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) CPU E5-2690 v4 @ 2.60GHz, 28 cores, 251 GB RAM

RAxML-NG was called at 02-Jul-2021 15:13:29 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/2_msa/Q9ULW8_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/3_mltree/Q9ULW8 --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/Q9ULW8/2_msa/Q9ULW8_trimmed_msa.fasta
[00:00:00] Loaded alignment with 405 taxa and 659 sites

WARNING: Sequences tr_H2PY57_H2PY57_PANTR_9598 and sp_Q9Y2J8_PADI2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H2PY57_H2PY57_PANTR_9598 and tr_A0A2R9BZA0_A0A2R9BZA0_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2PY58_H2PY58_PANTR_9598 and tr_A0A2R9CST9_A0A2R9CST9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_C6H7J6_C6H7J6_AJECH_544712 and tr_F0UBC3_F0UBC3_AJEC8_544711 are exactly identical!
WARNING: Sequences tr_F6X3G4_F6X3G4_MACMU_9544 and tr_G7NUR4_G7NUR4_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G7MH55_G7MH55_MACMU_9544 and tr_A0A0D9S8F7_A0A0D9S8F7_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G7MH55_G7MH55_MACMU_9544 and tr_A0A2K5YUS3_A0A2K5YUS3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2K5NBJ7_A0A2K5NBJ7_CERAT_9531 and tr_A0A2K5Y509_A0A2K5Y509_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2Y9LKG5_A0A2Y9LKG5_DELLE_9749 and tr_A0A2Y9MIS9_A0A2Y9MIS9_DELLE_9749 are exactly identical!
WARNING: Duplicate sequences found: 9

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/Q9ULW8/3_mltree/Q9ULW8.raxml.reduced.phy

Alignment comprises 1 partitions and 659 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 659 / 659
Gaps: 13.48 %
Invariant sites: 0.15 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/3_mltree/Q9ULW8.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 405 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 165 / 13200
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -369095.957068] Initial branch length optimization
[00:00:01 -312179.057575] Model parameter optimization (eps = 10.000000)
[00:00:30 -311321.212743] AUTODETECT spr round 1 (radius: 5)
[00:01:03 -193622.680539] AUTODETECT spr round 2 (radius: 10)
[00:01:45 -141634.714092] AUTODETECT spr round 3 (radius: 15)
[00:02:37 -129801.957113] AUTODETECT spr round 4 (radius: 20)
[00:03:49 -129142.696663] AUTODETECT spr round 5 (radius: 25)
[00:05:20 -129014.968795] SPR radius for FAST iterations: 25 (autodetect)
[00:05:20 -129014.968795] Model parameter optimization (eps = 3.000000)
[00:05:34 -128754.684839] FAST spr round 1 (radius: 25)
[00:06:20 -117690.529872] FAST spr round 2 (radius: 25)
[00:06:57 -117200.212357] FAST spr round 3 (radius: 25)
[00:07:30 -117173.282215] FAST spr round 4 (radius: 25)
[00:07:55 -117173.275094] Model parameter optimization (eps = 1.000000)
[00:08:03 -117171.414291] SLOW spr round 1 (radius: 5)
[00:08:50 -117158.859494] SLOW spr round 2 (radius: 5)
[00:09:35 -117158.494545] SLOW spr round 3 (radius: 5)
[00:10:17 -117158.492376] SLOW spr round 4 (radius: 10)
[00:11:00 -117158.491772] SLOW spr round 5 (radius: 15)
[00:12:25 -117158.491534] SLOW spr round 6 (radius: 20)
[00:14:26 -117158.491398] SLOW spr round 7 (radius: 25)
[00:16:43 -117158.491293] Model parameter optimization (eps = 0.100000)

[00:16:47] [worker #0] ML tree search #1, logLikelihood: -117158.454540

[00:16:47 -371831.616536] Initial branch length optimization
[00:16:49 -312445.513019] Model parameter optimization (eps = 10.000000)
[00:17:18 -311626.645892] AUTODETECT spr round 1 (radius: 5)
[00:17:51 -202488.015064] AUTODETECT spr round 2 (radius: 10)
[00:18:30 -153004.080898] AUTODETECT spr round 3 (radius: 15)
[00:19:18] [worker #1] ML tree search #2, logLikelihood: -117157.825746
[00:19:21 -137117.953541] AUTODETECT spr round 4 (radius: 20)
[00:20:31 -130660.116412] AUTODETECT spr round 5 (radius: 25)
[00:21:57 -130464.359061] SPR radius for FAST iterations: 25 (autodetect)
[00:21:57 -130464.359061] Model parameter optimization (eps = 3.000000)
[00:22:12 -130146.802939] FAST spr round 1 (radius: 25)
[00:22:55 -117756.050775] FAST spr round 2 (radius: 25)
[00:23:31 -117224.177939] FAST spr round 3 (radius: 25)
[00:24:02 -117191.313174] FAST spr round 4 (radius: 25)
[00:24:27 -117191.313055] Model parameter optimization (eps = 1.000000)
[00:24:37 -117180.784230] SLOW spr round 1 (radius: 5)
[00:25:24 -117163.602020] SLOW spr round 2 (radius: 5)
[00:26:09 -117158.823992] SLOW spr round 3 (radius: 5)
[00:26:52 -117158.823518] SLOW spr round 4 (radius: 10)
[00:27:38 -117157.730869] SLOW spr round 5 (radius: 5)
[00:28:39 -117156.105528] SLOW spr round 6 (radius: 5)
[00:29:30 -117154.330567] SLOW spr round 7 (radius: 5)
[00:30:17 -117154.248366] SLOW spr round 8 (radius: 10)
[00:31:02 -117154.248268] SLOW spr round 9 (radius: 15)
[00:32:29 -117154.248172] SLOW spr round 10 (radius: 20)
[00:34:32 -117154.248076] SLOW spr round 11 (radius: 25)
[00:36:45] [worker #1] ML tree search #4, logLikelihood: -117153.425616
[00:36:48 -117154.247980] Model parameter optimization (eps = 0.100000)

[00:36:52] [worker #0] ML tree search #3, logLikelihood: -117154.232845

[00:36:52 -368916.760131] Initial branch length optimization
[00:36:54 -310837.636537] Model parameter optimization (eps = 10.000000)
[00:37:21 -309946.690179] AUTODETECT spr round 1 (radius: 5)
[00:37:54 -204259.699663] AUTODETECT spr round 2 (radius: 10)
[00:38:34 -154610.559825] AUTODETECT spr round 3 (radius: 15)
[00:39:24 -140503.352810] AUTODETECT spr round 4 (radius: 20)
[00:40:29 -133001.870106] AUTODETECT spr round 5 (radius: 25)
[00:41:48 -132113.658981] SPR radius for FAST iterations: 25 (autodetect)
[00:41:48 -132113.658981] Model parameter optimization (eps = 3.000000)
[00:42:05 -131833.433570] FAST spr round 1 (radius: 25)
[00:42:53 -117786.319049] FAST spr round 2 (radius: 25)
[00:43:30 -117210.355674] FAST spr round 3 (radius: 25)
[00:44:03 -117182.063255] FAST spr round 4 (radius: 25)
[00:44:29 -117173.225498] FAST spr round 5 (radius: 25)
[00:44:55 -117173.225212] Model parameter optimization (eps = 1.000000)
[00:45:04 -117166.256229] SLOW spr round 1 (radius: 5)
[00:45:51 -117157.739894] SLOW spr round 2 (radius: 5)
[00:46:34 -117157.737772] SLOW spr round 3 (radius: 10)
[00:47:19 -117157.737436] SLOW spr round 4 (radius: 15)
[00:48:49 -117157.737311] SLOW spr round 5 (radius: 20)
[00:50:55 -117157.737213] SLOW spr round 6 (radius: 25)
[00:53:10 -117157.737118] Model parameter optimization (eps = 0.100000)

[00:53:12] [worker #0] ML tree search #5, logLikelihood: -117157.723692

[00:53:12 -367418.376358] Initial branch length optimization
[00:53:14 -311379.967055] Model parameter optimization (eps = 10.000000)
[00:53:40 -310538.514316] AUTODETECT spr round 1 (radius: 5)
[00:54:13 -204150.162816] AUTODETECT spr round 2 (radius: 10)
[00:54:16] [worker #1] ML tree search #6, logLikelihood: -117152.544249
[00:54:55 -159512.106884] AUTODETECT spr round 3 (radius: 15)
[00:55:49 -141493.183154] AUTODETECT spr round 4 (radius: 20)
[00:56:51 -131078.035032] AUTODETECT spr round 5 (radius: 25)
[00:58:06 -130711.184685] SPR radius for FAST iterations: 25 (autodetect)
[00:58:06 -130711.184685] Model parameter optimization (eps = 3.000000)
[00:58:22 -130457.335632] FAST spr round 1 (radius: 25)
[00:59:10 -117966.309237] FAST spr round 2 (radius: 25)
[00:59:49 -117250.870560] FAST spr round 3 (radius: 25)
[01:00:22 -117216.006505] FAST spr round 4 (radius: 25)
[01:00:47 -117216.006368] Model parameter optimization (eps = 1.000000)
[01:00:59 -117201.752401] SLOW spr round 1 (radius: 5)
[01:01:49 -117183.849599] SLOW spr round 2 (radius: 5)
[01:02:33 -117183.838778] SLOW spr round 3 (radius: 10)
[01:03:18 -117179.721157] SLOW spr round 4 (radius: 5)
[01:04:17 -117179.450563] SLOW spr round 5 (radius: 5)
[01:05:08 -117179.449762] SLOW spr round 6 (radius: 10)
[01:05:55 -117179.449605] SLOW spr round 7 (radius: 15)
[01:07:14 -117165.578581] SLOW spr round 8 (radius: 5)
[01:08:21 -117152.822622] SLOW spr round 9 (radius: 5)
[01:09:14 -117152.604965] SLOW spr round 10 (radius: 5)
[01:10:00 -117152.603334] SLOW spr round 11 (radius: 10)
[01:10:45 -117152.603114] SLOW spr round 12 (radius: 15)
[01:11:12] [worker #1] ML tree search #8, logLikelihood: -117158.304866
[01:12:10 -117152.602998] SLOW spr round 13 (radius: 20)
[01:14:14 -117152.602899] SLOW spr round 14 (radius: 25)
[01:16:35 -117152.602805] Model parameter optimization (eps = 0.100000)

[01:16:37] [worker #0] ML tree search #7, logLikelihood: -117152.532308

[01:16:37 -368933.084403] Initial branch length optimization
[01:16:39 -310998.734531] Model parameter optimization (eps = 10.000000)
[01:17:08 -310153.984910] AUTODETECT spr round 1 (radius: 5)
[01:17:40 -196169.993093] AUTODETECT spr round 2 (radius: 10)
[01:18:18 -147484.799336] AUTODETECT spr round 3 (radius: 15)
[01:19:07 -132974.299682] AUTODETECT spr round 4 (radius: 20)
[01:20:13 -128270.936940] AUTODETECT spr round 5 (radius: 25)
[01:21:28 -128259.197750] SPR radius for FAST iterations: 25 (autodetect)
[01:21:28 -128259.197750] Model parameter optimization (eps = 3.000000)
[01:21:43 -127970.836825] FAST spr round 1 (radius: 25)
[01:22:28 -117577.933724] FAST spr round 2 (radius: 25)
[01:23:03 -117239.258099] FAST spr round 3 (radius: 25)
[01:23:32 -117214.824329] FAST spr round 4 (radius: 25)
[01:23:58 -117207.802450] FAST spr round 5 (radius: 25)
[01:24:23 -117207.801343] Model parameter optimization (eps = 1.000000)
[01:24:34 -117198.494633] SLOW spr round 1 (radius: 5)
[01:25:22 -117184.091672] SLOW spr round 2 (radius: 5)
[01:26:04 -117182.844700] SLOW spr round 3 (radius: 5)
[01:26:46 -117182.844564] SLOW spr round 4 (radius: 10)
[01:27:29 -117182.844468] SLOW spr round 5 (radius: 15)
[01:28:43] [worker #1] ML tree search #10, logLikelihood: -117156.774893
[01:28:52 -117164.038438] SLOW spr round 6 (radius: 5)
[01:29:56 -117158.017089] SLOW spr round 7 (radius: 5)
[01:30:49 -117157.854821] SLOW spr round 8 (radius: 5)
[01:31:36 -117157.854289] SLOW spr round 9 (radius: 10)
[01:32:22 -117157.854065] SLOW spr round 10 (radius: 15)
[01:33:50 -117157.853929] SLOW spr round 11 (radius: 20)
[01:35:58 -117157.853820] SLOW spr round 12 (radius: 25)
[01:38:14 -117157.853720] Model parameter optimization (eps = 0.100000)

[01:38:18] [worker #0] ML tree search #9, logLikelihood: -117157.768699

[01:38:18 -368129.572345] Initial branch length optimization
[01:38:20 -306762.481274] Model parameter optimization (eps = 10.000000)
[01:38:47 -305971.190627] AUTODETECT spr round 1 (radius: 5)
[01:39:20 -193070.002284] AUTODETECT spr round 2 (radius: 10)
[01:39:58 -145153.763340] AUTODETECT spr round 3 (radius: 15)
[01:40:49 -127127.261318] AUTODETECT spr round 4 (radius: 20)
[01:41:57 -126471.556841] AUTODETECT spr round 5 (radius: 25)
[01:43:17 -126307.240743] SPR radius for FAST iterations: 25 (autodetect)
[01:43:17 -126307.240743] Model parameter optimization (eps = 3.000000)
[01:43:30 -126035.216321] FAST spr round 1 (radius: 25)
[01:44:15 -117828.153416] FAST spr round 2 (radius: 25)
[01:44:51 -117230.317622] FAST spr round 3 (radius: 25)
[01:44:55] [worker #1] ML tree search #12, logLikelihood: -117152.445440
[01:45:25 -117183.686852] FAST spr round 4 (radius: 25)
[01:45:52 -117178.999735] FAST spr round 5 (radius: 25)
[01:46:18 -117178.999735] Model parameter optimization (eps = 1.000000)
[01:46:29 -117173.480032] SLOW spr round 1 (radius: 5)
[01:47:16 -117159.919387] SLOW spr round 2 (radius: 5)
[01:47:59 -117158.908540] SLOW spr round 3 (radius: 5)
[01:48:41 -117158.830320] SLOW spr round 4 (radius: 10)
[01:49:25 -117158.830313] SLOW spr round 5 (radius: 15)
[01:50:55 -117158.830312] SLOW spr round 6 (radius: 20)
[01:52:59 -117158.830312] SLOW spr round 7 (radius: 25)
[01:55:17 -117158.830312] Model parameter optimization (eps = 0.100000)

[01:55:20] [worker #0] ML tree search #11, logLikelihood: -117158.816417

[01:55:20 -373171.337676] Initial branch length optimization
[01:55:22 -313376.685461] Model parameter optimization (eps = 10.000000)
[01:55:45 -312551.477560] AUTODETECT spr round 1 (radius: 5)
[01:56:18 -196973.465061] AUTODETECT spr round 2 (radius: 10)
[01:56:56 -150029.415862] AUTODETECT spr round 3 (radius: 15)
[01:57:45 -135904.445146] AUTODETECT spr round 4 (radius: 20)
[01:59:04 -130015.111510] AUTODETECT spr round 5 (radius: 25)
[02:00:24 -130012.368038] SPR radius for FAST iterations: 25 (autodetect)
[02:00:24 -130012.368038] Model parameter optimization (eps = 3.000000)
[02:00:38 -129762.726525] FAST spr round 1 (radius: 25)
[02:01:24 -117690.397417] FAST spr round 2 (radius: 25)
[02:02:02 -117242.553982] FAST spr round 3 (radius: 25)
[02:02:32 -117225.525662] FAST spr round 4 (radius: 25)
[02:02:58 -117224.396345] FAST spr round 5 (radius: 25)
[02:03:23 -117224.396147] Model parameter optimization (eps = 1.000000)
[02:03:34 -117197.794778] SLOW spr round 1 (radius: 5)
[02:04:22 -117157.795334] SLOW spr round 2 (radius: 5)
[02:04:59] [worker #1] ML tree search #14, logLikelihood: -117155.068953
[02:05:08 -117152.936193] SLOW spr round 3 (radius: 5)
[02:05:50 -117152.934418] SLOW spr round 4 (radius: 10)
[02:06:35 -117152.934161] SLOW spr round 5 (radius: 15)
[02:08:03 -117152.934047] SLOW spr round 6 (radius: 20)
[02:10:07 -117152.933949] SLOW spr round 7 (radius: 25)
[02:12:26 -117152.933852] Model parameter optimization (eps = 0.100000)

[02:12:30] [worker #0] ML tree search #13, logLikelihood: -117152.882385

[02:12:30 -367371.380863] Initial branch length optimization
[02:12:31 -311229.271105] Model parameter optimization (eps = 10.000000)
[02:12:56 -310486.058992] AUTODETECT spr round 1 (radius: 5)
[02:13:29 -204698.730026] AUTODETECT spr round 2 (radius: 10)
[02:14:11 -154304.875334] AUTODETECT spr round 3 (radius: 15)
[02:15:02 -139015.983885] AUTODETECT spr round 4 (radius: 20)
[02:16:07 -130254.390559] AUTODETECT spr round 5 (radius: 25)
[02:17:18 -130254.317961] SPR radius for FAST iterations: 20 (autodetect)
[02:17:18 -130254.317961] Model parameter optimization (eps = 3.000000)
[02:17:33 -129989.293347] FAST spr round 1 (radius: 20)
[02:18:16 -117524.014477] FAST spr round 2 (radius: 20)
[02:18:52 -117214.960787] FAST spr round 3 (radius: 20)
[02:19:23 -117202.672217] FAST spr round 4 (radius: 20)
[02:19:50 -117193.465480] FAST spr round 5 (radius: 20)
[02:20:15 -117193.462491] Model parameter optimization (eps = 1.000000)
[02:20:21 -117192.078651] SLOW spr round 1 (radius: 5)
[02:21:09 -117158.769193] SLOW spr round 2 (radius: 5)
[02:21:52 -117158.768406] SLOW spr round 3 (radius: 10)
[02:22:36 -117158.768213] SLOW spr round 4 (radius: 15)
[02:22:49] [worker #1] ML tree search #16, logLikelihood: -117156.776663
[02:24:03 -117158.768102] SLOW spr round 5 (radius: 20)
[02:26:04 -117158.768006] SLOW spr round 6 (radius: 25)
[02:28:25 -117158.767912] Model parameter optimization (eps = 0.100000)

[02:28:30] [worker #0] ML tree search #15, logLikelihood: -117158.650816

[02:28:30 -373824.945229] Initial branch length optimization
[02:28:32 -314679.606377] Model parameter optimization (eps = 10.000000)
[02:28:58 -313850.523010] AUTODETECT spr round 1 (radius: 5)
[02:29:30 -199855.213597] AUTODETECT spr round 2 (radius: 10)
[02:30:12 -144630.818097] AUTODETECT spr round 3 (radius: 15)
[02:31:07 -131586.106674] AUTODETECT spr round 4 (radius: 20)
[02:32:21 -130341.750124] AUTODETECT spr round 5 (radius: 25)
[02:33:49 -130341.719259] SPR radius for FAST iterations: 20 (autodetect)
[02:33:49 -130341.719259] Model parameter optimization (eps = 3.000000)
[02:34:02 -130088.509531] FAST spr round 1 (radius: 20)
[02:34:48 -118099.953457] FAST spr round 2 (radius: 20)
[02:35:24 -117248.318171] FAST spr round 3 (radius: 20)
[02:35:55 -117199.647851] FAST spr round 4 (radius: 20)
[02:36:21 -117197.993487] FAST spr round 5 (radius: 20)
[02:36:47 -117196.542967] FAST spr round 6 (radius: 20)
[02:37:11 -117196.542865] Model parameter optimization (eps = 1.000000)
[02:37:18 -117194.973441] SLOW spr round 1 (radius: 5)
[02:38:05 -117183.022812] SLOW spr round 2 (radius: 5)
[02:38:48 -117182.421299] SLOW spr round 3 (radius: 5)
[02:39:29 -117182.420667] SLOW spr round 4 (radius: 10)
[02:40:12 -117182.420504] SLOW spr round 5 (radius: 15)
[02:40:51] [worker #1] ML tree search #18, logLikelihood: -117153.200830
[02:41:33 -117163.563235] SLOW spr round 6 (radius: 5)
[02:42:39 -117157.650603] SLOW spr round 7 (radius: 5)
[02:43:32 -117157.551815] SLOW spr round 8 (radius: 10)
[02:44:20 -117157.551605] SLOW spr round 9 (radius: 15)
[02:45:46 -117157.551467] SLOW spr round 10 (radius: 20)
[02:47:52 -117157.551355] SLOW spr round 11 (radius: 25)
[02:50:09 -117157.551252] Model parameter optimization (eps = 0.100000)

[02:50:14] [worker #0] ML tree search #17, logLikelihood: -117157.465065

[02:50:14 -370980.683240] Initial branch length optimization
[02:50:15 -312451.117850] Model parameter optimization (eps = 10.000000)
[02:50:46 -311684.296181] AUTODETECT spr round 1 (radius: 5)
[02:51:19 -204354.335412] AUTODETECT spr round 2 (radius: 10)
[02:51:57 -155387.213096] AUTODETECT spr round 3 (radius: 15)
[02:52:46 -132764.026253] AUTODETECT spr round 4 (radius: 20)
[02:53:51 -130798.068872] AUTODETECT spr round 5 (radius: 25)
[02:54:55 -130591.453428] SPR radius for FAST iterations: 25 (autodetect)
[02:54:55 -130591.453428] Model parameter optimization (eps = 3.000000)
[02:55:13 -130351.892272] FAST spr round 1 (radius: 25)
[02:55:58 -117713.301273] FAST spr round 2 (radius: 25)
[02:56:36 -117226.670929] FAST spr round 3 (radius: 25)
[02:57:05 -117196.241667] FAST spr round 4 (radius: 25)
[02:57:32 -117182.795812] FAST spr round 5 (radius: 25)
[02:57:57 -117182.347176] FAST spr round 6 (radius: 25)
[02:58:21 -117182.347076] Model parameter optimization (eps = 1.000000)
[02:58:28 -117181.313787] SLOW spr round 1 (radius: 5)
[02:59:17 -117157.747992] SLOW spr round 2 (radius: 5)
[02:59:59 -117157.743601] SLOW spr round 3 (radius: 10)
[03:00:43 -117157.742551] SLOW spr round 4 (radius: 15)
[03:00:55] [worker #1] ML tree search #20, logLikelihood: -117158.162946
[03:02:10 -117157.742133] SLOW spr round 5 (radius: 20)
[03:04:14 -117157.741931] SLOW spr round 6 (radius: 25)
[03:06:28 -117157.741799] Model parameter optimization (eps = 0.100000)

[03:06:30] [worker #0] ML tree search #19, logLikelihood: -117157.737311


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.197705,0.475490) (0.179619,0.550286) (0.314012,0.809540) (0.308664,1.791419) 
   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: -117152.445440

AIC score: 235930.890880 / AICc score: 1559494.890880 / BIC score: 239581.849113
Free parameters (model + branch lengths): 813

WARNING: Number of free parameters (K=813) is larger than alignment size (n=659).
         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/Q9ULW8/3_mltree/Q9ULW8.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/3_mltree/Q9ULW8.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/3_mltree/Q9ULW8.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULW8/3_mltree/Q9ULW8.raxml.log

Analysis started: 02-Jul-2021 15:13:29 / finished: 02-Jul-2021 18:20:00

Elapsed time: 11190.894 seconds

Consumed energy: 866.380 Wh (= 4 km in an electric car, or 22 km with an e-scooter!)