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 10-Jul-2021 13:47:18 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/2_msa/P23083_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083 --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: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/2_msa/P23083_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 117 sites

WARNING: Sequences sp_P01756_HVM12_MOUSE_10090 and sp_P01757_HVM13_MOUSE_10090 are exactly identical!
WARNING: Sequences tr_A0A2I3RCM2_A0A2I3RCM2_PANTR_9598 and tr_A0A2R8ZPX9_A0A2R8ZPX9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3S4I1_A0A2I3S4I1_PANTR_9598 and tr_A0A2R8ZFN9_A0A2R8ZFN9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3SB50_A0A2I3SB50_PANTR_9598 and tr_A0A2R8ZJ75_A0A2R8ZJ75_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3SLP9_A0A2I3SLP9_PANTR_9598 and tr_A0A2R8ZD36_A0A2R8ZD36_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3SUC8_A0A2I3SUC8_PANTR_9598 and tr_A0A2R8ZB84_A0A2R8ZB84_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3T0N2_A0A2I3T0N2_PANTR_9598 and tr_A0A2R9APQ7_A0A2R9APQ7_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TM71_A0A2I3TM71_PANTR_9598 and tr_A0A2R8ZQ55_A0A2R8ZQ55_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2RIL7_H2RIL7_PANTR_9598 and tr_A0A2R8ZD60_A0A2R8ZD60_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6UMB9_F6UMB9_ORNAN_9258 and tr_F6WX17_F6WX17_ORNAN_9258 are exactly identical!
WARNING: Sequences tr_A0A0G2JT95_A0A0G2JT95_RAT_10116 and tr_M0R8Q9_M0R8Q9_RAT_10116 are exactly identical!
WARNING: Sequences sp_P01768_HV330_HUMAN_9606 and sp_P0DP03_HV335_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H9H495_H9H495_MACMU_9544 and tr_G8F4H4_G8F4H4_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A2K5NS22_A0A2K5NS22_CERAT_9531 and tr_A0A2K5XFH2_A0A2K5XFH2_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K6D0G6_A0A2K6D0G6_MACNE_9545 and tr_A0A2K5XSZ2_A0A2K5XSZ2_MANLE_9568 are exactly identical!
WARNING: Duplicate sequences found: 15

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/P23083/3_mltree/P23083.raxml.reduced.phy

Alignment comprises 1 partitions and 117 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 117 / 117
Gaps: 6.77 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083.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 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 117 / 9360
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -149037.207428] Initial branch length optimization
[00:00:03 -128476.202240] Model parameter optimization (eps = 10.000000)
[00:00:37 -127664.788290] AUTODETECT spr round 1 (radius: 5)
[00:02:47 -101446.930795] AUTODETECT spr round 2 (radius: 10)
[00:05:22 -82543.730678] AUTODETECT spr round 3 (radius: 15)
[00:08:33 -69261.708972] AUTODETECT spr round 4 (radius: 20)
[00:12:17 -61858.979600] AUTODETECT spr round 5 (radius: 25)
[00:16:22 -60870.185479] SPR radius for FAST iterations: 25 (autodetect)
[00:16:22 -60870.185479] Model parameter optimization (eps = 3.000000)
[00:16:44 -60784.071564] FAST spr round 1 (radius: 25)
[00:20:01 -54060.552588] FAST spr round 2 (radius: 25)
[00:22:23 -53661.779631] FAST spr round 3 (radius: 25)
[00:24:27 -53593.477010] FAST spr round 4 (radius: 25)
[00:26:22 -53566.178955] FAST spr round 5 (radius: 25)
[00:28:06 -53566.178860] Model parameter optimization (eps = 1.000000)
[00:28:22 -53560.978436] SLOW spr round 1 (radius: 5)
[00:30:43 -53542.704573] SLOW spr round 2 (radius: 5)
[00:32:56 -53539.546124] SLOW spr round 3 (radius: 5)
[00:35:01 -53539.528510] SLOW spr round 4 (radius: 10)
[00:37:13 -53536.323537] SLOW spr round 5 (radius: 5)
[00:39:53 -53529.852831] SLOW spr round 6 (radius: 5)
[00:42:15 -53528.294567] SLOW spr round 7 (radius: 5)
[00:44:25 -53528.294486] SLOW spr round 8 (radius: 10)
[00:46:39 -53527.316693] SLOW spr round 9 (radius: 5)
[00:49:14 -53527.316647] SLOW spr round 10 (radius: 10)
[00:51:41 -53527.263926] SLOW spr round 11 (radius: 15)
[00:55:33 -53527.263921] SLOW spr round 12 (radius: 20)
[01:01:41 -53527.263918] SLOW spr round 13 (radius: 25)
[01:07:42 -53527.263915] Model parameter optimization (eps = 0.100000)

[01:07:49] [worker #0] ML tree search #1, logLikelihood: -53527.240053

[01:07:49 -147255.400428] Initial branch length optimization
[01:07:51 -127657.309658] Model parameter optimization (eps = 10.000000)
[01:08:21 -126821.497035] AUTODETECT spr round 1 (radius: 5)
[01:10:31 -100938.393415] AUTODETECT spr round 2 (radius: 10)
[01:13:00 -80508.420155] AUTODETECT spr round 3 (radius: 15)
[01:15:53 -70465.598409] AUTODETECT spr round 4 (radius: 20)
[01:19:23 -64468.985095] AUTODETECT spr round 5 (radius: 25)
[01:23:08 -62543.649223] SPR radius for FAST iterations: 25 (autodetect)
[01:23:08 -62543.649223] Model parameter optimization (eps = 3.000000)
[01:23:29 -62460.553487] FAST spr round 1 (radius: 25)
[01:26:54 -54141.677800] FAST spr round 2 (radius: 25)
[01:29:27 -53656.874211] FAST spr round 3 (radius: 25)
[01:31:31 -53624.183525] FAST spr round 4 (radius: 25)
[01:33:26 -53619.960882] FAST spr round 5 (radius: 25)
[01:35:15 -53617.580042] FAST spr round 6 (radius: 25)
[01:36:59 -53616.820845] FAST spr round 7 (radius: 25)
[01:38:41 -53616.820816] Model parameter optimization (eps = 1.000000)
[01:38:57 -53610.949328] SLOW spr round 1 (radius: 5)
[01:41:15 -53589.589765] SLOW spr round 2 (radius: 5)
[01:43:26 -53587.824457] SLOW spr round 3 (radius: 5)
[01:45:35 -53586.336891] SLOW spr round 4 (radius: 5)
[01:47:41 -53586.336852] SLOW spr round 5 (radius: 10)
[01:49:53 -53581.066004] SLOW spr round 6 (radius: 5)
[01:52:30 -53577.706435] SLOW spr round 7 (radius: 5)
[01:54:51 -53577.505921] SLOW spr round 8 (radius: 5)
[01:57:03 -53577.505920] SLOW spr round 9 (radius: 10)
[01:59:14 -53576.098970] SLOW spr round 10 (radius: 5)
[02:01:52 -53574.870786] SLOW spr round 11 (radius: 5)
[02:04:13 -53570.211468] SLOW spr round 12 (radius: 5)
[02:06:28 -53567.733785] SLOW spr round 13 (radius: 5)
[02:08:37 -53567.543611] SLOW spr round 14 (radius: 5)
[02:10:44 -53567.543575] SLOW spr round 15 (radius: 10)
[02:12:50] [worker #1] ML tree search #2, logLikelihood: -53513.831585
[02:12:52 -53566.139699] SLOW spr round 16 (radius: 5)
[02:15:31 -53565.024358] SLOW spr round 17 (radius: 5)
[02:17:50 -53565.024128] SLOW spr round 18 (radius: 10)
[02:20:03 -53564.533926] SLOW spr round 19 (radius: 5)
[02:22:38 -53564.533877] SLOW spr round 20 (radius: 10)
[02:25:01 -53564.533877] SLOW spr round 21 (radius: 15)
[02:28:39 -53563.258678] SLOW spr round 22 (radius: 5)
[02:31:22 -53562.596366] SLOW spr round 23 (radius: 5)
[02:33:45 -53562.596301] SLOW spr round 24 (radius: 10)
[02:36:00 -53562.596301] SLOW spr round 25 (radius: 15)
[02:39:47 -53562.596301] SLOW spr round 26 (radius: 20)
[02:45:13 -53562.596301] SLOW spr round 27 (radius: 25)
[02:51:33 -53557.962075] SLOW spr round 28 (radius: 5)
[02:54:19 -53557.935325] SLOW spr round 29 (radius: 10)
[02:56:55 -53557.935325] SLOW spr round 30 (radius: 15)
[03:00:26 -53555.840348] SLOW spr round 31 (radius: 5)
[03:03:11 -53553.520346] SLOW spr round 32 (radius: 5)
[03:05:34 -53553.518061] SLOW spr round 33 (radius: 10)
[03:07:50 -53553.517701] SLOW spr round 34 (radius: 15)
[03:11:46 -53553.517667] SLOW spr round 35 (radius: 20)
[03:17:42 -53553.517665] SLOW spr round 36 (radius: 25)
[03:24:11 -53553.517665] Model parameter optimization (eps = 0.100000)

[03:24:24] [worker #0] ML tree search #3, logLikelihood: -53553.194946

[03:24:24 -148351.850620] Initial branch length optimization
[03:24:28 -128229.720210] Model parameter optimization (eps = 10.000000)
[03:24:58 -127498.711316] AUTODETECT spr round 1 (radius: 5)
[03:27:07 -101710.520071] AUTODETECT spr round 2 (radius: 10)
[03:29:41 -81578.542535] AUTODETECT spr round 3 (radius: 15)
[03:32:37 -67641.869261] AUTODETECT spr round 4 (radius: 20)
[03:36:04 -62344.592320] AUTODETECT spr round 5 (radius: 25)
[03:40:30 -61273.742058] SPR radius for FAST iterations: 25 (autodetect)
[03:40:30 -61273.742058] Model parameter optimization (eps = 3.000000)
[03:40:46 -61202.160248] FAST spr round 1 (radius: 25)
[03:44:18 -54086.658828] FAST spr round 2 (radius: 25)
[03:46:42 -53652.493410] FAST spr round 3 (radius: 25)
[03:48:49 -53592.409020] FAST spr round 4 (radius: 25)
[03:50:39 -53588.629310] FAST spr round 5 (radius: 25)
[03:51:40] [worker #1] ML tree search #4, logLikelihood: -53547.636590
[03:52:26 -53584.044742] FAST spr round 6 (radius: 25)
[03:54:09 -53582.176221] FAST spr round 7 (radius: 25)
[03:55:51 -53581.441610] FAST spr round 8 (radius: 25)
[03:57:33 -53581.441603] Model parameter optimization (eps = 1.000000)
[03:57:47 -53577.949921] SLOW spr round 1 (radius: 5)
[04:00:10 -53557.086979] SLOW spr round 2 (radius: 5)
[04:02:24 -53554.890521] SLOW spr round 3 (radius: 5)
[04:04:33 -53553.827375] SLOW spr round 4 (radius: 5)
[04:06:41 -53553.827294] SLOW spr round 5 (radius: 10)
[04:08:57 -53542.984456] SLOW spr round 6 (radius: 5)
[04:11:38 -53542.589373] SLOW spr round 7 (radius: 5)
[04:14:02 -53542.589203] SLOW spr round 8 (radius: 10)
[04:16:23 -53541.857523] SLOW spr round 9 (radius: 5)
[04:19:06 -53539.046865] SLOW spr round 10 (radius: 5)
[04:21:31 -53537.107192] SLOW spr round 11 (radius: 5)
[04:23:46 -53536.434678] SLOW spr round 12 (radius: 5)
[04:25:57 -53536.434667] SLOW spr round 13 (radius: 10)
[04:28:13 -53536.434660] SLOW spr round 14 (radius: 15)
[04:32:43 -53536.351889] SLOW spr round 15 (radius: 20)
[04:38:42 -53536.351877] SLOW spr round 16 (radius: 25)
[04:45:23 -53536.351872] Model parameter optimization (eps = 0.100000)

[04:45:30] [worker #0] ML tree search #5, logLikelihood: -53536.259563

[04:45:30 -148723.972908] Initial branch length optimization
[04:45:33 -128761.065494] Model parameter optimization (eps = 10.000000)
[04:46:08 -127990.084388] AUTODETECT spr round 1 (radius: 5)
[04:48:18 -102697.380577] AUTODETECT spr round 2 (radius: 10)
[04:50:52 -81778.853993] AUTODETECT spr round 3 (radius: 15)
[04:53:48 -69311.803065] AUTODETECT spr round 4 (radius: 20)
[04:57:25 -62972.799646] AUTODETECT spr round 5 (radius: 25)
[05:01:29 -61366.798179] SPR radius for FAST iterations: 25 (autodetect)
[05:01:29 -61366.798179] Model parameter optimization (eps = 3.000000)
[05:02:01 -61291.272300] FAST spr round 1 (radius: 25)
[05:05:25 -54007.343076] FAST spr round 2 (radius: 25)
[05:07:50 -53656.142069] FAST spr round 3 (radius: 25)
[05:09:58 -53603.223648] FAST spr round 4 (radius: 25)
[05:11:58 -53584.566609] FAST spr round 5 (radius: 25)
[05:13:45 -53582.134709] FAST spr round 6 (radius: 25)
[05:15:29 -53582.134705] Model parameter optimization (eps = 1.000000)
[05:15:38 -53581.557289] SLOW spr round 1 (radius: 5)
[05:18:03 -53553.706945] SLOW spr round 2 (radius: 5)
[05:20:19 -53543.575523] SLOW spr round 3 (radius: 5)
[05:22:28 -53541.307548] SLOW spr round 4 (radius: 5)
[05:24:35 -53541.307547] SLOW spr round 5 (radius: 10)
[05:26:48 -53539.869863] SLOW spr round 6 (radius: 5)
[05:29:25 -53539.869847] SLOW spr round 7 (radius: 10)
[05:31:55 -53536.955912] SLOW spr round 8 (radius: 5)
[05:34:35 -53530.858309] SLOW spr round 9 (radius: 5)
[05:36:54 -53530.858237] SLOW spr round 10 (radius: 10)
[05:39:11 -53529.338994] SLOW spr round 11 (radius: 5)
[05:41:50 -53528.569025] SLOW spr round 12 (radius: 5)
[05:44:09 -53528.569024] SLOW spr round 13 (radius: 10)
[05:46:26 -53528.569024] SLOW spr round 14 (radius: 15)
[05:50:34 -53527.651698] SLOW spr round 15 (radius: 5)
[05:53:18 -53526.647138] SLOW spr round 16 (radius: 5)
[05:55:41 -53526.647131] SLOW spr round 17 (radius: 10)
[05:58:00 -53526.647131] SLOW spr round 18 (radius: 15)
[06:02:05 -53526.522505] SLOW spr round 19 (radius: 5)
[06:04:49 -53526.403573] SLOW spr round 20 (radius: 5)
[06:07:13 -53526.403573] SLOW spr round 21 (radius: 10)
[06:09:32 -53526.403573] SLOW spr round 22 (radius: 15)
[06:13:38 -53526.390678] SLOW spr round 23 (radius: 20)
[06:19:16 -53526.390669] SLOW spr round 24 (radius: 25)
[06:26:01 -53526.390669] Model parameter optimization (eps = 0.100000)

[06:26:18] [worker #0] ML tree search #7, logLikelihood: -53525.872497

[06:26:18 -147477.613340] Initial branch length optimization
[06:26:22 -127741.475457] Model parameter optimization (eps = 10.000000)
[06:26:48 -127096.245536] AUTODETECT spr round 1 (radius: 5)
[06:29:00 -99614.868247] AUTODETECT spr round 2 (radius: 10)
[06:31:32 -80376.488738] AUTODETECT spr round 3 (radius: 15)
[06:34:24 -66441.932205] AUTODETECT spr round 4 (radius: 20)
[06:37:57 -62275.270460] AUTODETECT spr round 5 (radius: 25)
[06:42:44 -61515.385505] SPR radius for FAST iterations: 25 (autodetect)
[06:42:44 -61515.385505] Model parameter optimization (eps = 3.000000)
[06:43:03 -61456.863007] FAST spr round 1 (radius: 25)
[06:46:30 -54365.413065] FAST spr round 2 (radius: 25)
[06:48:56 -53690.300918] FAST spr round 3 (radius: 25)
[06:50:59 -53644.492746] FAST spr round 4 (radius: 25)
[06:52:50 -53635.062862] FAST spr round 5 (radius: 25)
[06:54:36 -53630.323898] FAST spr round 6 (radius: 25)
[06:56:19 -53630.323889] Model parameter optimization (eps = 1.000000)
[06:56:28 -53629.834677] SLOW spr round 1 (radius: 5)
[06:58:53 -53611.794337] SLOW spr round 2 (radius: 5)
[07:00:11] [worker #1] ML tree search #6, logLikelihood: -53550.482268
[07:01:10 -53611.061192] SLOW spr round 3 (radius: 5)
[07:03:23 -53611.061048] SLOW spr round 4 (radius: 10)
[07:05:39 -53605.088845] SLOW spr round 5 (radius: 5)
[07:08:21 -53602.860794] SLOW spr round 6 (radius: 5)
[07:10:48 -53600.255277] SLOW spr round 7 (radius: 5)
[07:13:03 -53600.255211] SLOW spr round 8 (radius: 10)
[07:15:19 -53597.482209] SLOW spr round 9 (radius: 5)
[07:17:59 -53596.780113] SLOW spr round 10 (radius: 5)
[07:20:20 -53596.427963] SLOW spr round 11 (radius: 5)
[07:22:34 -53596.427949] SLOW spr round 12 (radius: 10)
[07:24:48 -53594.967224] SLOW spr round 13 (radius: 5)
[07:27:27 -53594.967012] SLOW spr round 14 (radius: 10)
[07:29:57 -53594.704780] SLOW spr round 15 (radius: 5)
[07:32:33 -53594.704706] SLOW spr round 16 (radius: 10)
[07:35:00 -53593.805391] SLOW spr round 17 (radius: 5)
[07:37:36 -53593.805035] SLOW spr round 18 (radius: 10)
[07:40:04 -53592.694315] SLOW spr round 19 (radius: 5)
[07:42:46 -53584.166946] SLOW spr round 20 (radius: 5)
[07:45:07 -53583.982543] SLOW spr round 21 (radius: 5)
[07:47:19 -53583.982541] SLOW spr round 22 (radius: 10)
[07:49:34 -53583.073866] SLOW spr round 23 (radius: 5)
[07:52:16 -53575.280697] SLOW spr round 24 (radius: 5)
[07:54:38 -53575.279669] SLOW spr round 25 (radius: 10)
[07:56:56 -53575.043994] SLOW spr round 26 (radius: 5)
[07:59:35 -53572.940592] SLOW spr round 27 (radius: 5)
[08:01:57 -53572.940586] SLOW spr round 28 (radius: 10)
[08:04:14 -53572.940586] SLOW spr round 29 (radius: 15)
[08:08:38 -53560.993942] SLOW spr round 30 (radius: 5)
[08:11:25 -53552.653243] SLOW spr round 31 (radius: 5)
[08:13:52 -53550.792592] SLOW spr round 32 (radius: 5)
[08:16:07 -53550.792517] SLOW spr round 33 (radius: 10)
[08:18:21 -53550.792517] SLOW spr round 34 (radius: 15)
[08:22:40 -53548.906621] SLOW spr round 35 (radius: 5)
[08:25:26 -53547.691716] SLOW spr round 36 (radius: 5)
[08:27:51 -53546.359638] SLOW spr round 37 (radius: 5)
[08:30:05 -53546.359637] SLOW spr round 38 (radius: 10)
[08:32:19 -53546.359637] SLOW spr round 39 (radius: 15)
[08:36:38 -53545.906838] SLOW spr round 40 (radius: 5)
[08:39:20 -53545.906823] SLOW spr round 41 (radius: 10)
[08:41:55 -53545.906823] SLOW spr round 42 (radius: 15)
[08:45:45 -53545.906823] SLOW spr round 43 (radius: 20)
[08:52:00 -53545.906823] SLOW spr round 44 (radius: 25)
[08:54:20] [worker #1] ML tree search #8, logLikelihood: -53555.102691
[08:58:17 -53545.906823] Model parameter optimization (eps = 0.100000)

[08:58:28] [worker #0] ML tree search #9, logLikelihood: -53545.821571

[08:58:28 -147352.478404] Initial branch length optimization
[08:58:30 -127708.552022] Model parameter optimization (eps = 10.000000)
[08:59:01 -126946.140221] AUTODETECT spr round 1 (radius: 5)
[09:01:10 -101030.860341] AUTODETECT spr round 2 (radius: 10)
[09:03:46 -81028.549577] AUTODETECT spr round 3 (radius: 15)
[09:06:48 -67511.433316] AUTODETECT spr round 4 (radius: 20)
[09:10:34 -62138.416915] AUTODETECT spr round 5 (radius: 25)
[09:14:52 -60832.715846] SPR radius for FAST iterations: 25 (autodetect)
[09:14:52 -60832.715846] Model parameter optimization (eps = 3.000000)
[09:15:13 -60771.648534] FAST spr round 1 (radius: 25)
[09:18:37 -54083.437454] FAST spr round 2 (radius: 25)
[09:21:04 -53676.292854] FAST spr round 3 (radius: 25)
[09:23:10 -53631.160780] FAST spr round 4 (radius: 25)
[09:25:01 -53623.188909] FAST spr round 5 (radius: 25)
[09:26:47 -53619.070770] FAST spr round 6 (radius: 25)
[09:28:30 -53615.906297] FAST spr round 7 (radius: 25)
[09:30:11 -53615.905747] Model parameter optimization (eps = 1.000000)
[09:30:24 -53614.387954] SLOW spr round 1 (radius: 5)
[09:32:49 -53588.833350] SLOW spr round 2 (radius: 5)
[09:35:05 -53586.956688] SLOW spr round 3 (radius: 5)
[09:37:15 -53586.956642] SLOW spr round 4 (radius: 10)
[09:39:31 -53581.922338] SLOW spr round 5 (radius: 5)
[09:42:16 -53572.729536] SLOW spr round 6 (radius: 5)
[09:44:40 -53572.728458] SLOW spr round 7 (radius: 10)
[09:46:58 -53571.536183] SLOW spr round 8 (radius: 5)
[09:49:38 -53571.536138] SLOW spr round 9 (radius: 10)
[09:52:09 -53567.428937] SLOW spr round 10 (radius: 5)
[09:54:47 -53566.906910] SLOW spr round 11 (radius: 5)
[09:57:09 -53566.906908] SLOW spr round 12 (radius: 10)
[09:59:29 -53564.417374] SLOW spr round 13 (radius: 5)
[10:02:13 -53560.651179] SLOW spr round 14 (radius: 5)
[10:04:40 -53560.168874] SLOW spr round 15 (radius: 5)
[10:06:55 -53560.168865] SLOW spr round 16 (radius: 10)
[10:09:12 -53560.168865] SLOW spr round 17 (radius: 15)
[10:13:38 -53557.433701] SLOW spr round 18 (radius: 5)
[10:16:26 -53557.433694] SLOW spr round 19 (radius: 10)
[10:19:06 -53557.433694] SLOW spr round 20 (radius: 15)
[10:23:03 -53557.433694] SLOW spr round 21 (radius: 20)
[10:29:27 -53557.433694] SLOW spr round 22 (radius: 25)
[10:36:30 -53557.433694] Model parameter optimization (eps = 0.100000)

[10:36:37] [worker #0] ML tree search #11, logLikelihood: -53557.399617

[10:36:37 -147589.151618] Initial branch length optimization
[10:36:39 -128007.904013] Model parameter optimization (eps = 10.000000)
[10:37:10 -127213.592363] AUTODETECT spr round 1 (radius: 5)
[10:39:21 -100268.035855] AUTODETECT spr round 2 (radius: 10)
[10:41:52 -81094.362619] AUTODETECT spr round 3 (radius: 15)
[10:44:50 -70314.997920] AUTODETECT spr round 4 (radius: 20)
[10:48:26 -62917.745793] AUTODETECT spr round 5 (radius: 25)
[10:52:49 -62253.366504] SPR radius for FAST iterations: 25 (autodetect)
[10:52:49 -62253.366504] Model parameter optimization (eps = 3.000000)
[10:53:13 -62189.653882] FAST spr round 1 (radius: 25)
[10:56:38 -54079.296255] FAST spr round 2 (radius: 25)
[10:58:58 -53658.981215] FAST spr round 3 (radius: 25)
[11:01:00 -53607.837515] FAST spr round 4 (radius: 25)
[11:02:52 -53599.122783] FAST spr round 5 (radius: 25)
[11:04:24] [worker #1] ML tree search #10, logLikelihood: -53531.705235
[11:04:37 -53597.742511] FAST spr round 6 (radius: 25)
[11:06:20 -53597.741608] Model parameter optimization (eps = 1.000000)
[11:06:31 -53597.089058] SLOW spr round 1 (radius: 5)
[11:08:51 -53570.996755] SLOW spr round 2 (radius: 5)
[11:11:03 -53565.238828] SLOW spr round 3 (radius: 5)
[11:13:11 -53565.238819] SLOW spr round 4 (radius: 10)
[11:15:24 -53562.060254] SLOW spr round 5 (radius: 5)
[11:18:01 -53561.087215] SLOW spr round 6 (radius: 5)
[11:20:25 -53551.432175] SLOW spr round 7 (radius: 5)
[11:22:37 -53550.266408] SLOW spr round 8 (radius: 5)
[11:24:45 -53550.266365] SLOW spr round 9 (radius: 10)
[11:26:57 -53549.278024] SLOW spr round 10 (radius: 5)
[11:29:32 -53547.017735] SLOW spr round 11 (radius: 5)
[11:31:51 -53547.017709] SLOW spr round 12 (radius: 10)
[11:34:06 -53544.947227] SLOW spr round 13 (radius: 5)
[11:36:40 -53544.946147] SLOW spr round 14 (radius: 10)
[11:39:04 -53544.946095] SLOW spr round 15 (radius: 15)
[11:42:49 -53544.946093] SLOW spr round 16 (radius: 20)
[11:48:34 -53544.946093] SLOW spr round 17 (radius: 25)
[11:54:47 -53544.946093] Model parameter optimization (eps = 0.100000)

[11:54:53] [worker #0] ML tree search #13, logLikelihood: -53544.884571

[11:54:53 -147166.729261] Initial branch length optimization
[11:54:56 -127650.925783] Model parameter optimization (eps = 10.000000)
[11:55:23 -126930.820656] AUTODETECT spr round 1 (radius: 5)
[11:57:32 -100984.547905] AUTODETECT spr round 2 (radius: 10)
[12:00:07 -82338.476246] AUTODETECT spr round 3 (radius: 15)
[12:03:08 -67562.873570] AUTODETECT spr round 4 (radius: 20)
[12:06:37 -62133.938447] AUTODETECT spr round 5 (radius: 25)
[12:11:40 -61118.805681] SPR radius for FAST iterations: 25 (autodetect)
[12:11:40 -61118.805681] Model parameter optimization (eps = 3.000000)
[12:12:00 -61036.218835] FAST spr round 1 (radius: 25)
[12:12:37] [worker #1] ML tree search #12, logLikelihood: -53544.939247
[12:15:30 -54087.376563] FAST spr round 2 (radius: 25)
[12:17:54 -53667.667799] FAST spr round 3 (radius: 25)
[12:20:01 -53625.673504] FAST spr round 4 (radius: 25)
[12:21:50 -53625.670162] Model parameter optimization (eps = 1.000000)
[12:22:07 -53624.502554] SLOW spr round 1 (radius: 5)
[12:24:35 -53596.417338] SLOW spr round 2 (radius: 5)
[12:26:54 -53588.956440] SLOW spr round 3 (radius: 5)
[12:29:08 -53582.359772] SLOW spr round 4 (radius: 5)
[12:31:17 -53581.161311] SLOW spr round 5 (radius: 5)
[12:33:25 -53581.161215] SLOW spr round 6 (radius: 10)
[12:35:40 -53568.776992] SLOW spr round 7 (radius: 5)
[12:38:24 -53561.525461] SLOW spr round 8 (radius: 5)
[12:40:49 -53558.559576] SLOW spr round 9 (radius: 5)
[12:43:03 -53558.559510] SLOW spr round 10 (radius: 10)
[12:45:17 -53558.458130] SLOW spr round 11 (radius: 5)
[12:47:56 -53558.457993] SLOW spr round 12 (radius: 10)
[12:50:24 -53558.457993] SLOW spr round 13 (radius: 15)
[12:54:14 -53555.345508] SLOW spr round 14 (radius: 5)
[12:56:59 -53555.345492] SLOW spr round 15 (radius: 10)
[12:59:34 -53555.064483] SLOW spr round 16 (radius: 5)
[13:02:12 -53554.765516] SLOW spr round 17 (radius: 5)
[13:04:32 -53554.765488] SLOW spr round 18 (radius: 10)
[13:06:48 -53554.765488] SLOW spr round 19 (radius: 15)
[13:10:53 -53554.765488] SLOW spr round 20 (radius: 20)
[13:16:15 -53553.617171] SLOW spr round 21 (radius: 5)
[13:19:05 -53548.526684] SLOW spr round 22 (radius: 5)
[13:21:32 -53548.526671] SLOW spr round 23 (radius: 10)
[13:23:52 -53547.900133] SLOW spr round 24 (radius: 5)
[13:26:31 -53544.881551] SLOW spr round 25 (radius: 5)
[13:28:51 -53544.881551] SLOW spr round 26 (radius: 10)
[13:31:08 -53544.881551] SLOW spr round 27 (radius: 15)
[13:35:10 -53544.881551] SLOW spr round 28 (radius: 20)
[13:40:29 -53544.881551] SLOW spr round 29 (radius: 25)
[13:46:52 -53544.881551] Model parameter optimization (eps = 0.100000)

[13:47:01] [worker #0] ML tree search #15, logLikelihood: -53544.787087

[13:47:01 -147777.722727] Initial branch length optimization
[13:47:03 -127815.497588] Model parameter optimization (eps = 10.000000)
[13:47:27 -127224.946936] AUTODETECT spr round 1 (radius: 5)
[13:49:36 -99224.637701] AUTODETECT spr round 2 (radius: 10)
[13:52:07 -79884.314413] AUTODETECT spr round 3 (radius: 15)
[13:55:12 -65158.872195] AUTODETECT spr round 4 (radius: 20)
[13:58:58 -61540.525334] AUTODETECT spr round 5 (radius: 25)
[14:03:33 -61231.403128] SPR radius for FAST iterations: 25 (autodetect)
[14:03:33 -61231.403128] Model parameter optimization (eps = 3.000000)
[14:03:54 -61116.481213] FAST spr round 1 (radius: 25)
[14:07:23 -54009.902351] FAST spr round 2 (radius: 25)
[14:09:48 -53630.134445] FAST spr round 3 (radius: 25)
[14:11:53 -53597.164835] FAST spr round 4 (radius: 25)
[14:13:44 -53596.691032] FAST spr round 5 (radius: 25)
[14:15:29 -53596.690997] Model parameter optimization (eps = 1.000000)
[14:15:47 -53594.458070] SLOW spr round 1 (radius: 5)
[14:18:11 -53570.735992] SLOW spr round 2 (radius: 5)
[14:20:30 -53555.638456] SLOW spr round 3 (radius: 5)
[14:22:40 -53553.178176] SLOW spr round 4 (radius: 5)
[14:24:48 -53553.177901] SLOW spr round 5 (radius: 10)
[14:27:03 -53549.506398] SLOW spr round 6 (radius: 5)
[14:29:45 -53548.686959] SLOW spr round 7 (radius: 5)
[14:32:07 -53548.686900] SLOW spr round 8 (radius: 10)
[14:33:04] [worker #1] ML tree search #14, logLikelihood: -53538.371970
[14:34:29 -53547.303640] SLOW spr round 9 (radius: 5)
[14:37:15 -53542.794223] SLOW spr round 10 (radius: 5)
[14:39:38 -53542.793585] SLOW spr round 11 (radius: 10)
[14:42:00 -53542.673162] SLOW spr round 12 (radius: 5)
[14:44:42 -53542.210325] SLOW spr round 13 (radius: 5)
[14:47:06 -53542.210145] SLOW spr round 14 (radius: 10)
[14:49:27 -53542.210127] SLOW spr round 15 (radius: 15)
[14:53:55 -53532.498145] SLOW spr round 16 (radius: 5)
[14:56:46 -53529.623060] SLOW spr round 17 (radius: 5)
[14:59:16 -53529.326789] SLOW spr round 18 (radius: 5)
[15:01:33 -53529.326786] SLOW spr round 19 (radius: 10)
[15:03:50 -53529.326784] SLOW spr round 20 (radius: 15)
[15:08:29 -53526.274046] SLOW spr round 21 (radius: 5)
[15:11:19 -53526.045493] SLOW spr round 22 (radius: 5)
[15:13:47 -53526.045478] SLOW spr round 23 (radius: 10)
[15:16:10 -53526.045470] SLOW spr round 24 (radius: 15)
[15:20:30 -53521.676353] SLOW spr round 25 (radius: 5)
[15:23:17 -53521.676320] SLOW spr round 26 (radius: 10)
[15:25:56 -53521.676303] SLOW spr round 27 (radius: 15)
[15:29:57 -53521.676292] SLOW spr round 28 (radius: 20)
[15:36:25 -53515.481736] SLOW spr round 29 (radius: 5)
[15:39:16 -53512.436839] SLOW spr round 30 (radius: 5)
[15:41:44 -53512.436807] SLOW spr round 31 (radius: 10)
[15:44:05 -53512.436804] SLOW spr round 32 (radius: 15)
[15:48:17 -53512.436801] SLOW spr round 33 (radius: 20)
[15:51:41] [worker #1] ML tree search #16, logLikelihood: -53562.871592
[15:54:28 -53512.436799] SLOW spr round 34 (radius: 25)
[16:00:41 -53512.436796] Model parameter optimization (eps = 0.100000)

[16:00:50] [worker #0] ML tree search #17, logLikelihood: -53512.337313

[16:00:50 -147394.764861] Initial branch length optimization
[16:00:53 -127698.745920] Model parameter optimization (eps = 10.000000)
[16:01:19 -126929.783476] AUTODETECT spr round 1 (radius: 5)
[16:03:31 -99913.664775] AUTODETECT spr round 2 (radius: 10)
[16:06:04 -80124.160047] AUTODETECT spr round 3 (radius: 15)
[16:09:02 -65892.989398] AUTODETECT spr round 4 (radius: 20)
[16:12:26 -61811.280171] AUTODETECT spr round 5 (radius: 25)
[16:16:24 -60671.444513] SPR radius for FAST iterations: 25 (autodetect)
[16:16:24 -60671.444513] Model parameter optimization (eps = 3.000000)
[16:16:52 -60597.899401] FAST spr round 1 (radius: 25)
[16:20:09 -53941.231839] FAST spr round 2 (radius: 25)
[16:22:37 -53687.378024] FAST spr round 3 (radius: 25)
[16:24:41 -53650.854745] FAST spr round 4 (radius: 25)
[16:26:36 -53645.951016] FAST spr round 5 (radius: 25)
[16:28:25 -53639.011282] FAST spr round 6 (radius: 25)
[16:30:08 -53637.457882] FAST spr round 7 (radius: 25)
[16:31:49 -53637.457881] Model parameter optimization (eps = 1.000000)
[16:31:58 -53636.980233] SLOW spr round 1 (radius: 5)
[16:34:20 -53611.788382] SLOW spr round 2 (radius: 5)
[16:36:36 -53606.657752] SLOW spr round 3 (radius: 5)
[16:38:46 -53606.655565] SLOW spr round 4 (radius: 10)
[16:41:00 -53606.435570] SLOW spr round 5 (radius: 5)
[16:43:41 -53606.193180] SLOW spr round 6 (radius: 5)
[16:46:03 -53606.193043] SLOW spr round 7 (radius: 10)
[16:48:22 -53606.171718] SLOW spr round 8 (radius: 15)
[16:52:35 -53605.272360] SLOW spr round 9 (radius: 5)
[16:55:24 -53601.622144] SLOW spr round 10 (radius: 5)
[16:57:52 -53597.475847] SLOW spr round 11 (radius: 5)
[17:00:08 -53597.475669] SLOW spr round 12 (radius: 10)
[17:02:25 -53595.276350] SLOW spr round 13 (radius: 5)
[17:05:08 -53584.120141] SLOW spr round 14 (radius: 5)
[17:07:31 -53584.120042] SLOW spr round 15 (radius: 10)
[17:09:51 -53581.687565] SLOW spr round 16 (radius: 5)
[17:12:30 -53581.687563] SLOW spr round 17 (radius: 10)
[17:15:01 -53581.687563] SLOW spr round 18 (radius: 15)
[17:19:01 -53581.109231] SLOW spr round 19 (radius: 5)
[17:21:47 -53581.109054] SLOW spr round 20 (radius: 10)
[17:24:24 -53581.109048] SLOW spr round 21 (radius: 15)
[17:28:21 -53581.109048] SLOW spr round 22 (radius: 20)
[17:34:47 -53580.653702] SLOW spr round 23 (radius: 5)
[17:37:38 -53575.502200] SLOW spr round 24 (radius: 5)
[17:40:05 -53575.502188] SLOW spr round 25 (radius: 10)
[17:42:27 -53575.390786] SLOW spr round 26 (radius: 5)
[17:45:06 -53575.359529] SLOW spr round 27 (radius: 10)
[17:47:35 -53574.805974] SLOW spr round 28 (radius: 5)
[17:50:15 -53571.711478] SLOW spr round 29 (radius: 5)
[17:52:36 -53571.711321] SLOW spr round 30 (radius: 10)
[17:54:54 -53571.711321] SLOW spr round 31 (radius: 15)
[17:59:11 -53571.711321] SLOW spr round 32 (radius: 20)
[18:05:25 -53571.711321] SLOW spr round 33 (radius: 25)
[18:07:59] [worker #1] ML tree search #18, logLikelihood: -53540.047639
[18:12:06 -53571.711321] Model parameter optimization (eps = 0.100000)

[18:12:12] [worker #0] ML tree search #19, logLikelihood: -53571.678050

[19:43:23] [worker #1] ML tree search #20, logLikelihood: -53551.505776

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.208879,0.300042) (0.190443,0.560700) (0.515249,0.993850) (0.085429,3.727849) 
   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: -53512.337313

AIC score: 111034.674626 / AICc score: 8155094.674626 / BIC score: 116572.833366
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=117).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/P23083/3_mltree/P23083.raxml.log

Analysis started: 10-Jul-2021 13:47:18 / finished: 11-Jul-2021 09:30:41

Elapsed time: 71003.250 seconds