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 03-Jul-2021 12:17:56 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/2_msa/Q96A09_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/3_mltree/Q96A09 --seed 2 --threads 6 --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 (6 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/2_msa/Q96A09_trimmed_msa.fasta
[00:00:00] Loaded alignment with 546 taxa and 392 sites

WARNING: Sequences tr_M3Z324_M3Z324_MUSPF_9669 and tr_A0A286XJY7_A0A286XJY7_CAVPO_10141 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_A0A2I2YLA0_A0A2I2YLA0_GORGO_9595 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_H2N673_H2N673_PONAB_9601 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_G2HIG9_G2HIG9_PANTR_9598 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_F7CJC7_F7CJC7_MACMU_9544 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_G7NX57_G7NX57_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_A0A2K5KZL7_A0A2K5KZL7_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_A0A2K6AWU7_A0A2K6AWU7_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2I3H148_A0A2I3H148_NOMLE_61853 and tr_A0A2R8ZMB3_A0A2R8ZMB3_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_F7G705_F7G705_MACMU_9544 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A2R8MMQ7_A0A2R8MMQ7_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A2I3N7A5_A0A2I3N7A5_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A0D9RXU8_A0A0D9RXU8_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A2K5P1K6_A0A2K5P1K6_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A2K6BDI0_A0A2K6BDI0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G1RPH5_G1RPH5_NOMLE_61853 and tr_A0A2K5Z187_A0A2K5Z187_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G3QFV6_G3QFV6_GORGO_9595 and tr_H2PJN7_H2PJN7_PONAB_9601 are exactly identical!
WARNING: Sequences tr_G3QFV6_G3QFV6_GORGO_9595 and tr_A0A2I3RLJ1_A0A2I3RLJ1_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3QFV6_G3QFV6_GORGO_9595 and sp_Q96IP4_TET5A_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G3QFV6_G3QFV6_GORGO_9595 and tr_A0A2R8ZZJ1_A0A2R8ZZJ1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G3QYF7_G3QYF7_GORGO_9595 and tr_H2PYE9_H2PYE9_PANTR_9598 are exactly identical!
WARNING: Sequences tr_Q292G0_Q292G0_DROPS_46245 and tr_B4GDL0_B4GDL0_DROPE_7234 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_E1B8X5_E1B8X5_BOVIN_9913 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_A0A2U3VX30_A0A2U3VX30_ODORO_9708 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_A0A2U3XX15_A0A2U3XX15_LEPWE_9713 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_A0A2Y9PGG2_A0A2Y9PGG2_DELLE_9749 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_A0A2Y9TIR3_A0A2Y9TIR3_PHYCD_9755 are exactly identical!
WARNING: Sequences tr_F7AJW0_F7AJW0_HORSE_9796 and tr_A0A383YZ28_A0A383YZ28_BALAS_310752 are exactly identical!
WARNING: Sequences tr_A0A158NRG1_A0A158NRG1_ATTCE_12957 and tr_F4WBR5_F4WBR5_ACREC_103372 are exactly identical!
WARNING: Sequences tr_F6UZX0_F6UZX0_MACMU_9544 and tr_G8F374_G8F374_MACFA_9541 are exactly identical!
WARNING: Sequences tr_Q16FN8_Q16FN8_AEDAE_7159 and tr_Q16HP5_Q16HP5_AEDAE_7159 are exactly identical!
WARNING: Sequences tr_U3JJ39_U3JJ39_FICAL_59894 and tr_A0A218VBK2_A0A218VBK2_9PASE_299123 are exactly identical!
WARNING: Sequences tr_U3JJ39_U3JJ39_FICAL_59894 and tr_A0A226NE43_A0A226NE43_CALSU_9009 are exactly identical!
WARNING: Sequences tr_U3JJ39_U3JJ39_FICAL_59894 and tr_A0A226P6R9_A0A226P6R9_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A096MUR3_A0A096MUR3_PAPAN_9555 and tr_A0A2K6DTP2_A0A2K6DTP2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A151MWC1_A0A151MWC1_ALLMI_8496 and tr_A0A1U7S7M1_A0A1U7S7M1_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_A0A091KDS0_A0A091KDS0_EGRGA_188379 and tr_A0A091GCZ5_A0A091GCZ5_9AVES_55661 are exactly identical!
WARNING: Sequences tr_A0A093H8E4_A0A093H8E4_STRCA_441894 and tr_A0A091W7A6_A0A091W7A6_OPIHO_30419 are exactly identical!
WARNING: Sequences tr_A0A093H8E4_A0A093H8E4_STRCA_441894 and tr_A0A0A0AMR2_A0A0A0AMR2_CHAVO_50402 are exactly identical!
WARNING: Sequences tr_A0A093H8E4_A0A093H8E4_STRCA_441894 and tr_A0A091I3Q2_A0A091I3Q2_CALAN_9244 are exactly identical!
WARNING: Sequences tr_A0A0V0V1B2_A0A0V0V1B2_9BILA_181606 and tr_A0A0V1LKN7_A0A0V1LKN7_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A226MY52_A0A226MY52_CALSU_9009 and tr_A0A226MQD3_A0A226MQD3_COLVI_9014 are exactly identical!
WARNING: Duplicate sequences found: 42

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/Q96A09/3_mltree/Q96A09.raxml.reduced.phy

Alignment comprises 1 partitions and 391 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 392 / 391
Gaps: 6.96 %
Invariant sites: 2.55 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/3_mltree/Q96A09.raxml.rba

Parallelization scheme autoconfig: 3 worker(s) x 2 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 546 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 196 / 15680
[00:00:00] Data distribution: max. searches per worker: 7

Starting ML tree search with 20 distinct starting trees

[00:00:00 -232877.656854] Initial branch length optimization
[00:00:02 -195452.371455] Model parameter optimization (eps = 10.000000)
[00:00:19 -195272.357626] AUTODETECT spr round 1 (radius: 5)
[00:01:16 -126636.079243] AUTODETECT spr round 2 (radius: 10)
[00:02:17 -87540.558425] AUTODETECT spr round 3 (radius: 15)
[00:03:30 -65416.709730] AUTODETECT spr round 4 (radius: 20)
[00:04:54 -64396.733650] AUTODETECT spr round 5 (radius: 25)
[00:06:33 -64354.258496] SPR radius for FAST iterations: 25 (autodetect)
[00:06:33 -64354.258496] Model parameter optimization (eps = 3.000000)
[00:06:48 -64307.823188] FAST spr round 1 (radius: 25)
[00:07:51 -57115.930099] FAST spr round 2 (radius: 25)
[00:08:35 -56654.644721] FAST spr round 3 (radius: 25)
[00:09:20 -56616.302488] FAST spr round 4 (radius: 25)
[00:10:00 -56608.464060] FAST spr round 5 (radius: 25)
[00:10:37 -56608.464022] Model parameter optimization (eps = 1.000000)
[00:10:44 -56607.348176] SLOW spr round 1 (radius: 5)
[00:11:44 -56593.897952] SLOW spr round 2 (radius: 5)
[00:12:44 -56584.067795] SLOW spr round 3 (radius: 5)
[00:13:40 -56583.222275] SLOW spr round 4 (radius: 5)
[00:14:37 -56583.222264] SLOW spr round 5 (radius: 10)
[00:15:32 -56583.222254] SLOW spr round 6 (radius: 15)
[00:17:03 -56583.222243] SLOW spr round 7 (radius: 20)
[00:19:27 -56583.222233] SLOW spr round 8 (radius: 25)
[00:22:22] [worker #1] ML tree search #2, logLikelihood: -56598.954139
[00:22:38 -56583.222222] Model parameter optimization (eps = 0.100000)

[00:22:43] [worker #0] ML tree search #1, logLikelihood: -56583.117600

[00:22:43 -233733.884154] Initial branch length optimization
[00:22:46 -197967.489478] Model parameter optimization (eps = 10.000000)
[00:23:08 -197784.523260] AUTODETECT spr round 1 (radius: 5)
[00:24:06 -125357.198511] AUTODETECT spr round 2 (radius: 10)
[00:25:08 -90285.829383] AUTODETECT spr round 3 (radius: 15)
[00:25:19] [worker #2] ML tree search #3, logLikelihood: -56584.824707
[00:26:26 -72083.506321] AUTODETECT spr round 4 (radius: 20)
[00:27:52 -66322.194562] AUTODETECT spr round 5 (radius: 25)
[00:29:24 -65941.786694] SPR radius for FAST iterations: 25 (autodetect)
[00:29:24 -65941.786694] Model parameter optimization (eps = 3.000000)
[00:29:38 -65907.438400] FAST spr round 1 (radius: 25)
[00:30:47 -56869.478155] FAST spr round 2 (radius: 25)
[00:31:36 -56639.226443] FAST spr round 3 (radius: 25)
[00:32:25 -56609.371741] FAST spr round 4 (radius: 25)
[00:33:04 -56605.851212] FAST spr round 5 (radius: 25)
[00:33:42 -56605.850759] Model parameter optimization (eps = 1.000000)
[00:33:51 -56601.162066] SLOW spr round 1 (radius: 5)
[00:34:53 -56587.927141] SLOW spr round 2 (radius: 5)
[00:35:53 -56584.970708] SLOW spr round 3 (radius: 5)
[00:36:52 -56584.970059] SLOW spr round 4 (radius: 10)
[00:37:48 -56584.970046] SLOW spr round 5 (radius: 15)
[00:39:25 -56584.970046] SLOW spr round 6 (radius: 20)
[00:42:03 -56584.970046] SLOW spr round 7 (radius: 25)
[00:45:24 -56584.970045] Model parameter optimization (eps = 0.100000)

[00:45:30] [worker #0] ML tree search #4, logLikelihood: -56584.842491

[00:45:30 -234461.752929] Initial branch length optimization
[00:45:32 -197987.131914] Model parameter optimization (eps = 10.000000)
[00:45:53 -197797.573757] AUTODETECT spr round 1 (radius: 5)
[00:46:38] [worker #2] ML tree search #6, logLikelihood: -56577.175475
[00:46:52 -122014.972331] AUTODETECT spr round 2 (radius: 10)
[00:47:35] [worker #1] ML tree search #5, logLikelihood: -56587.263396
[00:47:53 -85008.240682] AUTODETECT spr round 3 (radius: 15)
[00:49:12 -70158.409950] AUTODETECT spr round 4 (radius: 20)
[00:50:40 -67013.617230] AUTODETECT spr round 5 (radius: 25)
[00:52:20 -66508.861526] SPR radius for FAST iterations: 25 (autodetect)
[00:52:20 -66508.861526] Model parameter optimization (eps = 3.000000)
[00:52:33 -66477.490468] FAST spr round 1 (radius: 25)
[00:53:39 -57124.806826] FAST spr round 2 (radius: 25)
[00:54:29 -56648.129088] FAST spr round 3 (radius: 25)
[00:55:14 -56632.313914] FAST spr round 4 (radius: 25)
[00:55:54 -56628.022171] FAST spr round 5 (radius: 25)
[00:56:31 -56628.008585] Model parameter optimization (eps = 1.000000)
[00:56:40 -56624.868394] SLOW spr round 1 (radius: 5)
[00:57:42 -56598.182951] SLOW spr round 2 (radius: 5)
[00:58:42 -56591.660093] SLOW spr round 3 (radius: 5)
[00:59:39 -56591.659770] SLOW spr round 4 (radius: 10)
[01:00:35 -56591.659763] SLOW spr round 5 (radius: 15)
[01:02:10 -56591.659760] SLOW spr round 6 (radius: 20)
[01:04:41 -56591.659758] SLOW spr round 7 (radius: 25)
[01:08:00 -56591.659756] Model parameter optimization (eps = 0.100000)

[01:08:04] [worker #0] ML tree search #7, logLikelihood: -56591.653435

[01:08:04 -232876.152888] Initial branch length optimization
[01:08:06 -196590.914361] Model parameter optimization (eps = 10.000000)
[01:08:28 -196404.468713] AUTODETECT spr round 1 (radius: 5)
[01:09:27 -120807.470418] AUTODETECT spr round 2 (radius: 10)
[01:10:28 -83894.958363] AUTODETECT spr round 3 (radius: 15)
[01:10:42] [worker #1] ML tree search #8, logLikelihood: -56579.691761
[01:11:38 -72760.531205] AUTODETECT spr round 4 (radius: 20)
[01:12:51] [worker #2] ML tree search #9, logLikelihood: -56578.092750
[01:13:05 -67197.629828] AUTODETECT spr round 5 (radius: 25)
[01:15:01 -66834.722575] SPR radius for FAST iterations: 25 (autodetect)
[01:15:01 -66834.722575] Model parameter optimization (eps = 3.000000)
[01:15:15 -66800.894849] FAST spr round 1 (radius: 25)
[01:16:16 -58346.109530] FAST spr round 2 (radius: 25)
[01:17:05 -57360.880482] FAST spr round 3 (radius: 25)
[01:17:51 -56623.725729] FAST spr round 4 (radius: 25)
[01:18:33 -56605.572590] FAST spr round 5 (radius: 25)
[01:19:11 -56605.549128] Model parameter optimization (eps = 1.000000)
[01:19:21 -56599.414120] SLOW spr round 1 (radius: 5)
[01:20:25 -56576.947388] SLOW spr round 2 (radius: 5)
[01:21:23 -56576.700207] SLOW spr round 3 (radius: 5)
[01:22:20 -56576.698828] SLOW spr round 4 (radius: 10)
[01:23:16 -56576.610338] SLOW spr round 5 (radius: 15)
[01:24:52 -56575.505548] SLOW spr round 6 (radius: 5)
[01:26:14 -56575.504810] SLOW spr round 7 (radius: 10)
[01:27:25 -56575.504789] SLOW spr round 8 (radius: 15)
[01:28:52 -56575.504787] SLOW spr round 9 (radius: 20)
[01:31:29 -56575.504785] SLOW spr round 10 (radius: 25)
[01:34:29] [worker #1] ML tree search #11, logLikelihood: -56604.008058
[01:34:44 -56575.504784] Model parameter optimization (eps = 0.100000)

[01:34:47] [worker #0] ML tree search #10, logLikelihood: -56575.483212

[01:34:48 -232668.282826] Initial branch length optimization
[01:34:49 -196499.728344] Model parameter optimization (eps = 10.000000)
[01:35:10 -196348.394556] AUTODETECT spr round 1 (radius: 5)
[01:36:03] [worker #2] ML tree search #12, logLikelihood: -56587.375005
[01:36:07 -125229.551288] AUTODETECT spr round 2 (radius: 10)
[01:37:09 -83507.635003] AUTODETECT spr round 3 (radius: 15)
[01:38:18 -67556.155459] AUTODETECT spr round 4 (radius: 20)
[01:39:31 -63434.856039] AUTODETECT spr round 5 (radius: 25)
[01:41:31 -62931.638562] SPR radius for FAST iterations: 25 (autodetect)
[01:41:31 -62931.638562] Model parameter optimization (eps = 3.000000)
[01:41:47 -62894.657489] FAST spr round 1 (radius: 25)
[01:42:42 -56794.562586] FAST spr round 2 (radius: 25)
[01:43:28 -56622.245136] FAST spr round 3 (radius: 25)
[01:44:09 -56617.137832] FAST spr round 4 (radius: 25)
[01:44:48 -56616.286180] FAST spr round 5 (radius: 25)
[01:45:25 -56616.284629] Model parameter optimization (eps = 1.000000)
[01:45:33 -56614.410630] SLOW spr round 1 (radius: 5)
[01:46:33 -56595.668674] SLOW spr round 2 (radius: 5)
[01:47:35 -56589.013486] SLOW spr round 3 (radius: 5)
[01:48:33 -56586.603282] SLOW spr round 4 (radius: 5)
[01:49:29 -56586.603235] SLOW spr round 5 (radius: 10)
[01:50:25 -56586.603223] SLOW spr round 6 (radius: 15)
[01:51:57 -56586.603212] SLOW spr round 7 (radius: 20)
[01:54:27 -56586.603201] SLOW spr round 8 (radius: 25)
[01:57:43 -56586.603191] Model parameter optimization (eps = 0.100000)

[01:57:46] [worker #0] ML tree search #13, logLikelihood: -56586.588497

[01:57:46 -232357.895439] Initial branch length optimization
[01:57:49 -196843.261592] Model parameter optimization (eps = 10.000000)
[01:58:09 -196688.732249] AUTODETECT spr round 1 (radius: 5)
[01:58:12] [worker #1] ML tree search #14, logLikelihood: -56580.163230
[01:58:59] [worker #2] ML tree search #15, logLikelihood: -56586.016213
[01:59:07 -120544.185171] AUTODETECT spr round 2 (radius: 10)
[02:00:10 -85661.620472] AUTODETECT spr round 3 (radius: 15)
[02:01:22 -71131.065432] AUTODETECT spr round 4 (radius: 20)
[02:03:09 -67582.140219] AUTODETECT spr round 5 (radius: 25)
[02:05:27 -66759.188424] SPR radius for FAST iterations: 25 (autodetect)
[02:05:27 -66759.188424] Model parameter optimization (eps = 3.000000)
[02:05:41 -66726.110132] FAST spr round 1 (radius: 25)
[02:06:46 -57046.628433] FAST spr round 2 (radius: 25)
[02:07:40 -56661.546603] FAST spr round 3 (radius: 25)
[02:08:24 -56644.965951] FAST spr round 4 (radius: 25)
[02:09:03 -56636.536964] FAST spr round 5 (radius: 25)
[02:09:41 -56636.533206] Model parameter optimization (eps = 1.000000)
[02:09:53 -56629.706542] SLOW spr round 1 (radius: 5)
[02:10:55 -56608.737101] SLOW spr round 2 (radius: 5)
[02:11:53 -56607.365888] SLOW spr round 3 (radius: 5)
[02:12:51 -56604.920100] SLOW spr round 4 (radius: 5)
[02:13:48 -56604.920001] SLOW spr round 5 (radius: 10)
[02:14:44 -56604.919996] SLOW spr round 6 (radius: 15)
[02:16:16 -56604.919995] SLOW spr round 7 (radius: 20)
[02:18:36 -56604.919995] SLOW spr round 8 (radius: 25)
[02:20:37] [worker #1] ML tree search #17, logLikelihood: -56587.249553
[02:21:53 -56604.919994] Model parameter optimization (eps = 0.100000)

[02:21:58] [worker #0] ML tree search #16, logLikelihood: -56604.889784

[02:21:59 -233950.473190] Initial branch length optimization
[02:22:01 -197604.772555] Model parameter optimization (eps = 10.000000)
[02:22:26 -197426.304076] AUTODETECT spr round 1 (radius: 5)
[02:23:17] [worker #2] ML tree search #18, logLikelihood: -56586.874574
[02:23:26 -123293.850377] AUTODETECT spr round 2 (radius: 10)
[02:24:29 -87977.071764] AUTODETECT spr round 3 (radius: 15)
[02:25:39 -75543.817955] AUTODETECT spr round 4 (radius: 20)
[02:27:15 -68716.461598] AUTODETECT spr round 5 (radius: 25)
[02:28:48 -68544.953315] SPR radius for FAST iterations: 25 (autodetect)
[02:28:48 -68544.953315] Model parameter optimization (eps = 3.000000)
[02:29:04 -68507.735156] FAST spr round 1 (radius: 25)
[02:30:02 -57228.169224] FAST spr round 2 (radius: 25)
[02:30:48 -56727.859651] FAST spr round 3 (radius: 25)
[02:31:35 -56623.032672] FAST spr round 4 (radius: 25)
[02:32:14 -56618.138453] FAST spr round 5 (radius: 25)
[02:32:52 -56618.135763] Model parameter optimization (eps = 1.000000)
[02:33:02 -56611.518367] SLOW spr round 1 (radius: 5)
[02:34:03 -56590.555659] SLOW spr round 2 (radius: 5)
[02:35:02 -56582.740743] SLOW spr round 3 (radius: 5)
[02:35:59 -56582.740409] SLOW spr round 4 (radius: 10)
[02:36:54 -56582.740368] SLOW spr round 5 (radius: 15)
[02:38:26 -56582.740329] SLOW spr round 6 (radius: 20)
[02:40:51 -56582.740292] SLOW spr round 7 (radius: 25)
[02:44:02 -56582.740257] Model parameter optimization (eps = 0.100000)

[02:44:08] [worker #0] ML tree search #19, logLikelihood: -56582.627727

[02:46:54] [worker #1] ML tree search #20, logLikelihood: -56582.232872

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.255596,0.258824) (0.236861,0.423324) (0.337588,1.132131) (0.169955,2.655898) 
   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: -56575.483212

AIC score: 115340.966425 / AICc score: 2515580.966425 / BIC score: 119689.498139
Free parameters (model + branch lengths): 1095

WARNING: Number of free parameters (K=1095) is larger than alignment size (n=392).
         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/Q96A09/3_mltree/Q96A09.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/3_mltree/Q96A09.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/3_mltree/Q96A09.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q96A09/3_mltree/Q96A09.raxml.log

Analysis started: 03-Jul-2021 12:17:56 / finished: 03-Jul-2021 15:04:51

Elapsed time: 10014.933 seconds