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 06-Jul-2021 01:06:06 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/2_msa/P40939_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939 --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/P40939/2_msa/P40939_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 688 sites

WARNING: Sequences tr_B8NYZ2_B8NYZ2_ASPFN_332952 and tr_Q2PIU9_Q2PIU9_ASPOR_510516 are exactly identical!
WARNING: Sequences tr_B8NYZ2_B8NYZ2_ASPFN_332952 and tr_A0A1S9D415_A0A1S9D415_ASPOZ_5062 are exactly identical!
WARNING: Sequences tr_H2QHK4_H2QHK4_PANTR_9598 and tr_A0A2R9CMA4_A0A2R9CMA4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A0E0FLC6_A0A0E0FLC6_ORYNI_4536 and tr_B8A7J7_B8A7J7_ORYSI_39946 are exactly identical!
WARNING: Sequences tr_A0A0E0FLC6_A0A0E0FLC6_ORYNI_4536 and tr_A0A0E0MVZ8_A0A0E0MVZ8_ORYRU_4529 are exactly identical!
WARNING: Sequences tr_A0A0E0FLC6_A0A0E0FLC6_ORYNI_4536 and tr_Q94CN1_Q94CN1_ORYSJ_39947 are exactly identical!
WARNING: Sequences tr_A0A0E0FUE0_A0A0E0FUE0_ORYNI_4536 and tr_A2WVZ2_A2WVZ2_ORYSI_39946 are exactly identical!
WARNING: Sequences tr_A0A0E0FUE0_A0A0E0FUE0_ORYNI_4536 and tr_I1NSD7_I1NSD7_ORYGL_4538 are exactly identical!
WARNING: Sequences tr_A0A0E0FUE0_A0A0E0FUE0_ORYNI_4536 and tr_A0A0D3EV13_A0A0D3EV13_9ORYZ_65489 are exactly identical!
WARNING: Sequences tr_A0A0E0FUE0_A0A0E0FUE0_ORYNI_4536 and tr_A0A0D9YG29_A0A0D9YG29_9ORYZ_40148 are exactly identical!
WARNING: Sequences tr_A0A0E0FUE0_A0A0E0FUE0_ORYNI_4536 and tr_Q8S1G9_Q8S1G9_ORYSJ_39947 are exactly identical!
WARNING: Sequences tr_F4P0M5_F4P0M5_BATDJ_684364 and tr_A0A177WE61_A0A177WE61_BATDE_403673 are exactly identical!
WARNING: Sequences tr_I1NZC4_I1NZC4_ORYGL_4538 and tr_A0A0D3F3I0_A0A0D3F3I0_9ORYZ_65489 are exactly identical!
WARNING: Sequences tr_H0Z0N4_H0Z0N4_TAEGU_59729 and tr_A0A218UTU7_A0A218UTU7_9PASE_299123 are exactly identical!
WARNING: Sequences tr_E3MAW6_E3MAW6_CAERE_31234 and tr_A0A261CLY9_A0A261CLY9_9PELO_1503980 are exactly identical!
WARNING: Sequences tr_A0A015LX37_A0A015LX37_9GLOM_1432141 and tr_A0A2H5TCT0_A0A2H5TCT0_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A0D3G6M6_A0A0D3G6M6_9ORYZ_65489 and tr_A0A0D9ZY33_A0A0D9ZY33_9ORYZ_40148 are exactly identical!
WARNING: Sequences tr_A0A0D9QVE6_A0A0D9QVE6_CHLSB_60711 and tr_A0A2K6BUW7_A0A2K6BUW7_MACNE_9545 are exactly identical!
WARNING: Sequences tr_V4TV49_V4TV49_9ROSI_85681 and tr_A0A2H5QMF9_A0A2H5QMF9_CITUN_55188 are exactly identical!
WARNING: Sequences tr_A0A0V1CNX6_A0A0V1CNX6_TRIBR_45882 and tr_A0A0V1P1M5_A0A0V1P1M5_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V1CNX6_A0A0V1CNX6_TRIBR_45882 and tr_A0A0V0U8P6_A0A0V0U8P6_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A0V1D390_A0A0V1D390_TRIBR_45882 and tr_A0A0V0UV02_A0A0V0UV02_9BILA_181606 are exactly identical!
WARNING: Sequences tr_A0A0V1D390_A0A0V1D390_TRIBR_45882 and tr_A0A0V1NLR2_A0A0V1NLR2_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V1D390_A0A0V1D390_TRIBR_45882 and tr_A0A0V0TR84_A0A0V0TR84_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A1S4A6H4_A0A1S4A6H4_TOBAC_4097 and tr_A0A1U7VJ13_A0A1U7VJ13_NICSY_4096 are exactly identical!
WARNING: Duplicate sequences found: 25

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/P40939/3_mltree/P40939.raxml.reduced.phy

Alignment comprises 1 partitions and 688 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 688 / 688
Gaps: 24.43 %
Invariant sites: 0.15 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.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 / 172 / 13760
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -993320.460094] Initial branch length optimization
[00:00:06 -830139.719217] Model parameter optimization (eps = 10.000000)
[00:00:46 -827137.886941] AUTODETECT spr round 1 (radius: 5)
[00:03:27 -571415.206193] AUTODETECT spr round 2 (radius: 10)
[00:06:17 -441131.303099] AUTODETECT spr round 3 (radius: 15)
[00:09:20 -373009.558938] AUTODETECT spr round 4 (radius: 20)
[00:12:55 -330687.001082] AUTODETECT spr round 5 (radius: 25)
[00:17:12 -325130.218963] SPR radius for FAST iterations: 25 (autodetect)
[00:17:12 -325130.218963] Model parameter optimization (eps = 3.000000)
[00:17:35 -325051.598593] FAST spr round 1 (radius: 25)
[00:21:05 -283327.727737] FAST spr round 2 (radius: 25)
[00:23:42 -281606.820424] FAST spr round 3 (radius: 25)
[00:26:01 -281546.950121] FAST spr round 4 (radius: 25)
[00:27:57 -281544.329756] FAST spr round 5 (radius: 25)
[00:29:51 -281539.164218] FAST spr round 6 (radius: 25)
[00:31:42 -281539.163704] Model parameter optimization (eps = 1.000000)
[00:31:59 -281531.943106] SLOW spr round 1 (radius: 5)
[00:34:50 -281442.938483] SLOW spr round 2 (radius: 5)
[00:37:34 -281426.930502] SLOW spr round 3 (radius: 5)
[00:39:59 -281426.929794] SLOW spr round 4 (radius: 10)
[00:42:21 -281423.953817] SLOW spr round 5 (radius: 5)
[00:45:27 -281422.013185] SLOW spr round 6 (radius: 5)
[00:48:13 -281421.001902] SLOW spr round 7 (radius: 5)
[00:50:47 -281421.001650] SLOW spr round 8 (radius: 10)
[00:53:23 -281421.001610] SLOW spr round 9 (radius: 15)
[00:57:51 -281421.001583] SLOW spr round 10 (radius: 20)
[01:03:50 -281421.001565] SLOW spr round 11 (radius: 25)
[01:10:40] [worker #1] ML tree search #2, logLikelihood: -281433.461778
[01:11:50 -281421.001553] Model parameter optimization (eps = 0.100000)

[01:12:03] [worker #0] ML tree search #1, logLikelihood: -281420.655936

[01:12:03 -986637.239243] Initial branch length optimization
[01:12:09 -826407.858325] Model parameter optimization (eps = 10.000000)
[01:13:04 -823395.532627] AUTODETECT spr round 1 (radius: 5)
[01:15:45 -566663.603883] AUTODETECT spr round 2 (radius: 10)
[01:18:37 -441832.100194] AUTODETECT spr round 3 (radius: 15)
[01:21:49 -369993.656183] AUTODETECT spr round 4 (radius: 20)
[01:25:15 -333653.514611] AUTODETECT spr round 5 (radius: 25)
[01:29:05 -326399.544207] SPR radius for FAST iterations: 25 (autodetect)
[01:29:05 -326399.544207] Model parameter optimization (eps = 3.000000)
[01:29:14 -326394.492055] FAST spr round 1 (radius: 25)
[01:32:47 -283619.148338] FAST spr round 2 (radius: 25)
[01:35:25 -281693.599221] FAST spr round 3 (radius: 25)
[01:37:40 -281559.846776] FAST spr round 4 (radius: 25)
[01:39:38 -281547.469101] FAST spr round 5 (radius: 25)
[01:41:30 -281546.549040] FAST spr round 6 (radius: 25)
[01:43:19 -281546.548975] Model parameter optimization (eps = 1.000000)
[01:43:24 -281545.931461] SLOW spr round 1 (radius: 5)
[01:46:10 -281481.509096] SLOW spr round 2 (radius: 5)
[01:48:46 -281471.361462] SLOW spr round 3 (radius: 5)
[01:51:14 -281467.890588] SLOW spr round 4 (radius: 5)
[01:53:41 -281466.189956] SLOW spr round 5 (radius: 5)
[01:56:07 -281466.189833] SLOW spr round 6 (radius: 10)
[01:58:41 -281462.647147] SLOW spr round 7 (radius: 5)
[02:01:49 -281461.107714] SLOW spr round 8 (radius: 5)
[02:04:33 -281461.107462] SLOW spr round 9 (radius: 10)
[02:07:10 -281461.107449] SLOW spr round 10 (radius: 15)
[02:11:25 -281461.107442] SLOW spr round 11 (radius: 20)
[02:12:16] [worker #1] ML tree search #4, logLikelihood: -281459.588032
[02:17:24 -281461.107437] SLOW spr round 12 (radius: 25)
[02:25:13 -281461.107433] Model parameter optimization (eps = 0.100000)

[02:25:17] [worker #0] ML tree search #3, logLikelihood: -281461.104649

[02:25:17 -993716.865542] Initial branch length optimization
[02:25:24 -836259.172701] Model parameter optimization (eps = 10.000000)
[02:26:07 -833418.508504] AUTODETECT spr round 1 (radius: 5)
[02:28:48 -579016.239185] AUTODETECT spr round 2 (radius: 10)
[02:31:34 -436864.451121] AUTODETECT spr round 3 (radius: 15)
[02:34:19 -373649.622536] AUTODETECT spr round 4 (radius: 20)
[02:37:24 -345245.039336] AUTODETECT spr round 5 (radius: 25)
[02:41:08 -332802.449652] SPR radius for FAST iterations: 25 (autodetect)
[02:41:08 -332802.449652] Model parameter optimization (eps = 3.000000)
[02:41:27 -332729.416542] FAST spr round 1 (radius: 25)
[02:44:42 -284260.285791] FAST spr round 2 (radius: 25)
[02:47:07 -281785.534172] FAST spr round 3 (radius: 25)
[02:49:14 -281552.020321] FAST spr round 4 (radius: 25)
[02:51:10 -281519.814761] FAST spr round 5 (radius: 25)
[02:52:57 -281509.094341] FAST spr round 6 (radius: 25)
[02:54:40 -281505.304066] FAST spr round 7 (radius: 25)
[02:56:29 -281496.496562] FAST spr round 8 (radius: 25)
[02:58:10 -281496.496540] Model parameter optimization (eps = 1.000000)
[02:58:23 -281494.971948] SLOW spr round 1 (radius: 5)
[03:00:54 -281423.071966] SLOW spr round 2 (radius: 5)
[03:03:14 -281422.220448] SLOW spr round 3 (radius: 5)
[03:05:29 -281422.219915] SLOW spr round 4 (radius: 10)
[03:07:48 -281420.412856] SLOW spr round 5 (radius: 5)
[03:09:55] [worker #1] ML tree search #6, logLikelihood: -281396.153116
[03:10:41 -281418.692575] SLOW spr round 6 (radius: 5)
[03:13:13 -281418.692452] SLOW spr round 7 (radius: 10)
[03:15:41 -281418.692389] SLOW spr round 8 (radius: 15)
[03:19:41 -281418.692346] SLOW spr round 9 (radius: 20)
[03:25:16 -281418.692319] SLOW spr round 10 (radius: 25)
[03:32:39 -281418.692300] Model parameter optimization (eps = 0.100000)

[03:32:48] [worker #0] ML tree search #5, logLikelihood: -281418.556776

[03:32:48 -998401.097247] Initial branch length optimization
[03:32:53 -839747.378466] Model parameter optimization (eps = 10.000000)
[03:33:33 -836646.424710] AUTODETECT spr round 1 (radius: 5)
[03:36:03 -585366.212334] AUTODETECT spr round 2 (radius: 10)
[03:38:40 -457003.844749] AUTODETECT spr round 3 (radius: 15)
[03:41:35 -383621.834234] AUTODETECT spr round 4 (radius: 20)
[03:45:21 -343157.305660] AUTODETECT spr round 5 (radius: 25)
[03:49:33 -327736.390024] SPR radius for FAST iterations: 25 (autodetect)
[03:49:33 -327736.390024] Model parameter optimization (eps = 3.000000)
[03:49:43 -327728.112044] FAST spr round 1 (radius: 25)
[03:53:46 -283363.853587] FAST spr round 2 (radius: 25)
[03:56:31 -281682.225789] FAST spr round 3 (radius: 25)
[03:58:58 -281575.684955] FAST spr round 4 (radius: 25)
[04:01:02 -281566.627986] FAST spr round 5 (radius: 25)
[04:02:59 -281566.627878] Model parameter optimization (eps = 1.000000)
[04:03:08 -281566.132996] SLOW spr round 1 (radius: 5)
[04:06:02 -281486.185968] SLOW spr round 2 (radius: 5)
[04:08:13 -281477.680510] SLOW spr round 3 (radius: 5)
[04:10:41 -281477.296454] SLOW spr round 4 (radius: 5)
[04:12:14] [worker #1] ML tree search #8, logLikelihood: -281456.336281
[04:13:27 -281466.965837] SLOW spr round 5 (radius: 5)
[04:16:04 -281466.965714] SLOW spr round 6 (radius: 10)
[04:18:48 -281466.965713] SLOW spr round 7 (radius: 15)
[04:23:40 -281466.965712] SLOW spr round 8 (radius: 20)
[04:30:05 -281466.965712] SLOW spr round 9 (radius: 25)
[04:38:43 -281466.965712] Model parameter optimization (eps = 0.100000)

[04:38:48] [worker #0] ML tree search #7, logLikelihood: -281466.948412

[04:38:48 -994435.635944] Initial branch length optimization
[04:38:53 -833110.633596] Model parameter optimization (eps = 10.000000)
[04:39:39 -829866.836060] AUTODETECT spr round 1 (radius: 5)
[04:42:37 -575340.627442] AUTODETECT spr round 2 (radius: 10)
[04:45:42 -443809.291592] AUTODETECT spr round 3 (radius: 15)
[04:49:00 -397536.255988] AUTODETECT spr round 4 (radius: 20)
[04:52:56 -363729.558449] AUTODETECT spr round 5 (radius: 25)
[04:57:27 -337087.229138] SPR radius for FAST iterations: 25 (autodetect)
[04:57:27 -337087.229138] Model parameter optimization (eps = 3.000000)
[04:57:36 -337079.257101] FAST spr round 1 (radius: 25)
[05:01:33 -284057.395544] FAST spr round 2 (radius: 25)
[05:04:17 -281970.918346] FAST spr round 3 (radius: 25)
[05:06:46 -281694.468202] FAST spr round 4 (radius: 25)
[05:08:53 -281562.354946] FAST spr round 5 (radius: 25)
[05:10:53 -281562.354813] Model parameter optimization (eps = 1.000000)
[05:11:13 -281521.576347] SLOW spr round 1 (radius: 5)
[05:14:16 -281472.395427] SLOW spr round 2 (radius: 5)
[05:17:11 -281460.678173] SLOW spr round 3 (radius: 5)
[05:19:51 -281457.506747] SLOW spr round 4 (radius: 5)
[05:22:27 -281457.505872] SLOW spr round 5 (radius: 10)
[05:25:09 -281457.505819] SLOW spr round 6 (radius: 15)
[05:29:51] [worker #1] ML tree search #10, logLikelihood: -281487.037717
[05:30:00 -281457.505807] SLOW spr round 7 (radius: 20)
[05:36:42 -281457.505800] SLOW spr round 8 (radius: 25)
[05:46:23 -281457.505796] Model parameter optimization (eps = 0.100000)

[05:46:37] [worker #0] ML tree search #9, logLikelihood: -281456.977557

[05:46:37 -995729.613973] Initial branch length optimization
[05:46:44 -834042.801121] Model parameter optimization (eps = 10.000000)
[05:47:35 -830974.969917] AUTODETECT spr round 1 (radius: 5)
[05:50:35 -584689.699137] AUTODETECT spr round 2 (radius: 10)
[05:53:44 -458016.205171] AUTODETECT spr round 3 (radius: 15)
[05:57:09 -392348.636769] AUTODETECT spr round 4 (radius: 20)
[06:01:19 -341078.913257] AUTODETECT spr round 5 (radius: 25)
[06:05:18 -328637.848799] SPR radius for FAST iterations: 25 (autodetect)
[06:05:18 -328637.848799] Model parameter optimization (eps = 3.000000)
[06:05:27 -328629.951111] FAST spr round 1 (radius: 25)
[06:09:11 -284194.421687] FAST spr round 2 (radius: 25)
[06:12:05 -281686.154311] FAST spr round 3 (radius: 25)
[06:14:32 -281560.525285] FAST spr round 4 (radius: 25)
[06:16:35 -281557.368617] FAST spr round 5 (radius: 25)
[06:18:36 -281557.365423] Model parameter optimization (eps = 1.000000)
[06:18:41 -281556.930826] SLOW spr round 1 (radius: 5)
[06:21:40 -281477.405723] SLOW spr round 2 (radius: 5)
[06:24:27 -281470.132815] SLOW spr round 3 (radius: 5)
[06:27:06 -281470.132558] SLOW spr round 4 (radius: 10)
[06:29:52 -281460.826529] SLOW spr round 5 (radius: 5)
[06:33:09 -281458.343454] SLOW spr round 6 (radius: 5)
[06:36:02 -281457.769032] SLOW spr round 7 (radius: 5)
[06:38:43 -281457.769026] SLOW spr round 8 (radius: 10)
[06:41:25 -281457.769026] SLOW spr round 9 (radius: 15)
[06:45:34] [worker #1] ML tree search #12, logLikelihood: -281409.130092
[06:46:00 -281457.769026] SLOW spr round 10 (radius: 20)
[06:52:08 -281457.769026] SLOW spr round 11 (radius: 25)
[07:00:23 -281457.769026] Model parameter optimization (eps = 0.100000)

[07:00:28] [worker #0] ML tree search #11, logLikelihood: -281457.760647

[07:00:28 -987775.212570] Initial branch length optimization
[07:00:33 -829103.639862] Model parameter optimization (eps = 10.000000)
[07:01:11 -826175.752431] AUTODETECT spr round 1 (radius: 5)
[07:03:56 -572540.030525] AUTODETECT spr round 2 (radius: 10)
[07:06:52 -427525.053293] AUTODETECT spr round 3 (radius: 15)
[07:10:10 -347450.592528] AUTODETECT spr round 4 (radius: 20)
[07:13:40 -326412.171170] AUTODETECT spr round 5 (radius: 25)
[07:17:46 -318986.082629] SPR radius for FAST iterations: 25 (autodetect)
[07:17:46 -318986.082629] Model parameter optimization (eps = 3.000000)
[07:17:55 -318980.555540] FAST spr round 1 (radius: 25)
[07:21:37 -282988.650873] FAST spr round 2 (radius: 25)
[07:24:25 -281670.562723] FAST spr round 3 (radius: 25)
[07:26:52 -281585.189789] FAST spr round 4 (radius: 25)
[07:29:02 -281573.138999] FAST spr round 5 (radius: 25)
[07:31:02 -281567.219985] FAST spr round 6 (radius: 25)
[07:32:57 -281567.219899] Model parameter optimization (eps = 1.000000)
[07:33:14 -281542.748714] SLOW spr round 1 (radius: 5)
[07:36:09 -281459.438866] SLOW spr round 2 (radius: 5)
[07:38:53 -281448.547818] SLOW spr round 3 (radius: 5)
[07:41:29 -281447.133882] SLOW spr round 4 (radius: 5)
[07:44:03 -281447.133856] SLOW spr round 5 (radius: 10)
[07:44:41] [worker #1] ML tree search #14, logLikelihood: -281442.987689
[07:46:47 -281444.651077] SLOW spr round 6 (radius: 5)
[07:50:08 -281443.700933] SLOW spr round 7 (radius: 5)
[07:53:03 -281443.700929] SLOW spr round 8 (radius: 10)
[07:55:54 -281443.700929] SLOW spr round 9 (radius: 15)
[08:00:41 -281443.700929] SLOW spr round 10 (radius: 20)
[08:07:23 -281443.700929] SLOW spr round 11 (radius: 25)
[08:16:58 -281443.700929] Model parameter optimization (eps = 0.100000)

[08:17:18] [worker #0] ML tree search #13, logLikelihood: -281443.206819

[08:17:18 -999339.212426] Initial branch length optimization
[08:17:23 -839166.146140] Model parameter optimization (eps = 10.000000)
[08:18:04 -835978.393424] AUTODETECT spr round 1 (radius: 5)
[08:20:54 -588832.164727] AUTODETECT spr round 2 (radius: 10)
[08:23:55 -451960.828943] AUTODETECT spr round 3 (radius: 15)
[08:27:18 -393834.987625] AUTODETECT spr round 4 (radius: 20)
[08:31:24 -334426.130744] AUTODETECT spr round 5 (radius: 25)
[08:35:23 -324131.509890] SPR radius for FAST iterations: 25 (autodetect)
[08:35:23 -324131.509890] Model parameter optimization (eps = 3.000000)
[08:35:31 -324123.889078] FAST spr round 1 (radius: 25)
[08:39:02 -283034.048506] FAST spr round 2 (radius: 25)
[08:41:36 -281633.031195] FAST spr round 3 (radius: 25)
[08:43:57 -281552.584400] FAST spr round 4 (radius: 25)
[08:45:55 -281551.936790] FAST spr round 5 (radius: 25)
[08:47:50 -281551.936713] Model parameter optimization (eps = 1.000000)
[08:48:07 -281514.804465] SLOW spr round 1 (radius: 5)
[08:48:52] [worker #1] ML tree search #16, logLikelihood: -281446.314950
[08:51:07 -281433.921956] SLOW spr round 2 (radius: 5)
[08:53:52 -281422.472920] SLOW spr round 3 (radius: 5)
[08:56:29 -281415.256474] SLOW spr round 4 (radius: 5)
[08:59:04 -281413.680486] SLOW spr round 5 (radius: 5)
[09:01:39 -281413.680273] SLOW spr round 6 (radius: 10)
[09:04:21 -281413.680226] SLOW spr round 7 (radius: 15)
[09:09:15 -281413.680197] SLOW spr round 8 (radius: 20)
[09:15:34 -281413.680178] SLOW spr round 9 (radius: 25)
[09:24:11 -281413.680166] Model parameter optimization (eps = 0.100000)

[09:24:17] [worker #0] ML tree search #15, logLikelihood: -281413.617327

[09:24:17 -990673.409477] Initial branch length optimization
[09:24:25 -831975.417279] Model parameter optimization (eps = 10.000000)
[09:25:06 -829003.626705] AUTODETECT spr round 1 (radius: 5)
[09:27:57 -568012.613448] AUTODETECT spr round 2 (radius: 10)
[09:30:59 -420215.965355] AUTODETECT spr round 3 (radius: 15)
[09:34:14 -370690.038688] AUTODETECT spr round 4 (radius: 20)
[09:38:07 -342835.304389] AUTODETECT spr round 5 (radius: 25)
[09:42:39 -335474.190640] SPR radius for FAST iterations: 25 (autodetect)
[09:42:39 -335474.190640] Model parameter optimization (eps = 3.000000)
[09:43:23 -335393.919273] FAST spr round 1 (radius: 25)
[09:47:19 -284750.949457] FAST spr round 2 (radius: 25)
[09:50:02 -281674.118964] FAST spr round 3 (radius: 25)
[09:52:23 -281560.907099] FAST spr round 4 (radius: 25)
[09:54:30 -281516.551120] FAST spr round 5 (radius: 25)
[09:55:30] [worker #1] ML tree search #18, logLikelihood: -281406.232741
[09:56:30 -281516.550053] Model parameter optimization (eps = 1.000000)
[09:56:44 -281512.425391] SLOW spr round 1 (radius: 5)
[09:59:42 -281440.880287] SLOW spr round 2 (radius: 5)
[10:02:27 -281438.817576] SLOW spr round 3 (radius: 5)
[10:05:05 -281438.817245] SLOW spr round 4 (radius: 10)
[10:07:48 -281438.817058] SLOW spr round 5 (radius: 15)
[10:12:40 -281438.816934] SLOW spr round 6 (radius: 20)
[10:19:18 -281438.816850] SLOW spr round 7 (radius: 25)
[10:28:34 -281438.816794] Model parameter optimization (eps = 0.100000)

[10:28:43] [worker #0] ML tree search #17, logLikelihood: -281438.715465

[10:28:43 -1000743.825313] Initial branch length optimization
[10:28:50 -833711.598068] Model parameter optimization (eps = 10.000000)
[10:29:36 -830669.574962] AUTODETECT spr round 1 (radius: 5)
[10:32:28 -583189.706755] AUTODETECT spr round 2 (radius: 10)
[10:35:36 -445759.657612] AUTODETECT spr round 3 (radius: 15)
[10:39:06 -377893.476142] AUTODETECT spr round 4 (radius: 20)
[10:43:02 -348187.550201] AUTODETECT spr round 5 (radius: 25)
[10:47:34 -343919.565380] SPR radius for FAST iterations: 25 (autodetect)
[10:47:34 -343919.565380] Model parameter optimization (eps = 3.000000)
[10:47:57 -343825.721148] FAST spr round 1 (radius: 25)
[10:51:56 -284408.420222] FAST spr round 2 (radius: 25)
[10:54:38 -281680.766295] FAST spr round 3 (radius: 25)
[10:57:00 -281526.206522] FAST spr round 4 (radius: 25)
[10:59:07 -281513.875562] FAST spr round 5 (radius: 25)
[11:01:10 -281506.343844] FAST spr round 6 (radius: 25)
[11:03:07 -281506.343800] Model parameter optimization (eps = 1.000000)
[11:03:22 -281501.200707] SLOW spr round 1 (radius: 5)
[11:06:15 -281442.803542] SLOW spr round 2 (radius: 5)
[11:09:03 -281428.765275] SLOW spr round 3 (radius: 5)
[11:11:24] [worker #1] ML tree search #20, logLikelihood: -281437.619627
[11:11:44 -281427.359867] SLOW spr round 4 (radius: 5)
[11:14:19 -281427.358729] SLOW spr round 5 (radius: 10)
[11:17:03 -281426.261497] SLOW spr round 6 (radius: 5)
[11:20:22 -281425.901988] SLOW spr round 7 (radius: 5)
[11:23:15 -281425.901957] SLOW spr round 8 (radius: 10)
[11:26:05 -281425.901943] SLOW spr round 9 (radius: 15)
[11:30:37 -281425.901936] SLOW spr round 10 (radius: 20)
[11:37:00 -281425.901932] SLOW spr round 11 (radius: 25)
[11:45:14 -281425.901930] Model parameter optimization (eps = 0.100000)

[11:45:26] [worker #0] ML tree search #19, logLikelihood: -281425.700464


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.166016,0.392120) (0.261892,0.490220) (0.331412,0.969655) (0.240679,2.015799) 
   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: -281396.153116

AIC score: 566802.306233 / AICc score: 8610862.306233 / BIC score: 575892.552853
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=688).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 49 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/P40939/3_mltree/P40939.raxml.log

Analysis started: 06-Jul-2021 01:06:06 / finished: 06-Jul-2021 12:51:33

Elapsed time: 42326.595 seconds

Consumed energy: 4035.508 Wh (= 20 km in an electric car, or 101 km with an e-scooter!)