:27:08 -308825.888503] FAST spr round 3 (radius: 25)
[11:29:57 -308583.588642] FAST spr round 4 (radius: 25)
[11:32:28 -308524.784509] FAST spr round 5 (radius: 25)
[11:34:37 -308524.196398] FAST spr round 6 (radius: 25)
[11:36:41 -308524.194002] Model parameter optimization (eps = 1.000000)
[11:37:05 -308520.676306] SLOW spr round 1 (radius: 5)
[11:40:35 -308464.148531] SLOW spr round 2 (radius: 5)
[11:43:49 -308458.799598] SLOW spr round 3 (radius: 5)
[11:46:58 -308458.157025] SLOW spr round 4 (radius: 5)
[11:48:22] [worker #1] ML tree search #16, logLikelihood: -308448.414619
[11:50:07 -308458.156699] SLOW spr round 5 (radius: 10)
[11:53:30 -308458.156561] SLOW spr round 6 (radius: 15)
[11:59:51 -308458.156468] SLOW spr round 7 (radius: 20)
[12:10:29 -308458.156405] SLOW spr round 8 (radius: 25)
[12:24:26 -308458.156361] Model parameter optimization (eps = 0.100000)

[12:24:40] [worker #0] ML tree search #15, logLikelihood: -308457.989319

[12:24:40 -1004750.413057] Initial branch length optimization
[12:24:48 -854147.906835] Model parameter optimization (eps = 10.000000)
[12:26:18 -852083.163337] AUTODETECT spr round 1 (radius: 5)
[12:29:17 -599444.962616] AUTODETECT spr round 2 (radius: 10)
[12:32:38 -447865.400247] AUTODETECT spr round 3 (radius: 15)
[12:36:21 -374933.048794] AUTODETECT spr round 4 (radius: 20)
[12:41:45 -349814.129470] AUTODETECT spr round 5 (radius: 25)
[12:47:48 -348175.423281] SPR radius for FAST iterations: 25 (autodetect)
[12:47:48 -348175.423281] Model parameter optimization (eps = 3.000000)
[12:48:38 -347920.928009] FAST spr round 1 (radius: 25)
[12:52:48 -309670.007460] FAST spr round 2 (radius: 25)
[12:55:56 -308780.294493] FAST spr round 3 (radius: 25)
[12:58:48 -308570.289372] FAST spr round 4 (radius: 25)
[13:01:11 -308556.857632] FAST spr round 5 (radius: 25)
[13:03:17 -308556.857294] Model parameter optimization (eps = 1.000000)
[13:03:31 -308555.982567] SLOW spr round 1 (radius: 5)
[13:07:05 -308475.904597] SLOW spr round 2 (radius: 5)
[13:10:20 -308473.106658] SLOW spr round 3 (radius: 5)
[13:11:45] [worker #1] ML tree search #18, logLikelihood: -308451.711873
[13:13:32 -308471.307208] SLOW spr round 4 (radius: 5)
[13:16:44 -308468.574744] SLOW spr round 5 (radius: 5)
[13:19:53 -308468.574709] SLOW spr round 6 (radius: 10)
[13:23:20 -308468.454310] SLOW spr round 7 (radius: 5)
[13:27:38 -308468.449951] SLOW spr round 8 (radius: 10)
[13:31:35 -308468.449090] SLOW spr round 9 (radius: 15)
[13:37:38 -308468.448947] SLOW spr round 10 (radius: 20)
[13:49:19 -308468.448926] SLOW spr round 11 (radius: 25)
[14:03:43 -308468.448924] Model parameter optimization (eps = 0.100000)

[14:04:11] [worker #0] ML tree search #17, logLikelihood: -308467.841951

[14:04:11 -1018578.951713] Initial branch length optimization
[14:04:20 -865445.258776] Model parameter optimization (eps = 10.000000)
[14:05:38 -863086.788239] AUTODETECT spr round 1 (radius: 5)
[14:08:41 -579810.537865] AUTODETECT spr round 2 (radius: 10)
[14:12:02 -441901.669949] AUTODETECT spr round 3 (radius: 15)
[14:15:59 -389460.464398] AUTODETECT spr round 4 (radius: 20)
[14:21:44 -353386.198946] AUTODETECT spr round 5 (radius: 25)
[14:29:01 -348147.764131] SPR radius for FAST iterations: 25 (autodetect)
[14:29:01 -348147.764131] Model parameter optimization (eps = 3.000000)
[14:29:40 -347885.772798] FAST spr round 1 (radius: 25)
[14:34:18 -309899.050858] FAST spr round 2 (radius: 25)
[14:37:21 -308705.509846] FAST spr round 3 (radius: 25)
[14:40:11 -308522.934594] FAST spr round 4 (radius: 25)
[14:42:24 -308519.661968] FAST spr round 5 (radius: 25)
[14:44:33 -308517.603360] FAST spr round 6 (radius: 25)
[14:46:38 -308517.603360] Model parameter optimization (eps = 1.000000)
[14:47:00 -308515.649807] SLOW spr round 1 (radius: 5)
[14:50:15] [worker #1] ML tree search #20, logLikelihood: -308466.581917
[14:50:29 -308455.064493] SLOW spr round 2 (radius: 5)
[14:53:05 -308446.119428] SLOW spr round 3 (radius: 5)
[14:55:35 -308446.118621] SLOW spr round 4 (radius: 10)
[14:58:14 -308446.118327] SLOW spr round 5 (radius: 15)
[15:03:13 -308446.118181] SLOW spr round 6 (radius: 20)
[15:11:52 -308446.118100] SLOW spr round 7 (radius: 25)
[15:23:19 -308446.118048] Model parameter optimization (eps = 0.100000)

[15:23:28] [worker #0] ML tree search #19, logLikelihood: -308445.853171


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.138310,0.405914) (0.147088,0.401272) (0.377562,0.841631) (0.337040,1.682494) 
   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: -308445.853171

AIC score: 619725.706341 / AICc score: 4638337.706341 / BIC score: 626543.239626
Free parameters (model + branch lengths): 1417

WARNING: Number of free parameters (K=1417) is larger than alignment size (n=908).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P19823/3_mltree/P19823.raxml.log

Analysis started: 03-Jul-2021 19:35:25 / finished: 04-Jul-2021 10:58:55

Elapsed time: 55409.128 seconds

Consumed energy: 2948.863 Wh (= 15 km in an electric car, or 74 km with an e-scooter!)