RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab.
Developed by: Alexey M. Kozlov and Alexandros Stamatakis.
Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth.
Latest version: https://github.com/amkozlov/raxml-ng
Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml

System: Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 40 cores, 376 GB RAM

RAxML-NG was called at 05-Jul-2021 21:40:07 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/2_msa/Q6PDB4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4 --seed 2 --threads 8 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/2_msa/Q6PDB4_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 751 sites

WARNING: Sequences tr_A0A2I3T1I2_A0A2I3T1I2_PANTR_9598 and tr_A0A2R9C8X5_A0A2R9C8X5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8QIB0_A0A2J8QIB0_PANTR_9598 and sp_Q5MCW4_ZN569_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A1D5QC17_A0A1D5QC17_MACMU_9544 and tr_A0A2K6BUH3_A0A2K6BUH3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A1D5R704_A0A1D5R704_MACMU_9544 and tr_A0A2K6B9B3_A0A2K6B9B3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F6UR85_F6UR85_MACMU_9544 and tr_A0A2K6ADH3_A0A2K6ADH3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F6V0U3_F6V0U3_MACMU_9544 and tr_G7PYP5_G7PYP5_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7DJD1_F7DJD1_MACMU_9544 and tr_G7PZ21_G7PZ21_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7DJD1_F7DJD1_MACMU_9544 and tr_A0A2K5NBK9_A0A2K5NBK9_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7DJD1_F7DJD1_MACMU_9544 and tr_A0A2K6CU82_A0A2K6CU82_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7FTJ3_F7FTJ3_MACMU_9544 and tr_A0A2K6CFR0_A0A2K6CFR0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7FX09_F7FX09_MACMU_9544 and tr_A0A2K6B732_A0A2K6B732_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GTJ8_F7GTJ8_MACMU_9544 and tr_A0A2K6BJH0_A0A2K6BJH0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7H368_F7H368_MACMU_9544 and tr_A0A2K6E4J5_A0A2K6E4J5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2K5LAJ0_A0A2K5LAJ0_CERAT_9531 and tr_A0A2K5Y6G8_A0A2K5Y6G8_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K5NJ59_A0A2K5NJ59_CERAT_9531 and tr_A0A2K5YNA2_A0A2K5YNA2_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: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.reduced.phy

Alignment comprises 1 partitions and 751 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 751 / 751
Gaps: 18.61 %
Invariant sites: 0.27 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 188 / 15040
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -963134.229701] Initial branch length optimization
[00:00:04 -856368.661886] Model parameter optimization (eps = 10.000000)
[00:00:38 -852879.908731] AUTODETECT spr round 1 (radius: 5)
[00:03:39 -667829.024276] AUTODETECT spr round 2 (radius: 10)
[00:07:09 -442688.797062] AUTODETECT spr round 3 (radius: 15)
[00:10:26 -359633.325876] AUTODETECT spr round 4 (radius: 20)
[00:14:22 -344369.196199] AUTODETECT spr round 5 (radius: 25)
[00:19:14 -343730.770035] SPR radius for FAST iterations: 25 (autodetect)
[00:19:14 -343730.770035] Model parameter optimization (eps = 3.000000)
[00:19:40 -343422.076392] FAST spr round 1 (radius: 25)
[00:23:15 -310257.182517] FAST spr round 2 (radius: 25)
[00:26:03 -309333.541428] FAST spr round 3 (radius: 25)
[00:28:25 -309269.334057] FAST spr round 4 (radius: 25)
[00:30:36 -309255.475450] FAST spr round 5 (radius: 25)
[00:32:41 -309243.976171] FAST spr round 6 (radius: 25)
[00:34:43 -309243.976037] Model parameter optimization (eps = 1.000000)
[00:34:55 -309242.811016] SLOW spr round 1 (radius: 5)
[00:37:48 -309112.920935] SLOW spr round 2 (radius: 5)
[00:40:38 -309083.428962] SLOW spr round 3 (radius: 5)
[00:43:19 -309083.280876] SLOW spr round 4 (radius: 5)
[00:45:59 -309083.280856] SLOW spr round 5 (radius: 10)
[00:48:58 -309083.157375] SLOW spr round 6 (radius: 5)
[00:52:27 -309083.157371] SLOW spr round 7 (radius: 10)
[00:55:47 -309081.935463] SLOW spr round 8 (radius: 5)
[00:58:56 -309081.251354] SLOW spr round 9 (radius: 5)
[01:01:46 -309081.251349] SLOW spr round 10 (radius: 10)
[01:04:45 -309080.928973] SLOW spr round 11 (radius: 5)
[01:08:00 -309080.928958] SLOW spr round 12 (radius: 10)
[01:11:18 -309080.928958] SLOW spr round 13 (radius: 15)
[01:16:22 -309073.863159] SLOW spr round 14 (radius: 5)
[01:19:45 -309072.280581] SLOW spr round 15 (radius: 5)
[01:22:40 -309072.280481] SLOW spr round 16 (radius: 10)
[01:25:44 -309072.280481] SLOW spr round 17 (radius: 15)
[01:30:37] [worker #1] ML tree search #2, logLikelihood: -309073.124188
[01:30:46 -309072.280480] SLOW spr round 18 (radius: 20)
[01:39:07 -309072.280480] SLOW spr round 19 (radius: 25)
[01:49:07 -309072.280480] Model parameter optimization (eps = 0.100000)

[01:49:22] [worker #0] ML tree search #1, logLikelihood: -309071.505828

[01:49:22 -962049.482135] Initial branch length optimization
[01:49:26 -856415.626760] Model parameter optimization (eps = 10.000000)
[01:50:03 -853068.277011] AUTODETECT spr round 1 (radius: 5)
[01:53:02 -673300.646062] AUTODETECT spr round 2 (radius: 10)
[01:56:17 -450581.560191] AUTODETECT spr round 3 (radius: 15)
[01:59:34 -365586.504931] AUTODETECT spr round 4 (radius: 20)
[02:03:39 -349691.592603] AUTODETECT spr round 5 (radius: 25)
[02:08:23 -347006.139028] SPR radius for FAST iterations: 25 (autodetect)
[02:08:23 -347006.139028] Model parameter optimization (eps = 3.000000)
[02:08:48 -346714.762137] FAST spr round 1 (radius: 25)
[02:12:26 -310897.525213] FAST spr round 2 (radius: 25)
[02:15:15 -309377.664090] FAST spr round 3 (radius: 25)
[02:17:45 -309286.663389] FAST spr round 4 (radius: 25)
[02:20:02 -309260.490604] FAST spr round 5 (radius: 25)
[02:22:06 -309254.729906] FAST spr round 6 (radius: 25)
[02:24:07 -309253.143786] FAST spr round 7 (radius: 25)
[02:26:06 -309253.143656] Model parameter optimization (eps = 1.000000)
[02:26:23 -309237.956177] SLOW spr round 1 (radius: 5)
[02:29:18 -309150.561210] SLOW spr round 2 (radius: 5)
[02:32:08 -309140.231091] SLOW spr round 3 (radius: 5)
[02:34:46 -309138.131394] SLOW spr round 4 (radius: 5)
[02:37:22 -309138.131376] SLOW spr round 5 (radius: 10)
[02:40:16 -309131.966052] SLOW spr round 6 (radius: 5)
[02:43:31 -309105.809521] SLOW spr round 7 (radius: 5)
[02:46:36 -309085.209847] SLOW spr round 8 (radius: 5)
[02:49:20 -309084.234920] SLOW spr round 9 (radius: 5)
[02:51:58 -309084.234803] SLOW spr round 10 (radius: 10)
[02:54:54 -309068.509869] SLOW spr round 11 (radius: 5)
[02:58:15 -309057.412872] SLOW spr round 12 (radius: 5)
[03:01:06 -309057.114804] SLOW spr round 13 (radius: 5)
[03:03:47 -309057.114792] SLOW spr round 14 (radius: 10)
[03:06:39 -309056.340584] SLOW spr round 15 (radius: 5)
[03:09:05] [worker #1] ML tree search #4, logLikelihood: -309044.289878
[03:09:54 -309048.996400] SLOW spr round 16 (radius: 5)
[03:12:45 -309048.996398] SLOW spr round 17 (radius: 10)
[03:15:43 -309047.839507] SLOW spr round 18 (radius: 5)
[03:18:51 -309047.839486] SLOW spr round 19 (radius: 10)
[03:22:03 -309047.839486] SLOW spr round 20 (radius: 15)
[03:26:51 -309047.839486] SLOW spr round 21 (radius: 20)
[03:34:50 -309047.839486] SLOW spr round 22 (radius: 25)
[03:44:19 -309047.839486] Model parameter optimization (eps = 0.100000)

[03:44:31] [worker #0] ML tree search #3, logLikelihood: -309047.149152

[03:44:31 -959443.521888] Initial branch length optimization
[03:44:35 -854609.269429] Model parameter optimization (eps = 10.000000)
[03:45:10 -851251.703602] AUTODETECT spr round 1 (radius: 5)
[03:48:07 -666445.328895] AUTODETECT spr round 2 (radius: 10)
[03:51:22 -433905.078243] AUTODETECT spr round 3 (radius: 15)
[03:54:29 -368948.491710] AUTODETECT spr round 4 (radius: 20)
[03:58:04 -345776.422317] AUTODETECT spr round 5 (radius: 25)
[04:01:57 -340393.912626] SPR radius for FAST iterations: 25 (autodetect)
[04:01:57 -340393.912626] Model parameter optimization (eps = 3.000000)
[04:02:27 -340067.904346] FAST spr round 1 (radius: 25)
[04:06:03 -310507.399631] FAST spr round 2 (radius: 25)
[04:08:47 -309315.205779] FAST spr round 3 (radius: 25)
[04:11:08 -309267.821683] FAST spr round 4 (radius: 25)
[04:13:17 -309266.162436] FAST spr round 5 (radius: 25)
[04:15:20 -309258.968683] FAST spr round 6 (radius: 25)
[04:17:19 -309258.968625] Model parameter optimization (eps = 1.000000)
[04:17:41 -309232.573785] SLOW spr round 1 (radius: 5)
[04:20:35 -309151.903520] SLOW spr round 2 (radius: 5)
[04:23:15 -309151.820901] SLOW spr round 3 (radius: 10)
[04:26:07 -309135.780572] SLOW spr round 4 (radius: 5)
[04:29:20 -309127.622158] SLOW spr round 5 (radius: 5)
[04:29:50] [worker #1] ML tree search #6, logLikelihood: -309075.756586
[04:32:11 -309121.738638] SLOW spr round 6 (radius: 5)
[04:34:54 -309117.687878] SLOW spr round 7 (radius: 5)
[04:37:31 -309117.687839] SLOW spr round 8 (radius: 10)
[04:40:21 -309113.674610] SLOW spr round 9 (radius: 5)
[04:43:39 -309090.014531] SLOW spr round 10 (radius: 5)
[04:46:29 -309088.914469] SLOW spr round 11 (radius: 5)
[04:49:16 -309074.850545] SLOW spr round 12 (radius: 5)
[04:51:53 -309074.850522] SLOW spr round 13 (radius: 10)
[04:54:44 -309074.850522] SLOW spr round 14 (radius: 15)
[04:59:59 -309074.369939] SLOW spr round 15 (radius: 5)
[05:03:20 -309072.764483] SLOW spr round 16 (radius: 5)
[05:06:16 -309072.764442] SLOW spr round 17 (radius: 10)
[05:09:15 -309072.764442] SLOW spr round 18 (radius: 15)
[05:14:14 -309072.764442] SLOW spr round 19 (radius: 20)
[05:22:03 -309072.764442] SLOW spr round 20 (radius: 25)
[05:31:32 -309072.764442] Model parameter optimization (eps = 0.100000)

[05:31:44] [worker #0] ML tree search #5, logLikelihood: -309072.503872

[05:31:44 -958779.729473] Initial branch length optimization
[05:31:49 -854628.508392] Model parameter optimization (eps = 10.000000)
[05:32:25 -851204.653742] AUTODETECT spr round 1 (radius: 5)
[05:35:21 -655639.379122] AUTODETECT spr round 2 (radius: 10)
[05:38:54 -437068.013656] AUTODETECT spr round 3 (radius: 15)
[05:42:12 -364450.088294] AUTODETECT spr round 4 (radius: 20)
[05:45:42 -345026.348010] AUTODETECT spr round 5 (radius: 25)
[05:49:38 -342502.533799] SPR radius for FAST iterations: 25 (autodetect)
[05:49:38 -342502.533799] Model parameter optimization (eps = 3.000000)
[05:50:11 -342189.350364] FAST spr round 1 (radius: 25)
[05:53:50 -310399.794239] FAST spr round 2 (radius: 25)
[05:56:42 -309375.480079] FAST spr round 3 (radius: 25)
[05:59:09 -309256.903219] FAST spr round 4 (radius: 25)
[06:01:18 -309244.958986] FAST spr round 5 (radius: 25)
[06:03:19 -309244.958871] Model parameter optimization (eps = 1.000000)
[06:03:36 -309225.303788] SLOW spr round 1 (radius: 5)
[06:06:27 -309099.092057] SLOW spr round 2 (radius: 5)
[06:09:12 -309083.391072] SLOW spr round 3 (radius: 5)
[06:11:48 -309083.391047] SLOW spr round 4 (radius: 10)
[06:14:40 -309073.994697] SLOW spr round 5 (radius: 5)
[06:16:17] [worker #1] ML tree search #8, logLikelihood: -309086.321675
[06:17:51 -309069.928394] SLOW spr round 6 (radius: 5)
[06:20:43 -309067.522502] SLOW spr round 7 (radius: 5)
[06:23:24 -309067.522367] SLOW spr round 8 (radius: 10)
[06:26:17 -309067.434305] SLOW spr round 9 (radius: 15)
[06:31:28 -309067.434191] SLOW spr round 10 (radius: 20)
[06:39:37 -309067.434191] SLOW spr round 11 (radius: 25)
[06:49:29 -309067.434190] Model parameter optimization (eps = 0.100000)

[06:49:41] [worker #0] ML tree search #7, logLikelihood: -309066.780666

[06:49:41 -961193.020650] Initial branch length optimization
[06:49:46 -856410.091317] Model parameter optimization (eps = 10.000000)
[06:50:29 -853035.221010] AUTODETECT spr round 1 (radius: 5)
[06:53:26 -674469.015637] AUTODETECT spr round 2 (radius: 10)
[06:56:59 -454069.572858] AUTODETECT spr round 3 (radius: 15)
[07:00:15 -364414.022600] AUTODETECT spr round 4 (radius: 20)
[07:04:27 -347766.676335] AUTODETECT spr round 5 (radius: 25)
[07:09:27 -346587.532923] SPR radius for FAST iterations: 25 (autodetect)
[07:09:27 -346587.532923] Model parameter optimization (eps = 3.000000)
[07:09:54 -346305.010275] FAST spr round 1 (radius: 25)
[07:13:42 -310619.694257] FAST spr round 2 (radius: 25)
[07:16:38 -309413.175369] FAST spr round 3 (radius: 25)
[07:19:14 -309280.666754] FAST spr round 4 (radius: 25)
[07:21:25 -309270.312207] FAST spr round 5 (radius: 25)
[07:23:34 -309258.587664] FAST spr round 6 (radius: 25)
[07:25:35 -309258.587618] Model parameter optimization (eps = 1.000000)
[07:25:52 -309250.174410] SLOW spr round 1 (radius: 5)
[07:28:46 -309160.043085] SLOW spr round 2 (radius: 5)
[07:31:32 -309150.750221] SLOW spr round 3 (radius: 5)
[07:34:10 -309149.030833] SLOW spr round 4 (radius: 5)
[07:36:46 -309149.030756] SLOW spr round 5 (radius: 10)
[07:39:43 -309107.471761] SLOW spr round 6 (radius: 5)
[07:42:59 -309092.964360] SLOW spr round 7 (radius: 5)
[07:45:52 -309084.735768] SLOW spr round 8 (radius: 5)
[07:48:35 -309083.459744] SLOW spr round 9 (radius: 5)
[07:51:14 -309082.694906] SLOW spr round 10 (radius: 5)
[07:53:50 -309082.694850] SLOW spr round 11 (radius: 10)
[07:56:43 -309078.063089] SLOW spr round 12 (radius: 5)
[07:59:54 -309078.063069] SLOW spr round 13 (radius: 10)
[08:03:11 -309078.063069] SLOW spr round 14 (radius: 15)
[08:07:22] [worker #1] ML tree search #10, logLikelihood: -309065.167247
[08:08:23 -309078.063068] SLOW spr round 15 (radius: 20)
[08:17:15 -309078.063068] SLOW spr round 16 (radius: 25)
[08:27:45 -309078.063068] Model parameter optimization (eps = 0.100000)

[08:27:51] [worker #0] ML tree search #9, logLikelihood: -309077.987321

[08:27:51 -958269.902107] Initial branch length optimization
[08:27:55 -853605.383903] Model parameter optimization (eps = 10.000000)
[08:28:31 -850428.903903] AUTODETECT spr round 1 (radius: 5)
[08:31:30 -660935.880470] AUTODETECT spr round 2 (radius: 10)
[08:34:49 -456616.552215] AUTODETECT spr round 3 (radius: 15)
[08:38:10 -362372.707090] AUTODETECT spr round 4 (radius: 20)
[08:41:56 -346651.235435] AUTODETECT spr round 5 (radius: 25)
[08:46:14 -343736.063980] SPR radius for FAST iterations: 25 (autodetect)
[08:46:14 -343736.063980] Model parameter optimization (eps = 3.000000)
[08:46:40 -343493.854902] FAST spr round 1 (radius: 25)
[08:50:12 -310636.039222] FAST spr round 2 (radius: 25)
[08:53:01 -309324.506393] FAST spr round 3 (radius: 25)
[08:55:28 -309178.465901] FAST spr round 4 (radius: 25)
[08:57:37 -309167.862647] FAST spr round 5 (radius: 25)
[08:59:40 -309160.632457] FAST spr round 6 (radius: 25)
[09:01:40 -309156.309244] FAST spr round 7 (radius: 25)
[09:03:40 -309152.976021] FAST spr round 8 (radius: 25)
[09:05:36 -309152.976015] Model parameter optimization (eps = 1.000000)
[09:05:52 -309146.207323] SLOW spr round 1 (radius: 5)
[09:08:47 -309081.313331] SLOW spr round 2 (radius: 5)
[09:11:32 -309078.930150] SLOW spr round 3 (radius: 5)
[09:14:11 -309078.930037] SLOW spr round 4 (radius: 10)
[09:17:02 -309059.489226] SLOW spr round 5 (radius: 5)
[09:20:13 -309057.250541] SLOW spr round 6 (radius: 5)
[09:23:04 -309054.958653] SLOW spr round 7 (radius: 5)
[09:25:46 -309052.676309] SLOW spr round 8 (radius: 5)
[09:28:24 -309051.885397] SLOW spr round 9 (radius: 5)
[09:29:32] [worker #1] ML tree search #12, logLikelihood: -309087.651730
[09:31:00 -309051.885342] SLOW spr round 10 (radius: 10)
[09:33:49 -309051.885342] SLOW spr round 11 (radius: 15)
[09:39:02 -309051.885342] SLOW spr round 12 (radius: 20)
[09:47:01 -309051.885342] SLOW spr round 13 (radius: 25)
[09:57:15 -309051.885342] Model parameter optimization (eps = 0.100000)

[09:57:20] [worker #0] ML tree search #11, logLikelihood: -309051.857242

[09:57:20 -960677.264740] Initial branch length optimization
[09:57:25 -853716.116514] Model parameter optimization (eps = 10.000000)
[09:57:59 -850323.693190] AUTODETECT spr round 1 (radius: 5)
[10:01:00 -663160.564125] AUTODETECT spr round 2 (radius: 10)
[10:04:21 -436313.327289] AUTODETECT spr round 3 (radius: 15)
[10:07:42 -356983.155769] AUTODETECT spr round 4 (radius: 20)
[10:11:31 -341836.159985] AUTODETECT spr round 5 (radius: 25)
[10:16:20 -340998.613448] SPR radius for FAST iterations: 25 (autodetect)
[10:16:20 -340998.613448] Model parameter optimization (eps = 3.000000)
[10:16:46 -340708.489738] FAST spr round 1 (radius: 25)
[10:20:22 -310224.335959] FAST spr round 2 (radius: 25)
[10:23:02 -309317.447238] FAST spr round 3 (radius: 25)
[10:25:27 -309219.403996] FAST spr round 4 (radius: 25)
[10:27:38 -309192.799266] FAST spr round 5 (radius: 25)
[10:29:44 -309171.612472] FAST spr round 6 (radius: 25)
[10:31:45 -309165.296563] FAST spr round 7 (radius: 25)
[10:33:44 -309165.296553] Model parameter optimization (eps = 1.000000)
[10:34:01 -309160.760440] SLOW spr round 1 (radius: 5)
[10:37:11 -309081.402488] SLOW spr round 2 (radius: 5)
[10:39:59 -309063.014004] SLOW spr round 3 (radius: 5)
[10:42:38 -309059.494147] SLOW spr round 4 (radius: 5)
[10:45:13 -309059.493644] SLOW spr round 5 (radius: 10)
[10:48:05 -309053.556654] SLOW spr round 6 (radius: 5)
[10:51:16 -309051.249082] SLOW spr round 7 (radius: 5)
[10:54:06 -309051.248995] SLOW spr round 8 (radius: 10)
[10:57:05 -309051.248995] SLOW spr round 9 (radius: 15)
[11:02:01 -309051.248995] SLOW spr round 10 (radius: 20)
[11:02:25] [worker #1] ML tree search #14, logLikelihood: -309065.526274
[11:09:56 -309051.248994] SLOW spr round 11 (radius: 25)
[11:19:18 -309051.248994] Model parameter optimization (eps = 0.100000)

[11:19:24] [worker #0] ML tree search #13, logLikelihood: -309051.193902

[11:19:24 -958337.518377] Initial branch length optimization
[11:19:30 -855933.523651] Model parameter optimization (eps = 10.000000)
[11:20:03 -852433.109081] AUTODETECT spr round 1 (radius: 5)
[11:23:04 -662449.220835] AUTODETECT spr round 2 (radius: 10)
[11:26:38 -440136.301872] AUTODETECT spr round 3 (radius: 15)
[11:30:04 -360566.116608] AUTODETECT spr round 4 (radius: 20)
[11:33:39 -353401.578273] AUTODETECT spr round 5 (radius: 25)
[11:38:33 -349863.577812] SPR radius for FAST iterations: 25 (autodetect)
[11:38:33 -349863.577812] Model parameter optimization (eps = 3.000000)
[11:39:03 -349562.894135] FAST spr round 1 (radius: 25)
[11:42:48 -311069.768725] FAST spr round 2 (radius: 25)
[11:45:40 -309410.825752] FAST spr round 3 (radius: 25)
[11:48:05 -309266.628242] FAST spr round 4 (radius: 25)
[11:50:23 -309201.105809] FAST spr round 5 (radius: 25)
[11:52:31 -309198.931505] FAST spr round 6 (radius: 25)
[11:54:31 -309198.931505] Model parameter optimization (eps = 1.000000)
[11:54:46 -309197.335476] SLOW spr round 1 (radius: 5)
[11:57:43 -309106.758592] SLOW spr round 2 (radius: 5)
[12:00:31 -309097.814139] SLOW spr round 3 (radius: 5)
[12:03:15 -309081.891434] SLOW spr round 4 (radius: 5)
[12:05:57 -309075.150367] SLOW spr round 5 (radius: 5)
[12:08:40 -309065.966522] SLOW spr round 6 (radius: 5)
[12:11:18 -309064.974116] SLOW spr round 7 (radius: 5)
[12:13:52 -309064.974004] SLOW spr round 8 (radius: 10)
[12:16:42 -309064.974003] SLOW spr round 9 (radius: 15)
[12:22:02 -309059.697122] SLOW spr round 10 (radius: 5)
[12:25:23 -309057.926580] SLOW spr round 11 (radius: 5)
[12:26:01] [worker #1] ML tree search #16, logLikelihood: -309081.008087
[12:28:21 -309056.065269] SLOW spr round 12 (radius: 5)
[12:31:05 -309056.065240] SLOW spr round 13 (radius: 10)
[12:34:01 -309056.065240] SLOW spr round 14 (radius: 15)
[12:39:14 -309056.065240] SLOW spr round 15 (radius: 20)
[12:47:45 -309056.065239] SLOW spr round 16 (radius: 25)
[12:58:16 -309056.065239] Model parameter optimization (eps = 0.100000)

[12:58:27] [worker #0] ML tree search #15, logLikelihood: -309055.724996

[12:58:27 -956564.804062] Initial branch length optimization
[12:58:31 -853418.174403] Model parameter optimization (eps = 10.000000)
[12:59:04 -850162.632755] AUTODETECT spr round 1 (radius: 5)
[13:02:02 -653784.360886] AUTODETECT spr round 2 (radius: 10)
[13:05:25 -450517.446167] AUTODETECT spr round 3 (radius: 15)
[13:08:33 -366957.899876] AUTODETECT spr round 4 (radius: 20)
[13:12:50 -346978.029718] AUTODETECT spr round 5 (radius: 25)
[13:17:32 -344463.847936] SPR radius for FAST iterations: 25 (autodetect)
[13:17:32 -344463.847936] Model parameter optimization (eps = 3.000000)
[13:18:01 -344202.436809] FAST spr round 1 (radius: 25)
[13:21:34 -310350.863469] FAST spr round 2 (radius: 25)
[13:24:18 -309323.948607] FAST spr round 3 (radius: 25)
[13:26:40 -309232.595251] FAST spr round 4 (radius: 25)
[13:28:52 -309203.678090] FAST spr round 5 (radius: 25)
[13:30:57 -309200.025193] FAST spr round 6 (radius: 25)
[13:32:56 -309200.025186] Model parameter optimization (eps = 1.000000)
[13:33:12 -309197.047376] SLOW spr round 1 (radius: 5)
[13:36:09 -309097.105925] SLOW spr round 2 (radius: 5)
[13:38:57 -309061.351993] SLOW spr round 3 (radius: 5)
[13:41:33 -309061.351955] SLOW spr round 4 (radius: 10)
[13:44:25 -309054.403849] SLOW spr round 5 (radius: 5)
[13:47:36 -309052.408098] SLOW spr round 6 (radius: 5)
[13:50:26 -309052.407974] SLOW spr round 7 (radius: 10)
[13:53:26 -309050.712477] SLOW spr round 8 (radius: 5)
[13:56:35 -309050.245701] SLOW spr round 9 (radius: 5)
[13:59:24 -309050.245700] SLOW spr round 10 (radius: 10)
[14:02:22 -309050.245699] SLOW spr round 11 (radius: 15)
[14:07:15 -309050.245699] SLOW spr round 12 (radius: 20)
[14:14:56 -309050.245699] SLOW spr round 13 (radius: 25)
[14:24:08 -309050.245699] Model parameter optimization (eps = 0.100000)

[14:24:16] [worker #0] ML tree search #17, logLikelihood: -309050.082246

[14:24:16 -961287.189317] Initial branch length optimization
[14:24:20 -856117.704680] Model parameter optimization (eps = 10.000000)
[14:25:04 -852593.240015] AUTODETECT spr round 1 (radius: 5)
[14:28:02 -655333.052413] AUTODETECT spr round 2 (radius: 10)
[14:31:35 -435729.830715] AUTODETECT spr round 3 (radius: 15)
[14:34:54 -358437.154052] AUTODETECT spr round 4 (radius: 20)
[14:37:10] [worker #1] ML tree search #18, logLikelihood: -309046.096484
[14:39:02 -340297.859085] AUTODETECT spr round 5 (radius: 25)
[14:43:38 -339204.431458] SPR radius for FAST iterations: 25 (autodetect)
[14:43:38 -339204.431458] Model parameter optimization (eps = 3.000000)
[14:44:05 -338908.487998] FAST spr round 1 (radius: 25)
[14:47:16 -310700.509982] FAST spr round 2 (radius: 25)
[14:49:48 -309411.187653] FAST spr round 3 (radius: 25)
[14:52:05 -309290.058127] FAST spr round 4 (radius: 25)
[14:54:04 -309263.682205] FAST spr round 5 (radius: 25)
[14:55:55 -309263.681836] Model parameter optimization (eps = 1.000000)
[14:56:07 -309261.770199] SLOW spr round 1 (radius: 5)
[14:58:47 -309185.444695] SLOW spr round 2 (radius: 5)
[15:01:18 -309167.548292] SLOW spr round 3 (radius: 5)
[15:03:40 -309167.548281] SLOW spr round 4 (radius: 10)
[15:06:19 -309158.346979] SLOW spr round 5 (radius: 5)
[15:09:32 -309153.769653] SLOW spr round 6 (radius: 5)
[15:12:07 -309153.769489] SLOW spr round 7 (radius: 10)
[15:14:50 -309153.195555] SLOW spr round 8 (radius: 5)
[15:17:45 -309144.558066] SLOW spr round 9 (radius: 5)
[15:20:25 -309123.662016] SLOW spr round 10 (radius: 5)
[15:23:20 -309113.693408] SLOW spr round 11 (radius: 5)
[15:26:10 -309110.480977] SLOW spr round 12 (radius: 5)
[15:29:04 -309109.943353] SLOW spr round 13 (radius: 5)
[15:31:49 -309109.943309] SLOW spr round 14 (radius: 10)
[15:34:45 -309109.943309] SLOW spr round 15 (radius: 15)
[15:40:40 -309109.943309] SLOW spr round 16 (radius: 20)
[15:49:28 -309109.943309] SLOW spr round 17 (radius: 25)
[16:00:28 -309109.943309] Model parameter optimization (eps = 0.100000)

[16:00:39] [worker #0] ML tree search #19, logLikelihood: -309109.832419

[16:06:23] [worker #1] ML tree search #20, logLikelihood: -309078.976574

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.141548,0.169014) (0.127006,0.612080) (0.359317,0.758247) (0.372128,1.681913) 
   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: -309044.289878

AIC score: 622098.579756 / AICc score: 8666158.579756 / BIC score: 631364.498088
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=751).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q6PDB4/3_mltree/Q6PDB4.raxml.log

Analysis started: 05-Jul-2021 21:40:07 / finished: 06-Jul-2021 13:46:31

Elapsed time: 57983.923 seconds

Consumed energy: 3826.688 Wh (= 19 km in an electric car, or 96 km with an e-scooter!)