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 6140 CPU @ 2.30GHz, 36 cores, 251 GB RAM

RAxML-NG was called at 12-Jul-2021 17:36:06 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/2_msa/Q5SRI9_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9 --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: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/2_msa/Q5SRI9_trimmed_msa.fasta
[00:00:00] Loaded alignment with 271 taxa and 1273 sites

WARNING: Sequences tr_G3QXA9_G3QXA9_GORGO_9595 and tr_A0A2K6AC39_A0A2K6AC39_MANLE_9568 are exactly identical!
WARNING: Sequences tr_M4AJI1_M4AJI1_XIPMA_8083 and tr_A0A087Y7Q5_A0A087Y7Q5_POEFO_48698 are exactly identical!
WARNING: Sequences tr_A0A0K0K0V4_A0A0K0K0V4_BRUMA_6279 and tr_A0A0R3R230_A0A0R3R230_9BILA_42155 are exactly identical!
WARNING: Sequences tr_F6VNN0_F6VNN0_MACMU_9544 and tr_G7P424_G7P424_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F6VNN0_F6VNN0_MACMU_9544 and tr_A0A2K6BM59_A0A2K6BM59_MACNE_9545 are exactly identical!
WARNING: Duplicate sequences found: 5

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.raxml.reduced.phy

Alignment comprises 1 partitions and 944 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1273 / 944
Gaps: 65.31 %
Invariant sites: 31.34 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.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 271 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 236 / 18880
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -178961.391859] Initial branch length optimization
[00:00:01 -146727.602475] Model parameter optimization (eps = 10.000000)
[00:00:17 -146399.943916] AUTODETECT spr round 1 (radius: 5)
[00:00:35 -106218.118181] AUTODETECT spr round 2 (radius: 10)
[00:01:01 -80919.083008] AUTODETECT spr round 3 (radius: 15)
[00:01:33 -79332.272185] AUTODETECT spr round 4 (radius: 20)
[00:02:19 -79035.477263] AUTODETECT spr round 5 (radius: 25)
[00:02:54 -78565.317722] SPR radius for FAST iterations: 25 (autodetect)
[00:02:54 -78565.317722] Model parameter optimization (eps = 3.000000)
[00:03:11 -78161.754284] FAST spr round 1 (radius: 25)
[00:03:41 -70321.045382] FAST spr round 2 (radius: 25)
[00:04:05 -70079.193174] FAST spr round 3 (radius: 25)
[00:04:22 -70057.339236] FAST spr round 4 (radius: 25)
[00:04:37 -70057.338370] Model parameter optimization (eps = 1.000000)
[00:04:43 -70049.294823] SLOW spr round 1 (radius: 5)
[00:05:13 -70039.928072] SLOW spr round 2 (radius: 5)
[00:05:40 -70039.927059] SLOW spr round 3 (radius: 10)
[00:06:10 -70038.995655] SLOW spr round 4 (radius: 5)
[00:06:49 -70038.995431] SLOW spr round 5 (radius: 10)
[00:07:24 -70038.995429] SLOW spr round 6 (radius: 15)
[00:08:11 -70038.823860] SLOW spr round 7 (radius: 5)
[00:08:54 -70038.823715] SLOW spr round 8 (radius: 10)
[00:09:32 -70038.542993] SLOW spr round 9 (radius: 5)
[00:10:10 -70038.542894] SLOW spr round 10 (radius: 10)
[00:10:44 -70038.542893] SLOW spr round 11 (radius: 15)
[00:11:33 -70038.542893] SLOW spr round 12 (radius: 20)
[00:12:41 -70038.542893] SLOW spr round 13 (radius: 25)
[00:12:59] [worker #1] ML tree search #2, logLikelihood: -70033.095938
[00:13:50 -70038.542892] Model parameter optimization (eps = 0.100000)

[00:13:52] [worker #0] ML tree search #1, logLikelihood: -70038.530988

[00:13:52 -178556.677709] Initial branch length optimization
[00:13:53 -145628.922959] Model parameter optimization (eps = 10.000000)
[00:14:13 -145234.690542] AUTODETECT spr round 1 (radius: 5)
[00:14:32 -110173.360142] AUTODETECT spr round 2 (radius: 10)
[00:14:57 -82198.885182] AUTODETECT spr round 3 (radius: 15)
[00:15:26 -78892.231415] AUTODETECT spr round 4 (radius: 20)
[00:16:02 -77789.354651] AUTODETECT spr round 5 (radius: 25)
[00:16:39 -77789.330871] SPR radius for FAST iterations: 20 (autodetect)
[00:16:39 -77789.330871] Model parameter optimization (eps = 3.000000)
[00:16:52 -77340.633618] FAST spr round 1 (radius: 20)
[00:17:21 -70323.904586] FAST spr round 2 (radius: 20)
[00:17:48 -70077.864827] FAST spr round 3 (radius: 20)
[00:18:07 -70059.472091] FAST spr round 4 (radius: 20)
[00:18:22 -70057.790396] FAST spr round 5 (radius: 20)
[00:18:37 -70057.790048] Model parameter optimization (eps = 1.000000)
[00:18:44 -70052.766069] SLOW spr round 1 (radius: 5)
[00:19:16 -70038.256066] SLOW spr round 2 (radius: 5)
[00:19:43 -70037.603094] SLOW spr round 3 (radius: 5)
[00:20:10 -70037.603063] SLOW spr round 4 (radius: 10)
[00:20:40 -70037.135348] SLOW spr round 5 (radius: 5)
[00:21:20 -70036.857582] SLOW spr round 6 (radius: 5)
[00:21:52 -70036.857122] SLOW spr round 7 (radius: 10)
[00:22:24 -70036.857115] SLOW spr round 8 (radius: 15)
[00:23:14 -70036.664084] SLOW spr round 9 (radius: 5)
[00:23:56 -70036.663869] SLOW spr round 10 (radius: 10)
[00:24:34 -70036.378986] SLOW spr round 11 (radius: 5)
[00:24:36] [worker #1] ML tree search #4, logLikelihood: -70037.065046
[00:25:13 -70036.378889] SLOW spr round 12 (radius: 10)
[00:25:47 -70036.378888] SLOW spr round 13 (radius: 15)
[00:26:35 -70036.378888] SLOW spr round 14 (radius: 20)
[00:27:46 -70036.378888] SLOW spr round 15 (radius: 25)
[00:28:55 -70036.378888] Model parameter optimization (eps = 0.100000)

[00:28:57] [worker #0] ML tree search #3, logLikelihood: -70036.338468

[00:28:57 -175890.914532] Initial branch length optimization
[00:28:58 -145044.701337] Model parameter optimization (eps = 10.000000)
[00:29:10 -144773.028481] AUTODETECT spr round 1 (radius: 5)
[00:29:28 -104718.450360] AUTODETECT spr round 2 (radius: 10)
[00:29:54 -88166.939036] AUTODETECT spr round 3 (radius: 15)
[00:30:22 -81176.551158] AUTODETECT spr round 4 (radius: 20)
[00:31:02 -78877.573170] AUTODETECT spr round 5 (radius: 25)
[00:31:32 -78877.543378] SPR radius for FAST iterations: 20 (autodetect)
[00:31:32 -78877.543378] Model parameter optimization (eps = 3.000000)
[00:31:46 -78491.617754] FAST spr round 1 (radius: 20)
[00:32:15 -70498.804058] FAST spr round 2 (radius: 20)
[00:32:40 -70074.360072] FAST spr round 3 (radius: 20)
[00:32:59 -70057.328499] FAST spr round 4 (radius: 20)
[00:33:14 -70055.719772] FAST spr round 5 (radius: 20)
[00:33:29 -70055.719485] Model parameter optimization (eps = 1.000000)
[00:33:35 -70052.776410] SLOW spr round 1 (radius: 5)
[00:34:06 -70031.929370] SLOW spr round 2 (radius: 5)
[00:34:34 -70031.923547] SLOW spr round 3 (radius: 10)
[00:35:04 -70030.903700] SLOW spr round 4 (radius: 5)
[00:35:44 -70030.630898] SLOW spr round 5 (radius: 5)
[00:36:16 -70030.629287] SLOW spr round 6 (radius: 10)
[00:36:47 -70030.629229] SLOW spr round 7 (radius: 15)
[00:37:35 -70030.629227] SLOW spr round 8 (radius: 20)
[00:38:43 -70030.629227] SLOW spr round 9 (radius: 25)
[00:39:37] [worker #1] ML tree search #6, logLikelihood: -70037.913649
[00:39:52 -70030.629227] Model parameter optimization (eps = 0.100000)

[00:39:56] [worker #0] ML tree search #5, logLikelihood: -70030.526142

[00:39:56 -178355.588509] Initial branch length optimization
[00:39:57 -146179.582007] Model parameter optimization (eps = 10.000000)
[00:40:11 -145831.095332] AUTODETECT spr round 1 (radius: 5)
[00:40:29 -105140.567656] AUTODETECT spr round 2 (radius: 10)
[00:40:54 -85493.116052] AUTODETECT spr round 3 (radius: 15)
[00:41:24 -78742.386117] AUTODETECT spr round 4 (radius: 20)
[00:42:03 -77653.970713] AUTODETECT spr round 5 (radius: 25)
[00:42:40 -77638.495095] SPR radius for FAST iterations: 25 (autodetect)
[00:42:40 -77638.495095] Model parameter optimization (eps = 3.000000)
[00:42:53 -77210.287058] FAST spr round 1 (radius: 25)
[00:43:20 -70373.876344] FAST spr round 2 (radius: 25)
[00:43:43 -70058.905429] FAST spr round 3 (radius: 25)
[00:44:00 -70044.872262] FAST spr round 4 (radius: 25)
[00:44:15 -70044.871959] Model parameter optimization (eps = 1.000000)
[00:44:21 -70038.936320] SLOW spr round 1 (radius: 5)
[00:44:51 -70031.496087] SLOW spr round 2 (radius: 5)
[00:45:19 -70030.100506] SLOW spr round 3 (radius: 5)
[00:45:46 -70030.100406] SLOW spr round 4 (radius: 10)
[00:46:15 -70030.100403] SLOW spr round 5 (radius: 15)
[00:47:09 -70029.924342] SLOW spr round 6 (radius: 5)
[00:47:52 -70029.651124] SLOW spr round 7 (radius: 5)
[00:48:26 -70029.649559] SLOW spr round 8 (radius: 10)
[00:48:57 -70029.649502] SLOW spr round 9 (radius: 15)
[00:49:48 -70029.649500] SLOW spr round 10 (radius: 20)
[00:50:57 -70029.649500] SLOW spr round 11 (radius: 25)
[00:52:05 -70029.649500] Model parameter optimization (eps = 0.100000)

[00:52:06] [worker #0] ML tree search #7, logLikelihood: -70029.621827

[00:52:06 -178045.500878] Initial branch length optimization
[00:52:07 -147042.066251] Model parameter optimization (eps = 10.000000)
[00:52:21 -146613.039108] AUTODETECT spr round 1 (radius: 5)
[00:52:39 -102340.377412] AUTODETECT spr round 2 (radius: 10)
[00:53:02 -85843.058282] AUTODETECT spr round 3 (radius: 15)
[00:53:30 -80883.506808] AUTODETECT spr round 4 (radius: 20)
[00:53:54] [worker #1] ML tree search #8, logLikelihood: -70038.266981
[00:54:09 -77988.909849] AUTODETECT spr round 5 (radius: 25)
[00:54:51 -76920.873351] SPR radius for FAST iterations: 25 (autodetect)
[00:54:51 -76920.873351] Model parameter optimization (eps = 3.000000)
[00:55:07 -76481.615239] FAST spr round 1 (radius: 25)
[00:55:37 -70470.223906] FAST spr round 2 (radius: 25)
[00:56:01 -70097.397484] FAST spr round 3 (radius: 25)
[00:56:20 -70071.915011] FAST spr round 4 (radius: 25)
[00:56:36 -70069.800425] FAST spr round 5 (radius: 25)
[00:56:50 -70069.800423] Model parameter optimization (eps = 1.000000)
[00:56:57 -70055.250550] SLOW spr round 1 (radius: 5)
[00:57:27 -70047.672415] SLOW spr round 2 (radius: 5)
[00:57:55 -70044.106452] SLOW spr round 3 (radius: 5)
[00:58:22 -70044.106297] SLOW spr round 4 (radius: 10)
[00:58:52 -70043.646443] SLOW spr round 5 (radius: 5)
[00:59:32 -70043.367097] SLOW spr round 6 (radius: 5)
[01:00:05 -70043.366602] SLOW spr round 7 (radius: 10)
[01:00:38 -70043.366595] SLOW spr round 8 (radius: 15)
[01:01:27 -70043.172118] SLOW spr round 9 (radius: 5)
[01:02:11 -70043.171902] SLOW spr round 10 (radius: 10)
[01:02:51 -70042.885113] SLOW spr round 11 (radius: 5)
[01:03:29 -70042.885016] SLOW spr round 12 (radius: 10)
[01:04:05 -70042.885015] SLOW spr round 13 (radius: 15)
[01:04:52 -70042.885015] SLOW spr round 14 (radius: 20)
[01:06:06 -70042.885015] SLOW spr round 15 (radius: 25)
[01:06:21] [worker #1] ML tree search #10, logLikelihood: -70032.473676
[01:07:15 -70042.885015] Model parameter optimization (eps = 0.100000)

[01:07:17] [worker #0] ML tree search #9, logLikelihood: -70042.853163

[01:07:17 -178241.492650] Initial branch length optimization
[01:07:18 -146552.088201] Model parameter optimization (eps = 10.000000)
[01:07:35 -146172.278878] AUTODETECT spr round 1 (radius: 5)
[01:07:54 -101519.542073] AUTODETECT spr round 2 (radius: 10)
[01:08:18 -88214.985469] AUTODETECT spr round 3 (radius: 15)
[01:08:51 -78312.723132] AUTODETECT spr round 4 (radius: 20)
[01:09:20 -77602.581006] AUTODETECT spr round 5 (radius: 25)
[01:09:53 -77569.703783] SPR radius for FAST iterations: 25 (autodetect)
[01:09:53 -77569.703783] Model parameter optimization (eps = 3.000000)
[01:10:10 -77081.398999] FAST spr round 1 (radius: 25)
[01:10:41 -70332.265221] FAST spr round 2 (radius: 25)
[01:11:05 -70075.169215] FAST spr round 3 (radius: 25)
[01:11:22 -70054.490297] FAST spr round 4 (radius: 25)
[01:11:37 -70054.479421] Model parameter optimization (eps = 1.000000)
[01:11:43 -70050.236419] SLOW spr round 1 (radius: 5)
[01:12:14 -70035.031481] SLOW spr round 2 (radius: 5)
[01:12:42 -70033.052251] SLOW spr round 3 (radius: 5)
[01:13:09 -70033.052042] SLOW spr round 4 (radius: 10)
[01:13:38 -70033.052042] SLOW spr round 5 (radius: 15)
[01:14:31 -70032.881936] SLOW spr round 6 (radius: 5)
[01:15:13 -70032.881752] SLOW spr round 7 (radius: 10)
[01:15:50 -70032.881751] SLOW spr round 8 (radius: 15)
[01:16:37 -70032.881751] SLOW spr round 9 (radius: 20)
[01:17:47 -70032.881750] SLOW spr round 10 (radius: 25)
[01:18:14] [worker #1] ML tree search #12, logLikelihood: -70037.432530
[01:18:57 -70032.881750] Model parameter optimization (eps = 0.100000)

[01:18:59] [worker #0] ML tree search #11, logLikelihood: -70032.847523

[01:18:59 -175749.715852] Initial branch length optimization
[01:19:00 -144062.465785] Model parameter optimization (eps = 10.000000)
[01:19:21 -143598.945639] AUTODETECT spr round 1 (radius: 5)
[01:19:40 -101254.817993] AUTODETECT spr round 2 (radius: 10)
[01:20:06 -84320.698548] AUTODETECT spr round 3 (radius: 15)
[01:20:35 -78811.680093] AUTODETECT spr round 4 (radius: 20)
[01:21:12 -77941.960184] AUTODETECT spr round 5 (radius: 25)
[01:21:50 -77835.885747] SPR radius for FAST iterations: 25 (autodetect)
[01:21:50 -77835.885747] Model parameter optimization (eps = 3.000000)
[01:22:07 -77356.932387] FAST spr round 1 (radius: 25)
[01:22:35 -70512.342275] FAST spr round 2 (radius: 25)
[01:22:56 -70090.217083] FAST spr round 3 (radius: 25)
[01:23:14 -70068.451196] FAST spr round 4 (radius: 25)
[01:23:30 -70067.933400] FAST spr round 5 (radius: 25)
[01:23:45 -70067.926343] Model parameter optimization (eps = 1.000000)
[01:23:52 -70062.132038] SLOW spr round 1 (radius: 5)
[01:24:23 -70040.791041] SLOW spr round 2 (radius: 5)
[01:24:50 -70040.790524] SLOW spr round 3 (radius: 10)
[01:25:19 -70040.790511] SLOW spr round 4 (radius: 15)
[01:26:12 -70040.651943] SLOW spr round 5 (radius: 5)
[01:26:55 -70040.651740] SLOW spr round 6 (radius: 10)
[01:27:30 -70040.651739] SLOW spr round 7 (radius: 15)
[01:28:18 -70040.651739] SLOW spr round 8 (radius: 20)
[01:29:27 -70040.651739] SLOW spr round 9 (radius: 25)
[01:30:36 -70040.651739] Model parameter optimization (eps = 0.100000)

[01:30:38] [worker #0] ML tree search #13, logLikelihood: -70040.597221

[01:30:38 -179595.379164] Initial branch length optimization
[01:30:39 -146583.904616] Model parameter optimization (eps = 10.000000)
[01:30:53 -146209.299055] AUTODETECT spr round 1 (radius: 5)
[01:31:06] [worker #1] ML tree search #14, logLikelihood: -70038.162077
[01:31:12 -105885.070145] AUTODETECT spr round 2 (radius: 10)
[01:31:36 -82192.968909] AUTODETECT spr round 3 (radius: 15)
[01:32:03 -79363.478306] AUTODETECT spr round 4 (radius: 20)
[01:32:37 -76824.303384] AUTODETECT spr round 5 (radius: 25)
[01:33:16 -76544.505146] SPR radius for FAST iterations: 25 (autodetect)
[01:33:16 -76544.505146] Model parameter optimization (eps = 3.000000)
[01:33:32 -76074.823336] FAST spr round 1 (radius: 25)
[01:34:00 -70286.240877] FAST spr round 2 (radius: 25)
[01:34:20 -70051.652731] FAST spr round 3 (radius: 25)
[01:34:37 -70046.616276] FAST spr round 4 (radius: 25)
[01:34:51 -70046.615943] Model parameter optimization (eps = 1.000000)
[01:34:57 -70041.440520] SLOW spr round 1 (radius: 5)
[01:35:27 -70038.789202] SLOW spr round 2 (radius: 5)
[01:35:54 -70038.788637] SLOW spr round 3 (radius: 10)
[01:36:24 -70038.788628] SLOW spr round 4 (radius: 15)
[01:37:18 -70038.620212] SLOW spr round 5 (radius: 5)
[01:38:01 -70038.619999] SLOW spr round 6 (radius: 10)
[01:38:39 -70038.338317] SLOW spr round 7 (radius: 5)
[01:39:18 -70038.338221] SLOW spr round 8 (radius: 10)
[01:39:52 -70038.338218] SLOW spr round 9 (radius: 15)
[01:40:41 -70038.338216] SLOW spr round 10 (radius: 20)
[01:41:53 -70038.338215] SLOW spr round 11 (radius: 25)
[01:43:01 -70038.338215] Model parameter optimization (eps = 0.100000)

[01:43:03] [worker #0] ML tree search #15, logLikelihood: -70038.329649

[01:43:03 -176406.608275] Initial branch length optimization
[01:43:05 -145003.569952] Model parameter optimization (eps = 10.000000)
[01:43:20 -144636.444960] AUTODETECT spr round 1 (radius: 5)
[01:43:37 -97755.312239] AUTODETECT spr round 2 (radius: 10)
[01:44:01 -81466.763107] AUTODETECT spr round 3 (radius: 15)
[01:44:33 -75611.957872] AUTODETECT spr round 4 (radius: 20)
[01:44:57] [worker #1] ML tree search #16, logLikelihood: -70038.678366
[01:45:09 -75525.892420] AUTODETECT spr round 5 (radius: 25)
[01:45:41 -75525.887298] SPR radius for FAST iterations: 20 (autodetect)
[01:45:41 -75525.887298] Model parameter optimization (eps = 3.000000)
[01:45:56 -75079.860252] FAST spr round 1 (radius: 20)
[01:46:20 -70217.137741] FAST spr round 2 (radius: 20)
[01:46:41 -70076.795195] FAST spr round 3 (radius: 20)
[01:46:57 -70068.236592] FAST spr round 4 (radius: 20)
[01:47:13 -70059.500953] FAST spr round 5 (radius: 20)
[01:47:27 -70059.500543] Model parameter optimization (eps = 1.000000)
[01:47:34 -70049.773743] SLOW spr round 1 (radius: 5)
[01:48:05 -70032.193480] SLOW spr round 2 (radius: 5)
[01:48:33 -70032.176549] SLOW spr round 3 (radius: 10)
[01:49:02 -70031.304640] SLOW spr round 4 (radius: 5)
[01:49:42 -70031.304453] SLOW spr round 5 (radius: 10)
[01:50:15 -70031.304453] SLOW spr round 6 (radius: 15)
[01:51:06 -70031.304453] SLOW spr round 7 (radius: 20)
[01:52:16 -70031.150975] SLOW spr round 8 (radius: 5)
[01:53:00 -70031.150780] SLOW spr round 9 (radius: 10)
[01:53:38 -70031.150779] SLOW spr round 10 (radius: 15)
[01:54:27 -70031.150779] SLOW spr round 11 (radius: 20)
[01:55:38 -70031.150779] SLOW spr round 12 (radius: 25)
[01:56:48 -70031.150779] Model parameter optimization (eps = 0.100000)
[01:56:48] [worker #1] ML tree search #18, logLikelihood: -70039.407618

[01:56:50] [worker #0] ML tree search #17, logLikelihood: -70031.089096

[01:56:50 -176855.039028] Initial branch length optimization
[01:56:51 -143535.741090] Model parameter optimization (eps = 10.000000)
[01:57:10 -143098.230856] AUTODETECT spr round 1 (radius: 5)
[01:57:29 -102958.151498] AUTODETECT spr round 2 (radius: 10)
[01:57:55 -80183.274554] AUTODETECT spr round 3 (radius: 15)
[01:58:24 -77535.410776] AUTODETECT spr round 4 (radius: 20)
[01:58:57 -77009.701828] AUTODETECT spr round 5 (radius: 25)
[01:59:29 -76830.656139] SPR radius for FAST iterations: 25 (autodetect)
[01:59:29 -76830.656139] Model parameter optimization (eps = 3.000000)
[01:59:44 -76369.470092] FAST spr round 1 (radius: 25)
[02:00:14 -70292.299764] FAST spr round 2 (radius: 25)
[02:00:37 -70059.818126] FAST spr round 3 (radius: 25)
[02:00:53 -70057.251163] FAST spr round 4 (radius: 25)
[02:01:08 -70057.250190] Model parameter optimization (eps = 1.000000)
[02:01:14 -70051.973585] SLOW spr round 1 (radius: 5)
[02:01:45 -70039.492891] SLOW spr round 2 (radius: 5)
[02:02:13 -70038.610292] SLOW spr round 3 (radius: 5)
[02:02:41 -70037.895261] SLOW spr round 4 (radius: 5)
[02:03:08 -70037.895260] SLOW spr round 5 (radius: 10)
[02:03:38 -70037.895259] SLOW spr round 6 (radius: 15)
[02:04:30 -70037.746894] SLOW spr round 7 (radius: 5)
[02:05:12 -70037.746711] SLOW spr round 8 (radius: 10)
[02:05:50 -70037.464770] SLOW spr round 9 (radius: 5)
[02:06:28 -70037.464669] SLOW spr round 10 (radius: 10)
[02:07:02 -70037.464669] SLOW spr round 11 (radius: 15)
[02:07:50 -70037.464668] SLOW spr round 12 (radius: 20)
[02:08:59 -70037.464668] SLOW spr round 13 (radius: 25)
[02:09:53] [worker #1] ML tree search #20, logLikelihood: -70033.413550
[02:10:09 -70037.464668] Model parameter optimization (eps = 0.100000)

[02:10:13] [worker #0] ML tree search #19, logLikelihood: -70037.343145


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.143142,0.349896) (0.213103,0.516316) (0.327316,0.862372) (0.316439,1.762169) 
   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: -70029.621827

AIC score: 141149.243653 / AICc score: 141967.868138 / BIC score: 143955.520375
Free parameters (model + branch lengths): 545

Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SRI9/3_mltree/Q5SRI9.raxml.log

Analysis started: 12-Jul-2021 17:36:06 / finished: 12-Jul-2021 19:46:19

Elapsed time: 7813.339 seconds