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 19-Jul-2021 03:47:24 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/2_msa/Q9NXL9_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/3_mltree/Q9NXL9 --seed 2 --threads 8 --tree rand{20} pars{20}

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

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/2_msa/Q9NXL9_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 658 sites

WARNING: Sequences tr_A0A0A0MQ52_A0A0A0MQ52_CHICK_9031 and sp_I0IUP4_MCM9_CHICK_9031 are exactly identical!
WARNING: Sequences tr_J3K3M6_J3K3M6_COCIM_246410 and tr_A0A0J6YG33_A0A0J6YG33_COCIT_404692 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_H2QNA7_H2QNA7_PANTR_9598 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and sp_P49736_MCM2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_F7HLV9_F7HLV9_MACMU_9544 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_G7PIZ9_G7PIZ9_MACFA_9541 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_A0A096MXM7_A0A096MXM7_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_A0A2K5LCM6_A0A2K5LCM6_CERAT_9531 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_A0A2K6CCM9_A0A2K6CCM9_MACNE_9545 are exactly identical!
WARNING: Sequences tr_H2P9G0_H2P9G0_PONAB_9601 and tr_A0A2R8ZAB9_A0A2R8ZAB9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8PTV7_A0A2J8PTV7_PANTR_9598 and tr_A0A2R8ZWC4_A0A2R8ZWC4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2QV16_H2QV16_PANTR_9598 and tr_A0A2R9B174_A0A2R9B174_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F9GFG5_F9GFG5_FUSOF_660025 and tr_X0DAQ9_X0DAQ9_FUSOX_1089458 are exactly identical!
WARNING: Sequences tr_F9GFG5_F9GFG5_FUSOF_660025 and tr_A0A2H3T4S0_A0A2H3T4S0_FUSOX_5507 are exactly identical!
WARNING: Sequences tr_A0A0E0HBC5_A0A0E0HBC5_ORYNI_4536 and tr_A0A0E0PJC1_A0A0E0PJC1_ORYRU_4529 are exactly identical!
WARNING: Sequences tr_A0A0E0HBC5_A0A0E0HBC5_ORYNI_4536 and tr_A0A0D9ZW24_A0A0D9ZW24_9ORYZ_40148 are exactly identical!
WARNING: Sequences tr_F4NXZ8_F4NXZ8_BATDJ_684364 and tr_A0A177WLF2_A0A177WLF2_BATDE_403673 are exactly identical!
WARNING: Sequences tr_E3LKW3_E3LKW3_CAERE_31234 and tr_A0A261ACB1_A0A261ACB1_9PELO_1503980 are exactly identical!
WARNING: Sequences tr_E3N2S4_E3N2S4_CAERE_31234 and tr_A0A261C2Y9_A0A261C2Y9_9PELO_1503980 are exactly identical!
WARNING: Sequences tr_B3RUX5_B3RUX5_TRIAD_10228 and tr_A0A369SAB1_A0A369SAB1_9METZ_287889 are exactly identical!
WARNING: Sequences tr_C4V8R3_C4V8R3_NOSCE_578460 and tr_A0A0F9ZD36_A0A0F9ZD36_9MICR_40302 are exactly identical!
WARNING: Sequences tr_C4VA92_C4VA92_NOSCE_578460 and tr_A0A0F9WV17_A0A0F9WV17_9MICR_40302 are exactly identical!
WARNING: Sequences tr_G7P3A0_G7P3A0_MACFA_9541 and tr_A0A2K6CJD3_A0A2K6CJD3_MACNE_9545 are exactly identical!
WARNING: Sequences tr_S0DT55_S0DT55_GIBF5_1279085 and tr_A0A365MR19_A0A365MR19_GIBIN_948311 are exactly identical!
WARNING: Sequences tr_A0A015KNS9_A0A015KNS9_9GLOM_1432141 and tr_A0A2H5R8W2_A0A2H5R8W2_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A084QJY0_A0A084QJY0_STAC4_1283841 and tr_A0A084RAY4_A0A084RAY4_STACH_1283842 are exactly identical!
WARNING: Sequences tr_A0A096NAA1_A0A096NAA1_PAPAN_9555 and tr_A0A2K5N346_A0A2K5N346_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A094F5Y8_A0A094F5Y8_9PEZI_1420912 and tr_A0A1B8GY89_A0A1B8GY89_9PEZI_342668 are exactly identical!
WARNING: Sequences tr_A0A0D2Q0W2_A0A0D2Q0W2_GOSRA_29730 and tr_A0A1U8HW27_A0A1U8HW27_GOSHI_3635 are exactly identical!
WARNING: Sequences tr_A0A091VHL5_A0A091VHL5_NIPNI_128390 and tr_A0A093HHH3_A0A093HHH3_STRCA_441894 are exactly identical!
WARNING: Sequences tr_A0A164PTE6_A0A164PTE6_9HOMO_1314777 and tr_A0A166DZF7_A0A166DZF7_9HOMO_1314776 are exactly identical!
WARNING: Sequences tr_A0A2H5PSQ7_A0A2H5PSQ7_CITUN_55188 and tr_A0A2H5PSR2_A0A2H5PSR2_CITUN_55188 are exactly identical!
WARNING: Duplicate sequences found: 32

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/Q9NXL9/3_mltree/Q9NXL9.raxml.reduced.phy

Alignment comprises 1 partitions and 658 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 658 / 658
Gaps: 9.84 %
Invariant sites: 0.15 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/3_mltree/Q9NXL9.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 / 165 / 13200
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1177314.257841] Initial branch length optimization
[00:00:07 -974517.889763] Model parameter optimization (eps = 10.000000)
[00:01:00 -973007.261216] AUTODETECT spr round 1 (radius: 5)
[00:03:53 -648315.726466] AUTODETECT spr round 2 (radius: 10)
[00:07:03 -498444.341465] AUTODETECT spr round 3 (radius: 15)
[00:10:38 -431279.968143] AUTODETECT spr round 4 (radius: 20)
[00:14:50 -389522.175522] AUTODETECT spr round 5 (radius: 25)
[00:19:34 -354488.259773] SPR radius for FAST iterations: 25 (autodetect)
[00:19:34 -354488.259773] Model parameter optimization (eps = 3.000000)
[00:20:03 -354446.186332] FAST spr round 1 (radius: 25)
[00:23:51 -296378.425239] FAST spr round 2 (radius: 25)
[00:26:27 -294775.829017] FAST spr round 3 (radius: 25)
[00:28:46 -294592.546151] FAST spr round 4 (radius: 25)
[00:30:49 -294571.037350] FAST spr round 5 (radius: 25)
[00:32:45 -294568.557961] FAST spr round 6 (radius: 25)
[00:34:39 -294568.557768] Model parameter optimization (eps = 1.000000)
[00:34:56 -294564.643460] SLOW spr round 1 (radius: 5)
[00:37:45 -294489.908665] SLOW spr round 2 (radius: 5)
[00:40:20 -294482.566562] SLOW spr round 3 (radius: 5)
[00:42:54 -294480.923927] SLOW spr round 4 (radius: 5)
[00:45:24 -294480.923779] SLOW spr round 5 (radius: 10)
[00:47:52 -294476.540869] SLOW spr round 6 (radius: 5)
[00:50:58 -294474.628664] SLOW spr round 7 (radius: 5)
[00:53:43 -294474.537572] SLOW spr round 8 (radius: 10)
[00:56:15 -294474.537278] SLOW spr round 9 (radius: 15)
[00:59:51 -294474.537257] SLOW spr round 10 (radius: 20)
[01:04:46 -294474.537240] SLOW spr round 11 (radius: 25)
[01:09:02] [worker #1] ML tree search #2, logLikelihood: -294483.681993
[01:11:02 -294474.537225] Model parameter optimization (eps = 0.100000)

[01:11:08] [worker #0] ML tree search #1, logLikelihood: -294474.471738

[01:11:08 -1178629.284858] Initial branch length optimization
[01:11:13 -980136.254918] Model parameter optimization (eps = 10.000000)
[01:11:59 -978601.225209] AUTODETECT spr round 1 (radius: 5)
[01:14:52 -650939.012310] AUTODETECT spr round 2 (radius: 10)
[01:18:11 -502091.399908] AUTODETECT spr round 3 (radius: 15)
[01:21:45 -411352.121561] AUTODETECT spr round 4 (radius: 20)
[01:25:30 -381394.782996] AUTODETECT spr round 5 (radius: 25)
[01:29:39 -349975.831389] SPR radius for FAST iterations: 25 (autodetect)
[01:29:39 -349975.831389] Model parameter optimization (eps = 3.000000)
[01:30:08 -349921.698476] FAST spr round 1 (radius: 25)
[01:33:47 -298892.524515] FAST spr round 2 (radius: 25)
[01:36:29 -294961.126715] FAST spr round 3 (radius: 25)
[01:38:45 -294672.041086] FAST spr round 4 (radius: 25)
[01:40:47 -294659.942421] FAST spr round 5 (radius: 25)
[01:42:43 -294659.939374] Model parameter optimization (eps = 1.000000)
[01:42:58 -294656.240787] SLOW spr round 1 (radius: 5)
[01:45:47 -294540.021953] SLOW spr round 2 (radius: 5)
[01:48:31 -294505.194854] SLOW spr round 3 (radius: 5)
[01:51:04 -294504.425893] SLOW spr round 4 (radius: 5)
[01:53:37 -294502.650551] SLOW spr round 5 (radius: 5)
[01:56:08 -294502.297802] SLOW spr round 6 (radius: 5)
[01:58:39 -294502.297441] SLOW spr round 7 (radius: 10)
[02:01:09 -294497.319878] SLOW spr round 8 (radius: 5)
[02:04:16 -294496.144397] SLOW spr round 9 (radius: 5)
[02:07:02 -294496.143690] SLOW spr round 10 (radius: 10)
[02:09:36 -294491.330978] SLOW spr round 11 (radius: 5)
[02:12:41 -294488.608305] SLOW spr round 12 (radius: 5)
[02:15:26 -294488.608212] SLOW spr round 13 (radius: 10)
[02:17:58 -294485.101994] SLOW spr round 14 (radius: 5)
[02:21:05 -294475.362188] SLOW spr round 15 (radius: 5)
[02:23:51 -294474.809026] SLOW spr round 16 (radius: 5)
[02:24:23] [worker #1] ML tree search #4, logLikelihood: -294485.994565
[02:26:28 -294474.808939] SLOW spr round 17 (radius: 10)
[02:28:58 -294474.808852] SLOW spr round 18 (radius: 15)
[02:32:41 -294474.808766] SLOW spr round 19 (radius: 20)
[02:37:40 -294474.808680] SLOW spr round 20 (radius: 25)
[02:44:02 -294474.808594] Model parameter optimization (eps = 0.100000)

[02:44:14] [worker #0] ML tree search #3, logLikelihood: -294474.559607

[02:44:14 -1173810.250300] Initial branch length optimization
[02:44:19 -972903.709904] Model parameter optimization (eps = 10.000000)
[02:44:58 -971472.903179] AUTODETECT spr round 1 (radius: 5)
[02:47:50 -651811.214320] AUTODETECT spr round 2 (radius: 10)
[02:51:05 -478305.332039] AUTODETECT spr round 3 (radius: 15)
[02:54:26 -401372.345272] AUTODETECT spr round 4 (radius: 20)
[02:58:13 -376171.050076] AUTODETECT spr round 5 (radius: 25)
[03:03:14 -351384.411555] SPR radius for FAST iterations: 25 (autodetect)
[03:03:14 -351384.411555] Model parameter optimization (eps = 3.000000)
[03:03:37 -351235.826263] FAST spr round 1 (radius: 25)
[03:07:20 -297716.364291] FAST spr round 2 (radius: 25)
[03:10:06 -294824.068923] FAST spr round 3 (radius: 25)
[03:12:29 -294637.137933] FAST spr round 4 (radius: 25)
[03:14:39 -294597.870284] FAST spr round 5 (radius: 25)
[03:16:36 -294589.362348] FAST spr round 6 (radius: 25)
[03:18:35 -294586.421948] FAST spr round 7 (radius: 25)
[03:20:26 -294586.420131] Model parameter optimization (eps = 1.000000)
[03:20:41 -294582.783482] SLOW spr round 1 (radius: 5)
[03:23:30 -294503.911861] SLOW spr round 2 (radius: 5)
[03:26:06 -294500.268610] SLOW spr round 3 (radius: 5)
[03:28:41 -294494.816592] SLOW spr round 4 (radius: 5)
[03:31:14 -294493.699456] SLOW spr round 5 (radius: 5)
[03:31:41] [worker #1] ML tree search #6, logLikelihood: -294484.498550
[03:33:46 -294493.368365] SLOW spr round 6 (radius: 5)
[03:36:18 -294493.368146] SLOW spr round 7 (radius: 10)
[03:38:45 -294493.368110] SLOW spr round 8 (radius: 15)
[03:42:33 -294493.368090] SLOW spr round 9 (radius: 20)
[03:47:35 -294493.368074] SLOW spr round 10 (radius: 25)
[03:54:08 -294493.368060] Model parameter optimization (eps = 0.100000)

[03:54:17] [worker #0] ML tree search #5, logLikelihood: -294493.122111

[03:54:17 -1182402.381335] Initial branch length optimization
[03:54:23 -977944.636124] Model parameter optimization (eps = 10.000000)
[03:55:03 -976340.339716] AUTODETECT spr round 1 (radius: 5)
[03:57:56 -662125.736287] AUTODETECT spr round 2 (radius: 10)
[04:01:12 -471845.233030] AUTODETECT spr round 3 (radius: 15)
[04:04:36 -386675.352342] AUTODETECT spr round 4 (radius: 20)
[04:07:57 -364776.273478] AUTODETECT spr round 5 (radius: 25)
[04:12:21 -345061.792330] SPR radius for FAST iterations: 25 (autodetect)
[04:12:21 -345061.792330] Model parameter optimization (eps = 3.000000)
[04:12:27 -345061.305620] FAST spr round 1 (radius: 25)
[04:16:17 -296295.775176] FAST spr round 2 (radius: 25)
[04:18:55 -294769.315503] FAST spr round 3 (radius: 25)
[04:21:16 -294670.182081] FAST spr round 4 (radius: 25)
[04:23:23 -294630.972146] FAST spr round 5 (radius: 25)
[04:25:21 -294622.541849] FAST spr round 6 (radius: 25)
[04:27:17 -294613.003383] FAST spr round 7 (radius: 25)
[04:29:10 -294611.213448] FAST spr round 8 (radius: 25)
[04:31:02 -294611.213168] Model parameter optimization (eps = 1.000000)
[04:31:28 -294571.816918] SLOW spr round 1 (radius: 5)
[04:34:08 -294494.055908] SLOW spr round 2 (radius: 5)
[04:36:45 -294475.813348] SLOW spr round 3 (radius: 5)
[04:38:55] [worker #1] ML tree search #8, logLikelihood: -294480.051414
[04:39:17 -294475.812962] SLOW spr round 4 (radius: 10)
[04:41:47 -294475.812904] SLOW spr round 5 (radius: 15)
[04:45:30 -294475.812879] SLOW spr round 6 (radius: 20)
[04:50:30 -294475.812860] SLOW spr round 7 (radius: 25)
[04:56:59 -294475.812843] Model parameter optimization (eps = 0.100000)

[04:57:12] [worker #0] ML tree search #7, logLikelihood: -294475.458031

[04:57:12 -1177923.588743] Initial branch length optimization
[04:57:18 -976308.916495] Model parameter optimization (eps = 10.000000)
[04:57:54 -974742.071245] AUTODETECT spr round 1 (radius: 5)
[05:00:46 -659252.106368] AUTODETECT spr round 2 (radius: 10)
[05:03:58 -489194.119237] AUTODETECT spr round 3 (radius: 15)
[05:07:27 -401479.761470] AUTODETECT spr round 4 (radius: 20)
[05:11:08 -383996.569037] AUTODETECT spr round 5 (radius: 25)
[05:15:25 -373012.329084] SPR radius for FAST iterations: 25 (autodetect)
[05:15:25 -373012.329084] Model parameter optimization (eps = 3.000000)
[05:15:31 -373011.886307] FAST spr round 1 (radius: 25)
[05:19:14 -305942.326852] FAST spr round 2 (radius: 25)
[05:21:58 -295015.537029] FAST spr round 3 (radius: 25)
[05:24:16 -294693.836754] FAST spr round 4 (radius: 25)
[05:26:23 -294656.944701] FAST spr round 5 (radius: 25)
[05:28:18 -294656.455084] FAST spr round 6 (radius: 25)
[05:30:11 -294656.454686] Model parameter optimization (eps = 1.000000)
[05:30:39 -294611.827841] SLOW spr round 1 (radius: 5)
[05:33:25 -294513.164629] SLOW spr round 2 (radius: 5)
[05:36:06 -294495.641291] SLOW spr round 3 (radius: 5)
[05:37:19] [worker #1] ML tree search #10, logLikelihood: -294499.375189
[05:38:39 -294495.640751] SLOW spr round 4 (radius: 10)
[05:41:08 -294495.157445] SLOW spr round 5 (radius: 5)
[05:44:15 -294495.155930] SLOW spr round 6 (radius: 10)
[05:47:00 -294495.155518] SLOW spr round 7 (radius: 15)
[05:50:32 -294495.155355] SLOW spr round 8 (radius: 20)
[05:55:35 -294495.155251] SLOW spr round 9 (radius: 25)
[06:01:58 -294495.155161] Model parameter optimization (eps = 0.100000)

[06:02:12] [worker #0] ML tree search #9, logLikelihood: -294494.438810

[06:02:12 -1179779.345228] Initial branch length optimization
[06:02:18 -979185.727846] Model parameter optimization (eps = 10.000000)
[06:03:08 -977617.207066] AUTODETECT spr round 1 (radius: 5)
[06:06:05 -678989.440144] AUTODETECT spr round 2 (radius: 10)
[06:09:20 -504953.666334] AUTODETECT spr round 3 (radius: 15)
[06:12:54 -405571.385277] AUTODETECT spr round 4 (radius: 20)
[06:17:06 -346728.454392] AUTODETECT spr round 5 (radius: 25)
[06:21:30 -336759.174316] SPR radius for FAST iterations: 25 (autodetect)
[06:21:30 -336759.174316] Model parameter optimization (eps = 3.000000)
[06:21:57 -336685.886286] FAST spr round 1 (radius: 25)
[06:25:38 -296266.277062] FAST spr round 2 (radius: 25)
[06:28:15 -294829.364082] FAST spr round 3 (radius: 25)
[06:30:39 -294588.520521] FAST spr round 4 (radius: 25)
[06:32:46 -294578.421446] FAST spr round 5 (radius: 25)
[06:34:42 -294570.399103] FAST spr round 6 (radius: 25)
[06:36:36 -294570.398944] Model parameter optimization (eps = 1.000000)
[06:36:42 -294569.695749] SLOW spr round 1 (radius: 5)
[06:39:33 -294501.078079] SLOW spr round 2 (radius: 5)
[06:42:14 -294497.385650] SLOW spr round 3 (radius: 5)
[06:44:50 -294492.049464] SLOW spr round 4 (radius: 5)
[06:47:21 -294492.048982] SLOW spr round 5 (radius: 10)
[06:49:49 -294492.048794] SLOW spr round 6 (radius: 15)
[06:53:33 -294492.048667] SLOW spr round 7 (radius: 20)
[06:58:27 -294492.048566] SLOW spr round 8 (radius: 25)
[07:03:58] [worker #1] ML tree search #12, logLikelihood: -294493.299817
[07:04:47 -294492.048475] Model parameter optimization (eps = 0.100000)

[07:04:51] [worker #0] ML tree search #11, logLikelihood: -294492.042265

[07:04:51 -1179913.288547] Initial branch length optimization
[07:04:57 -974267.095565] Model parameter optimization (eps = 10.000000)
[07:05:32 -972701.617410] AUTODETECT spr round 1 (radius: 5)
[07:08:27 -650684.977111] AUTODETECT spr round 2 (radius: 10)
[07:11:41 -488963.410813] AUTODETECT spr round 3 (radius: 15)
[07:15:07 -393428.760815] AUTODETECT spr round 4 (radius: 20)
[07:18:41 -355568.213583] AUTODETECT spr round 5 (radius: 25)
[07:22:45 -338721.011113] SPR radius for FAST iterations: 25 (autodetect)
[07:22:45 -338721.011113] Model parameter optimization (eps = 3.000000)
[07:23:07 -338645.237763] FAST spr round 1 (radius: 25)
[07:26:52 -296885.400313] FAST spr round 2 (radius: 25)
[07:29:34 -294770.773485] FAST spr round 3 (radius: 25)
[07:31:54 -294667.738942] FAST spr round 4 (radius: 25)
[07:34:06 -294624.064114] FAST spr round 5 (radius: 25)
[07:36:09 -294607.459575] FAST spr round 6 (radius: 25)
[07:38:03 -294607.459482] Model parameter optimization (eps = 1.000000)
[07:38:08 -294607.445579] SLOW spr round 1 (radius: 5)
[07:40:55 -294521.061336] SLOW spr round 2 (radius: 5)
[07:43:35 -294500.462836] SLOW spr round 3 (radius: 5)
[07:46:11 -294498.365660] SLOW spr round 4 (radius: 5)
[07:48:44 -294495.138844] SLOW spr round 5 (radius: 5)
[07:51:16 -294494.683749] SLOW spr round 6 (radius: 5)
[07:53:47 -294494.683687] SLOW spr round 7 (radius: 10)
[07:56:17 -294484.253779] SLOW spr round 8 (radius: 5)
[07:59:28 -294482.213984] SLOW spr round 9 (radius: 5)
[08:02:14 -294482.213650] SLOW spr round 10 (radius: 10)
[08:04:48 -294482.213636] SLOW spr round 11 (radius: 15)
[08:08:25 -294482.213626] SLOW spr round 12 (radius: 20)
[08:13:14 -294482.213617] SLOW spr round 13 (radius: 25)
[08:19:17 -294482.213608] Model parameter optimization (eps = 0.100000)

[08:19:23] [worker #0] ML tree search #13, logLikelihood: -294482.200929

[08:19:23 -1180784.629740] Initial branch length optimization
[08:19:27] [worker #1] ML tree search #14, logLikelihood: -294485.523417
[08:19:31 -975997.356269] Model parameter optimization (eps = 10.000000)
[08:20:12 -974394.314685] AUTODETECT spr round 1 (radius: 5)
[08:23:08 -652374.960968] AUTODETECT spr round 2 (radius: 10)
[08:26:24 -491315.523864] AUTODETECT spr round 3 (radius: 15)
[08:29:57 -414567.020373] AUTODETECT spr round 4 (radius: 20)
[08:33:48 -359369.328229] AUTODETECT spr round 5 (radius: 25)
[08:37:48 -349679.398491] SPR radius for FAST iterations: 25 (autodetect)
[08:37:48 -349679.398491] Model parameter optimization (eps = 3.000000)
[08:37:54 -349679.220484] FAST spr round 1 (radius: 25)
[08:41:32 -297200.567856] FAST spr round 2 (radius: 25)
[08:44:13 -294795.886021] FAST spr round 3 (radius: 25)
[08:46:35 -294657.002802] FAST spr round 4 (radius: 25)
[08:48:36 -294646.580586] FAST spr round 5 (radius: 25)
[08:50:32 -294646.580499] Model parameter optimization (eps = 1.000000)
[08:50:53 -294614.525207] SLOW spr round 1 (radius: 5)
[08:53:47 -294523.593345] SLOW spr round 2 (radius: 5)
[08:56:27 -294496.965132] SLOW spr round 3 (radius: 5)
[08:59:05 -294494.102595] SLOW spr round 4 (radius: 5)
[09:01:39 -294492.950228] SLOW spr round 5 (radius: 5)
[09:04:12 -294492.949865] SLOW spr round 6 (radius: 10)
[09:06:40 -294492.949746] SLOW spr round 7 (radius: 15)
[09:10:28 -294492.949720] SLOW spr round 8 (radius: 20)
[09:15:23 -294492.949701] SLOW spr round 9 (radius: 25)
[09:21:42 -294492.949684] Model parameter optimization (eps = 0.100000)

[09:22:11] [worker #0] ML tree search #15, logLikelihood: -294488.313180

[09:22:11 -1178760.565772] Initial branch length optimization
[09:22:18 -968577.755247] Model parameter optimization (eps = 10.000000)
[09:23:10 -967060.774688] AUTODETECT spr round 1 (radius: 5)
[09:26:05 -666181.188451] AUTODETECT spr round 2 (radius: 10)
[09:26:05] [worker #1] ML tree search #16, logLikelihood: -294485.115069
[09:29:20 -494643.490697] AUTODETECT spr round 3 (radius: 15)
[09:32:47 -403893.088025] AUTODETECT spr round 4 (radius: 20)
[09:36:26 -365571.533138] AUTODETECT spr round 5 (radius: 25)
[09:40:49 -350960.308852] SPR radius for FAST iterations: 25 (autodetect)
[09:40:49 -350960.308852] Model parameter optimization (eps = 3.000000)
[09:41:12 -350876.684814] FAST spr round 1 (radius: 25)
[09:45:07 -296188.708290] FAST spr round 2 (radius: 25)
[09:47:47 -294656.702190] FAST spr round 3 (radius: 25)
[09:50:11 -294608.850197] FAST spr round 4 (radius: 25)
[09:52:14 -294600.537710] FAST spr round 5 (radius: 25)
[09:54:10 -294599.725628] FAST spr round 6 (radius: 25)
[09:56:04 -294599.725267] Model parameter optimization (eps = 1.000000)
[09:56:17 -294595.290338] SLOW spr round 1 (radius: 5)
[09:59:11 -294516.233898] SLOW spr round 2 (radius: 5)
[10:01:49 -294513.500712] SLOW spr round 3 (radius: 5)
[10:04:22 -294513.500603] SLOW spr round 4 (radius: 10)
[10:06:55 -294511.428756] SLOW spr round 5 (radius: 5)
[10:10:02 -294511.428552] SLOW spr round 6 (radius: 10)
[10:12:50 -294509.233225] SLOW spr round 7 (radius: 5)
[10:15:54 -294508.229680] SLOW spr round 8 (radius: 5)
[10:18:38 -294508.229531] SLOW spr round 9 (radius: 10)
[10:21:11 -294508.229443] SLOW spr round 10 (radius: 15)
[10:24:50 -294508.229355] SLOW spr round 11 (radius: 20)
[10:25:58] [worker #1] ML tree search #18, logLikelihood: -294484.419104
[10:29:43 -294508.229316] SLOW spr round 12 (radius: 25)
[10:35:42 -294508.229298] Model parameter optimization (eps = 0.100000)

[10:35:49] [worker #0] ML tree search #17, logLikelihood: -294508.156685

[10:35:49 -1171812.323540] Initial branch length optimization
[10:35:55 -970068.321857] Model parameter optimization (eps = 10.000000)
[10:36:38 -968498.234277] AUTODETECT spr round 1 (radius: 5)
[10:39:37 -649382.780561] AUTODETECT spr round 2 (radius: 10)
[10:42:49 -504616.530987] AUTODETECT spr round 3 (radius: 15)
[10:46:30 -421703.051137] AUTODETECT spr round 4 (radius: 20)
[10:50:26 -387006.336680] AUTODETECT spr round 5 (radius: 25)
[10:54:46 -353219.368946] SPR radius for FAST iterations: 25 (autodetect)
[10:54:46 -353219.368946] Model parameter optimization (eps = 3.000000)
[10:55:16 -353081.222159] FAST spr round 1 (radius: 25)
[10:59:04 -297131.414643] FAST spr round 2 (radius: 25)
[11:01:46 -294685.754925] FAST spr round 3 (radius: 25)
[11:04:10 -294599.696803] FAST spr round 4 (radius: 25)
[11:06:11 -294584.290111] FAST spr round 5 (radius: 25)
[11:08:08 -294577.833090] FAST spr round 6 (radius: 25)
[11:10:02 -294577.832994] Model parameter optimization (eps = 1.000000)
[11:10:18 -294575.180327] SLOW spr round 1 (radius: 5)
[11:13:07 -294500.992949] SLOW spr round 2 (radius: 5)
[11:15:44 -294498.386810] SLOW spr round 3 (radius: 5)
[11:18:17 -294496.306957] SLOW spr round 4 (radius: 5)
[11:20:49 -294495.348554] SLOW spr round 5 (radius: 5)
[11:23:20 -294495.348428] SLOW spr round 6 (radius: 10)
[11:25:51 -294490.360913] SLOW spr round 7 (radius: 5)
[11:29:00 -294486.070556] SLOW spr round 8 (radius: 5)
[11:31:54 -294480.693655] SLOW spr round 9 (radius: 5)
[11:34:33 -294479.119836] SLOW spr round 10 (radius: 5)
[11:37:08 -294479.119584] SLOW spr round 11 (radius: 10)
[11:39:38 -294477.858095] SLOW spr round 12 (radius: 5)
[11:40:53] [worker #1] ML tree search #20, logLikelihood: -294479.072765
[11:42:43 -294477.857990] SLOW spr round 13 (radius: 10)
[11:45:27 -294477.857981] SLOW spr round 14 (radius: 15)
[11:48:57 -294477.857974] SLOW spr round 15 (radius: 20)
[11:53:51 -294477.857968] SLOW spr round 16 (radius: 25)
[11:59:55 -294477.857961] Model parameter optimization (eps = 0.100000)

[12:00:06] [worker #0] ML tree search #19, logLikelihood: -294477.739296


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.190708,0.291110) (0.254965,0.404209) (0.335613,1.057175) (0.218714,2.224920) 
   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: -294474.471738

AIC score: 592958.943475 / AICc score: 8637018.943475 / BIC score: 601959.799362
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=658).
         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/Q9NXL9/3_mltree/Q9NXL9.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/3_mltree/Q9NXL9.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/3_mltree/Q9NXL9.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q9NXL9/3_mltree/Q9NXL9.raxml.log

Analysis started: 19-Jul-2021 03:47:24 / finished: 19-Jul-2021 15:47:31

Elapsed time: 43206.754 seconds