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 14-Jul-2021 16:51:57 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/2_msa/Q9P2J5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/3_mltree/Q9P2J5 --seed 2 --threads 9 --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 (9 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/2_msa/Q9P2J5_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 1268 sites

WARNING: Sequences tr_A0A0E1RZZ0_A0A0E1RZZ0_COCIM_246410 and tr_A0A0J7AWE7_A0A0J7AWE7_COCIT_404692 are exactly identical!
WARNING: Sequences tr_B6QDK7_B6QDK7_TALMQ_441960 and tr_A0A093V2H7_A0A093V2H7_TALMA_1077442 are exactly identical!
WARNING: Sequences tr_B2W5T8_B2W5T8_PYRTR_426418 and tr_A0A2W1FIQ6_A0A2W1FIQ6_9PLEO_45151 are exactly identical!
WARNING: Sequences tr_B8N248_B8N248_ASPFN_332952 and tr_A0A1S9DNK5_A0A1S9DNK5_ASPOZ_5062 are exactly identical!
WARNING: Sequences tr_A0A179U8V3_A0A179U8V3_BLAGS_559298 and tr_C5GVI4_C5GVI4_AJEDR_559297 are exactly identical!
WARNING: Sequences tr_I1QNJ1_I1QNJ1_ORYGL_4538 and tr_A0A0D3H684_A0A0D3H684_9ORYZ_65489 are exactly identical!
WARNING: Sequences tr_F9WY68_F9WY68_ZYMTI_336722 and tr_A0A1X7RGI4_A0A1X7RGI4_ZYMTR_1276538 are exactly identical!
WARNING: Sequences tr_G3YFV8_G3YFV8_ASPNA_380704 and tr_A0A319A0N3_A0A319A0N3_9EURO_1450533 are exactly identical!
WARNING: Sequences tr_W2RA63_W2RA63_PHYPN_761204 and tr_A0A0W8BW27_A0A0W8BW27_PHYNI_4790 are exactly identical!
WARNING: Sequences tr_A0A015IRJ0_A0A015IRJ0_9GLOM_1432141 and tr_U9ULT5_U9ULT5_RHIID_747089 are exactly identical!
WARNING: Sequences tr_A0A094EL43_A0A094EL43_9PEZI_1420912 and tr_A0A1B8G8W3_A0A1B8G8W3_9PEZI_342668 are exactly identical!
WARNING: Sequences tr_X0D069_X0D069_FUSOX_1089458 and tr_A0A2H3HG27_A0A2H3HG27_FUSOX_327505 are exactly identical!
WARNING: Sequences tr_A0A0F8X1P1_A0A0F8X1P1_9EURO_308745 and tr_A0A2T5LPE4_A0A2T5LPE4_9EURO_1392256 are exactly identical!
WARNING: Sequences tr_A0A0A1NWX1_A0A0A1NWX1_9FUNG_58291 and tr_A0A367KDV4_A0A367KDV4_9FUNG_86630 are exactly identical!
WARNING: Sequences tr_A0A319CET6_A0A319CET6_9EURO_1448315 and tr_A0A2V5J0E0_A0A2V5J0E0_9EURO_1450541 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/Q9P2J5/3_mltree/Q9P2J5.raxml.reduced.phy

Alignment comprises 1 partitions and 1268 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1268 / 1268
Gaps: 15.03 %
Invariant sites: 0.55 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/3_mltree/Q9P2J5.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 9 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 / 141 / 11280
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1707243.948502] Initial branch length optimization
[00:00:04 -1486825.919624] Model parameter optimization (eps = 10.000000)
[00:00:34 -1484157.424087] AUTODETECT spr round 1 (radius: 5)
[00:02:48 -1069349.705373] AUTODETECT spr round 2 (radius: 10)
[00:05:22 -785006.133453] AUTODETECT spr round 3 (radius: 15)
[00:08:22 -664115.550490] AUTODETECT spr round 4 (radius: 20)
[00:11:20 -631608.875144] AUTODETECT spr round 5 (radius: 25)
[00:15:02 -627333.696424] SPR radius for FAST iterations: 25 (autodetect)
[00:15:02 -627333.696424] Model parameter optimization (eps = 3.000000)
[00:15:07 -627333.048365] FAST spr round 1 (radius: 25)
[00:18:09 -552789.355109] FAST spr round 2 (radius: 25)
[00:20:19 -549738.971155] FAST spr round 3 (radius: 25)
[00:22:13 -549595.082628] FAST spr round 4 (radius: 25)
[00:23:53 -549587.772839] FAST spr round 5 (radius: 25)
[00:25:25 -549587.772741] Model parameter optimization (eps = 1.000000)
[00:25:41 -549451.094681] SLOW spr round 1 (radius: 5)
[00:28:07 -549338.386383] SLOW spr round 2 (radius: 5)
[00:30:23 -549314.641319] SLOW spr round 3 (radius: 5)
[00:32:30 -549313.924317] SLOW spr round 4 (radius: 5)
[00:34:36 -549313.691703] SLOW spr round 5 (radius: 5)
[00:36:40 -549313.691695] SLOW spr round 6 (radius: 10)
[00:38:50 -549313.147827] SLOW spr round 7 (radius: 5)
[00:41:33 -549312.120241] SLOW spr round 8 (radius: 5)
[00:43:55 -549312.120236] SLOW spr round 9 (radius: 10)
[00:46:07 -549312.120233] SLOW spr round 10 (radius: 15)
[00:49:45 -549312.120230] SLOW spr round 11 (radius: 20)
[00:55:18 -549312.120228] SLOW spr round 12 (radius: 25)
[01:02:14 -549312.120225] Model parameter optimization (eps = 0.100000)

[01:02:21] ML tree search #1, logLikelihood: -549311.596435

[01:02:21 -1696484.696988] Initial branch length optimization
[01:02:26 -1476595.125612] Model parameter optimization (eps = 10.000000)
[01:02:53 -1473924.916140] AUTODETECT spr round 1 (radius: 5)
[01:05:07 -1084222.068650] AUTODETECT spr round 2 (radius: 10)
[01:07:42 -791955.126940] AUTODETECT spr round 3 (radius: 15)
[01:10:21 -671598.743018] AUTODETECT spr round 4 (radius: 20)
[01:13:23 -630759.057403] AUTODETECT spr round 5 (radius: 25)
[01:17:15 -627699.321776] SPR radius for FAST iterations: 25 (autodetect)
[01:17:15 -627699.321776] Model parameter optimization (eps = 3.000000)
[01:17:21 -627697.057403] FAST spr round 1 (radius: 25)
[01:20:18 -552672.465972] FAST spr round 2 (radius: 25)
[01:22:28 -549698.234304] FAST spr round 3 (radius: 25)
[01:24:20 -549594.671273] FAST spr round 4 (radius: 25)
[01:25:56 -549593.816522] FAST spr round 5 (radius: 25)
[01:27:29 -549593.816483] Model parameter optimization (eps = 1.000000)
[01:27:44 -549464.538186] SLOW spr round 1 (radius: 5)
[01:30:10 -549364.825297] SLOW spr round 2 (radius: 5)
[01:32:23 -549349.194268] SLOW spr round 3 (radius: 5)
[01:34:31 -549349.193472] SLOW spr round 4 (radius: 10)
[01:36:41 -549349.169525] SLOW spr round 5 (radius: 15)
[01:40:28 -549349.169443] SLOW spr round 6 (radius: 20)
[01:46:00 -549349.169439] SLOW spr round 7 (radius: 25)
[01:53:07 -549349.169436] Model parameter optimization (eps = 0.100000)

[01:53:14] ML tree search #2, logLikelihood: -549349.044780

[01:53:14 -1707416.496070] Initial branch length optimization
[01:53:19 -1487981.911410] Model parameter optimization (eps = 10.000000)
[01:53:48 -1485399.496910] AUTODETECT spr round 1 (radius: 5)
[01:56:03 -1056256.012392] AUTODETECT spr round 2 (radius: 10)
[01:58:40 -763491.510573] AUTODETECT spr round 3 (radius: 15)
[02:01:20 -627230.012372] AUTODETECT spr round 4 (radius: 20)
[02:04:32 -611290.882964] AUTODETECT spr round 5 (radius: 25)
[02:08:15 -610992.693138] SPR radius for FAST iterations: 25 (autodetect)
[02:08:15 -610992.693138] Model parameter optimization (eps = 3.000000)
[02:08:21 -610990.484003] FAST spr round 1 (radius: 25)
[02:11:17 -551717.192976] FAST spr round 2 (radius: 25)
[02:13:30 -549649.777264] FAST spr round 3 (radius: 25)
[02:15:28 -549546.369937] FAST spr round 4 (radius: 25)
[02:17:05 -549535.743799] FAST spr round 5 (radius: 25)
[02:18:38 -549535.743686] Model parameter optimization (eps = 1.000000)
[02:18:52 -549418.907696] SLOW spr round 1 (radius: 5)
[02:21:23 -549330.991697] SLOW spr round 2 (radius: 5)
[02:23:35 -549327.102955] SLOW spr round 3 (radius: 5)
[02:25:43 -549327.102925] SLOW spr round 4 (radius: 10)
[02:27:54 -549321.520048] SLOW spr round 5 (radius: 5)
[02:30:38 -549318.925807] SLOW spr round 6 (radius: 5)
[02:33:01 -549318.925754] SLOW spr round 7 (radius: 10)
[02:35:15 -549318.925750] SLOW spr round 8 (radius: 15)
[02:38:54 -549318.925747] SLOW spr round 9 (radius: 20)
[02:44:27 -549318.925745] SLOW spr round 10 (radius: 25)
[02:51:24 -549318.925742] Model parameter optimization (eps = 0.100000)

[02:51:35] ML tree search #3, logLikelihood: -549318.467380

[02:51:35 -1708310.426831] Initial branch length optimization
[02:51:40 -1483386.518863] Model parameter optimization (eps = 10.000000)
[02:52:11 -1480727.079181] AUTODETECT spr round 1 (radius: 5)
[02:54:26 -1046896.395740] AUTODETECT spr round 2 (radius: 10)
[02:56:57 -760558.544827] AUTODETECT spr round 3 (radius: 15)
[02:59:34 -646941.861299] AUTODETECT spr round 4 (radius: 20)
[03:02:52 -622945.292099] AUTODETECT spr round 5 (radius: 25)
[03:06:26 -618388.898070] SPR radius for FAST iterations: 25 (autodetect)
[03:06:26 -618388.898070] Model parameter optimization (eps = 3.000000)
[03:06:31 -618387.469163] FAST spr round 1 (radius: 25)
[03:09:28 -551319.973793] FAST spr round 2 (radius: 25)
[03:11:41 -549721.184895] FAST spr round 3 (radius: 25)
[03:13:32 -549654.598489] FAST spr round 4 (radius: 25)
[03:15:08 -549654.598470] Model parameter optimization (eps = 1.000000)
[03:15:23 -549487.370810] SLOW spr round 1 (radius: 5)
[03:17:58 -549351.210001] SLOW spr round 2 (radius: 5)
[03:20:18 -549338.026498] SLOW spr round 3 (radius: 5)
[03:22:28 -549336.334380] SLOW spr round 4 (radius: 5)
[03:24:35 -549336.334234] SLOW spr round 5 (radius: 10)
[03:26:47 -549332.182820] SLOW spr round 6 (radius: 5)
[03:29:32 -549321.427608] SLOW spr round 7 (radius: 5)
[03:31:55 -549321.427276] SLOW spr round 8 (radius: 10)
[03:34:09 -549321.427227] SLOW spr round 9 (radius: 15)
[03:37:47 -549321.427218] SLOW spr round 10 (radius: 20)
[03:43:11 -549321.427215] SLOW spr round 11 (radius: 25)
[03:50:05 -549321.427214] Model parameter optimization (eps = 0.100000)

[03:50:12] ML tree search #4, logLikelihood: -549321.011616

[03:50:13 -1700324.416827] Initial branch length optimization
[03:50:17 -1476566.585069] Model parameter optimization (eps = 10.000000)
[03:50:43 -1474003.706207] AUTODETECT spr round 1 (radius: 5)
[03:52:59 -1043434.076334] AUTODETECT spr round 2 (radius: 10)
[03:55:30 -742505.655475] AUTODETECT spr round 3 (radius: 15)
[03:58:13 -653186.857741] AUTODETECT spr round 4 (radius: 20)
[04:01:33 -624324.374284] AUTODETECT spr round 5 (radius: 25)
[04:05:10 -613854.588927] SPR radius for FAST iterations: 25 (autodetect)
[04:05:10 -613854.588927] Model parameter optimization (eps = 3.000000)
[04:05:25 -613756.456019] FAST spr round 1 (radius: 25)
[04:08:23 -552235.934703] FAST spr round 2 (radius: 25)
[04:10:34 -549652.618893] FAST spr round 3 (radius: 25)
[04:12:34 -549537.049892] FAST spr round 4 (radius: 25)
[04:14:13 -549531.606760] FAST spr round 5 (radius: 25)
[04:15:48 -549528.890005] FAST spr round 6 (radius: 25)
[04:17:20 -549528.889992] Model parameter optimization (eps = 1.000000)
[04:17:33 -549520.352209] SLOW spr round 1 (radius: 5)
[04:19:57 -549384.230566] SLOW spr round 2 (radius: 5)
[04:22:10 -549359.556498] SLOW spr round 3 (radius: 5)
[04:24:18 -549356.138870] SLOW spr round 4 (radius: 5)
[04:26:25 -549356.138024] SLOW spr round 5 (radius: 10)
[04:28:35 -549356.137833] SLOW spr round 6 (radius: 15)
[04:32:26 -549356.137790] SLOW spr round 7 (radius: 20)
[04:38:10 -549356.137780] SLOW spr round 8 (radius: 25)
[04:45:28 -549356.137778] Model parameter optimization (eps = 0.100000)

[04:45:38] ML tree search #5, logLikelihood: -549356.015591

[04:45:38 -1709927.082031] Initial branch length optimization
[04:45:42 -1487964.236116] Model parameter optimization (eps = 10.000000)
[04:46:17 -1485426.498179] AUTODETECT spr round 1 (radius: 5)
[04:48:32 -1053861.059169] AUTODETECT spr round 2 (radius: 10)
[04:51:08 -736238.118982] AUTODETECT spr round 3 (radius: 15)
[04:53:47 -643750.872447] AUTODETECT spr round 4 (radius: 20)
[04:57:05 -622367.216477] AUTODETECT spr round 5 (radius: 25)
[05:01:13 -619915.067227] SPR radius for FAST iterations: 25 (autodetect)
[05:01:13 -619915.067227] Model parameter optimization (eps = 3.000000)
[05:01:27 -619762.180296] FAST spr round 1 (radius: 25)
[05:04:28 -552172.553487] FAST spr round 2 (radius: 25)
[05:06:39 -549656.909826] FAST spr round 3 (radius: 25)
[05:08:33 -549527.409109] FAST spr round 4 (radius: 25)
[05:10:14 -549489.933383] FAST spr round 5 (radius: 25)
[05:11:46 -549489.700881] FAST spr round 6 (radius: 25)
[05:13:16 -549489.700845] Model parameter optimization (eps = 1.000000)
[05:13:28 -549482.954091] SLOW spr round 1 (radius: 5)
[05:15:54 -549349.148666] SLOW spr round 2 (radius: 5)
[05:18:05 -549338.362735] SLOW spr round 3 (radius: 5)
[05:20:12 -549336.070884] SLOW spr round 4 (radius: 5)
[05:22:16 -549336.070830] SLOW spr round 5 (radius: 10)
[05:24:26 -549333.120166] SLOW spr round 6 (radius: 5)
[05:27:16 -549322.536781] SLOW spr round 7 (radius: 5)
[05:29:37 -549322.536733] SLOW spr round 8 (radius: 10)
[05:31:49 -549322.536727] SLOW spr round 9 (radius: 15)
[05:35:27 -549322.536726] SLOW spr round 10 (radius: 20)
[05:40:59 -549322.536726] SLOW spr round 11 (radius: 25)
[05:47:55 -549322.536726] Model parameter optimization (eps = 0.100000)

[05:48:02] ML tree search #6, logLikelihood: -549322.378659

[05:48:02 -1702590.177743] Initial branch length optimization
[05:48:06 -1482301.782996] Model parameter optimization (eps = 10.000000)
[05:48:41 -1479549.058264] AUTODETECT spr round 1 (radius: 5)
[05:50:53 -1061080.108296] AUTODETECT spr round 2 (radius: 10)
[05:53:28 -770317.218024] AUTODETECT spr round 3 (radius: 15)
[05:56:21 -668464.678157] AUTODETECT spr round 4 (radius: 20)
[05:59:31 -638263.153409] AUTODETECT spr round 5 (radius: 25)
[06:03:28 -621888.667959] SPR radius for FAST iterations: 25 (autodetect)
[06:03:28 -621888.667959] Model parameter optimization (eps = 3.000000)
[06:03:44 -621757.717755] FAST spr round 1 (radius: 25)
[06:06:51 -552187.535903] FAST spr round 2 (radius: 25)
[06:09:01 -549720.479405] FAST spr round 3 (radius: 25)
[06:10:58 -549474.124433] FAST spr round 4 (radius: 25)
[06:12:40 -549450.359841] FAST spr round 5 (radius: 25)
[06:14:12 -549450.359658] Model parameter optimization (eps = 1.000000)
[06:14:24 -549445.694311] SLOW spr round 1 (radius: 5)
[06:16:51 -549364.370408] SLOW spr round 2 (radius: 5)
[06:19:03 -549359.004983] SLOW spr round 3 (radius: 5)
[06:21:09 -549359.004668] SLOW spr round 4 (radius: 10)
[06:23:18 -549359.004646] SLOW spr round 5 (radius: 15)
[06:27:02 -549359.004642] SLOW spr round 6 (radius: 20)
[06:32:26 -549359.004641] SLOW spr round 7 (radius: 25)
[06:39:29 -549359.004640] Model parameter optimization (eps = 0.100000)

[06:39:33] ML tree search #7, logLikelihood: -549358.945509

[06:39:33 -1715580.603818] Initial branch length optimization
[06:39:37 -1493837.780974] Model parameter optimization (eps = 10.000000)
[06:40:07 -1491092.498140] AUTODETECT spr round 1 (radius: 5)
[06:42:20 -1059666.535421] AUTODETECT spr round 2 (radius: 10)
[06:44:50 -782772.612415] AUTODETECT spr round 3 (radius: 15)
[06:47:31 -690036.539873] AUTODETECT spr round 4 (radius: 20)
[06:50:39 -644059.061012] AUTODETECT spr round 5 (radius: 25)
[06:54:54 -633167.643933] SPR radius for FAST iterations: 25 (autodetect)
[06:54:54 -633167.643933] Model parameter optimization (eps = 3.000000)
[06:55:00 -633165.870425] FAST spr round 1 (radius: 25)
[06:58:02 -552591.264909] FAST spr round 2 (radius: 25)
[07:00:11 -549868.009040] FAST spr round 3 (radius: 25)
[07:02:06 -549658.986225] FAST spr round 4 (radius: 25)
[07:03:42 -549658.986218] Model parameter optimization (eps = 1.000000)
[07:03:55 -549510.383185] SLOW spr round 1 (radius: 5)
[07:06:27 -549385.725583] SLOW spr round 2 (radius: 5)
[07:08:45 -549352.840257] SLOW spr round 3 (radius: 5)
[07:10:53 -549335.528209] SLOW spr round 4 (radius: 5)
[07:12:58 -549335.528091] SLOW spr round 5 (radius: 10)
[07:15:07 -549335.528090] SLOW spr round 6 (radius: 15)
[07:18:50 -549335.528089] SLOW spr round 7 (radius: 20)
[07:24:11 -549335.528087] SLOW spr round 8 (radius: 25)
[07:31:10 -549335.528086] Model parameter optimization (eps = 0.100000)

[07:31:21] ML tree search #8, logLikelihood: -549334.623254

[07:31:21 -1706047.319578] Initial branch length optimization
[07:31:28 -1484198.301815] Model parameter optimization (eps = 10.000000)
[07:31:55 -1481568.944193] AUTODETECT spr round 1 (radius: 5)
[07:34:07 -1062906.489994] AUTODETECT spr round 2 (radius: 10)
[07:36:38 -798309.719134] AUTODETECT spr round 3 (radius: 15)
[07:39:40 -651154.369166] AUTODETECT spr round 4 (radius: 20)
[07:43:05 -620428.075233] AUTODETECT spr round 5 (radius: 25)
[07:46:46 -619683.483106] SPR radius for FAST iterations: 25 (autodetect)
[07:46:46 -619683.483106] Model parameter optimization (eps = 3.000000)
[07:47:04 -619497.110306] FAST spr round 1 (radius: 25)
[07:49:59 -551117.304597] FAST spr round 2 (radius: 25)
[07:52:06 -549738.624287] FAST spr round 3 (radius: 25)
[07:54:03 -549526.014810] FAST spr round 4 (radius: 25)
[07:55:48 -549480.002213] FAST spr round 5 (radius: 25)
[07:57:20 -549480.002184] Model parameter optimization (eps = 1.000000)
[07:57:32 -549473.885129] SLOW spr round 1 (radius: 5)
[08:00:01 -549322.845028] SLOW spr round 2 (radius: 5)
[08:02:18 -549311.931762] SLOW spr round 3 (radius: 5)
[08:04:24 -549311.931739] SLOW spr round 4 (radius: 10)
[08:06:34 -549311.931736] SLOW spr round 5 (radius: 15)
[08:10:18 -549311.931733] SLOW spr round 6 (radius: 20)
[08:15:50 -549311.931731] SLOW spr round 7 (radius: 25)
[08:22:57 -549311.931728] Model parameter optimization (eps = 0.100000)

[08:23:05] ML tree search #9, logLikelihood: -549311.794332

[08:23:05 -1712780.514041] Initial branch length optimization
[08:23:11 -1487465.928325] Model parameter optimization (eps = 10.000000)
[08:23:42 -1484828.248010] AUTODETECT spr round 1 (radius: 5)
[08:25:57 -1071071.521169] AUTODETECT spr round 2 (radius: 10)
[08:28:29 -828062.142655] AUTODETECT spr round 3 (radius: 15)
[08:31:37 -670781.223308] AUTODETECT spr round 4 (radius: 20)
[08:34:43 -642004.939928] AUTODETECT spr round 5 (radius: 25)
[08:38:56 -634246.541161] SPR radius for FAST iterations: 25 (autodetect)
[08:38:56 -634246.541161] Model parameter optimization (eps = 3.000000)
[08:39:11 -634140.643085] FAST spr round 1 (radius: 25)
[08:42:24 -552122.121257] FAST spr round 2 (radius: 25)
[08:44:32 -549628.751200] FAST spr round 3 (radius: 25)
[08:46:26 -549485.489969] FAST spr round 4 (radius: 25)
[08:48:03 -549465.433021] FAST spr round 5 (radius: 25)
[08:49:35 -549465.432996] Model parameter optimization (eps = 1.000000)
[08:49:49 -549455.773184] SLOW spr round 1 (radius: 5)
[08:52:14 -549341.511634] SLOW spr round 2 (radius: 5)
[08:54:26 -549333.343272] SLOW spr round 3 (radius: 5)
[08:56:33 -549333.342996] SLOW spr round 4 (radius: 10)
[08:58:42 -549333.078891] SLOW spr round 5 (radius: 5)
[09:01:25 -549329.125238] SLOW spr round 6 (radius: 5)
[09:03:47 -549329.125233] SLOW spr round 7 (radius: 10)
[09:05:59 -549329.125232] SLOW spr round 8 (radius: 15)
[09:09:35 -549329.125231] SLOW spr round 9 (radius: 20)
[09:15:00 -549329.125230] SLOW spr round 10 (radius: 25)
[09:21:58 -549329.125229] Model parameter optimization (eps = 0.100000)

[09:22:07] ML tree search #10, logLikelihood: -549328.998100

[09:22:07 -1706130.557687] Initial branch length optimization
[09:22:11 -1483734.415240] Model parameter optimization (eps = 10.000000)
[09:22:41 -1481063.254928] AUTODETECT spr round 1 (radius: 5)
[09:24:55 -1060906.550620] AUTODETECT spr round 2 (radius: 10)
[09:27:26 -774964.737434] AUTODETECT spr round 3 (radius: 15)
[09:29:58 -649879.682768] AUTODETECT spr round 4 (radius: 20)
[09:33:06 -624991.145071] AUTODETECT spr round 5 (radius: 25)
[09:36:42 -614223.678650] SPR radius for FAST iterations: 25 (autodetect)
[09:36:42 -614223.678650] Model parameter optimization (eps = 3.000000)
[09:36:58 -614061.618143] FAST spr round 1 (radius: 25)
[09:39:52 -551280.539745] FAST spr round 2 (radius: 25)
[09:42:02 -549586.807407] FAST spr round 3 (radius: 25)
[09:43:55 -549483.520553] FAST spr round 4 (radius: 25)
[09:45:31 -549477.271276] FAST spr round 5 (radius: 25)
[09:47:03 -549470.413488] FAST spr round 6 (radius: 25)
[09:48:33 -549470.413481] Model parameter optimization (eps = 1.000000)
[09:48:44 -549468.686848] SLOW spr round 1 (radius: 5)
[09:51:05 -549349.506554] SLOW spr round 2 (radius: 5)
[09:53:15 -549341.266070] SLOW spr round 3 (radius: 5)
[09:55:22 -549337.654469] SLOW spr round 4 (radius: 5)
[09:57:27 -549337.652936] SLOW spr round 5 (radius: 10)
[09:59:34 -549337.652586] SLOW spr round 6 (radius: 15)
[10:03:20 -549337.652504] SLOW spr round 7 (radius: 20)
[10:08:49 -549337.652484] SLOW spr round 8 (radius: 25)
[10:16:02 -549337.652478] Model parameter optimization (eps = 0.100000)

[10:16:08] ML tree search #11, logLikelihood: -549337.616307

[10:16:08 -1705759.612465] Initial branch length optimization
[10:16:12 -1484575.939403] Model parameter optimization (eps = 10.000000)
[10:16:38 -1481979.314401] AUTODETECT spr round 1 (radius: 5)
[10:18:51 -1058475.617187] AUTODETECT spr round 2 (radius: 10)
[10:21:26 -745871.051265] AUTODETECT spr round 3 (radius: 15)
[10:24:10 -645249.685032] AUTODETECT spr round 4 (radius: 20)
[10:27:11 -619992.261298] AUTODETECT spr round 5 (radius: 25)
[10:30:44 -617587.332019] SPR radius for FAST iterations: 25 (autodetect)
[10:30:44 -617587.332019] Model parameter optimization (eps = 3.000000)
[10:31:06 -617477.681570] FAST spr round 1 (radius: 25)
[10:34:04 -552370.482741] FAST spr round 2 (radius: 25)
[10:36:11 -549775.410821] FAST spr round 3 (radius: 25)
[10:38:04 -549485.358472] FAST spr round 4 (radius: 25)
[10:39:41 -549474.239421] FAST spr round 5 (radius: 25)
[10:41:13 -549474.239417] Model parameter optimization (eps = 1.000000)
[10:41:22 -549473.450996] SLOW spr round 1 (radius: 5)
[10:43:47 -549328.973907] SLOW spr round 2 (radius: 5)
[10:46:00 -549318.963444] SLOW spr round 3 (radius: 5)
[10:48:06 -549318.963400] SLOW spr round 4 (radius: 10)
[10:50:16 -549318.963396] SLOW spr round 5 (radius: 15)
[10:54:00 -549318.963393] SLOW spr round 6 (radius: 20)
[10:59:27 -549318.963390] SLOW spr round 7 (radius: 25)
[11:06:32 -549318.963387] Model parameter optimization (eps = 0.100000)

[11:06:41] ML tree search #12, logLikelihood: -549318.518419

[11:06:41 -1703933.971556] Initial branch length optimization
[11:06:46 -1485514.295375] Model parameter optimization (eps = 10.000000)
[11:07:21 -1482906.543700] AUTODETECT spr round 1 (radius: 5)
[11:09:35 -1064073.444431] AUTODETECT spr round 2 (radius: 10)
[11:12:08 -748248.283646] AUTODETECT spr round 3 (radius: 15)
[11:14:45 -649046.278130] AUTODETECT spr round 4 (radius: 20)
[11:17:55 -627693.454759] AUTODETECT spr round 5 (radius: 25)
[11:21:30 -623595.547286] SPR radius for FAST iterations: 25 (autodetect)
[11:21:30 -623595.547286] Model parameter optimization (eps = 3.000000)
[11:21:49 -623433.731163] FAST spr round 1 (radius: 25)
[11:24:43 -551711.890001] FAST spr round 2 (radius: 25)
[11:26:51 -549594.736767] FAST spr round 3 (radius: 25)
[11:28:40 -549518.056257] FAST spr round 4 (radius: 25)
[11:30:15 -549512.402815] FAST spr round 5 (radius: 25)
[11:31:47 -549512.402169] Model parameter optimization (eps = 1.000000)
[11:31:58 -549507.482978] SLOW spr round 1 (radius: 5)
[11:34:23 -549378.064622] SLOW spr round 2 (radius: 5)
[11:36:36 -549369.282242] SLOW spr round 3 (radius: 5)
[11:38:44 -549366.962821] SLOW spr round 4 (radius: 5)
[11:40:50 -549366.962811] SLOW spr round 5 (radius: 10)
[11:43:01 -549364.581252] SLOW spr round 6 (radius: 5)
[11:45:46 -549355.638333] SLOW spr round 7 (radius: 5)
[11:48:08 -549355.638028] SLOW spr round 8 (radius: 10)
[11:50:22 -549355.637997] SLOW spr round 9 (radius: 15)
[11:54:00 -549355.637989] SLOW spr round 10 (radius: 20)
[11:59:31 -549355.637984] SLOW spr round 11 (radius: 25)
[12:06:29 -549355.637980] Model parameter optimization (eps = 0.100000)

[12:06:36] ML tree search #13, logLikelihood: -549354.893969

[12:06:36 -1709953.453240] Initial branch length optimization
[12:06:40 -1488073.845523] Model parameter optimization (eps = 10.000000)
[12:07:10 -1485317.252299] AUTODETECT spr round 1 (radius: 5)
[12:09:24 -1065528.087183] AUTODETECT spr round 2 (radius: 10)
[12:11:55 -779471.656676] AUTODETECT spr round 3 (radius: 15)
[12:14:35 -661644.764899] AUTODETECT spr round 4 (radius: 20)
[12:17:34 -645228.762884] AUTODETECT spr round 5 (radius: 25)
[12:20:46 -636979.391411] SPR radius for FAST iterations: 25 (autodetect)
[12:20:46 -636979.391411] Model parameter optimization (eps = 3.000000)
[12:21:04 -636890.459851] FAST spr round 1 (radius: 25)
[12:24:11 -552581.648476] FAST spr round 2 (radius: 25)
[12:26:23 -549616.502224] FAST spr round 3 (radius: 25)
[12:28:17 -549485.602865] FAST spr round 4 (radius: 25)
[12:29:57 -549470.626296] FAST spr round 5 (radius: 25)
[12:31:29 -549470.626242] Model parameter optimization (eps = 1.000000)
[12:31:39 -549465.689247] SLOW spr round 1 (radius: 5)
[12:34:10 -549342.993799] SLOW spr round 2 (radius: 5)
[12:36:28 -549329.553027] SLOW spr round 3 (radius: 5)
[12:38:37 -549327.202445] SLOW spr round 4 (radius: 5)
[12:40:43 -549327.202439] SLOW spr round 5 (radius: 10)
[12:42:53 -549321.164783] SLOW spr round 6 (radius: 5)
[12:45:36 -549319.562957] SLOW spr round 7 (radius: 5)
[12:47:58 -549319.562956] SLOW spr round 8 (radius: 10)
[12:50:11 -549319.562956] SLOW spr round 9 (radius: 15)
[12:53:49 -549319.562956] SLOW spr round 10 (radius: 20)
[12:59:24 -549319.562956] SLOW spr round 11 (radius: 25)
[13:06:28 -549319.562956] Model parameter optimization (eps = 0.100000)

[13:06:35] ML tree search #14, logLikelihood: -549318.953531

[13:06:35 -1704668.307831] Initial branch length optimization
[13:06:39 -1481761.816668] Model parameter optimization (eps = 10.000000)
[13:07:12 -1479317.743290] AUTODETECT spr round 1 (radius: 5)
[13:09:26 -1058454.272916] AUTODETECT spr round 2 (radius: 10)
[13:11:59 -762838.962248] AUTODETECT spr round 3 (radius: 15)
[13:14:39 -706789.768443] AUTODETECT spr round 4 (radius: 20)
[13:18:01 -652305.869338] AUTODETECT spr round 5 (radius: 25)
[13:21:48 -642784.661226] SPR radius for FAST iterations: 25 (autodetect)
[13:21:48 -642784.661226] Model parameter optimization (eps = 3.000000)
[13:22:07 -642611.328111] FAST spr round 1 (radius: 25)
[13:25:19 -553262.282140] FAST spr round 2 (radius: 25)
[13:27:27 -549687.619558] FAST spr round 3 (radius: 25)
[13:29:19 -549472.951296] FAST spr round 4 (radius: 25)
[13:30:56 -549465.928989] FAST spr round 5 (radius: 25)
[13:32:28 -549465.928963] Model parameter optimization (eps = 1.000000)
[13:32:38 -549463.288810] SLOW spr round 1 (radius: 5)
[13:35:04 -549363.959547] SLOW spr round 2 (radius: 5)
[13:37:21 -549345.031535] SLOW spr round 3 (radius: 5)
[13:39:30 -549343.458468] SLOW spr round 4 (radius: 5)
[13:41:35 -549343.458136] SLOW spr round 5 (radius: 10)
[13:43:45 -549343.458063] SLOW spr round 6 (radius: 15)
[13:47:32 -549343.458045] SLOW spr round 7 (radius: 20)
[13:53:06 -549343.458039] SLOW spr round 8 (radius: 25)
[14:00:24 -549343.458036] Model parameter optimization (eps = 0.100000)

[14:00:32] ML tree search #15, logLikelihood: -549343.277234

[14:00:33 -1703985.991308] Initial branch length optimization
[14:00:36 -1483238.462512] Model parameter optimization (eps = 10.000000)
[14:01:02 -1480633.200204] AUTODETECT spr round 1 (radius: 5)
[14:03:14 -1075915.643904] AUTODETECT spr round 2 (radius: 10)
[14:05:48 -790028.973161] AUTODETECT spr round 3 (radius: 15)
[14:08:31 -667737.300952] AUTODETECT spr round 4 (radius: 20)
[14:11:31 -631582.778876] AUTODETECT spr round 5 (radius: 25)
[14:14:36 -624989.105190] SPR radius for FAST iterations: 25 (autodetect)
[14:14:36 -624989.105190] Model parameter optimization (eps = 3.000000)
[14:14:51 -624877.403542] FAST spr round 1 (radius: 25)
[14:17:46 -551936.675357] FAST spr round 2 (radius: 25)
[14:19:56 -549639.178993] FAST spr round 3 (radius: 25)
[14:21:51 -549578.872533] FAST spr round 4 (radius: 25)
[14:23:35 -549488.883504] FAST spr round 5 (radius: 25)
[14:25:14 -549474.891128] FAST spr round 6 (radius: 25)
[14:26:45 -549474.890889] Model parameter optimization (eps = 1.000000)
[14:26:56 -549472.452456] SLOW spr round 1 (radius: 5)
[14:29:22 -549372.062599] SLOW spr round 2 (radius: 5)
[14:31:40 -549341.230188] SLOW spr round 3 (radius: 5)
[14:33:47 -549341.229906] SLOW spr round 4 (radius: 10)
[14:35:57 -549339.756637] SLOW spr round 5 (radius: 5)
[14:38:40 -549338.884170] SLOW spr round 6 (radius: 5)
[14:41:02 -549338.884170] SLOW spr round 7 (radius: 10)
[14:43:16 -549338.884169] SLOW spr round 8 (radius: 15)
[14:46:55 -549338.884169] SLOW spr round 9 (radius: 20)
[14:52:31 -549338.884169] SLOW spr round 10 (radius: 25)
[14:59:37 -549338.884169] Model parameter optimization (eps = 0.100000)

[14:59:44] ML tree search #16, logLikelihood: -549338.677777

[14:59:44 -1705814.173870] Initial branch length optimization
[14:59:48 -1483130.971490] Model parameter optimization (eps = 10.000000)
[15:00:35 -1480675.966290] AUTODETECT spr round 1 (radius: 5)
[15:02:48 -1054098.692531] AUTODETECT spr round 2 (radius: 10)
[15:05:20 -768920.960871] AUTODETECT spr round 3 (radius: 15)
[15:08:06 -650618.536504] AUTODETECT spr round 4 (radius: 20)
[15:11:04 -624429.900468] AUTODETECT spr round 5 (radius: 25)
[15:14:31 -620151.225855] SPR radius for FAST iterations: 25 (autodetect)
[15:14:31 -620151.225855] Model parameter optimization (eps = 3.000000)
[15:14:46 -620016.422355] FAST spr round 1 (radius: 25)
[15:17:46 -551794.646487] FAST spr round 2 (radius: 25)
[15:19:55 -549592.566446] FAST spr round 3 (radius: 25)
[15:21:50 -549495.695390] FAST spr round 4 (radius: 25)
[15:23:24 -549495.695379] Model parameter optimization (eps = 1.000000)
[15:23:32 -549495.059010] SLOW spr round 1 (radius: 5)
[15:26:02 -549370.771615] SLOW spr round 2 (radius: 5)
[15:28:17 -549358.161298] SLOW spr round 3 (radius: 5)
[15:30:25 -549356.973461] SLOW spr round 4 (radius: 5)
[15:32:31 -549356.973431] SLOW spr round 5 (radius: 10)
[15:34:42 -549353.696896] SLOW spr round 6 (radius: 5)
[15:37:25 -549346.837468] SLOW spr round 7 (radius: 5)
[15:39:47 -549344.329485] SLOW spr round 8 (radius: 5)
[15:41:58 -549344.329357] SLOW spr round 9 (radius: 10)
[15:44:08 -549344.329347] SLOW spr round 10 (radius: 15)
[15:47:50 -549344.329343] SLOW spr round 11 (radius: 20)
[15:53:15 -549344.329342] SLOW spr round 12 (radius: 25)
[16:00:10 -549344.329340] Model parameter optimization (eps = 0.100000)

[16:00:15] ML tree search #17, logLikelihood: -549344.269149

[16:00:15 -1702119.648377] Initial branch length optimization
[16:00:21 -1481513.884673] Model parameter optimization (eps = 10.000000)
[16:00:50 -1478815.613630] AUTODETECT spr round 1 (radius: 5)
[16:03:04 -1060278.620234] AUTODETECT spr round 2 (radius: 10)
[16:05:33 -788271.689744] AUTODETECT spr round 3 (radius: 15)
[16:08:20 -682941.217624] AUTODETECT spr round 4 (radius: 20)
[16:11:35 -633910.080442] AUTODETECT spr round 5 (radius: 25)
[16:15:17 -629681.275303] SPR radius for FAST iterations: 25 (autodetect)
[16:15:17 -629681.275303] Model parameter optimization (eps = 3.000000)
[16:15:23 -629679.236522] FAST spr round 1 (radius: 25)
[16:18:23 -551908.234893] FAST spr round 2 (radius: 25)
[16:20:34 -549771.771537] FAST spr round 3 (radius: 25)
[16:22:25 -549675.508823] FAST spr round 4 (radius: 25)
[16:24:09 -549631.380907] FAST spr round 5 (radius: 25)
[16:25:46 -549614.901610] FAST spr round 6 (radius: 25)
[16:27:16 -549614.901605] Model parameter optimization (eps = 1.000000)
[16:27:31 -549453.655257] SLOW spr round 1 (radius: 5)
[16:29:59 -549351.709701] SLOW spr round 2 (radius: 5)
[16:32:10 -549339.327315] SLOW spr round 3 (radius: 5)
[16:34:16 -549335.949282] SLOW spr round 4 (radius: 5)
[16:36:23 -549333.879504] SLOW spr round 5 (radius: 5)
[16:38:28 -549332.219247] SLOW spr round 6 (radius: 5)
[16:40:32 -549332.219211] SLOW spr round 7 (radius: 10)
[16:42:41 -549332.219203] SLOW spr round 8 (radius: 15)
[16:46:27 -549332.219200] SLOW spr round 9 (radius: 20)
[16:51:55 -549332.219198] SLOW spr round 10 (radius: 25)
[16:59:06 -549332.219197] Model parameter optimization (eps = 0.100000)

[16:59:13] ML tree search #18, logLikelihood: -549331.985377

[16:59:13 -1707140.962062] Initial branch length optimization
[16:59:17 -1487219.382208] Model parameter optimization (eps = 10.000000)
[16:59:49 -1484575.947842] AUTODETECT spr round 1 (radius: 5)
[17:02:03 -1053335.756797] AUTODETECT spr round 2 (radius: 10)
[17:04:36 -761052.522112] AUTODETECT spr round 3 (radius: 15)
[17:07:13 -639648.310120] AUTODETECT spr round 4 (radius: 20)
[17:10:37 -617723.785982] AUTODETECT spr round 5 (radius: 25)
[17:14:13 -616195.280401] SPR radius for FAST iterations: 25 (autodetect)
[17:14:13 -616195.280401] Model parameter optimization (eps = 3.000000)
[17:14:32 -616067.861988] FAST spr round 1 (radius: 25)
[17:17:31 -551840.034170] FAST spr round 2 (radius: 25)
[17:19:44 -549645.257460] FAST spr round 3 (radius: 25)
[17:21:41 -549466.425968] FAST spr round 4 (radius: 25)
[17:23:22 -549451.266951] FAST spr round 5 (radius: 25)
[17:24:54 -549451.266753] Model parameter optimization (eps = 1.000000)
[17:25:07 -549450.150447] SLOW spr round 1 (radius: 5)
[17:27:32 -549358.404689] SLOW spr round 2 (radius: 5)
[17:29:44 -549354.605055] SLOW spr round 3 (radius: 5)
[17:31:51 -549354.604932] SLOW spr round 4 (radius: 10)
[17:34:01 -549348.835563] SLOW spr round 5 (radius: 5)
[17:36:44 -549347.227426] SLOW spr round 6 (radius: 5)
[17:39:06 -549347.227424] SLOW spr round 7 (radius: 10)
[17:41:19 -549347.227424] SLOW spr round 8 (radius: 15)
[17:44:59 -549347.227424] SLOW spr round 9 (radius: 20)
[17:50:35 -549347.227424] SLOW spr round 10 (radius: 25)
[17:57:47 -549347.227424] Model parameter optimization (eps = 0.100000)

[17:57:52] ML tree search #19, logLikelihood: -549347.133442

[17:57:52 -1705095.702703] Initial branch length optimization
[17:57:56 -1482682.542567] Model parameter optimization (eps = 10.000000)
[17:58:28 -1480032.238908] AUTODETECT spr round 1 (radius: 5)
[18:00:42 -1062824.212364] AUTODETECT spr round 2 (radius: 10)
[18:03:13 -756643.616574] AUTODETECT spr round 3 (radius: 15)
[18:05:58 -637563.013449] AUTODETECT spr round 4 (radius: 20)
[18:08:56 -615680.162974] AUTODETECT spr round 5 (radius: 25)
[18:12:06 -613043.800771] SPR radius for FAST iterations: 25 (autodetect)
[18:12:07 -613043.800771] Model parameter optimization (eps = 3.000000)
[18:12:25 -612904.248952] FAST spr round 1 (radius: 25)
[18:15:24 -551276.039450] FAST spr round 2 (radius: 25)
[18:17:37 -549703.719223] FAST spr round 3 (radius: 25)
[18:19:31 -549510.348009] FAST spr round 4 (radius: 25)
[18:21:11 -549491.481379] FAST spr round 5 (radius: 25)
[18:22:45 -549488.193531] FAST spr round 6 (radius: 25)
[18:24:16 -549488.193451] Model parameter optimization (eps = 1.000000)
[18:24:27 -549486.080261] SLOW spr round 1 (radius: 5)
[18:26:55 -549363.310722] SLOW spr round 2 (radius: 5)
[18:29:09 -549350.998384] SLOW spr round 3 (radius: 5)
[18:31:16 -549350.458664] SLOW spr round 4 (radius: 5)
[18:33:22 -549350.458459] SLOW spr round 5 (radius: 10)
[18:35:32 -549350.458412] SLOW spr round 6 (radius: 15)
[18:39:22 -549350.458400] SLOW spr round 7 (radius: 20)
[18:44:58 -549350.458396] SLOW spr round 8 (radius: 25)
[18:52:18 -549350.458394] Model parameter optimization (eps = 0.100000)

[18:52:25] ML tree search #20, logLikelihood: -549350.113424


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.172461,0.238436) (0.263838,0.408074) (0.284519,0.914261) (0.279182,2.117217) 
   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: -549311.596435

AIC score: 1102633.192869 / AICc score: 9146693.192869 / BIC score: 1112949.311120
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=1268).
         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/Q9P2J5/3_mltree/Q9P2J5.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/3_mltree/Q9P2J5.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/3_mltree/Q9P2J5.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P2J5/3_mltree/Q9P2J5.raxml.log

Analysis started: 14-Jul-2021 16:51:57 / finished: 15-Jul-2021 11:44:22

Elapsed time: 67945.251 seconds

Consumed energy: 5919.889 Wh (= 30 km in an electric car, or 148 km with an e-scooter!)