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 00:38:31 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/2_msa/A6NI87_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87 --seed 2 --threads 2 --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 (2 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/2_msa/A6NI87_trimmed_msa.fasta
[00:00:00] Loaded alignment with 175 taxa and 119 sites

WARNING: Sequences sp_Q9D1C2_CBY1_MOUSE_10090 and sp_Q8K4I6_CBY1_RAT_10116 are exactly identical!
WARNING: Sequences tr_M3YNZ5_M3YNZ5_MUSPF_9669 and tr_G1LVX9_G1LVX9_AILME_9646 are exactly identical!
WARNING: Sequences tr_A0A2I2ZH35_A0A2I2ZH35_GORGO_9595 and tr_K7CQ99_K7CQ99_PANTR_9598 are exactly identical!
WARNING: Sequences tr_A0A2I2ZH35_A0A2I2ZH35_GORGO_9595 and sp_Q9Y3M2_CBY1_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2I2ZH35_A0A2I2ZH35_GORGO_9595 and tr_A0A2R9AIB6_A0A2R9AIB6_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G3R8L4_G3R8L4_GORGO_9595 and tr_A0A2I3S3H2_A0A2I3S3H2_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3R8L4_G3R8L4_GORGO_9595 and tr_A0A2R9CQH5_A0A2R9CQH5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3S558_A0A2I3S558_PANTR_9598 and tr_A0A2R9BJ08_A0A2R9BJ08_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6W811_F6W811_HORSE_9796 and tr_A0A2Y9T251_A0A2Y9T251_PHYCD_9755 are exactly identical!
WARNING: Sequences tr_M4ADI7_M4ADI7_XIPMA_8083 and tr_A0A087XKG7_A0A087XKG7_POEFO_48698 are exactly identical!
WARNING: Sequences tr_A0A1D5RHE2_A0A1D5RHE2_MACMU_9544 and tr_A0A096NK27_A0A096NK27_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_A0A1D5RHE2_A0A1D5RHE2_MACMU_9544 and tr_A0A0D9R2J8_A0A0D9R2J8_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A1D5RHE2_A0A1D5RHE2_MACMU_9544 and tr_A0A2K6B2M5_A0A2K6B2M5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A1D5RHE2_A0A1D5RHE2_MACMU_9544 and tr_A0A2K5XN65_A0A2K5XN65_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G7MUI8_G7MUI8_MACMU_9544 and tr_G8F5F6_G8F5F6_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G7MUI8_G7MUI8_MACMU_9544 and tr_A0A096MZH5_A0A096MZH5_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_H0ZJD3_H0ZJD3_TAEGU_59729 and tr_A0A218UYW0_A0A218UYW0_9PASE_299123 are exactly identical!
WARNING: Sequences sp_Q8MJK1_CBY1_BOVIN_9913 and tr_A0A384AP57_A0A384AP57_BALAS_310752 are exactly identical!
WARNING: Sequences tr_A0A151NHM8_A0A151NHM8_ALLMI_8496 and tr_A0A1U7S283_A0A1U7S283_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_R7VMK6_R7VMK6_COLLI_8932 and tr_A0A1V4J9H4_A0A1V4J9H4_PATFA_372326 are exactly identical!
WARNING: Sequences tr_A0A2U4C0H2_A0A2U4C0H2_TURTR_9739 and tr_A0A2U4C0K0_A0A2U4C0K0_TURTR_9739 are exactly identical!
WARNING: Sequences tr_A0A2U4C0H2_A0A2U4C0H2_TURTR_9739 and tr_A0A2U4C0L8_A0A2U4C0L8_TURTR_9739 are exactly identical!
WARNING: Sequences tr_A0A2U4C0H2_A0A2U4C0H2_TURTR_9739 and tr_A0A2U4C0S2_A0A2U4C0S2_TURTR_9739 are exactly identical!
WARNING: Sequences tr_A0A2U4C0H2_A0A2U4C0H2_TURTR_9739 and tr_A0A2Y9Q5B8_A0A2Y9Q5B8_DELLE_9749 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/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.reduced.phy

Alignment comprises 1 partitions and 119 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 119 / 119
Gaps: 3.41 %
Invariant sites: 2.52 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.rba

Parallelization scheme autoconfig: 2 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 175 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 119 / 9520
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -28313.838621] Initial branch length optimization
[00:00:00 -22061.056535] Model parameter optimization (eps = 10.000000)
[00:00:11 -21857.036426] AUTODETECT spr round 1 (radius: 5)
[00:00:20 -14358.810870] AUTODETECT spr round 2 (radius: 10)
[00:00:32 -11411.406966] AUTODETECT spr round 3 (radius: 15)
[00:00:52 -10651.302420] AUTODETECT spr round 4 (radius: 20)
[00:01:07 -10254.476385] AUTODETECT spr round 5 (radius: 25)
[00:01:22 -10249.932995] SPR radius for FAST iterations: 25 (autodetect)
[00:01:22 -10249.932995] Model parameter optimization (eps = 3.000000)
[00:01:29 -10234.906702] FAST spr round 1 (radius: 25)
[00:01:42 -9636.882403] FAST spr round 2 (radius: 25)
[00:01:52 -9607.112138] FAST spr round 3 (radius: 25)
[00:02:00 -9606.378406] FAST spr round 4 (radius: 25)
[00:02:09 -9605.469867] FAST spr round 5 (radius: 25)
[00:02:16 -9605.469803] Model parameter optimization (eps = 1.000000)
[00:02:25 -9603.036916] SLOW spr round 1 (radius: 5)
[00:02:42 -9599.340880] SLOW spr round 2 (radius: 5)
[00:02:58 -9598.625777] SLOW spr round 3 (radius: 5)
[00:03:14 -9598.625725] SLOW spr round 4 (radius: 10)
[00:03:29 -9595.042683] SLOW spr round 5 (radius: 5)
[00:03:50 -9593.622607] SLOW spr round 6 (radius: 5)
[00:04:07 -9593.621977] SLOW spr round 7 (radius: 10)
[00:04:22 -9593.210668] SLOW spr round 8 (radius: 5)
[00:04:42 -9592.656448] SLOW spr round 9 (radius: 5)
[00:04:59 -9592.656432] SLOW spr round 10 (radius: 10)
[00:05:14 -9592.656431] SLOW spr round 11 (radius: 15)
[00:05:25] [worker #1] ML tree search #2, logLikelihood: -9588.952053
[00:05:34 -9592.656431] SLOW spr round 12 (radius: 20)
[00:06:00 -9592.656431] SLOW spr round 13 (radius: 25)
[00:06:26 -9592.656431] Model parameter optimization (eps = 0.100000)

[00:06:32] [worker #0] ML tree search #1, logLikelihood: -9591.530295

[00:06:32 -27309.269544] Initial branch length optimization
[00:06:32 -21327.803736] Model parameter optimization (eps = 10.000000)
[00:06:45 -21134.299285] AUTODETECT spr round 1 (radius: 5)
[00:06:54 -14663.963928] AUTODETECT spr round 2 (radius: 10)
[00:07:07 -11128.818273] AUTODETECT spr round 3 (radius: 15)
[00:07:22 -10353.670186] AUTODETECT spr round 4 (radius: 20)
[00:07:37 -10338.178523] AUTODETECT spr round 5 (radius: 25)
[00:07:53 -10326.578688] SPR radius for FAST iterations: 25 (autodetect)
[00:07:53 -10326.578688] Model parameter optimization (eps = 3.000000)
[00:08:01 -10307.909224] FAST spr round 1 (radius: 25)
[00:08:15 -9629.828818] FAST spr round 2 (radius: 25)
[00:08:25 -9603.827025] FAST spr round 3 (radius: 25)
[00:08:33 -9603.826324] Model parameter optimization (eps = 1.000000)
[00:08:40 -9602.797795] SLOW spr round 1 (radius: 5)
[00:08:57 -9600.341218] SLOW spr round 2 (radius: 5)
[00:09:14 -9600.145291] SLOW spr round 3 (radius: 5)
[00:09:30 -9600.145201] SLOW spr round 4 (radius: 10)
[00:09:37] [worker #1] ML tree search #4, logLikelihood: -9594.449740
[00:09:45 -9599.039846] SLOW spr round 5 (radius: 5)
[00:10:06 -9596.050650] SLOW spr round 6 (radius: 5)
[00:10:24 -9596.050223] SLOW spr round 7 (radius: 10)
[00:10:40 -9592.802606] SLOW spr round 8 (radius: 5)
[00:11:01 -9592.389324] SLOW spr round 9 (radius: 5)
[00:11:19 -9592.389163] SLOW spr round 10 (radius: 10)
[00:11:34 -9592.389101] SLOW spr round 11 (radius: 15)
[00:11:55 -9592.389041] SLOW spr round 12 (radius: 20)
[00:12:19 -9592.388982] SLOW spr round 13 (radius: 25)
[00:12:39 -9592.388922] Model parameter optimization (eps = 0.100000)

[00:12:48] [worker #0] ML tree search #3, logLikelihood: -9592.034653

[00:12:48 -28060.258332] Initial branch length optimization
[00:12:48 -21768.168042] Model parameter optimization (eps = 10.000000)
[00:12:59 -21567.574794] AUTODETECT spr round 1 (radius: 5)
[00:13:08 -15233.940497] AUTODETECT spr round 2 (radius: 10)
[00:13:21 -12103.247290] AUTODETECT spr round 3 (radius: 15)
[00:13:37 -10667.942595] AUTODETECT spr round 4 (radius: 20)
[00:13:57 -10372.736912] AUTODETECT spr round 5 (radius: 25)
[00:14:13 -10372.718795] SPR radius for FAST iterations: 20 (autodetect)
[00:14:13 -10372.718795] Model parameter optimization (eps = 3.000000)
[00:14:19 -10357.759521] FAST spr round 1 (radius: 20)
[00:14:29 -9638.377624] FAST spr round 2 (radius: 20)
[00:14:39 -9609.966500] FAST spr round 3 (radius: 20)
[00:14:48 -9598.224334] FAST spr round 4 (radius: 20)
[00:14:56 -9598.224193] Model parameter optimization (eps = 1.000000)
[00:15:05] [worker #1] ML tree search #6, logLikelihood: -9589.503735
[00:15:06 -9595.655690] SLOW spr round 1 (radius: 5)
[00:15:23 -9593.606017] SLOW spr round 2 (radius: 5)
[00:15:38 -9593.605871] SLOW spr round 3 (radius: 10)
[00:15:53 -9592.485246] SLOW spr round 4 (radius: 5)
[00:16:14 -9592.485198] SLOW spr round 5 (radius: 10)
[00:16:32 -9592.485156] SLOW spr round 6 (radius: 15)
[00:16:53 -9592.485113] SLOW spr round 7 (radius: 20)
[00:17:22 -9592.485069] SLOW spr round 8 (radius: 25)
[00:17:46 -9592.485026] Model parameter optimization (eps = 0.100000)

[00:17:47] [worker #0] ML tree search #5, logLikelihood: -9592.479979

[00:17:47 -28253.027833] Initial branch length optimization
[00:17:48 -21840.156309] Model parameter optimization (eps = 10.000000)
[00:18:03 -21664.525058] AUTODETECT spr round 1 (radius: 5)
[00:18:12 -14820.126608] AUTODETECT spr round 2 (radius: 10)
[00:18:25 -11692.457809] AUTODETECT spr round 3 (radius: 15)
[00:18:40 -10467.995384] AUTODETECT spr round 4 (radius: 20)
[00:18:58 -10380.975234] AUTODETECT spr round 5 (radius: 25)
[00:19:13 -10376.474369] SPR radius for FAST iterations: 25 (autodetect)
[00:19:13 -10376.474369] Model parameter optimization (eps = 3.000000)
[00:19:24 -10353.192328] FAST spr round 1 (radius: 25)
[00:19:36 -9613.818552] FAST spr round 2 (radius: 25)
[00:19:46 -9603.730685] FAST spr round 3 (radius: 25)
[00:19:54 -9602.567859] FAST spr round 4 (radius: 25)
[00:20:02 -9602.567812] Model parameter optimization (eps = 1.000000)
[00:20:06] [worker #1] ML tree search #8, logLikelihood: -9589.582448
[00:20:20 -9598.934225] SLOW spr round 1 (radius: 5)
[00:20:37 -9595.334245] SLOW spr round 2 (radius: 5)
[00:20:53 -9595.334066] SLOW spr round 3 (radius: 10)
[00:21:08 -9589.131018] SLOW spr round 4 (radius: 5)
[00:21:28 -9589.127350] SLOW spr round 5 (radius: 10)
[00:21:46 -9589.127086] SLOW spr round 6 (radius: 15)
[00:22:05 -9589.127010] SLOW spr round 7 (radius: 20)
[00:22:30 -9589.126945] SLOW spr round 8 (radius: 25)
[00:22:52 -9589.126881] Model parameter optimization (eps = 0.100000)

[00:22:56] [worker #0] ML tree search #7, logLikelihood: -9588.875510

[00:22:56 -27532.788120] Initial branch length optimization
[00:22:56 -21742.974325] Model parameter optimization (eps = 10.000000)
[00:23:09 -21549.845921] AUTODETECT spr round 1 (radius: 5)
[00:23:18 -14674.779944] AUTODETECT spr round 2 (radius: 10)
[00:23:30 -11915.894132] AUTODETECT spr round 3 (radius: 15)
[00:23:45 -10910.563492] AUTODETECT spr round 4 (radius: 20)
[00:24:04 -10599.794713] AUTODETECT spr round 5 (radius: 25)
[00:24:17 -10584.126189] SPR radius for FAST iterations: 25 (autodetect)
[00:24:17 -10584.126189] Model parameter optimization (eps = 3.000000)
[00:24:26 -10559.119734] FAST spr round 1 (radius: 25)
[00:24:38 -9662.441132] FAST spr round 2 (radius: 25)
[00:24:49 -9599.155948] FAST spr round 3 (radius: 25)
[00:24:57 -9594.613701] FAST spr round 4 (radius: 25)
[00:25:05 -9594.612186] Model parameter optimization (eps = 1.000000)
[00:25:10 -9594.246326] SLOW spr round 1 (radius: 5)
[00:25:20] [worker #1] ML tree search #10, logLikelihood: -9591.312028
[00:25:27 -9591.798813] SLOW spr round 2 (radius: 5)
[00:25:42 -9591.798697] SLOW spr round 3 (radius: 10)
[00:25:57 -9589.826548] SLOW spr round 4 (radius: 5)
[00:26:18 -9588.585638] SLOW spr round 5 (radius: 5)
[00:26:36 -9588.585518] SLOW spr round 6 (radius: 10)
[00:26:51 -9588.585442] SLOW spr round 7 (radius: 15)
[00:27:12 -9588.585366] SLOW spr round 8 (radius: 20)
[00:27:37 -9588.585290] SLOW spr round 9 (radius: 25)
[00:27:58 -9588.585213] Model parameter optimization (eps = 0.100000)

[00:28:02] [worker #0] ML tree search #9, logLikelihood: -9588.466183

[00:28:02 -28235.391233] Initial branch length optimization
[00:28:02 -21957.824799] Model parameter optimization (eps = 10.000000)
[00:28:17 -21778.558384] AUTODETECT spr round 1 (radius: 5)
[00:28:26 -15556.076091] AUTODETECT spr round 2 (radius: 10)
[00:28:39 -13092.574709] AUTODETECT spr round 3 (radius: 15)
[00:28:53 -11524.176713] AUTODETECT spr round 4 (radius: 20)
[00:29:10 -10639.566967] AUTODETECT spr round 5 (radius: 25)
[00:29:25 -10639.560138] SPR radius for FAST iterations: 20 (autodetect)
[00:29:25 -10639.560138] Model parameter optimization (eps = 3.000000)
[00:29:36 -10603.679933] FAST spr round 1 (radius: 20)
[00:29:47 -9643.253384] FAST spr round 2 (radius: 20)
[00:29:57 -9604.418842] FAST spr round 3 (radius: 20)
[00:30:06 -9602.841198] FAST spr round 4 (radius: 20)
[00:30:14 -9602.247775] FAST spr round 5 (radius: 20)
[00:30:22 -9602.247647] Model parameter optimization (eps = 1.000000)
[00:30:25] [worker #1] ML tree search #12, logLikelihood: -9587.478001
[00:30:33 -9598.707638] SLOW spr round 1 (radius: 5)
[00:30:50 -9595.639299] SLOW spr round 2 (radius: 5)
[00:31:07 -9594.892158] SLOW spr round 3 (radius: 5)
[00:31:22 -9594.891347] SLOW spr round 4 (radius: 10)
[00:31:37 -9589.737035] SLOW spr round 5 (radius: 5)
[00:31:58 -9589.733370] SLOW spr round 6 (radius: 10)
[00:32:16 -9589.733134] SLOW spr round 7 (radius: 15)
[00:32:36 -9589.733055] SLOW spr round 8 (radius: 20)
[00:33:04 -9589.732983] SLOW spr round 9 (radius: 25)
[00:33:30 -9589.732911] Model parameter optimization (eps = 0.100000)

[00:33:39] [worker #0] ML tree search #11, logLikelihood: -9589.323886

[00:33:39 -28438.512162] Initial branch length optimization
[00:33:39 -22127.022821] Model parameter optimization (eps = 10.000000)
[00:33:51 -21923.891976] AUTODETECT spr round 1 (radius: 5)
[00:34:01 -14945.202313] AUTODETECT spr round 2 (radius: 10)
[00:34:14 -12119.203120] AUTODETECT spr round 3 (radius: 15)
[00:34:28 -10950.416639] AUTODETECT spr round 4 (radius: 20)
[00:34:43 -10949.467875] AUTODETECT spr round 5 (radius: 25)
[00:34:48] [worker #1] ML tree search #14, logLikelihood: -9587.365610
[00:34:57 -10851.802390] SPR radius for FAST iterations: 25 (autodetect)
[00:34:57 -10851.802390] Model parameter optimization (eps = 3.000000)
[00:35:10 -10823.549618] FAST spr round 1 (radius: 25)
[00:35:21 -9707.357676] FAST spr round 2 (radius: 25)
[00:35:31 -9605.650828] FAST spr round 3 (radius: 25)
[00:35:39 -9602.308218] FAST spr round 4 (radius: 25)
[00:35:47 -9602.308015] Model parameter optimization (eps = 1.000000)
[00:35:59 -9598.144933] SLOW spr round 1 (radius: 5)
[00:36:16 -9595.982708] SLOW spr round 2 (radius: 5)
[00:36:31 -9595.981115] SLOW spr round 3 (radius: 10)
[00:36:46 -9593.594500] SLOW spr round 4 (radius: 5)
[00:37:07 -9591.456425] SLOW spr round 5 (radius: 5)
[00:37:25 -9591.182029] SLOW spr round 6 (radius: 5)
[00:37:40 -9591.181990] SLOW spr round 7 (radius: 10)
[00:37:55 -9590.922029] SLOW spr round 8 (radius: 5)
[00:38:16 -9590.921902] SLOW spr round 9 (radius: 10)
[00:38:32 -9590.921886] SLOW spr round 10 (radius: 15)
[00:38:53 -9590.921884] SLOW spr round 11 (radius: 20)
[00:39:17 -9590.921883] SLOW spr round 12 (radius: 25)
[00:39:40 -9590.921883] Model parameter optimization (eps = 0.100000)

[00:39:47] [worker #0] ML tree search #13, logLikelihood: -9589.113095

[00:39:47 -27902.763451] Initial branch length optimization
[00:39:48 -21903.063456] Model parameter optimization (eps = 10.000000)
[00:40:00 -21705.484759] AUTODETECT spr round 1 (radius: 5)
[00:40:09 -15428.981474] AUTODETECT spr round 2 (radius: 10)
[00:40:15] [worker #1] ML tree search #16, logLikelihood: -9589.817123
[00:40:23 -12169.231624] AUTODETECT spr round 3 (radius: 15)
[00:40:39 -11097.407901] AUTODETECT spr round 4 (radius: 20)
[00:40:58 -10639.773794] AUTODETECT spr round 5 (radius: 25)
[00:41:14 -10639.734803] SPR radius for FAST iterations: 20 (autodetect)
[00:41:14 -10639.734803] Model parameter optimization (eps = 3.000000)
[00:41:22 -10608.263249] FAST spr round 1 (radius: 20)
[00:41:34 -9635.382628] FAST spr round 2 (radius: 20)
[00:41:44 -9600.173038] FAST spr round 3 (radius: 20)
[00:41:53 -9596.762745] FAST spr round 4 (radius: 20)
[00:42:01 -9596.762391] Model parameter optimization (eps = 1.000000)
[00:42:06 -9595.992675] SLOW spr round 1 (radius: 5)
[00:42:23 -9592.020424] SLOW spr round 2 (radius: 5)
[00:42:39 -9592.020278] SLOW spr round 3 (radius: 10)
[00:42:53 -9589.972566] SLOW spr round 4 (radius: 5)
[00:43:15 -9589.870312] SLOW spr round 5 (radius: 5)
[00:43:32 -9589.868809] SLOW spr round 6 (radius: 10)
[00:43:47 -9589.868620] SLOW spr round 7 (radius: 15)
[00:44:06 -9589.868514] SLOW spr round 8 (radius: 20)
[00:44:30 -9589.868412] SLOW spr round 9 (radius: 25)
[00:44:50 -9589.868309] Model parameter optimization (eps = 0.100000)

[00:45:00] [worker #0] ML tree search #15, logLikelihood: -9587.315037

[00:45:00 -27506.164258] Initial branch length optimization
[00:45:01 -21550.392906] Model parameter optimization (eps = 10.000000)
[00:45:11 -21350.470092] AUTODETECT spr round 1 (radius: 5)
[00:45:20 -14907.277428] AUTODETECT spr round 2 (radius: 10)
[00:45:34 -12046.311250] AUTODETECT spr round 3 (radius: 15)
[00:45:49] [worker #1] ML tree search #18, logLikelihood: -9587.222909
[00:45:53 -11169.730698] AUTODETECT spr round 4 (radius: 20)
[00:46:12 -10594.719112] AUTODETECT spr round 5 (radius: 25)
[00:46:26 -10592.573578] SPR radius for FAST iterations: 25 (autodetect)
[00:46:26 -10592.573578] Model parameter optimization (eps = 3.000000)
[00:46:33 -10575.527065] FAST spr round 1 (radius: 25)
[00:46:44 -9624.132030] FAST spr round 2 (radius: 25)
[00:46:55 -9612.475464] FAST spr round 3 (radius: 25)
[00:47:05 -9603.968340] FAST spr round 4 (radius: 25)
[00:47:15 -9597.171819] FAST spr round 5 (radius: 25)
[00:47:23 -9594.263743] FAST spr round 6 (radius: 25)
[00:47:30 -9594.261813] Model parameter optimization (eps = 1.000000)
[00:47:40 -9592.869153] SLOW spr round 1 (radius: 5)
[00:47:56 -9591.858067] SLOW spr round 2 (radius: 5)
[00:48:11 -9591.857445] SLOW spr round 3 (radius: 10)
[00:48:25 -9590.342169] SLOW spr round 4 (radius: 5)
[00:48:48 -9588.488834] SLOW spr round 5 (radius: 5)
[00:49:06 -9588.488246] SLOW spr round 6 (radius: 10)
[00:49:21 -9588.216306] SLOW spr round 7 (radius: 5)
[00:49:42 -9587.333503] SLOW spr round 8 (radius: 5)
[00:49:59 -9587.333501] SLOW spr round 9 (radius: 10)
[00:50:15 -9587.333501] SLOW spr round 10 (radius: 15)
[00:50:36 -9587.333501] SLOW spr round 11 (radius: 20)
[00:51:03 -9587.333501] SLOW spr round 12 (radius: 25)
[00:51:07] [worker #1] ML tree search #20, logLikelihood: -9588.886130
[00:51:25 -9587.333501] Model parameter optimization (eps = 0.100000)

[00:51:29] [worker #0] ML tree search #17, logLikelihood: -9586.852561

[00:51:29 -28034.389653] Initial branch length optimization
[00:51:30 -21572.566592] Model parameter optimization (eps = 10.000000)
[00:51:46 -21375.378304] AUTODETECT spr round 1 (radius: 5)
[00:51:55 -14894.329448] AUTODETECT spr round 2 (radius: 10)
[00:52:08 -12130.550960] AUTODETECT spr round 3 (radius: 15)
[00:52:24 -11132.986093] AUTODETECT spr round 4 (radius: 20)
[00:52:41 -10733.563553] AUTODETECT spr round 5 (radius: 25)
[00:52:54 -10733.555125] SPR radius for FAST iterations: 20 (autodetect)
[00:52:54 -10733.555125] Model parameter optimization (eps = 3.000000)
[00:53:04 -10708.790529] FAST spr round 1 (radius: 20)
[00:53:14 -9701.563547] FAST spr round 2 (radius: 20)
[00:53:24 -9605.447607] FAST spr round 3 (radius: 20)
[00:53:32 -9604.208314] FAST spr round 4 (radius: 20)
[00:53:40 -9603.431231] FAST spr round 5 (radius: 20)
[00:53:48 -9603.431200] Model parameter optimization (eps = 1.000000)
[00:53:52 -9602.379348] SLOW spr round 1 (radius: 5)
[00:54:10 -9596.367362] SLOW spr round 2 (radius: 5)
[00:54:26 -9595.708428] SLOW spr round 3 (radius: 5)
[00:54:41 -9595.708395] SLOW spr round 4 (radius: 10)
[00:54:55 -9593.469793] SLOW spr round 5 (radius: 5)
[00:55:16 -9593.242720] SLOW spr round 6 (radius: 5)
[00:55:33 -9593.241769] SLOW spr round 7 (radius: 10)
[00:55:48 -9593.241618] SLOW spr round 8 (radius: 15)
[00:56:09 -9593.241513] SLOW spr round 9 (radius: 20)
[00:56:33 -9593.241409] SLOW spr round 10 (radius: 25)
[00:56:54 -9593.241305] Model parameter optimization (eps = 0.100000)

[00:57:05] [worker #0] ML tree search #19, logLikelihood: -9590.777582


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.122858,0.344881) (0.142936,0.728582) (0.512678,0.886398) (0.221528,1.801355) 
   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: -9586.852561

AIC score: 19879.705122 / AICc score: 269803.705122 / BIC score: 20860.735715
Free parameters (model + branch lengths): 353

WARNING: Number of free parameters (K=353) is larger than alignment size (n=119).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 1 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/250721_run/phylogeny-snakemake/results/A6NI87/3_mltree/A6NI87.raxml.log

Analysis started: 26-Jul-2021 00:38:31 / finished: 26-Jul-2021 01:35:36

Elapsed time: 3425.337 seconds

Consumed energy: 167.427 Wh