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 07:09:23 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/2_msa/Q96MG7_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/3_mltree/Q96MG7 --seed 2 --threads 7 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (7 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/2_msa/Q96MG7_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 712 sites

WARNING: Sequences tr_G3QIN6_G3QIN6_GORGO_9595 and tr_A0A2R9BXN3_A0A2R9BXN3_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2NML2_H2NML2_PONAB_9601 and sp_Q99608_NECD_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2J8IKX4_A0A2J8IKX4_PANTR_9598 and sp_Q96JG8_MAGD4_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2J8IKX4_A0A2J8IKX4_PANTR_9598 and tr_A0A2R9CB18_A0A2R9CB18_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8ILL3_A0A2J8ILL3_PANTR_9598 and tr_A0A2R9A741_A0A2R9A741_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8L3B6_A0A2J8L3B6_PANTR_9598 and tr_A0A2R8ZNL5_A0A2R8ZNL5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8L3C9_A0A2J8L3C9_PANTR_9598 and tr_A0A2R8Z7Y2_A0A2R8Z7Y2_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QNW0_H2QNW0_PANTR_9598 and tr_A0A2R8ZRZ5_A0A2R8ZRZ5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QYF3_H2QYF3_PANTR_9598 and tr_A0A2R8ZFE5_A0A2R8ZFE5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QYF7_H2QYF7_PANTR_9598 and tr_A0A2R8Z756_A0A2R8Z756_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QYG1_H2QYG1_PANTR_9598 and tr_A0A2R9BBM4_A0A2R9BBM4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QZ87_H2QZ87_PANTR_9598 and tr_A0A2R8Z8F4_A0A2R8Z8F4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2R4N6_H2R4N6_PANTR_9598 and sp_Q9HCI5_MAGE1_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_K7B4B1_K7B4B1_PANTR_9598 and tr_A0A2R9BW42_A0A2R9BW42_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5RA99_A0A1D5RA99_MACMU_9544 and tr_G7Q2S1_G7Q2S1_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F6TEU0_F6TEU0_MACMU_9544 and tr_G7Q2E5_G7Q2E5_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F6U8Q6_F6U8Q6_MACMU_9544 and tr_G7Q2F1_G7Q2F1_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7D5S3_F7D5S3_MACMU_9544 and tr_A0A096NB08_A0A096NB08_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7D5S3_F7D5S3_MACMU_9544 and tr_A0A2K6CXP0_A0A2K6CXP0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7EIN2_F7EIN2_MACMU_9544 and tr_G7Q2F6_G7Q2F6_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7EIP2_F7EIP2_MACMU_9544 and tr_G7Q2F5_G7Q2F5_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7HCY3_F7HCY3_MACMU_9544 and tr_G7Q2A6_G7Q2A6_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G7NYZ0_G7NYZ0_MACFA_9541 and tr_A0A2K6AMH0_A0A2K6AMH0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2U4C6N1_A0A2U4C6N1_TURTR_9739 and tr_A0A2U4C6P2_A0A2U4C6P2_TURTR_9739 are exactly identical!
WARNING: Duplicate sequences found: 24

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/Q96MG7/3_mltree/Q96MG7.raxml.reduced.phy

Alignment comprises 1 partitions and 712 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 712 / 712
Gaps: 47.76 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/3_mltree/Q96MG7.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 7 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 102 / 8160
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -737430.744567] Initial branch length optimization
[00:00:03 -648322.281737] Model parameter optimization (eps = 10.000000)
[00:00:42 -644115.152130] AUTODETECT spr round 1 (radius: 5)
[00:02:44 -476370.383459] AUTODETECT spr round 2 (radius: 10)
[00:04:56 -332396.353481] AUTODETECT spr round 3 (radius: 15)
[00:07:23 -271882.736566] AUTODETECT spr round 4 (radius: 20)
[00:10:24 -262305.934995] AUTODETECT spr round 5 (radius: 25)
[00:14:10 -260741.844184] SPR radius for FAST iterations: 25 (autodetect)
[00:14:10 -260741.844184] Model parameter optimization (eps = 3.000000)
[00:14:33 -260597.662432] FAST spr round 1 (radius: 25)
[00:17:14 -228185.106575] FAST spr round 2 (radius: 25)
[00:19:14 -227263.722136] FAST spr round 3 (radius: 25)
[00:21:00 -227204.320084] FAST spr round 4 (radius: 25)
[00:22:38 -227188.369001] FAST spr round 5 (radius: 25)
[00:24:09 -227188.368771] Model parameter optimization (eps = 1.000000)
[00:24:23 -227174.214917] SLOW spr round 1 (radius: 5)
[00:26:32 -227143.613969] SLOW spr round 2 (radius: 5)
[00:28:33 -227141.963191] SLOW spr round 3 (radius: 5)
[00:30:31 -227141.377959] SLOW spr round 4 (radius: 5)
[00:32:27 -227141.377955] SLOW spr round 5 (radius: 10)
[00:34:28 -227141.377955] SLOW spr round 6 (radius: 15)
[00:39:24 -227141.334747] SLOW spr round 7 (radius: 20)
[00:48:46 -227141.334620] SLOW spr round 8 (radius: 25)
[00:58:53 -227141.334619] Model parameter optimization (eps = 0.100000)

[00:58:59] ML tree search #1, logLikelihood: -227141.246763

[00:58:59 -743125.948155] Initial branch length optimization
[00:59:02 -651247.736098] Model parameter optimization (eps = 10.000000)
[00:59:39 -646869.581349] AUTODETECT spr round 1 (radius: 5)
[01:01:40 -491114.454872] AUTODETECT spr round 2 (radius: 10)
[01:03:50 -329829.577071] AUTODETECT spr round 3 (radius: 15)
[01:06:12 -272598.238634] AUTODETECT spr round 4 (radius: 20)
[01:09:02 -259977.834336] AUTODETECT spr round 5 (radius: 25)
[01:12:46 -257908.644323] SPR radius for FAST iterations: 25 (autodetect)
[01:12:46 -257908.644323] Model parameter optimization (eps = 3.000000)
[01:13:11 -257713.417278] FAST spr round 1 (radius: 25)
[01:15:51 -228382.786230] FAST spr round 2 (radius: 25)
[01:17:55 -227233.051942] FAST spr round 3 (radius: 25)
[01:19:45 -227184.439163] FAST spr round 4 (radius: 25)
[01:21:23 -227179.487138] FAST spr round 5 (radius: 25)
[01:22:55 -227179.487086] Model parameter optimization (eps = 1.000000)
[01:23:09 -227176.959264] SLOW spr round 1 (radius: 5)
[01:25:22 -227151.558051] SLOW spr round 2 (radius: 5)
[01:27:24 -227151.309724] SLOW spr round 3 (radius: 5)
[01:29:21 -227151.309685] SLOW spr round 4 (radius: 10)
[01:31:22 -227146.637094] SLOW spr round 5 (radius: 5)
[01:33:53 -227136.332147] SLOW spr round 6 (radius: 5)
[01:36:01 -227136.328863] SLOW spr round 7 (radius: 10)
[01:38:06 -227136.141897] SLOW spr round 8 (radius: 5)
[01:40:31 -227136.141221] SLOW spr round 9 (radius: 10)
[01:42:47 -227136.141190] SLOW spr round 10 (radius: 15)
[01:46:55 -227136.141170] SLOW spr round 11 (radius: 20)
[01:56:38 -227136.141152] SLOW spr round 12 (radius: 25)
[02:07:12 -227136.141134] Model parameter optimization (eps = 0.100000)

[02:07:23] ML tree search #2, logLikelihood: -227135.920910

[02:07:23 -739261.264342] Initial branch length optimization
[02:07:26 -650677.702586] Model parameter optimization (eps = 10.000000)
[02:08:00 -646720.688464] AUTODETECT spr round 1 (radius: 5)
[02:10:02 -490109.552352] AUTODETECT spr round 2 (radius: 10)
[02:12:11 -342828.690703] AUTODETECT spr round 3 (radius: 15)
[02:14:33 -275201.883819] AUTODETECT spr round 4 (radius: 20)
[02:17:28 -261785.411351] AUTODETECT spr round 5 (radius: 25)
[02:20:52 -258622.127188] SPR radius for FAST iterations: 25 (autodetect)
[02:20:52 -258622.127188] Model parameter optimization (eps = 3.000000)
[02:21:19 -258443.617809] FAST spr round 1 (radius: 25)
[02:24:01 -228437.036179] FAST spr round 2 (radius: 25)
[02:26:04 -227318.752132] FAST spr round 3 (radius: 25)
[02:27:56 -227273.026775] FAST spr round 4 (radius: 25)
[02:29:39 -227249.273589] FAST spr round 5 (radius: 25)
[02:31:12 -227249.273485] Model parameter optimization (eps = 1.000000)
[02:31:27 -227199.414959] SLOW spr round 1 (radius: 5)
[02:33:42 -227161.552199] SLOW spr round 2 (radius: 5)
[02:35:43 -227159.560040] SLOW spr round 3 (radius: 5)
[02:37:40 -227159.559924] SLOW spr round 4 (radius: 10)
[02:39:41 -227159.191355] SLOW spr round 5 (radius: 5)
[02:42:06 -227159.191168] SLOW spr round 6 (radius: 10)
[02:44:21 -227159.191125] SLOW spr round 7 (radius: 15)
[02:48:27 -227156.206834] SLOW spr round 8 (radius: 5)
[02:51:00 -227151.672346] SLOW spr round 9 (radius: 5)
[02:53:15 -227149.271229] SLOW spr round 10 (radius: 5)
[02:55:19 -227149.271134] SLOW spr round 11 (radius: 10)
[02:57:23 -227149.271095] SLOW spr round 12 (radius: 15)
[03:01:58 -227149.271057] SLOW spr round 13 (radius: 20)
[03:10:30 -227149.271019] SLOW spr round 14 (radius: 25)
[03:20:46 -227149.270981] Model parameter optimization (eps = 0.100000)

[03:20:53] ML tree search #3, logLikelihood: -227149.164317

[03:20:53 -738999.851599] Initial branch length optimization
[03:20:56 -649317.257335] Model parameter optimization (eps = 10.000000)
[03:21:37 -645122.801520] AUTODETECT spr round 1 (radius: 5)
[03:23:37 -482136.851383] AUTODETECT spr round 2 (radius: 10)
[03:25:49 -328981.341093] AUTODETECT spr round 3 (radius: 15)
[03:28:12 -270306.631994] AUTODETECT spr round 4 (radius: 20)
[03:31:00 -261255.873946] AUTODETECT spr round 5 (radius: 25)
[03:34:19 -259715.471042] SPR radius for FAST iterations: 25 (autodetect)
[03:34:19 -259715.471042] Model parameter optimization (eps = 3.000000)
[03:34:41 -259528.018315] FAST spr round 1 (radius: 25)
[03:37:25 -228317.944707] FAST spr round 2 (radius: 25)
[03:39:30 -227243.631139] FAST spr round 3 (radius: 25)
[03:41:20 -227202.108192] FAST spr round 4 (radius: 25)
[03:42:56 -227191.897044] FAST spr round 5 (radius: 25)
[03:44:28 -227191.896998] Model parameter optimization (eps = 1.000000)
[03:44:43 -227188.550298] SLOW spr round 1 (radius: 5)
[03:46:57 -227147.663083] SLOW spr round 2 (radius: 5)
[03:48:58 -227146.456266] SLOW spr round 3 (radius: 5)
[03:50:55 -227146.456167] SLOW spr round 4 (radius: 10)
[03:52:55 -227146.146710] SLOW spr round 5 (radius: 5)
[03:55:20 -227146.146566] SLOW spr round 6 (radius: 10)
[03:57:35 -227146.146535] SLOW spr round 7 (radius: 15)
[04:01:48 -227146.146504] SLOW spr round 8 (radius: 20)
[04:11:54 -227146.146474] SLOW spr round 9 (radius: 25)
[04:21:55 -227146.146444] Model parameter optimization (eps = 0.100000)

[04:22:08] ML tree search #4, logLikelihood: -227144.845917

[04:22:08 -741745.848952] Initial branch length optimization
[04:22:12 -652632.125294] Model parameter optimization (eps = 10.000000)
[04:23:02 -648303.222152] AUTODETECT spr round 1 (radius: 5)
[04:25:06 -484248.620856] AUTODETECT spr round 2 (radius: 10)
[04:27:21 -339048.007731] AUTODETECT spr round 3 (radius: 15)
[04:29:47 -274692.382695] AUTODETECT spr round 4 (radius: 20)
[04:32:58 -260235.164408] AUTODETECT spr round 5 (radius: 25)
[04:37:24 -256448.197134] SPR radius for FAST iterations: 25 (autodetect)
[04:37:24 -256448.197134] Model parameter optimization (eps = 3.000000)
[04:37:49 -256249.917221] FAST spr round 1 (radius: 25)
[04:40:39 -228032.495113] FAST spr round 2 (radius: 25)
[04:42:48 -227265.703686] FAST spr round 3 (radius: 25)
[04:44:37 -227218.101703] FAST spr round 4 (radius: 25)
[04:46:14 -227215.957532] FAST spr round 5 (radius: 25)
[04:47:49 -227215.957144] Model parameter optimization (eps = 1.000000)
[04:48:03 -227212.679601] SLOW spr round 1 (radius: 5)
[04:50:15 -227153.216137] SLOW spr round 2 (radius: 5)
[04:52:18 -227144.430676] SLOW spr round 3 (radius: 5)
[04:54:17 -227144.430502] SLOW spr round 4 (radius: 10)
[04:56:20 -227144.325877] SLOW spr round 5 (radius: 5)
[04:58:49 -227144.325476] SLOW spr round 6 (radius: 10)
[05:01:05 -227144.325473] SLOW spr round 7 (radius: 15)
[05:05:15 -227144.325473] SLOW spr round 8 (radius: 20)
[05:15:19 -227144.325473] SLOW spr round 9 (radius: 25)
[05:26:03 -227144.325473] Model parameter optimization (eps = 0.100000)

[05:26:15] ML tree search #5, logLikelihood: -227143.632315

[05:26:16 -741284.053718] Initial branch length optimization
[05:26:19 -651321.929739] Model parameter optimization (eps = 10.000000)
[05:27:03 -647228.990130] AUTODETECT spr round 1 (radius: 5)
[05:29:05 -467893.208520] AUTODETECT spr round 2 (radius: 10)
[05:31:17 -322941.939965] AUTODETECT spr round 3 (radius: 15)
[05:33:41 -270089.659214] AUTODETECT spr round 4 (radius: 20)
[05:36:53 -258970.795192] AUTODETECT spr round 5 (radius: 25)
[05:40:42 -256971.092089] SPR radius for FAST iterations: 25 (autodetect)
[05:40:42 -256971.092089] Model parameter optimization (eps = 3.000000)
[05:41:08 -256784.309681] FAST spr round 1 (radius: 25)
[05:43:55 -228456.664112] FAST spr round 2 (radius: 25)
[05:46:02 -227309.545094] FAST spr round 3 (radius: 25)
[05:47:51 -227231.411881] FAST spr round 4 (radius: 25)
[05:49:27 -227225.750500] FAST spr round 5 (radius: 25)
[05:51:01 -227222.538473] FAST spr round 6 (radius: 25)
[05:52:34 -227215.327637] FAST spr round 7 (radius: 25)
[05:54:05 -227213.368117] FAST spr round 8 (radius: 25)
[05:55:36 -227213.367786] Model parameter optimization (eps = 1.000000)
[05:55:48 -227208.854976] SLOW spr round 1 (radius: 5)
[05:57:54 -227177.435191] SLOW spr round 2 (radius: 5)
[05:59:57 -227168.118640] SLOW spr round 3 (radius: 5)
[06:01:55 -227168.118415] SLOW spr round 4 (radius: 10)
[06:03:58 -227167.793252] SLOW spr round 5 (radius: 5)
[06:06:24 -227167.793114] SLOW spr round 6 (radius: 10)
[06:08:40 -227167.539256] SLOW spr round 7 (radius: 5)
[06:11:03 -227167.539190] SLOW spr round 8 (radius: 10)
[06:13:16 -227167.539159] SLOW spr round 9 (radius: 15)
[06:17:26 -227167.539128] SLOW spr round 10 (radius: 20)
[06:27:06 -227167.539097] SLOW spr round 11 (radius: 25)
[06:37:08 -227167.539067] Model parameter optimization (eps = 0.100000)

[06:37:29] ML tree search #6, logLikelihood: -227166.411195

[06:37:29 -741002.241440] Initial branch length optimization
[06:37:32 -650992.414748] Model parameter optimization (eps = 10.000000)
[06:38:09 -646464.424487] AUTODETECT spr round 1 (radius: 5)
[06:40:09 -491242.452684] AUTODETECT spr round 2 (radius: 10)
[06:42:22 -327399.755398] AUTODETECT spr round 3 (radius: 15)
[06:44:46 -271239.769999] AUTODETECT spr round 4 (radius: 20)
[06:47:47 -261007.130742] AUTODETECT spr round 5 (radius: 25)
[06:51:44 -260633.530480] SPR radius for FAST iterations: 25 (autodetect)
[06:51:44 -260633.530480] Model parameter optimization (eps = 3.000000)
[06:52:03 -260467.223172] FAST spr round 1 (radius: 25)
[06:54:43 -228739.683362] FAST spr round 2 (radius: 25)
[06:56:47 -227413.769561] FAST spr round 3 (radius: 25)
[06:58:32 -227300.315591] FAST spr round 4 (radius: 25)
[07:00:08 -227291.302765] FAST spr round 5 (radius: 25)
[07:01:40 -227289.066428] FAST spr round 6 (radius: 25)
[07:03:11 -227289.066235] Model parameter optimization (eps = 1.000000)
[07:03:27 -227232.836833] SLOW spr round 1 (radius: 5)
[07:05:35 -227171.832505] SLOW spr round 2 (radius: 5)
[07:07:40 -227171.297904] SLOW spr round 3 (radius: 5)
[07:09:42 -227171.297713] SLOW spr round 4 (radius: 10)
[07:11:45 -227167.476791] SLOW spr round 5 (radius: 5)
[07:14:13 -227167.475742] SLOW spr round 6 (radius: 10)
[07:16:30 -227167.139709] SLOW spr round 7 (radius: 5)
[07:18:53 -227167.139119] SLOW spr round 8 (radius: 10)
[07:21:06 -227167.139087] SLOW spr round 9 (radius: 15)
[07:25:24 -227166.893819] SLOW spr round 10 (radius: 5)
[07:28:02 -227154.006890] SLOW spr round 11 (radius: 5)
[07:30:17 -227153.515810] SLOW spr round 12 (radius: 5)
[07:32:22 -227153.515778] SLOW spr round 13 (radius: 10)
[07:34:28 -227153.515749] SLOW spr round 14 (radius: 15)
[07:39:13 -227153.515719] SLOW spr round 15 (radius: 20)
[07:48:38 -227153.515690] SLOW spr round 16 (radius: 25)
[07:58:53 -227153.515661] Model parameter optimization (eps = 0.100000)

[07:58:59] ML tree search #7, logLikelihood: -227153.473035

[07:58:59 -739872.113035] Initial branch length optimization
[07:59:03 -649786.716367] Model parameter optimization (eps = 10.000000)
[07:59:38 -645336.947352] AUTODETECT spr round 1 (radius: 5)
[08:01:39 -476581.444219] AUTODETECT spr round 2 (radius: 10)
[08:03:52 -336097.947662] AUTODETECT spr round 3 (radius: 15)
[08:06:15 -276489.151852] AUTODETECT spr round 4 (radius: 20)
[08:09:25 -261210.939339] AUTODETECT spr round 5 (radius: 25)
[08:14:16 -260067.358936] SPR radius for FAST iterations: 25 (autodetect)
[08:14:16 -260067.358936] Model parameter optimization (eps = 3.000000)
[08:14:36 -259880.122552] FAST spr round 1 (radius: 25)
[08:17:27 -228285.799647] FAST spr round 2 (radius: 25)
[08:19:34 -227249.534433] FAST spr round 3 (radius: 25)
[08:21:25 -227187.950929] FAST spr round 4 (radius: 25)
[08:23:03 -227185.632537] FAST spr round 5 (radius: 25)
[08:24:38 -227185.631838] Model parameter optimization (eps = 1.000000)
[08:24:58 -227182.611870] SLOW spr round 1 (radius: 5)
[08:27:09 -227148.262610] SLOW spr round 2 (radius: 5)
[08:29:15 -227146.119524] SLOW spr round 3 (radius: 5)
[08:31:14 -227146.119451] SLOW spr round 4 (radius: 10)
[08:33:17 -227146.119451] SLOW spr round 5 (radius: 15)
[08:38:04 -227146.119451] SLOW spr round 6 (radius: 20)
[08:47:06 -227146.119451] SLOW spr round 7 (radius: 25)
[08:57:09 -227146.119451] Model parameter optimization (eps = 0.100000)

[08:57:25] ML tree search #8, logLikelihood: -227144.702646

[08:57:25 -733030.538246] Initial branch length optimization
[08:57:28 -646225.117680] Model parameter optimization (eps = 10.000000)
[08:58:07 -642001.560428] AUTODETECT spr round 1 (radius: 5)
[09:00:07 -470804.281774] AUTODETECT spr round 2 (radius: 10)
[09:02:16 -329924.917479] AUTODETECT spr round 3 (radius: 15)
[09:04:37 -275416.642419] AUTODETECT spr round 4 (radius: 20)
[09:07:22 -262117.655378] AUTODETECT spr round 5 (radius: 25)
[09:10:57 -261703.830063] SPR radius for FAST iterations: 25 (autodetect)
[09:10:57 -261703.830063] Model parameter optimization (eps = 3.000000)
[09:11:15 -261536.773754] FAST spr round 1 (radius: 25)
[09:13:57 -228519.080824] FAST spr round 2 (radius: 25)
[09:16:03 -227281.479188] FAST spr round 3 (radius: 25)
[09:17:54 -227210.708737] FAST spr round 4 (radius: 25)
[09:19:30 -227204.487483] FAST spr round 5 (radius: 25)
[09:21:02 -227204.487253] Model parameter optimization (eps = 1.000000)
[09:21:15 -227200.433605] SLOW spr round 1 (radius: 5)
[09:23:28 -227155.235028] SLOW spr round 2 (radius: 5)
[09:25:29 -227152.470661] SLOW spr round 3 (radius: 5)
[09:27:26 -227152.470440] SLOW spr round 4 (radius: 10)
[09:29:27 -227148.078765] SLOW spr round 5 (radius: 5)
[09:31:52 -227144.416810] SLOW spr round 6 (radius: 5)
[09:34:00 -227144.416731] SLOW spr round 7 (radius: 10)
[09:36:05 -227144.416676] SLOW spr round 8 (radius: 15)
[09:40:24 -227144.416622] SLOW spr round 9 (radius: 20)
[09:49:12 -227144.416569] SLOW spr round 10 (radius: 25)
[09:59:56 -227144.416516] Model parameter optimization (eps = 0.100000)

[10:00:03] ML tree search #9, logLikelihood: -227144.360699

[10:00:04 -739563.643237] Initial branch length optimization
[10:00:07 -649814.240223] Model parameter optimization (eps = 10.000000)
[10:00:54 -645927.531304] AUTODETECT spr round 1 (radius: 5)
[10:02:54 -493851.002366] AUTODETECT spr round 2 (radius: 10)
[10:05:07 -340084.741385] AUTODETECT spr round 3 (radius: 15)
[10:07:29 -281056.689326] AUTODETECT spr round 4 (radius: 20)
[10:10:35 -267062.516244] AUTODETECT spr round 5 (radius: 25)
[10:14:56 -263050.056118] SPR radius for FAST iterations: 25 (autodetect)
[10:14:56 -263050.056118] Model parameter optimization (eps = 3.000000)
[10:15:28 -262883.789223] FAST spr round 1 (radius: 25)
[10:18:13 -228695.602852] FAST spr round 2 (radius: 25)
[10:20:17 -227288.168299] FAST spr round 3 (radius: 25)
[10:22:02 -227219.378247] FAST spr round 4 (radius: 25)
[10:23:37 -227214.188408] FAST spr round 5 (radius: 25)
[10:25:09 -227208.496621] FAST spr round 6 (radius: 25)
[10:26:39 -227208.496616] Model parameter optimization (eps = 1.000000)
[10:26:54 -227206.654643] SLOW spr round 1 (radius: 5)
[10:28:59 -227170.879052] SLOW spr round 2 (radius: 5)
[10:30:57 -227169.361771] SLOW spr round 3 (radius: 5)
[10:32:55 -227163.592651] SLOW spr round 4 (radius: 5)
[10:34:49 -227163.592487] SLOW spr round 5 (radius: 10)
[10:36:48 -227163.510125] SLOW spr round 6 (radius: 15)
[10:41:32 -227163.509846] SLOW spr round 7 (radius: 20)
[10:51:05 -227163.509839] SLOW spr round 8 (radius: 25)
[11:01:50 -227163.509839] Model parameter optimization (eps = 0.100000)

[11:02:12] ML tree search #10, logLikelihood: -227162.687398

[11:02:12 -741425.021688] Initial branch length optimization
[11:02:16 -650582.768968] Model parameter optimization (eps = 10.000000)
[11:02:55 -646654.447970] AUTODETECT spr round 1 (radius: 5)
[11:04:55 -474861.891347] AUTODETECT spr round 2 (radius: 10)
[11:07:06 -333671.773724] AUTODETECT spr round 3 (radius: 15)
[11:09:30 -273519.985151] AUTODETECT spr round 4 (radius: 20)
[11:12:44 -259439.707331] AUTODETECT spr round 5 (radius: 25)
[11:17:16 -258591.369445] SPR radius for FAST iterations: 25 (autodetect)
[11:17:16 -258591.369445] Model parameter optimization (eps = 3.000000)
[11:17:35 -258452.589394] FAST spr round 1 (radius: 25)
[11:20:17 -228401.601210] FAST spr round 2 (radius: 25)
[11:22:18 -227414.508843] FAST spr round 3 (radius: 25)
[11:24:03 -227243.974456] FAST spr round 4 (radius: 25)
[11:25:38 -227237.478291] FAST spr round 5 (radius: 25)
[11:27:09 -227237.395949] Model parameter optimization (eps = 1.000000)
[11:27:26 -227206.798597] SLOW spr round 1 (radius: 5)
[11:29:33 -227158.222095] SLOW spr round 2 (radius: 5)
[11:31:33 -227156.553395] SLOW spr round 3 (radius: 5)
[11:33:29 -227156.553325] SLOW spr round 4 (radius: 10)
[11:35:29 -227156.553268] SLOW spr round 5 (radius: 15)
[11:40:14 -227156.553211] SLOW spr round 6 (radius: 20)
[11:49:16 -227156.553155] SLOW spr round 7 (radius: 25)
[11:59:30 -227156.553099] Model parameter optimization (eps = 0.100000)

[11:59:38] ML tree search #11, logLikelihood: -227156.187402

[11:59:39 -743173.630554] Initial branch length optimization
[11:59:41 -655083.462063] Model parameter optimization (eps = 10.000000)
[12:00:27 -650828.532145] AUTODETECT spr round 1 (radius: 5)
[12:02:27 -490045.332081] AUTODETECT spr round 2 (radius: 10)
[12:04:40 -335108.677209] AUTODETECT spr round 3 (radius: 15)
[12:06:59 -279261.421580] AUTODETECT spr round 4 (radius: 20)
[12:09:48 -260324.660711] AUTODETECT spr round 5 (radius: 25)
[12:12:58 -257224.114483] SPR radius for FAST iterations: 25 (autodetect)
[12:12:58 -257224.114483] Model parameter optimization (eps = 3.000000)
[12:13:23 -257032.127414] FAST spr round 1 (radius: 25)
[12:16:02 -228009.193961] FAST spr round 2 (radius: 25)
[12:18:05 -227299.370378] FAST spr round 3 (radius: 25)
[12:19:53 -227263.578067] FAST spr round 4 (radius: 25)
[12:21:28 -227261.013137] FAST spr round 5 (radius: 25)
[12:22:59 -227261.013128] Model parameter optimization (eps = 1.000000)
[12:23:15 -227218.700488] SLOW spr round 1 (radius: 5)
[12:25:26 -227142.786385] SLOW spr round 2 (radius: 5)
[12:27:29 -227139.342256] SLOW spr round 3 (radius: 5)
[12:29:26 -227139.341945] SLOW spr round 4 (radius: 10)
[12:31:25 -227139.013372] SLOW spr round 5 (radius: 5)
[12:33:49 -227139.012869] SLOW spr round 6 (radius: 10)
[12:36:03 -227139.012823] SLOW spr round 7 (radius: 15)
[12:40:06 -227139.012787] SLOW spr round 8 (radius: 20)
[12:49:59 -227139.012754] SLOW spr round 9 (radius: 25)
[13:00:27 -227139.012723] Model parameter optimization (eps = 0.100000)

[13:00:32] ML tree search #12, logLikelihood: -227138.996955

[13:00:32 -738298.629797] Initial branch length optimization
[13:00:35 -648660.311513] Model parameter optimization (eps = 10.000000)
[13:01:15 -644512.203742] AUTODETECT spr round 1 (radius: 5)
[13:03:14 -483096.131287] AUTODETECT spr round 2 (radius: 10)
[13:05:24 -332942.910919] AUTODETECT spr round 3 (radius: 15)
[13:07:46 -275011.186202] AUTODETECT spr round 4 (radius: 20)
[13:10:51 -262161.124901] AUTODETECT spr round 5 (radius: 25)
[13:15:29 -259063.136249] SPR radius for FAST iterations: 25 (autodetect)
[13:15:29 -259063.136249] Model parameter optimization (eps = 3.000000)
[13:15:53 -258897.713587] FAST spr round 1 (radius: 25)
[13:18:33 -228493.610373] FAST spr round 2 (radius: 25)
[13:20:33 -227273.608152] FAST spr round 3 (radius: 25)
[13:22:21 -227206.819370] FAST spr round 4 (radius: 25)
[13:23:56 -227202.308953] FAST spr round 5 (radius: 25)
[13:25:26 -227202.308071] Model parameter optimization (eps = 1.000000)
[13:25:41 -227197.878478] SLOW spr round 1 (radius: 5)
[13:27:47 -227145.649553] SLOW spr round 2 (radius: 5)
[13:29:50 -227141.416160] SLOW spr round 3 (radius: 5)
[13:31:47 -227141.416032] SLOW spr round 4 (radius: 10)
[13:33:47 -227141.416032] SLOW spr round 5 (radius: 15)
[13:38:27 -227141.416032] SLOW spr round 6 (radius: 20)
[13:46:59 -227141.416032] SLOW spr round 7 (radius: 25)
[13:57:15 -227141.416032] Model parameter optimization (eps = 0.100000)

[13:57:32] ML tree search #13, logLikelihood: -227139.834771

[13:57:32 -736607.003238] Initial branch length optimization
[13:57:35 -649073.278440] Model parameter optimization (eps = 10.000000)
[13:58:16 -644643.624413] AUTODETECT spr round 1 (radius: 5)
[14:00:15 -480867.187326] AUTODETECT spr round 2 (radius: 10)
[14:02:25 -338141.116303] AUTODETECT spr round 3 (radius: 15)
[14:04:47 -272427.168384] AUTODETECT spr round 4 (radius: 20)
[14:07:52 -264239.205131] AUTODETECT spr round 5 (radius: 25)
[14:12:18 -259413.429818] SPR radius for FAST iterations: 25 (autodetect)
[14:12:18 -259413.429818] Model parameter optimization (eps = 3.000000)
[14:12:47 -259256.844437] FAST spr round 1 (radius: 25)
[14:15:35 -228104.248951] FAST spr round 2 (radius: 25)
[14:17:40 -227335.227298] FAST spr round 3 (radius: 25)
[14:19:29 -227271.157664] FAST spr round 4 (radius: 25)
[14:21:03 -227271.157440] Model parameter optimization (eps = 1.000000)
[14:21:18 -227211.461382] SLOW spr round 1 (radius: 5)
[14:23:27 -227164.958166] SLOW spr round 2 (radius: 5)
[14:25:29 -227163.353765] SLOW spr round 3 (radius: 5)
[14:27:26 -227163.353456] SLOW spr round 4 (radius: 10)
[14:29:26 -227163.353448] SLOW spr round 5 (radius: 15)
[14:34:10 -227163.353446] SLOW spr round 6 (radius: 20)
[14:42:54 -227163.353445] SLOW spr round 7 (radius: 25)
[14:52:57 -227163.353445] Model parameter optimization (eps = 0.100000)

[14:53:06] ML tree search #14, logLikelihood: -227163.067337

[14:53:06 -742968.356750] Initial branch length optimization
[14:53:09 -653787.021377] Model parameter optimization (eps = 10.000000)
[14:54:01 -649495.194612] AUTODETECT spr round 1 (radius: 5)
[14:56:01 -481242.114736] AUTODETECT spr round 2 (radius: 10)
[14:58:11 -321667.007790] AUTODETECT spr round 3 (radius: 15)
[15:00:30 -270128.280865] AUTODETECT spr round 4 (radius: 20)
[15:03:31 -258750.467269] AUTODETECT spr round 5 (radius: 25)
[15:06:53 -257251.323043] SPR radius for FAST iterations: 25 (autodetect)
[15:06:53 -257251.323043] Model parameter optimization (eps = 3.000000)
[15:07:14 -257075.853290] FAST spr round 1 (radius: 25)
[15:09:48 -228525.738585] FAST spr round 2 (radius: 25)
[15:11:51 -227368.378142] FAST spr round 3 (radius: 25)
[15:13:42 -227293.393514] FAST spr round 4 (radius: 25)
[15:15:24 -227285.274768] FAST spr round 5 (radius: 25)
[15:16:59 -227285.274454] Model parameter optimization (eps = 1.000000)
[15:17:13 -227278.429792] SLOW spr round 1 (radius: 5)
[15:19:29 -227227.159235] SLOW spr round 2 (radius: 5)
[15:21:37 -227218.415888] SLOW spr round 3 (radius: 5)
[15:23:36 -227218.336942] SLOW spr round 4 (radius: 10)
[15:25:38 -227217.411274] SLOW spr round 5 (radius: 5)
[15:28:04 -227217.411218] SLOW spr round 6 (radius: 10)
[15:30:20 -227217.411218] SLOW spr round 7 (radius: 15)
[15:34:25 -227216.788650] SLOW spr round 8 (radius: 5)
[15:37:01 -227210.751032] SLOW spr round 9 (radius: 5)
[15:39:15 -227210.229802] SLOW spr round 10 (radius: 5)
[15:41:20 -227210.229616] SLOW spr round 11 (radius: 10)
[15:43:23 -227210.229615] SLOW spr round 12 (radius: 15)
[15:48:00 -227210.229615] SLOW spr round 13 (radius: 20)
[15:58:11 -227210.229615] SLOW spr round 14 (radius: 25)
[16:09:40 -227210.229615] Model parameter optimization (eps = 0.100000)

[16:09:50] ML tree search #15, logLikelihood: -227209.739035

[16:09:50 -734222.658444] Initial branch length optimization
[16:09:54 -645328.631373] Model parameter optimization (eps = 10.000000)
[16:10:47 -641354.254162] AUTODETECT spr round 1 (radius: 5)
[16:12:58 -482790.133197] AUTODETECT spr round 2 (radius: 10)
[16:15:21 -328915.001176] AUTODETECT spr round 3 (radius: 15)
[16:17:54 -266442.395479] AUTODETECT spr round 4 (radius: 20)
[16:21:14 -258847.549799] AUTODETECT spr round 5 (radius: 25)
[16:25:36 -258496.591373] SPR radius for FAST iterations: 25 (autodetect)
[16:25:36 -258496.591373] Model parameter optimization (eps = 3.000000)
[16:26:04 -258339.084061] FAST spr round 1 (radius: 25)
[16:29:06 -228280.399399] FAST spr round 2 (radius: 25)
[16:31:22 -227292.025340] FAST spr round 3 (radius: 25)
[16:33:16 -227252.842693] FAST spr round 4 (radius: 25)
[16:35:00 -227238.441081] FAST spr round 5 (radius: 25)
[16:36:40 -227236.982186] FAST spr round 6 (radius: 25)
[16:38:19 -227231.467063] FAST spr round 7 (radius: 25)
[16:39:56 -227230.405828] FAST spr round 8 (radius: 25)
[16:41:32 -227230.405684] Model parameter optimization (eps = 1.000000)
[16:41:43 -227228.623566] SLOW spr round 1 (radius: 5)
[16:44:01 -227175.915003] SLOW spr round 2 (radius: 5)
[16:46:10 -227163.424150] SLOW spr round 3 (radius: 5)
[16:48:17 -227163.255803] SLOW spr round 4 (radius: 5)
[16:50:24 -227160.025340] SLOW spr round 5 (radius: 5)
[16:52:29 -227160.025334] SLOW spr round 6 (radius: 10)
[16:54:38 -227160.025334] SLOW spr round 7 (radius: 15)
[16:59:59 -227159.895882] SLOW spr round 8 (radius: 5)
[17:02:45 -227156.331197] SLOW spr round 9 (radius: 5)
[17:05:06 -227156.331195] SLOW spr round 10 (radius: 10)
[17:07:21 -227156.331195] SLOW spr round 11 (radius: 15)
[17:12:16 -227156.331195] SLOW spr round 12 (radius: 20)
[17:22:40 -227156.331195] SLOW spr round 13 (radius: 25)
[17:33:14 -227156.331194] Model parameter optimization (eps = 0.100000)

[17:33:25] ML tree search #16, logLikelihood: -227155.969419

[17:33:25 -738134.930449] Initial branch length optimization
[17:33:29 -650522.455761] Model parameter optimization (eps = 10.000000)
[17:34:19 -646140.591596] AUTODETECT spr round 1 (radius: 5)
[17:36:29 -477930.468713] AUTODETECT spr round 2 (radius: 10)
[17:38:50 -321552.503535] AUTODETECT spr round 3 (radius: 15)
[17:41:29 -270212.011449] AUTODETECT spr round 4 (radius: 20)
[17:45:08 -258861.002784] AUTODETECT spr round 5 (radius: 25)
[17:49:57 -258747.821132] SPR radius for FAST iterations: 25 (autodetect)
[17:49:57 -258747.821132] Model parameter optimization (eps = 3.000000)
[17:50:18 -258549.166882] FAST spr round 1 (radius: 25)
[17:53:12 -228280.543336] FAST spr round 2 (radius: 25)
[17:55:23 -227265.880902] FAST spr round 3 (radius: 25)
[17:57:17 -227198.658683] FAST spr round 4 (radius: 25)
[17:58:59 -227198.658502] Model parameter optimization (eps = 1.000000)
[17:59:13 -227196.896273] SLOW spr round 1 (radius: 5)
[18:01:33 -227151.742065] SLOW spr round 2 (radius: 5)
[18:03:46 -227146.187775] SLOW spr round 3 (radius: 5)
[18:05:54 -227146.187696] SLOW spr round 4 (radius: 10)
[18:08:05 -227145.216232] SLOW spr round 5 (radius: 5)
[18:10:40 -227145.216133] SLOW spr round 6 (radius: 10)
[18:13:06 -227145.216089] SLOW spr round 7 (radius: 15)
[18:17:32 -227144.871291] SLOW spr round 8 (radius: 5)
[18:20:15 -227141.575325] SLOW spr round 9 (radius: 5)
[18:22:36 -227141.575275] SLOW spr round 10 (radius: 10)
[18:24:53 -227141.575234] SLOW spr round 11 (radius: 15)
[18:29:41 -227141.575193] SLOW spr round 12 (radius: 20)
[18:39:22 -227141.575152] SLOW spr round 13 (radius: 25)
[18:50:09 -227141.575112] Model parameter optimization (eps = 0.100000)

[18:50:19] ML tree search #17, logLikelihood: -227141.496088

[18:50:19 -738413.445001] Initial branch length optimization
[18:50:23 -649364.317645] Model parameter optimization (eps = 10.000000)
[18:51:07 -645086.902267] AUTODETECT spr round 1 (radius: 5)
[18:53:16 -486616.954780] AUTODETECT spr round 2 (radius: 10)
[18:55:35 -323044.670873] AUTODETECT spr round 3 (radius: 15)
[18:58:04 -262827.672917] AUTODETECT spr round 4 (radius: 20)
[19:01:25 -257348.238377] AUTODETECT spr round 5 (radius: 25)
[19:06:35 -257074.800275] SPR radius for FAST iterations: 25 (autodetect)
[19:06:35 -257074.800275] Model parameter optimization (eps = 3.000000)
[19:06:54 -256941.302529] FAST spr round 1 (radius: 25)
[19:09:47 -228046.147285] FAST spr round 2 (radius: 25)
[19:11:59 -227315.944574] FAST spr round 3 (radius: 25)
[19:13:52 -227266.253776] FAST spr round 4 (radius: 25)
[19:15:36 -227250.029758] FAST spr round 5 (radius: 25)
[19:17:14 -227250.029743] Model parameter optimization (eps = 1.000000)
[19:17:29 -227237.237669] SLOW spr round 1 (radius: 5)
[19:19:52 -227171.955487] SLOW spr round 2 (radius: 5)
[19:22:01 -227163.617726] SLOW spr round 3 (radius: 5)
[19:24:07 -227161.953338] SLOW spr round 4 (radius: 5)
[19:26:10 -227161.953326] SLOW spr round 5 (radius: 10)
[19:28:17 -227157.031344] SLOW spr round 6 (radius: 5)
[19:30:57 -227153.076619] SLOW spr round 7 (radius: 5)
[19:33:14 -227152.933167] SLOW spr round 8 (radius: 5)
[19:35:23 -227152.933166] SLOW spr round 9 (radius: 10)
[19:37:32 -227151.419919] SLOW spr round 10 (radius: 5)
[19:40:08 -227151.419761] SLOW spr round 11 (radius: 10)
[19:42:31 -227151.292388] SLOW spr round 12 (radius: 5)
[19:45:02 -227151.291875] SLOW spr round 13 (radius: 10)
[19:47:21 -227151.291865] SLOW spr round 14 (radius: 15)
[19:51:46 -227151.291864] SLOW spr round 15 (radius: 20)
[20:02:16 -227151.291863] SLOW spr round 16 (radius: 25)
[20:13:33 -227151.291863] Model parameter optimization (eps = 0.100000)

[20:13:45] ML tree search #18, logLikelihood: -227150.659193

[20:13:45 -739526.526750] Initial branch length optimization
[20:13:49 -650386.493386] Model parameter optimization (eps = 10.000000)
[20:14:20 -646007.394139] AUTODETECT spr round 1 (radius: 5)
[20:16:30 -483456.663172] AUTODETECT spr round 2 (radius: 10)
[20:18:54 -337603.318746] AUTODETECT spr round 3 (radius: 15)
[20:21:40 -275803.483383] AUTODETECT spr round 4 (radius: 20)
[20:25:31 -261201.310287] AUTODETECT spr round 5 (radius: 25)
[20:30:44 -259936.985395] SPR radius for FAST iterations: 25 (autodetect)
[20:30:44 -259936.985395] Model parameter optimization (eps = 3.000000)
[20:31:08 -259785.465222] FAST spr round 1 (radius: 25)
[20:34:11 -228615.430659] FAST spr round 2 (radius: 25)
[20:36:27 -227322.731160] FAST spr round 3 (radius: 25)
[20:38:28 -227256.417454] FAST spr round 4 (radius: 25)
[20:40:17 -227248.987500] FAST spr round 5 (radius: 25)
[20:42:01 -227247.927518] FAST spr round 6 (radius: 25)
[20:43:43 -227246.123745] FAST spr round 7 (radius: 25)
[20:45:22 -227246.123741] Model parameter optimization (eps = 1.000000)
[20:45:40 -227191.339323] SLOW spr round 1 (radius: 5)
[20:48:01 -227149.802379] SLOW spr round 2 (radius: 5)
[20:50:14 -227148.016221] SLOW spr round 3 (radius: 5)
[20:52:24 -227148.015973] SLOW spr round 4 (radius: 10)
[20:54:38 -227143.204361] SLOW spr round 5 (radius: 5)
[20:57:19 -227139.448795] SLOW spr round 6 (radius: 5)
[20:59:41 -227139.448751] SLOW spr round 7 (radius: 10)
[21:01:55 -227139.448720] SLOW spr round 8 (radius: 15)
[21:06:43 -227139.448689] SLOW spr round 9 (radius: 20)
[21:16:55 -227139.448659] SLOW spr round 10 (radius: 25)
[21:28:25 -227139.448629] Model parameter optimization (eps = 0.100000)

[21:28:36] ML tree search #19, logLikelihood: -227139.313623

[21:28:37 -742522.275012] Initial branch length optimization
[21:28:39 -651691.851236] Model parameter optimization (eps = 10.000000)
[21:29:14 -647562.003535] AUTODETECT spr round 1 (radius: 5)
[21:31:25 -497015.535035] AUTODETECT spr round 2 (radius: 10)
[21:33:47 -327001.891563] AUTODETECT spr round 3 (radius: 15)
[21:36:28 -267617.106014] AUTODETECT spr round 4 (radius: 20)
[21:39:54 -260228.348782] AUTODETECT spr round 5 (radius: 25)
[21:44:24 -259278.377457] SPR radius for FAST iterations: 25 (autodetect)
[21:44:24 -259278.377457] Model parameter optimization (eps = 3.000000)
[21:44:48 -259084.637037] FAST spr round 1 (radius: 25)
[21:47:38 -228468.356021] FAST spr round 2 (radius: 25)
[21:49:51 -227346.236872] FAST spr round 3 (radius: 25)
[21:51:45 -227254.149708] FAST spr round 4 (radius: 25)
[21:53:30 -227248.618487] FAST spr round 5 (radius: 25)
[21:55:13 -227245.252647] FAST spr round 6 (radius: 25)
[21:56:53 -227239.421326] FAST spr round 7 (radius: 25)
[21:58:30 -227239.421097] Model parameter optimization (eps = 1.000000)
[21:58:46 -227225.208001] SLOW spr round 1 (radius: 5)
[22:01:01 -227178.268810] SLOW spr round 2 (radius: 5)
[22:03:12 -227170.418700] SLOW spr round 3 (radius: 5)
[22:05:18 -227169.763334] SLOW spr round 4 (radius: 5)
[22:07:22 -227169.763218] SLOW spr round 5 (radius: 10)
[22:09:33 -227167.318954] SLOW spr round 6 (radius: 5)
[22:12:10 -227164.478597] SLOW spr round 7 (radius: 5)
[22:14:29 -227164.478540] SLOW spr round 8 (radius: 10)
[22:16:43 -227164.478492] SLOW spr round 9 (radius: 15)
[22:21:37 -227160.434942] SLOW spr round 10 (radius: 5)
[22:24:19 -227156.164867] SLOW spr round 11 (radius: 5)
[22:26:40 -227156.164774] SLOW spr round 12 (radius: 10)
[22:28:57 -227156.164729] SLOW spr round 13 (radius: 15)
[22:33:48 -227156.164686] SLOW spr round 14 (radius: 20)
[22:44:04 -227156.164643] SLOW spr round 15 (radius: 25)
[22:55:20 -227156.164600] Model parameter optimization (eps = 0.100000)

[22:55:27] ML tree search #20, logLikelihood: -227156.062154


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.072162,0.464470) (0.070326,0.397748) (0.245081,0.651862) (0.612431,1.271575) 
   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: -227135.920910

AIC score: 458281.841820 / AICc score: 8502341.841820 / BIC score: 467440.838032
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=712).
         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/Q96MG7/3_mltree/Q96MG7.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/3_mltree/Q96MG7.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/3_mltree/Q96MG7.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q96MG7/3_mltree/Q96MG7.raxml.log

Analysis started: 03-Jul-2021 07:09:23 / finished: 04-Jul-2021 06:04:51

Elapsed time: 82527.337 seconds

Consumed energy: 7607.315 Wh (= 38 km in an electric car, or 190 km with an e-scooter!)