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 6258R CPU @ 2.70GHz, 56 cores, 187 GB RAM

RAxML-NG was called at 26-Jul-2021 00:10:21 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/2_msa/A8MTY7_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7 --seed 2 --threads 3 --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 (3 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/2_msa/A8MTY7_trimmed_msa.fasta
[00:00:00] Loaded alignment with 726 taxa and 145 sites

WARNING: Sequences tr_G1QPD3_G1QPD3_NOMLE_61853 and sp_P59990_KR121_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2I3RYQ7_A0A2I3RYQ7_PANTR_9598 and tr_A0A2R9ACU5_A0A2R9ACU5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TDL2_A0A2I3TDL2_PANTR_9598 and tr_A0A2R8ZLW8_A0A2R8ZLW8_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QL50_H2QL50_PANTR_9598 and tr_A0A2R9AR64_A0A2R9AR64_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2RGZ0_H2RGZ0_PANTR_9598 and tr_A0A2R8ZL57_A0A2R8ZL57_PANPA_9597 are exactly identical!
WARNING: Sequences tr_I3MUE7_I3MUE7_ICTTR_43179 and tr_I3N3Q9_I3N3Q9_ICTTR_43179 are exactly identical!
WARNING: Sequences tr_A0A140TA64_A0A140TA64_HUMAN_9606 and sp_Q9BYR0_KRA47_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_F7GZ53_F7GZ53_MACMU_9544 and tr_A0A096P5J5_A0A096P5J5_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_A5PJJ0_A5PJJ0_BOVIN_9913 and tr_Q0VC31_Q0VC31_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_A0A2I3MP20_A0A2I3MP20_PAPAN_9555 and tr_A0A2K6DXU4_A0A2K6DXU4_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A3Q0CKQ6_A0A3Q0CKQ6_MESAU_10036 and tr_A0A3Q0CR37_A0A3Q0CR37_MESAU_10036 are exactly identical!
WARNING: Duplicate sequences found: 11

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.reduced.phy

Alignment comprises 1 partitions and 145 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 145 / 145
Gaps: 21.08 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.rba

Parallelization scheme autoconfig: 3 worker(s) x 1 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 726 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 145 / 11600
[00:00:00] Data distribution: max. searches per worker: 7

Starting ML tree search with 20 distinct starting trees

[00:00:00 -111634.766685] Initial branch length optimization
[00:00:03 -98467.415551] Model parameter optimization (eps = 10.000000)
[00:00:43 -98014.764226] AUTODETECT spr round 1 (radius: 5)
[00:02:54 -64925.317547] AUTODETECT spr round 2 (radius: 10)
[00:05:20 -49858.186644] AUTODETECT spr round 3 (radius: 15)
[00:08:13 -43280.366203] AUTODETECT spr round 4 (radius: 20)
[00:11:29 -41959.550333] AUTODETECT spr round 5 (radius: 25)
[00:15:34 -41740.477832] SPR radius for FAST iterations: 25 (autodetect)
[00:15:34 -41740.477832] Model parameter optimization (eps = 3.000000)
[00:16:30 -41091.851131] FAST spr round 1 (radius: 25)
[00:19:20 -36743.494867] FAST spr round 2 (radius: 25)
[00:21:28 -36551.444051] FAST spr round 3 (radius: 25)
[00:23:25 -36529.120322] FAST spr round 4 (radius: 25)
[00:25:14 -36519.192014] FAST spr round 5 (radius: 25)
[00:26:54 -36516.724811] FAST spr round 6 (radius: 25)
[00:28:32 -36513.411628] FAST spr round 7 (radius: 25)
[00:30:08 -36513.411495] Model parameter optimization (eps = 1.000000)
[00:30:25 -36510.907293] SLOW spr round 1 (radius: 5)
[00:32:52 -36502.913307] SLOW spr round 2 (radius: 5)
[00:35:13 -36500.044976] SLOW spr round 3 (radius: 5)
[00:37:25 -36500.044812] SLOW spr round 4 (radius: 10)
[00:39:40 -36499.904703] SLOW spr round 5 (radius: 5)
[00:42:34 -36499.902949] SLOW spr round 6 (radius: 10)
[00:45:07 -36499.869863] SLOW spr round 7 (radius: 15)
[00:48:28 -36497.564711] SLOW spr round 8 (radius: 5)
[00:51:36 -36495.139661] SLOW spr round 9 (radius: 5)
[00:54:15 -36494.253342] SLOW spr round 10 (radius: 5)
[00:56:38 -36494.171283] SLOW spr round 11 (radius: 10)
[00:58:55 -36493.833866] SLOW spr round 12 (radius: 5)
[01:01:53 -36493.438232] SLOW spr round 13 (radius: 5)
[01:04:24 -36493.438133] SLOW spr round 14 (radius: 10)
[01:06:45 -36492.556889] SLOW spr round 15 (radius: 5)
[01:09:38 -36487.647248] SLOW spr round 16 (radius: 5)
[01:12:08 -36487.637670] SLOW spr round 17 (radius: 10)
[01:14:27 -36487.637669] SLOW spr round 18 (radius: 15)
[01:18:00 -36487.637669] SLOW spr round 19 (radius: 20)
[01:22:22 -36486.809404] SLOW spr round 20 (radius: 5)
[01:25:26 -36486.809390] SLOW spr round 21 (radius: 10)
[01:26:32] [worker #1] ML tree search #2, logLikelihood: -36490.350505
[01:28:14 -36486.809390] SLOW spr round 22 (radius: 15)
[01:31:33 -36486.809390] SLOW spr round 23 (radius: 20)
[01:35:58 -36486.809390] SLOW spr round 24 (radius: 25)
[01:41:18 -36486.809390] Model parameter optimization (eps = 0.100000)

[01:41:33] [worker #0] ML tree search #1, logLikelihood: -36486.556947

[01:41:33 -111846.487234] Initial branch length optimization
[01:41:36 -98333.774471] Model parameter optimization (eps = 10.000000)
[01:42:10 -97869.318293] AUTODETECT spr round 1 (radius: 5)
[01:44:20 -65426.357069] AUTODETECT spr round 2 (radius: 10)
[01:46:43 -50261.231868] AUTODETECT spr round 3 (radius: 15)
[01:49:33 -42758.305924] AUTODETECT spr round 4 (radius: 20)
[01:52:52 -41142.348597] AUTODETECT spr round 5 (radius: 25)
[01:56:38 -40997.510085] SPR radius for FAST iterations: 25 (autodetect)
[01:56:38 -40997.510085] Model parameter optimization (eps = 3.000000)
[01:57:17 -40370.016143] FAST spr round 1 (radius: 25)
[02:00:06 -36747.589636] FAST spr round 2 (radius: 25)
[02:01:48] [worker #2] ML tree search #3, logLikelihood: -36518.768062
[02:02:12 -36554.088437] FAST spr round 3 (radius: 25)
[02:04:05 -36527.121579] FAST spr round 4 (radius: 25)
[02:05:50 -36518.111686] FAST spr round 5 (radius: 25)
[02:07:28 -36518.111360] Model parameter optimization (eps = 1.000000)
[02:07:45 -36516.445137] SLOW spr round 1 (radius: 5)
[02:10:11 -36505.025304] SLOW spr round 2 (radius: 5)
[02:12:29 -36505.023371] SLOW spr round 3 (radius: 10)
[02:14:45 -36502.552618] SLOW spr round 4 (radius: 5)
[02:17:37 -36502.552168] SLOW spr round 5 (radius: 10)
[02:20:09 -36502.551791] SLOW spr round 6 (radius: 15)
[02:23:36 -36501.387937] SLOW spr round 7 (radius: 5)
[02:26:36 -36501.387003] SLOW spr round 8 (radius: 10)
[02:29:19 -36501.386685] SLOW spr round 9 (radius: 15)
[02:32:44 -36501.386415] SLOW spr round 10 (radius: 20)
[02:37:18 -36501.386139] SLOW spr round 11 (radius: 25)
[02:42:46 -36498.180206] SLOW spr round 12 (radius: 5)
[02:45:50 -36498.179997] SLOW spr round 13 (radius: 10)
[02:48:43 -36498.179997] SLOW spr round 14 (radius: 15)
[02:52:08 -36498.179997] SLOW spr round 15 (radius: 20)
[02:56:42 -36498.179997] SLOW spr round 16 (radius: 25)
[03:02:07 -36498.179997] Model parameter optimization (eps = 0.100000)

[03:02:14] [worker #0] ML tree search #4, logLikelihood: -36498.168670

[03:02:14 -112618.406549] Initial branch length optimization
[03:02:17 -98829.404996] Model parameter optimization (eps = 10.000000)
[03:02:58 -98408.731373] AUTODETECT spr round 1 (radius: 5)
[03:05:07 -66973.680925] AUTODETECT spr round 2 (radius: 10)
[03:07:36 -51644.449963] AUTODETECT spr round 3 (radius: 15)
[03:08:21] [worker #2] ML tree search #6, logLikelihood: -36529.009097
[03:10:01] [worker #1] ML tree search #5, logLikelihood: -36495.250748
[03:10:23 -46351.303958] AUTODETECT spr round 4 (radius: 20)
[03:14:05 -43182.006723] AUTODETECT spr round 5 (radius: 25)
[03:18:17 -43027.143976] SPR radius for FAST iterations: 25 (autodetect)
[03:18:17 -43027.143976] Model parameter optimization (eps = 3.000000)
[03:19:09 -42434.954751] FAST spr round 1 (radius: 25)
[03:22:04 -36825.207007] FAST spr round 2 (radius: 25)
[03:24:11 -36548.056545] FAST spr round 3 (radius: 25)
[03:26:04 -36507.899079] FAST spr round 4 (radius: 25)
[03:27:48 -36506.780944] FAST spr round 5 (radius: 25)
[03:29:27 -36506.780921] Model parameter optimization (eps = 1.000000)
[03:29:49 -36500.832021] SLOW spr round 1 (radius: 5)
[03:32:20 -36492.401619] SLOW spr round 2 (radius: 5)
[03:34:39 -36492.399462] SLOW spr round 3 (radius: 10)
[03:36:55 -36492.165592] SLOW spr round 4 (radius: 5)
[03:39:48 -36492.165557] SLOW spr round 5 (radius: 10)
[03:42:22 -36492.165530] SLOW spr round 6 (radius: 15)
[03:45:46 -36489.972236] SLOW spr round 7 (radius: 5)
[03:48:56 -36485.586683] SLOW spr round 8 (radius: 5)
[03:51:35 -36485.583864] SLOW spr round 9 (radius: 10)
[03:53:59 -36484.425812] SLOW spr round 10 (radius: 5)
[03:56:50 -36484.425507] SLOW spr round 11 (radius: 10)
[03:59:23 -36484.407328] SLOW spr round 12 (radius: 15)
[04:02:47 -36484.364429] SLOW spr round 13 (radius: 20)
[04:07:31 -36484.364310] SLOW spr round 14 (radius: 25)
[04:13:23 -36484.364189] Model parameter optimization (eps = 0.100000)

[04:13:32] [worker #0] ML tree search #7, logLikelihood: -36484.349386

[04:13:32 -112095.406608] Initial branch length optimization
[04:13:35 -98809.245232] Model parameter optimization (eps = 10.000000)
[04:14:07 -98345.706628] AUTODETECT spr round 1 (radius: 5)
[04:16:14 -65492.613842] AUTODETECT spr round 2 (radius: 10)
[04:18:38 -50649.387158] AUTODETECT spr round 3 (radius: 15)
[04:18:54] [worker #1] ML tree search #8, logLikelihood: -36541.722739
[04:21:29 -44339.482451] AUTODETECT spr round 4 (radius: 20)
[04:25:00 -42347.536659] AUTODETECT spr round 5 (radius: 25)
[04:29:06 -42046.003392] SPR radius for FAST iterations: 25 (autodetect)
[04:29:06 -42046.003392] Model parameter optimization (eps = 3.000000)
[04:29:42 -41406.603237] FAST spr round 1 (radius: 25)
[04:32:36 -36714.370649] FAST spr round 2 (radius: 25)
[04:34:46 -36551.059349] FAST spr round 3 (radius: 25)
[04:36:40 -36535.935469] FAST spr round 4 (radius: 25)
[04:38:25 -36531.428690] FAST spr round 5 (radius: 25)
[04:40:03 -36531.425889] Model parameter optimization (eps = 1.000000)
[04:40:14 -36530.755687] SLOW spr round 1 (radius: 5)
[04:42:44 -36518.074021] SLOW spr round 2 (radius: 5)
[04:45:06 -36516.210935] SLOW spr round 3 (radius: 5)
[04:47:18 -36516.210901] SLOW spr round 4 (radius: 10)
[04:49:33 -36514.949728] SLOW spr round 5 (radius: 5)
[04:52:28 -36512.509503] SLOW spr round 6 (radius: 5)
[04:55:03 -36507.844264] SLOW spr round 7 (radius: 5)
[04:57:21 -36507.843440] SLOW spr round 8 (radius: 10)
[04:59:38 -36506.132358] SLOW spr round 9 (radius: 5)
[05:01:45] [worker #2] ML tree search #9, logLikelihood: -36496.589320
[05:02:28 -36506.132287] SLOW spr round 10 (radius: 10)
[05:05:03 -36506.132284] SLOW spr round 11 (radius: 15)
[05:08:38 -36505.405739] SLOW spr round 12 (radius: 5)
[05:11:39 -36505.405738] SLOW spr round 13 (radius: 10)
[05:14:27 -36505.405738] SLOW spr round 14 (radius: 15)
[05:17:58 -36505.360237] SLOW spr round 15 (radius: 20)
[05:22:59 -36503.027138] SLOW spr round 16 (radius: 5)
[05:26:03 -36503.027086] SLOW spr round 17 (radius: 10)
[05:28:57 -36503.027086] SLOW spr round 18 (radius: 15)
[05:32:29 -36503.027086] SLOW spr round 19 (radius: 20)
[05:33:11] [worker #1] ML tree search #11, logLikelihood: -36549.466202
[05:37:29 -36502.734714] SLOW spr round 20 (radius: 5)
[05:40:35 -36502.725057] SLOW spr round 21 (radius: 10)
[05:43:29 -36502.725057] SLOW spr round 22 (radius: 15)
[05:47:01 -36502.725057] SLOW spr round 23 (radius: 20)
[05:52:01 -36502.725057] SLOW spr round 24 (radius: 25)
[05:58:08 -36502.725057] Model parameter optimization (eps = 0.100000)

[05:58:15] [worker #0] ML tree search #10, logLikelihood: -36502.672017

[05:58:15 -112291.169050] Initial branch length optimization
[05:58:18 -98719.822442] Model parameter optimization (eps = 10.000000)
[05:59:00 -98206.963995] AUTODETECT spr round 1 (radius: 5)
[06:01:11 -65531.491855] AUTODETECT spr round 2 (radius: 10)
[06:03:34 -48438.250118] AUTODETECT spr round 3 (radius: 15)
[06:06:09 -44172.186738] AUTODETECT spr round 4 (radius: 20)
[06:09:19 -42882.586619] AUTODETECT spr round 5 (radius: 25)
[06:13:06 -42048.928858] SPR radius for FAST iterations: 25 (autodetect)
[06:13:06 -42048.928858] Model parameter optimization (eps = 3.000000)
[06:14:00 -41361.162120] FAST spr round 1 (radius: 25)
[06:16:49 -36852.869962] FAST spr round 2 (radius: 25)
[06:18:55 -36523.690674] FAST spr round 3 (radius: 25)
[06:20:47 -36508.979427] FAST spr round 4 (radius: 25)
[06:22:27 -36508.978467] Model parameter optimization (eps = 1.000000)
[06:22:42 -36508.012078] SLOW spr round 1 (radius: 5)
[06:25:16 -36494.763934] SLOW spr round 2 (radius: 5)
[06:27:38 -36493.300137] SLOW spr round 3 (radius: 5)
[06:29:56 -36492.541153] SLOW spr round 4 (radius: 5)
[06:32:08 -36492.241105] SLOW spr round 5 (radius: 5)
[06:34:18 -36492.239995] SLOW spr round 6 (radius: 10)
[06:36:34 -36487.897870] SLOW spr round 7 (radius: 5)
[06:38:37] [worker #2] ML tree search #12, logLikelihood: -36488.889569
[06:39:31 -36484.134094] SLOW spr round 8 (radius: 5)
[06:41:59 -36484.133845] SLOW spr round 9 (radius: 10)
[06:44:19 -36483.709601] SLOW spr round 10 (radius: 5)
[06:47:09 -36483.708921] SLOW spr round 11 (radius: 10)
[06:49:43 -36483.465020] SLOW spr round 12 (radius: 5)
[06:52:34 -36482.519941] SLOW spr round 13 (radius: 5)
[06:55:06 -36481.622206] SLOW spr round 14 (radius: 5)
[06:57:22 -36481.622020] SLOW spr round 15 (radius: 10)
[06:59:39 -36479.881300] SLOW spr round 16 (radius: 5)
[07:02:31 -36479.416024] SLOW spr round 17 (radius: 5)
[07:04:59 -36479.416018] SLOW spr round 18 (radius: 10)
[07:07:18 -36479.416018] SLOW spr round 19 (radius: 15)
[07:10:58 -36475.482385] SLOW spr round 20 (radius: 5)
[07:13:58 -36475.482316] SLOW spr round 21 (radius: 10)
[07:16:42 -36475.482315] SLOW spr round 22 (radius: 15)
[07:19:03] [worker #1] ML tree search #14, logLikelihood: -36485.635621
[07:20:11 -36475.079155] SLOW spr round 23 (radius: 5)
[07:23:12 -36474.954976] SLOW spr round 24 (radius: 5)
[07:25:47 -36474.954936] SLOW spr round 25 (radius: 10)
[07:28:08 -36474.954936] SLOW spr round 26 (radius: 15)
[07:31:43 -36474.954936] SLOW spr round 27 (radius: 20)
[07:36:36 -36474.954936] SLOW spr round 28 (radius: 25)
[07:42:45 -36474.954936] Model parameter optimization (eps = 0.100000)

[07:42:54] [worker #0] ML tree search #13, logLikelihood: -36474.931573

[07:42:54 -112335.354941] Initial branch length optimization
[07:42:57 -98930.081247] Model parameter optimization (eps = 10.000000)
[07:43:35 -98465.158660] AUTODETECT spr round 1 (radius: 5)
[07:45:45 -67395.348112] AUTODETECT spr round 2 (radius: 10)
[07:48:04 -50954.291641] AUTODETECT spr round 3 (radius: 15)
[07:50:53 -44454.594611] AUTODETECT spr round 4 (radius: 20)
[07:54:04 -42621.973523] AUTODETECT spr round 5 (radius: 25)
[07:57:32 -42179.223117] SPR radius for FAST iterations: 25 (autodetect)
[07:57:32 -42179.223117] Model parameter optimization (eps = 3.000000)
[07:58:26 -41474.155383] FAST spr round 1 (radius: 25)
[07:58:35] [worker #2] ML tree search #15, logLikelihood: -36501.226473
[08:01:21 -36792.229078] FAST spr round 2 (radius: 25)
[08:03:31 -36585.770017] FAST spr round 3 (radius: 25)
[08:05:22 -36569.287642] FAST spr round 4 (radius: 25)
[08:07:03 -36567.458973] FAST spr round 5 (radius: 25)
[08:08:42 -36567.157909] FAST spr round 6 (radius: 25)
[08:10:18 -36567.157186] Model parameter optimization (eps = 1.000000)
[08:10:44 -36564.582992] SLOW spr round 1 (radius: 5)
[08:13:09 -36549.917715] SLOW spr round 2 (radius: 5)
[08:15:28 -36549.292374] SLOW spr round 3 (radius: 5)
[08:17:43 -36542.628720] SLOW spr round 4 (radius: 5)
[08:19:54 -36542.628518] SLOW spr round 5 (radius: 10)
[08:22:07 -36541.967097] SLOW spr round 6 (radius: 5)
[08:25:08 -36535.978061] SLOW spr round 7 (radius: 5)
[08:27:38 -36535.977769] SLOW spr round 8 (radius: 10)
[08:29:57 -36535.399456] SLOW spr round 9 (radius: 5)
[08:32:47 -36535.377110] SLOW spr round 10 (radius: 10)
[08:35:18 -36535.205794] SLOW spr round 11 (radius: 5)
[08:38:09 -36534.589742] SLOW spr round 12 (radius: 5)
[08:39:26] [worker #1] ML tree search #17, logLikelihood: -36519.603691
[08:40:38 -36534.589674] SLOW spr round 13 (radius: 10)
[08:42:57 -36534.589657] SLOW spr round 14 (radius: 15)
[08:46:34 -36533.372645] SLOW spr round 15 (radius: 5)
[08:49:40 -36527.477503] SLOW spr round 16 (radius: 5)
[08:52:19 -36522.459722] SLOW spr round 17 (radius: 5)
[08:54:46 -36521.005674] SLOW spr round 18 (radius: 5)
[08:57:00 -36521.005519] SLOW spr round 19 (radius: 10)
[08:59:14 -36521.005518] SLOW spr round 20 (radius: 15)
[09:03:00 -36520.837917] SLOW spr round 21 (radius: 5)
[09:06:01 -36520.837896] SLOW spr round 22 (radius: 10)
[09:08:46 -36520.837896] SLOW spr round 23 (radius: 15)
[09:12:15 -36520.837896] SLOW spr round 24 (radius: 20)
[09:16:58 -36520.837896] SLOW spr round 25 (radius: 25)
[09:22:37 -36518.596032] SLOW spr round 26 (radius: 5)
[09:25:45 -36517.983263] SLOW spr round 27 (radius: 5)
[09:28:24 -36517.983235] SLOW spr round 28 (radius: 10)
[09:30:47 -36517.983235] SLOW spr round 29 (radius: 15)
[09:34:22 -36517.913391] SLOW spr round 30 (radius: 20)
[09:38:58 -36517.913374] SLOW spr round 31 (radius: 25)
[09:40:58] [worker #2] ML tree search #18, logLikelihood: -36507.421095
[09:44:32 -36517.913374] Model parameter optimization (eps = 0.100000)

[09:44:49] [worker #0] ML tree search #16, logLikelihood: -36517.815096

[09:44:50 -111466.942053] Initial branch length optimization
[09:44:53 -98017.759985] Model parameter optimization (eps = 10.000000)
[09:45:29 -97554.603446] AUTODETECT spr round 1 (radius: 5)
[09:47:38 -67096.723773] AUTODETECT spr round 2 (radius: 10)
[09:50:00 -51612.589463] AUTODETECT spr round 3 (radius: 15)
[09:52:47 -45507.263935] AUTODETECT spr round 4 (radius: 20)
[09:56:13 -43240.178270] AUTODETECT spr round 5 (radius: 25)
[09:59:42 -42222.439559] SPR radius for FAST iterations: 25 (autodetect)
[09:59:42 -42222.439559] Model parameter optimization (eps = 3.000000)
[10:00:26 -41576.287826] FAST spr round 1 (radius: 25)
[10:03:16 -37112.483760] FAST spr round 2 (radius: 25)
[10:05:26 -36623.353060] FAST spr round 3 (radius: 25)
[10:07:19 -36590.748462] FAST spr round 4 (radius: 25)
[10:08:59 -36586.572942] FAST spr round 5 (radius: 25)
[10:10:37 -36586.571614] Model parameter optimization (eps = 1.000000)
[10:10:46 -36586.288604] SLOW spr round 1 (radius: 5)
[10:13:14 -36570.009807] SLOW spr round 2 (radius: 5)
[10:15:36 -36564.356355] SLOW spr round 3 (radius: 5)
[10:17:51 -36562.888521] SLOW spr round 4 (radius: 5)
[10:20:00 -36562.887541] SLOW spr round 5 (radius: 10)
[10:22:14 -36560.612794] SLOW spr round 6 (radius: 5)
[10:25:12 -36558.689833] SLOW spr round 7 (radius: 5)
[10:27:47 -36557.462972] SLOW spr round 8 (radius: 5)
[10:30:05 -36557.462732] SLOW spr round 9 (radius: 10)
[10:32:17 -36556.561455] SLOW spr round 10 (radius: 5)
[10:35:08 -36556.561433] SLOW spr round 11 (radius: 10)
[10:37:38 -36556.153839] SLOW spr round 12 (radius: 5)
[10:40:26 -36556.152027] SLOW spr round 13 (radius: 10)
[10:42:52 -36556.074966] SLOW spr round 14 (radius: 15)
[10:45:45] [worker #1] ML tree search #20, logLikelihood: -36517.497342
[10:46:15 -36554.405928] SLOW spr round 15 (radius: 5)
[10:49:15 -36554.405813] SLOW spr round 16 (radius: 10)
[10:51:54 -36554.405812] SLOW spr round 17 (radius: 15)
[10:55:12 -36554.405812] SLOW spr round 18 (radius: 20)
[10:59:28 -36554.405812] SLOW spr round 19 (radius: 25)
[11:04:45 -36554.405812] Model parameter optimization (eps = 0.100000)

[11:04:54] [worker #0] ML tree search #19, logLikelihood: -36554.304444


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.522285,0.728683) (0.006895,1.672551) (0.217562,1.141906) (0.253258,1.419311) 
   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: -36474.931573

AIC score: 75859.863145 / AICc score: 4312819.863145 / BIC score: 80191.010740
Free parameters (model + branch lengths): 1455

WARNING: Number of free parameters (K=1455) is larger than alignment size (n=145).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 144 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A8MTY7/3_mltree/A8MTY7.raxml.log

Analysis started: 26-Jul-2021 00:10:21 / finished: 26-Jul-2021 11:15:15

Elapsed time: 39894.388 seconds

Consumed energy: 1494.974 Wh (= 7 km in an electric car, or 37 km with an e-scooter!)