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 01-Jul-2021 08:54:51 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/2_msa/A8MX76_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/3_mltree/A8MX76 --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/A8MX76/2_msa/A8MX76_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 681 sites

WARNING: Sequences tr_Q2LZQ6_Q2LZQ6_DROPS_46245 and tr_B4H3H2_B4H3H2_DROPE_7234 are exactly identical!
WARNING: Sequences tr_A0A2I3RT65_A0A2I3RT65_PANTR_9598 and tr_A0A2R9A0U6_A0A2R9A0U6_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2RBT6_H2RBT6_PANTR_9598 and tr_A0A2R9B0M1_A0A2R9B0M1_PANPA_9597 are exactly identical!
WARNING: Sequences sp_O14815_CAN9_HUMAN_9606 and tr_A0A2R9BRS7_A0A2R9BRS7_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A1D5QLX3_A0A1D5QLX3_MACMU_9544 and tr_A0A2K6CWT1_A0A2K6CWT1_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F6ZLR4_F6ZLR4_MACMU_9544 and tr_A0A0D9R5U5_A0A0D9R5U5_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A3Q0KJ03_A0A3Q0KJ03_SCHMA_6183 and tr_A0A3Q0KJ04_A0A3Q0KJ04_SCHMA_6183 are exactly identical!
WARNING: Sequences tr_A0A2D0RL55_A0A2D0RL55_ICTPU_7998 and tr_A0A2D0RMT1_A0A2D0RMT1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2K5LM94_A0A2K5LM94_CERAT_9531 and tr_A0A2K5YZR5_A0A2K5YZR5_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 9

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/A8MX76/3_mltree/A8MX76.raxml.reduced.phy

Alignment comprises 1 partitions and 681 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 681 / 681
Gaps: 8.48 %
Invariant sites: 0.15 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/3_mltree/A8MX76.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 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 171 / 13680
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1053303.344358] Initial branch length optimization
[00:00:10 -904040.060379] Model parameter optimization (eps = 10.000000)
[00:00:56 -901074.702951] AUTODETECT spr round 1 (radius: 5)
[00:04:12 -656099.449571] AUTODETECT spr round 2 (radius: 10)
[00:07:27 -502729.238872] AUTODETECT spr round 3 (radius: 15)
[00:11:18 -431560.343024] AUTODETECT spr round 4 (radius: 20)
[00:15:36 -404612.928543] AUTODETECT spr round 5 (radius: 25)
[00:20:50 -373941.408251] SPR radius for FAST iterations: 25 (autodetect)
[00:20:50 -373941.408251] Model parameter optimization (eps = 3.000000)
[00:21:16 -373604.863700] FAST spr round 1 (radius: 25)
[00:24:50 -326038.744739] FAST spr round 2 (radius: 25)
[00:28:06 -323843.235573] FAST spr round 3 (radius: 25)
[00:30:44 -323767.458673] FAST spr round 4 (radius: 25)
[00:32:45 -323765.553128] FAST spr round 5 (radius: 25)
[00:34:46 -323765.552864] Model parameter optimization (eps = 1.000000)
[00:35:02 -323754.071671] SLOW spr round 1 (radius: 5)
[00:38:08 -323660.787718] SLOW spr round 2 (radius: 5)
[00:40:54 -323652.879798] SLOW spr round 3 (radius: 5)
[00:43:30 -323652.023773] SLOW spr round 4 (radius: 5)
[00:46:07 -323652.023636] SLOW spr round 5 (radius: 10)
[00:48:42 -323652.023636] SLOW spr round 6 (radius: 15)
[00:54:06 -323652.023636] SLOW spr round 7 (radius: 20)
[01:02:48 -323652.023636] SLOW spr round 8 (radius: 25)
[01:14:03] [worker #1] ML tree search #2, logLikelihood: -323669.964198
[01:14:46 -323652.023636] Model parameter optimization (eps = 0.100000)

[01:14:53] [worker #0] ML tree search #1, logLikelihood: -323651.948746

[01:14:53 -1055669.364904] Initial branch length optimization
[01:14:59 -901997.811703] Model parameter optimization (eps = 10.000000)
[01:15:32 -899124.246246] AUTODETECT spr round 1 (radius: 5)
[01:18:40 -656029.526048] AUTODETECT spr round 2 (radius: 10)
[01:21:58 -477733.690596] AUTODETECT spr round 3 (radius: 15)
[01:25:35 -419595.650398] AUTODETECT spr round 4 (radius: 20)
[01:29:49 -383850.563426] AUTODETECT spr round 5 (radius: 25)
[01:34:50 -374917.272589] SPR radius for FAST iterations: 25 (autodetect)
[01:34:50 -374917.272589] Model parameter optimization (eps = 3.000000)
[01:35:19 -374610.860006] FAST spr round 1 (radius: 25)
[01:39:10 -326932.372897] FAST spr round 2 (radius: 25)
[01:42:12 -323951.089490] FAST spr round 3 (radius: 25)
[01:44:44 -323820.999682] FAST spr round 4 (radius: 25)
[01:46:48 -323805.723210] FAST spr round 5 (radius: 25)
[01:48:50 -323805.723187] Model parameter optimization (eps = 1.000000)
[01:49:04 -323801.731686] SLOW spr round 1 (radius: 5)
[01:52:13 -323692.307177] SLOW spr round 2 (radius: 5)
[01:55:09 -323673.230892] SLOW spr round 3 (radius: 5)
[01:57:42 -323670.883386] SLOW spr round 4 (radius: 5)
[02:00:21 -323670.883265] SLOW spr round 5 (radius: 10)
[02:02:49 -323670.883265] SLOW spr round 6 (radius: 15)
[02:08:18 -323670.883265] SLOW spr round 7 (radius: 20)
[02:17:07 -323670.883265] SLOW spr round 8 (radius: 25)
[02:29:38 -323670.883265] Model parameter optimization (eps = 0.100000)

[02:29:52] [worker #0] ML tree search #3, logLikelihood: -323670.482506

[02:29:52 -1054772.454049] Initial branch length optimization
[02:29:59 -899819.985617] Model parameter optimization (eps = 10.000000)
[02:30:42 -896973.253564] AUTODETECT spr round 1 (radius: 5)
[02:33:35 -659666.655292] AUTODETECT spr round 2 (radius: 10)
[02:36:04] [worker #1] ML tree search #4, logLikelihood: -323703.912662
[02:36:57 -474807.901844] AUTODETECT spr round 3 (radius: 15)
[02:40:35 -399305.454929] AUTODETECT spr round 4 (radius: 20)
[02:45:33 -367498.381116] AUTODETECT spr round 5 (radius: 25)
[02:53:14 -365735.710917] SPR radius for FAST iterations: 25 (autodetect)
[02:53:14 -365735.710917] Model parameter optimization (eps = 3.000000)
[02:53:38 -365347.682639] FAST spr round 1 (radius: 25)
[02:57:17 -325896.671051] FAST spr round 2 (radius: 25)
[02:59:48 -323895.850097] FAST spr round 3 (radius: 25)
[03:02:09 -323752.894406] FAST spr round 4 (radius: 25)
[03:04:18 -323752.470348] FAST spr round 5 (radius: 25)
[03:06:19 -323752.470346] Model parameter optimization (eps = 1.000000)
[03:06:37 -323747.344138] SLOW spr round 1 (radius: 5)
[03:09:25 -323681.323501] SLOW spr round 2 (radius: 5)
[03:12:19 -323675.661066] SLOW spr round 3 (radius: 5)
[03:14:51 -323675.660765] SLOW spr round 4 (radius: 10)
[03:17:56 -323675.249548] SLOW spr round 5 (radius: 5)
[03:21:19 -323675.249545] SLOW spr round 6 (radius: 10)
[03:24:12 -323675.249545] SLOW spr round 7 (radius: 15)
[03:28:44 -323675.249545] SLOW spr round 8 (radius: 20)
[03:37:07 -323675.249545] SLOW spr round 9 (radius: 25)
[03:48:48 -323675.249545] Model parameter optimization (eps = 0.100000)

[03:48:57] [worker #0] ML tree search #5, logLikelihood: -323675.156854

[03:48:57 -1055069.352894] Initial branch length optimization
[03:49:07 -899059.357040] Model parameter optimization (eps = 10.000000)
[03:49:44 -896240.971234] AUTODETECT spr round 1 (radius: 5)
[03:52:43 -653010.416251] AUTODETECT spr round 2 (radius: 10)
[03:55:54 -486984.702858] AUTODETECT spr round 3 (radius: 15)
[03:59:24 -418110.966460] AUTODETECT spr round 4 (radius: 20)
[04:00:31] [worker #1] ML tree search #6, logLikelihood: -323679.223294
[04:04:06 -382460.957833] AUTODETECT spr round 5 (radius: 25)
[04:09:15 -370945.811915] SPR radius for FAST iterations: 25 (autodetect)
[04:09:15 -370945.811915] Model parameter optimization (eps = 3.000000)
[04:09:44 -370649.217129] FAST spr round 1 (radius: 25)
[04:13:21 -325624.089517] FAST spr round 2 (radius: 25)
[04:16:11 -323879.219486] FAST spr round 3 (radius: 25)
[04:18:30 -323774.901333] FAST spr round 4 (radius: 25)
[04:20:36 -323762.865064] FAST spr round 5 (radius: 25)
[04:22:40 -323762.865059] Model parameter optimization (eps = 1.000000)
[04:22:58 -323760.186964] SLOW spr round 1 (radius: 5)
[04:25:54 -323671.018392] SLOW spr round 2 (radius: 5)
[04:29:05 -323664.042132] SLOW spr round 3 (radius: 5)
[04:31:59 -323661.090965] SLOW spr round 4 (radius: 5)
[04:34:28 -323661.090850] SLOW spr round 5 (radius: 10)
[04:37:08 -323661.090850] SLOW spr round 6 (radius: 15)
[04:42:03 -323661.090850] SLOW spr round 7 (radius: 20)
[04:50:42 -323661.090850] SLOW spr round 8 (radius: 25)
[05:03:02 -323661.090850] Model parameter optimization (eps = 0.100000)

[05:03:13] [worker #0] ML tree search #7, logLikelihood: -323660.757499

[05:03:13 -1051482.874501] Initial branch length optimization
[05:03:19 -897945.760971] Model parameter optimization (eps = 10.000000)
[05:03:55 -895114.710767] AUTODETECT spr round 1 (radius: 5)
[05:06:49 -655193.433502] AUTODETECT spr round 2 (radius: 10)
[05:10:17 -497571.690436] AUTODETECT spr round 3 (radius: 15)
[05:14:00 -400714.651274] AUTODETECT spr round 4 (radius: 20)
[05:18:46 -377107.515017] AUTODETECT spr round 5 (radius: 25)
[05:18:49] [worker #1] ML tree search #8, logLikelihood: -323661.573580
[05:24:21 -373611.829083] SPR radius for FAST iterations: 25 (autodetect)
[05:24:21 -373611.829083] Model parameter optimization (eps = 3.000000)
[05:24:54 -373238.779502] FAST spr round 1 (radius: 25)
[05:28:32 -326425.849078] FAST spr round 2 (radius: 25)
[05:31:20 -323896.618474] FAST spr round 3 (radius: 25)
[05:33:50 -323761.028613] FAST spr round 4 (radius: 25)
[05:36:26 -323749.143732] FAST spr round 5 (radius: 25)
[05:38:22 -323740.165499] FAST spr round 6 (radius: 25)
[05:40:48 -323740.165300] Model parameter optimization (eps = 1.000000)
[05:41:01 -323737.608121] SLOW spr round 1 (radius: 5)
[05:44:13 -323682.188959] SLOW spr round 2 (radius: 5)
[05:46:54 -323672.450750] SLOW spr round 3 (radius: 5)
[05:49:44 -323672.146594] SLOW spr round 4 (radius: 5)
[05:52:45 -323672.146590] SLOW spr round 5 (radius: 10)
[05:55:34 -323669.858006] SLOW spr round 6 (radius: 5)
[05:58:49 -323669.857978] SLOW spr round 7 (radius: 10)
[06:01:50 -323666.424043] SLOW spr round 8 (radius: 5)
[06:05:00 -323666.424041] SLOW spr round 9 (radius: 10)
[06:08:16 -323666.424041] SLOW spr round 10 (radius: 15)
[06:12:46 -323666.424041] SLOW spr round 11 (radius: 20)
[06:21:10 -323666.424041] SLOW spr round 12 (radius: 25)
[06:32:44 -323666.424041] Model parameter optimization (eps = 0.100000)

[06:32:49] [worker #0] ML tree search #9, logLikelihood: -323666.331768

[06:32:49 -1053540.972814] Initial branch length optimization
[06:32:55 -901809.649275] Model parameter optimization (eps = 10.000000)
[06:33:40 -898889.121056] AUTODETECT spr round 1 (radius: 5)
[06:36:34 -654329.626581] AUTODETECT spr round 2 (radius: 10)
[06:40:02 -491601.818132] AUTODETECT spr round 3 (radius: 15)
[06:43:50 -392937.871484] AUTODETECT spr round 4 (radius: 20)
[06:47:57 -371177.471359] AUTODETECT spr round 5 (radius: 25)
[06:52:13] [worker #1] ML tree search #10, logLikelihood: -323655.553625
[06:53:11 -366670.164640] SPR radius for FAST iterations: 25 (autodetect)
[06:53:11 -366670.164640] Model parameter optimization (eps = 3.000000)
[06:53:46 -366332.908675] FAST spr round 1 (radius: 25)
[06:57:47 -325442.307561] FAST spr round 2 (radius: 25)
[07:00:27 -323942.239680] FAST spr round 3 (radius: 25)
[07:02:54 -323777.098999] FAST spr round 4 (radius: 25)
[07:05:09 -323766.175019] FAST spr round 5 (radius: 25)
[07:07:15 -323766.175015] Model parameter optimization (eps = 1.000000)
[07:07:33 -323761.988310] SLOW spr round 1 (radius: 5)
[07:10:20 -323686.565648] SLOW spr round 2 (radius: 5)
[07:13:07 -323670.204626] SLOW spr round 3 (radius: 5)
[07:15:48 -323666.281243] SLOW spr round 4 (radius: 5)
[07:18:39 -323666.066264] SLOW spr round 5 (radius: 5)
[07:21:28 -323666.066263] SLOW spr round 6 (radius: 10)
[07:24:09 -323664.787720] SLOW spr round 7 (radius: 5)
[07:27:23 -323664.787376] SLOW spr round 8 (radius: 10)
[07:30:27 -323664.787374] SLOW spr round 9 (radius: 15)
[07:34:52 -323664.787374] SLOW spr round 10 (radius: 20)
[07:43:33 -323664.787374] SLOW spr round 11 (radius: 25)
[07:55:22 -323664.787374] Model parameter optimization (eps = 0.100000)

[07:55:31] [worker #0] ML tree search #11, logLikelihood: -323664.230357

[07:55:31 -1057370.812552] Initial branch length optimization
[07:55:36 -899817.696529] Model parameter optimization (eps = 10.000000)
[07:56:11 -896941.484103] AUTODETECT spr round 1 (radius: 5)
[07:59:06 -668670.236576] AUTODETECT spr round 2 (radius: 10)
[08:02:21 -502308.596370] AUTODETECT spr round 3 (radius: 15)
[08:06:06 -410354.032039] AUTODETECT spr round 4 (radius: 20)
[08:10:47 -379631.937725] AUTODETECT spr round 5 (radius: 25)
[08:12:53] [worker #1] ML tree search #12, logLikelihood: -323649.736151
[08:16:34 -370769.582267] SPR radius for FAST iterations: 25 (autodetect)
[08:16:34 -370769.582267] Model parameter optimization (eps = 3.000000)
[08:16:45 -370753.702189] FAST spr round 1 (radius: 25)
[08:20:29 -325937.612471] FAST spr round 2 (radius: 25)
[08:23:12 -324217.552936] FAST spr round 3 (radius: 25)
[08:25:32 -324090.610329] FAST spr round 4 (radius: 25)
[08:27:37 -324080.139484] FAST spr round 5 (radius: 25)
[08:29:44 -324080.138911] Model parameter optimization (eps = 1.000000)
[08:30:09 -323755.786601] SLOW spr round 1 (radius: 5)
[08:33:11 -323670.843668] SLOW spr round 2 (radius: 5)
[08:36:04 -323666.786280] SLOW spr round 3 (radius: 5)
[08:38:48 -323658.693103] SLOW spr round 4 (radius: 5)
[08:41:20 -323658.693103] SLOW spr round 5 (radius: 10)
[08:44:03 -323658.375091] SLOW spr round 6 (radius: 5)
[08:47:19 -323658.375088] SLOW spr round 7 (radius: 10)
[08:50:10 -323658.250000] SLOW spr round 8 (radius: 5)
[08:53:28 -323656.495331] SLOW spr round 9 (radius: 5)
[08:56:11 -323656.495330] SLOW spr round 10 (radius: 10)
[08:59:22 -323656.495330] SLOW spr round 11 (radius: 15)
[09:04:05 -323656.495330] SLOW spr round 12 (radius: 20)
[09:12:57 -323656.495330] SLOW spr round 13 (radius: 25)
[09:25:22 -323656.495330] Model parameter optimization (eps = 0.100000)

[09:25:36] [worker #0] ML tree search #13, logLikelihood: -323655.806120

[09:25:36 -1059441.142722] Initial branch length optimization
[09:25:41 -901021.624054] Model parameter optimization (eps = 10.000000)
[09:26:13 -898126.741970] AUTODETECT spr round 1 (radius: 5)
[09:29:07 -665796.047456] AUTODETECT spr round 2 (radius: 10)
[09:32:30 -481972.145895] AUTODETECT spr round 3 (radius: 15)
[09:36:06 -402979.770514] AUTODETECT spr round 4 (radius: 20)
[09:38:10] [worker #1] ML tree search #14, logLikelihood: -323680.209074
[09:40:17 -380347.500112] AUTODETECT spr round 5 (radius: 25)
[09:46:17 -371870.143028] SPR radius for FAST iterations: 25 (autodetect)
[09:46:17 -371870.143028] Model parameter optimization (eps = 3.000000)
[09:46:42 -371526.108722] FAST spr round 1 (radius: 25)
[09:50:38 -326379.808358] FAST spr round 2 (radius: 25)
[09:53:24 -324015.946225] FAST spr round 3 (radius: 25)
[09:56:01 -323832.369184] FAST spr round 4 (radius: 25)
[09:58:12 -323771.724237] FAST spr round 5 (radius: 25)
[10:00:08 -323769.150474] FAST spr round 6 (radius: 25)
[10:02:06 -323769.150462] Model parameter optimization (eps = 1.000000)
[10:02:29 -323762.416360] SLOW spr round 1 (radius: 5)
[10:05:26 -323687.176784] SLOW spr round 2 (radius: 5)
[10:08:03 -323680.446639] SLOW spr round 3 (radius: 5)
[10:11:08 -323680.022804] SLOW spr round 4 (radius: 5)
[10:13:56 -323680.022803] SLOW spr round 5 (radius: 10)
[10:16:30 -323676.074549] SLOW spr round 6 (radius: 5)
[10:19:56 -323675.209043] SLOW spr round 7 (radius: 5)
[10:22:57 -323675.209043] SLOW spr round 8 (radius: 10)
[10:25:37 -323675.209043] SLOW spr round 9 (radius: 15)
[10:30:30 -323675.209043] SLOW spr round 10 (radius: 20)
[10:39:37 -323675.209043] SLOW spr round 11 (radius: 25)
[10:51:12 -323675.209043] Model parameter optimization (eps = 0.100000)

[10:51:19] [worker #0] ML tree search #15, logLikelihood: -323675.117177

[10:51:19 -1056426.015237] Initial branch length optimization
[10:51:25 -901956.179991] Model parameter optimization (eps = 10.000000)
[10:52:14 -899056.245326] AUTODETECT spr round 1 (radius: 5)
[10:53:49] [worker #1] ML tree search #16, logLikelihood: -323650.665908
[10:55:09 -671995.785373] AUTODETECT spr round 2 (radius: 10)
[10:58:56 -504269.236489] AUTODETECT spr round 3 (radius: 15)
[11:02:37 -417906.707678] AUTODETECT spr round 4 (radius: 20)
[11:06:59 -368426.647756] AUTODETECT spr round 5 (radius: 25)
[11:13:27 -366549.066634] SPR radius for FAST iterations: 25 (autodetect)
[11:13:27 -366549.066634] Model parameter optimization (eps = 3.000000)
[11:13:53 -366238.387418] FAST spr round 1 (radius: 25)
[11:17:31 -325410.010766] FAST spr round 2 (radius: 25)
[11:20:12 -323927.704966] FAST spr round 3 (radius: 25)
[11:22:56 -323791.743605] FAST spr round 4 (radius: 25)
[11:25:12 -323770.872563] FAST spr round 5 (radius: 25)
[11:27:20 -323770.872430] Model parameter optimization (eps = 1.000000)
[11:27:37 -323763.283317] SLOW spr round 1 (radius: 5)
[11:30:24 -323676.997682] SLOW spr round 2 (radius: 5)
[11:33:16 -323666.248153] SLOW spr round 3 (radius: 5)
[11:36:02 -323654.620580] SLOW spr round 4 (radius: 5)
[11:38:38 -323654.620570] SLOW spr round 5 (radius: 10)
[11:41:12 -323654.620570] SLOW spr round 6 (radius: 15)
[11:46:09 -323654.620570] SLOW spr round 7 (radius: 20)
[11:54:57 -323654.620570] SLOW spr round 8 (radius: 25)
[12:06:36 -323654.620570] Model parameter optimization (eps = 0.100000)

[12:06:45] [worker #0] ML tree search #17, logLikelihood: -323654.177868

[12:06:45 -1056206.791218] Initial branch length optimization
[12:06:51 -902678.688849] Model parameter optimization (eps = 10.000000)
[12:07:28 -899799.033318] AUTODETECT spr round 1 (radius: 5)
[12:10:26 -666185.589976] AUTODETECT spr round 2 (radius: 10)
[12:14:16 -477149.710898] AUTODETECT spr round 3 (radius: 15)
[12:18:01 -389527.415763] AUTODETECT spr round 4 (radius: 20)
[12:23:12 -370948.316294] AUTODETECT spr round 5 (radius: 25)
[12:29:34 -364395.428880] SPR radius for FAST iterations: 25 (autodetect)
[12:29:34 -364395.428880] Model parameter optimization (eps = 3.000000)
[12:29:57 -364051.077406] FAST spr round 1 (radius: 25)
[12:33:33 -325598.653599] FAST spr round 2 (radius: 25)
[12:35:13] [worker #1] ML tree search #18, logLikelihood: -323653.547806
[12:36:01 -323904.460353] FAST spr round 3 (radius: 25)
[12:38:52 -323802.589273] FAST spr round 4 (radius: 25)
[12:41:11 -323782.566667] FAST spr round 5 (radius: 25)
[12:43:09 -323782.566634] Model parameter optimization (eps = 1.000000)
[12:43:24 -323779.374703] SLOW spr round 1 (radius: 5)
[12:46:18 -323683.525864] SLOW spr round 2 (radius: 5)
[12:49:07 -323679.382897] SLOW spr round 3 (radius: 5)
[12:51:45 -323679.382871] SLOW spr round 4 (radius: 10)
[12:54:22 -323676.425616] SLOW spr round 5 (radius: 5)
[12:57:55 -323666.510432] SLOW spr round 6 (radius: 5)
[13:00:57 -323666.510428] SLOW spr round 7 (radius: 10)
[13:03:56 -323666.065800] SLOW spr round 8 (radius: 5)
[13:07:13 -323666.065799] SLOW spr round 9 (radius: 10)
[13:10:08 -323665.762459] SLOW spr round 10 (radius: 5)
[13:13:27 -323663.700863] SLOW spr round 11 (radius: 5)
[13:16:16 -323663.700863] SLOW spr round 12 (radius: 10)
[13:18:54 -323663.700863] SLOW spr round 13 (radius: 15)
[13:23:36 -323663.700863] SLOW spr round 14 (radius: 20)
[13:32:33 -323663.700863] SLOW spr round 15 (radius: 25)
[13:43:57 -323663.700863] Model parameter optimization (eps = 0.100000)

[13:44:08] [worker #0] ML tree search #19, logLikelihood: -323663.400010

[13:49:34] [worker #1] ML tree search #20, logLikelihood: -323680.658050

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.142204,0.424789) (0.211513,0.441666) (0.327326,0.834180) (0.318956,1.796879) 
   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: -323649.736151

AIC score: 651309.472303 / AICc score: 8695369.472303 / BIC score: 660379.214726
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=681).
         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/A8MX76/3_mltree/A8MX76.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/3_mltree/A8MX76.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/3_mltree/A8MX76.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A8MX76/3_mltree/A8MX76.raxml.log

Analysis started: 01-Jul-2021 08:54:51 / finished: 01-Jul-2021 22:44:25

Elapsed time: 49774.417 seconds

Consumed energy: 4570.707 Wh (= 23 km in an electric car, or 114 km with an e-scooter!)