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

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

RAxML-NG was called at 05-Jul-2021 21:08:16 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/2_msa/Q9UN74_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74 --seed 2 --threads 8 --tree rand{20} pars{20}

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

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/2_msa/Q9UN74_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 653 sites

WARNING: Sequences tr_A0A0J9YJK6_A0A0J9YJK6_DANRE_7955 and tr_A0A2R8Q015_A0A2R8Q015_DANRE_7955 are exactly identical!
WARNING: Sequences tr_A0A0N4SUG2_A0A0N4SUG2_DANRE_7955 and tr_A0A2R8QMY8_A0A2R8QMY8_DANRE_7955 are exactly identical!
WARNING: Sequences tr_A0A2R8QGH0_A0A2R8QGH0_DANRE_7955 and tr_A0A2R8RQG5_A0A2R8RQG5_DANRE_7955 are exactly identical!
WARNING: Sequences tr_E9PXQ7_E9PXQ7_MOUSE_10090 and tr_A0A1U7QCW6_A0A1U7QCW6_MESAU_10036 are exactly identical!
WARNING: Sequences tr_M3Z0Y2_M3Z0Y2_MUSPF_9669 and tr_A0A2U3X6Y0_A0A2U3X6Y0_LEPWE_9713 are exactly identical!
WARNING: Sequences tr_G3S7B8_G3S7B8_GORGO_9595 and tr_H2PEB5_H2PEB5_PONAB_9601 are exactly identical!
WARNING: Sequences tr_G3S7B8_G3S7B8_GORGO_9595 and tr_H2QQ62_H2QQ62_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G3S7B8_G3S7B8_GORGO_9595 and sp_Q9P2E7_PCD10_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H2QRN1_H2QRN1_PANTR_9598 and sp_Q9Y5I4_PCDC2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_H2QRN1_H2QRN1_PANTR_9598 and tr_A0A2R8ZNN9_A0A2R8ZNN9_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2UGN5_H2UGN5_TAKRU_31033 and tr_H2UGN6_H2UGN6_TAKRU_31033 are exactly identical!
WARNING: Sequences tr_F7GRQ8_F7GRQ8_MACMU_9544 and tr_A0A096N740_A0A096N740_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7GRQ8_F7GRQ8_MACMU_9544 and tr_A0A2K6DA37_A0A2K6DA37_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GRQ8_F7GRQ8_MACMU_9544 and tr_A0A2K5XAY4_A0A2K5XAY4_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A2R8M9N1_A0A2R8M9N1_CALJA_9483 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A2I3N6E1_A0A2I3N6E1_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A0D9S0V7_A0A0D9S0V7_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A2K5P019_A0A2K5P019_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A2K6AT55_A0A2K6AT55_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7HQ33_F7HQ33_MACMU_9544 and tr_A0A2K5XFB2_A0A2K5XFB2_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F1N2W7_F1N2W7_BOVIN_9913 and tr_A0A383ZC11_A0A383ZC11_BALAS_310752 are exactly identical!
WARNING: Sequences tr_A0A1S3RRM6_A0A1S3RRM6_SALSA_8030 and tr_A0A1S3RST3_A0A1S3RST3_SALSA_8030 are exactly identical!
WARNING: Sequences tr_A0A2I4BFF1_A0A2I4BFF1_9TELE_52670 and tr_A0A2I4D630_A0A2I4D630_9TELE_52670 are exactly identical!
WARNING: Sequences tr_A0A2D0RIS0_A0A2D0RIS0_ICTPU_7998 and tr_A0A2D0RIT1_A0A2D0RIT1_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0RIS0_A0A2D0RIS0_ICTPU_7998 and tr_A0A2D0RKH0_A0A2D0RKH0_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0SDP6_A0A2D0SDP6_ICTPU_7998 and tr_A0A2D0SEF2_A0A2D0SEF2_ICTPU_7998 are exactly identical!
WARNING: Duplicate sequences found: 26

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/Q9UN74/3_mltree/Q9UN74.raxml.reduced.phy

Alignment comprises 1 partitions and 652 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 653 / 652
Gaps: 1.65 %
Invariant sites: 2.45 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.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 / 163 / 13040
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1042707.636630] Initial branch length optimization
[00:00:04 -916238.011103] Model parameter optimization (eps = 10.000000)
[00:00:37 -912082.615377] AUTODETECT spr round 1 (radius: 5)
[00:03:04 -672143.685180] AUTODETECT spr round 2 (radius: 10)
[00:05:44 -476685.896527] AUTODETECT spr round 3 (radius: 15)
[00:08:31 -418518.337198] AUTODETECT spr round 4 (radius: 20)
[00:12:00 -390168.000601] AUTODETECT spr round 5 (radius: 25)
[00:17:09 -388132.294703] SPR radius for FAST iterations: 25 (autodetect)
[00:17:09 -388132.294703] Model parameter optimization (eps = 3.000000)
[00:17:29 -387976.485531] FAST spr round 1 (radius: 25)
[00:20:05 -334338.792725] FAST spr round 2 (radius: 25)
[00:22:13 -332613.088642] FAST spr round 3 (radius: 25)
[00:24:03 -332507.302706] FAST spr round 4 (radius: 25)
[00:25:44 -332502.276981] FAST spr round 5 (radius: 25)
[00:27:22 -332502.276932] Model parameter optimization (eps = 1.000000)
[00:27:35 -332500.382098] SLOW spr round 1 (radius: 5)
[00:29:54 -332413.539675] SLOW spr round 2 (radius: 5)
[00:32:08 -332413.325337] SLOW spr round 3 (radius: 5)
[00:34:17 -332413.325337] SLOW spr round 4 (radius: 10)
[00:36:38 -332411.788336] SLOW spr round 5 (radius: 5)
[00:39:34 -332411.788334] SLOW spr round 6 (radius: 10)
[00:41:56 -332411.788334] SLOW spr round 7 (radius: 15)
[00:45:39 -332411.788334] SLOW spr round 8 (radius: 20)
[00:52:33 -332405.654210] SLOW spr round 9 (radius: 5)
[00:55:34 -332405.654206] SLOW spr round 10 (radius: 10)
[00:58:05 -332405.654206] SLOW spr round 11 (radius: 15)
[01:01:44 -332405.654206] SLOW spr round 12 (radius: 20)
[01:08:39 -332405.654206] SLOW spr round 13 (radius: 25)
[01:16:24] [worker #1] ML tree search #2, logLikelihood: -332434.531433
[01:18:24 -332405.654206] Model parameter optimization (eps = 0.100000)

[01:18:34] [worker #0] ML tree search #1, logLikelihood: -332405.246264

[01:18:34 -1038650.447512] Initial branch length optimization
[01:18:38 -915024.696070] Model parameter optimization (eps = 10.000000)
[01:19:15 -911082.264724] AUTODETECT spr round 1 (radius: 5)
[01:21:44 -674726.259691] AUTODETECT spr round 2 (radius: 10)
[01:24:24 -488737.842522] AUTODETECT spr round 3 (radius: 15)
[01:27:26 -408955.774914] AUTODETECT spr round 4 (radius: 20)
[01:31:25 -389588.539843] AUTODETECT spr round 5 (radius: 25)
[01:35:49 -387506.122930] SPR radius for FAST iterations: 25 (autodetect)
[01:35:49 -387506.122930] Model parameter optimization (eps = 3.000000)
[01:35:57 -387501.058478] FAST spr round 1 (radius: 25)
[01:38:52 -335344.050850] FAST spr round 2 (radius: 25)
[01:41:02 -332741.723688] FAST spr round 3 (radius: 25)
[01:43:00 -332640.355978] FAST spr round 4 (radius: 25)
[01:44:40 -332634.654979] FAST spr round 5 (radius: 25)
[01:46:17 -332634.654978] Model parameter optimization (eps = 1.000000)
[01:46:21 -332634.171870] SLOW spr round 1 (radius: 5)
[01:48:45 -332557.910791] SLOW spr round 2 (radius: 5)
[01:50:59 -332545.772974] SLOW spr round 3 (radius: 5)
[01:53:06 -332545.772930] SLOW spr round 4 (radius: 10)
[01:55:20 -332545.772922] SLOW spr round 5 (radius: 15)
[01:59:36 -332545.772922] SLOW spr round 6 (radius: 20)
[02:06:22 -332545.772922] SLOW spr round 7 (radius: 25)
[02:17:14 -332545.772922] Model parameter optimization (eps = 0.100000)

[02:17:18] [worker #0] ML tree search #3, logLikelihood: -332545.766003

[02:17:19 -1037099.477580] Initial branch length optimization
[02:17:23 -913449.679910] Model parameter optimization (eps = 10.000000)
[02:17:54 -909716.595368] AUTODETECT spr round 1 (radius: 5)
[02:20:19 -657884.834942] AUTODETECT spr round 2 (radius: 10)
[02:22:53 -479870.064231] AUTODETECT spr round 3 (radius: 15)
[02:25:54 -419724.417355] AUTODETECT spr round 4 (radius: 20)
[02:29:41 -393292.354111] AUTODETECT spr round 5 (radius: 25)
[02:35:18 -391170.098647] SPR radius for FAST iterations: 25 (autodetect)
[02:35:18 -391170.098647] Model parameter optimization (eps = 3.000000)
[02:35:39 -390992.436647] FAST spr round 1 (radius: 25)
[02:38:46 -335599.709934] FAST spr round 2 (radius: 25)
[02:40:58 -332756.233176] FAST spr round 3 (radius: 25)
[02:42:57 -332537.526776] FAST spr round 4 (radius: 25)
[02:44:39 -332481.548945] FAST spr round 5 (radius: 25)
[02:46:19 -332465.447094] FAST spr round 6 (radius: 25)
[02:47:55 -332465.447091] Model parameter optimization (eps = 1.000000)
[02:48:04 -332464.815159] SLOW spr round 1 (radius: 5)
[02:50:26 -332397.709806] SLOW spr round 2 (radius: 5)
[02:52:38 -332384.241642] SLOW spr round 3 (radius: 5)
[02:54:43 -332384.241637] SLOW spr round 4 (radius: 10)
[02:56:55 -332384.241637] SLOW spr round 5 (radius: 15)
[02:59:36] [worker #1] ML tree search #4, logLikelihood: -332295.432769
[03:01:02 -332384.241637] SLOW spr round 6 (radius: 20)
[03:07:57 -332384.241637] SLOW spr round 7 (radius: 25)
[03:19:16 -332384.241637] Model parameter optimization (eps = 0.100000)

[03:19:28] [worker #0] ML tree search #5, logLikelihood: -332383.966185

[03:19:28 -1031270.061749] Initial branch length optimization
[03:19:33 -908563.236898] Model parameter optimization (eps = 10.000000)
[03:20:04 -904526.843397] AUTODETECT spr round 1 (radius: 5)
[03:22:33 -655754.044808] AUTODETECT spr round 2 (radius: 10)
[03:25:04 -470561.066241] AUTODETECT spr round 3 (radius: 15)
[03:28:06 -404833.214431] AUTODETECT spr round 4 (radius: 20)
[03:32:36 -381088.343343] AUTODETECT spr round 5 (radius: 25)
[03:37:54 -379583.430033] SPR radius for FAST iterations: 25 (autodetect)
[03:37:54 -379583.430033] Model parameter optimization (eps = 3.000000)
[03:38:02 -379578.631309] FAST spr round 1 (radius: 25)
[03:40:55 -334338.306101] FAST spr round 2 (radius: 25)
[03:43:02 -332822.214220] FAST spr round 3 (radius: 25)
[03:44:57 -332694.185740] FAST spr round 4 (radius: 25)
[03:46:44 -332642.600443] FAST spr round 5 (radius: 25)
[03:48:24 -332639.948283] FAST spr round 6 (radius: 25)
[03:50:04 -332639.948273] Model parameter optimization (eps = 1.000000)
[03:50:08 -332639.751065] SLOW spr round 1 (radius: 5)
[03:52:31 -332481.508271] SLOW spr round 2 (radius: 5)
[03:54:47 -332475.909081] SLOW spr round 3 (radius: 5)
[03:57:01 -332469.957796] SLOW spr round 4 (radius: 5)
[03:59:07 -332468.080513] SLOW spr round 5 (radius: 5)
[04:01:20 -332468.080445] SLOW spr round 6 (radius: 10)
[04:03:02] [worker #1] ML tree search #6, logLikelihood: -332304.891828
[04:03:38 -332468.080445] SLOW spr round 7 (radius: 15)
[04:08:00 -332440.458596] SLOW spr round 8 (radius: 5)
[04:10:59 -332433.903963] SLOW spr round 9 (radius: 5)
[04:13:30 -332433.903961] SLOW spr round 10 (radius: 10)
[04:15:45 -332433.903961] SLOW spr round 11 (radius: 15)
[04:19:47 -332433.903961] SLOW spr round 12 (radius: 20)
[04:27:10 -332433.903961] SLOW spr round 13 (radius: 25)
[04:38:49 -332433.903961] Model parameter optimization (eps = 0.100000)

[04:38:53] [worker #0] ML tree search #7, logLikelihood: -332433.857865

[04:38:53 -1038500.658807] Initial branch length optimization
[04:38:57 -914579.216399] Model parameter optimization (eps = 10.000000)
[04:39:30 -910381.931720] AUTODETECT spr round 1 (radius: 5)
[04:42:03 -667144.509304] AUTODETECT spr round 2 (radius: 10)
[04:44:39 -468855.831952] AUTODETECT spr round 3 (radius: 15)
[04:47:34 -391916.169373] AUTODETECT spr round 4 (radius: 20)
[04:51:11 -377634.509546] AUTODETECT spr round 5 (radius: 25)
[04:55:51 -376670.400305] SPR radius for FAST iterations: 25 (autodetect)
[04:55:51 -376670.400305] Model parameter optimization (eps = 3.000000)
[04:56:14 -376512.363474] FAST spr round 1 (radius: 25)
[04:58:58 -333763.043089] FAST spr round 2 (radius: 25)
[05:01:12 -332646.945748] FAST spr round 3 (radius: 25)
[05:03:18 -332572.244850] FAST spr round 4 (radius: 25)
[05:05:06 -332551.744840] FAST spr round 5 (radius: 25)
[05:06:45 -332547.539154] FAST spr round 6 (radius: 25)
[05:08:20 -332547.539118] Model parameter optimization (eps = 1.000000)
[05:08:32 -332542.892517] SLOW spr round 1 (radius: 5)
[05:10:54 -332458.212669] SLOW spr round 2 (radius: 5)
[05:13:10 -332452.714086] SLOW spr round 3 (radius: 5)
[05:15:16 -332452.714032] SLOW spr round 4 (radius: 10)
[05:16:47] [worker #1] ML tree search #8, logLikelihood: -332400.414189
[05:17:34 -332451.677999] SLOW spr round 5 (radius: 5)
[05:20:25 -332451.677768] SLOW spr round 6 (radius: 10)
[05:22:51 -332451.677765] SLOW spr round 7 (radius: 15)
[05:26:51 -332451.677765] SLOW spr round 8 (radius: 20)
[05:34:52 -332451.677765] SLOW spr round 9 (radius: 25)
[05:45:51 -332451.677765] Model parameter optimization (eps = 0.100000)

[05:46:02] [worker #0] ML tree search #9, logLikelihood: -332451.344794

[05:46:02 -1036725.865098] Initial branch length optimization
[05:46:06 -913583.681527] Model parameter optimization (eps = 10.000000)
[05:46:55 -909582.661729] AUTODETECT spr round 1 (radius: 5)
[05:49:31 -683293.764555] AUTODETECT spr round 2 (radius: 10)
[05:52:17 -498677.157194] AUTODETECT spr round 3 (radius: 15)
[05:55:13 -407794.633278] AUTODETECT spr round 4 (radius: 20)
[05:59:00 -385585.663666] AUTODETECT spr round 5 (radius: 25)
[06:03:21 -384551.364928] SPR radius for FAST iterations: 25 (autodetect)
[06:03:21 -384551.364928] Model parameter optimization (eps = 3.000000)
[06:03:50 -384389.398674] FAST spr round 1 (radius: 25)
[06:06:44 -334869.975024] FAST spr round 2 (radius: 25)
[06:08:58 -332517.397046] FAST spr round 3 (radius: 25)
[06:11:01 -332437.505855] FAST spr round 4 (radius: 25)
[06:12:53 -332425.891948] FAST spr round 5 (radius: 25)
[06:14:34 -332417.353415] FAST spr round 6 (radius: 25)
[06:16:14 -332417.353305] Model parameter optimization (eps = 1.000000)
[06:16:29 -332414.400845] SLOW spr round 1 (radius: 5)
[06:18:56 -332350.939473] SLOW spr round 2 (radius: 5)
[06:21:03 -332348.361476] SLOW spr round 3 (radius: 5)
[06:23:08 -332347.842933] SLOW spr round 4 (radius: 5)
[06:25:20 -332332.573286] SLOW spr round 5 (radius: 5)
[06:27:26 -332330.633815] SLOW spr round 6 (radius: 5)
[06:29:29 -332329.761400] SLOW spr round 7 (radius: 5)
[06:30:23] [worker #1] ML tree search #10, logLikelihood: -332302.532453
[06:31:33 -332329.761379] SLOW spr round 8 (radius: 10)
[06:33:46 -332329.761379] SLOW spr round 9 (radius: 15)
[06:38:05 -332329.761379] SLOW spr round 10 (radius: 20)
[06:45:50 -332329.761379] SLOW spr round 11 (radius: 25)
[06:57:15 -332329.761379] Model parameter optimization (eps = 0.100000)

[06:57:22] [worker #0] ML tree search #11, logLikelihood: -332329.590525

[06:57:23 -1040286.090525] Initial branch length optimization
[06:57:27 -915911.780806] Model parameter optimization (eps = 10.000000)
[06:58:04 -911890.412163] AUTODETECT spr round 1 (radius: 5)
[07:00:30 -670718.843998] AUTODETECT spr round 2 (radius: 10)
[07:03:06 -472197.765400] AUTODETECT spr round 3 (radius: 15)
[07:06:03 -404703.453616] AUTODETECT spr round 4 (radius: 20)
[07:09:31 -390920.051640] AUTODETECT spr round 5 (radius: 25)
[07:13:59 -388925.407115] SPR radius for FAST iterations: 25 (autodetect)
[07:13:59 -388925.407115] Model parameter optimization (eps = 3.000000)
[07:14:07 -388917.387438] FAST spr round 1 (radius: 25)
[07:17:05 -334541.838783] FAST spr round 2 (radius: 25)
[07:19:11 -332633.835601] FAST spr round 3 (radius: 25)
[07:21:06 -332563.982059] FAST spr round 4 (radius: 25)
[07:22:50 -332545.840825] FAST spr round 5 (radius: 25)
[07:24:27 -332543.356008] FAST spr round 6 (radius: 25)
[07:26:02 -332543.355986] Model parameter optimization (eps = 1.000000)
[07:26:20 -332422.627143] SLOW spr round 1 (radius: 5)
[07:28:41 -332324.688303] SLOW spr round 2 (radius: 5)
[07:30:51 -332319.826264] SLOW spr round 3 (radius: 5)
[07:33:00 -332317.239317] SLOW spr round 4 (radius: 5)
[07:35:11 -332317.239315] SLOW spr round 5 (radius: 10)
[07:35:30] [worker #1] ML tree search #12, logLikelihood: -332421.610973
[07:37:24 -332317.239315] SLOW spr round 6 (radius: 15)
[07:41:38 -332317.239315] SLOW spr round 7 (radius: 20)
[07:48:57 -332317.239315] SLOW spr round 8 (radius: 25)
[08:00:12 -332317.239315] Model parameter optimization (eps = 0.100000)

[08:00:23] [worker #0] ML tree search #13, logLikelihood: -332316.798258

[08:00:23 -1040056.218142] Initial branch length optimization
[08:00:27 -915724.043994] Model parameter optimization (eps = 10.000000)
[08:01:04 -911690.802233] AUTODETECT spr round 1 (radius: 5)
[08:03:30 -675361.756784] AUTODETECT spr round 2 (radius: 10)
[08:06:11 -472186.769155] AUTODETECT spr round 3 (radius: 15)
[08:09:09 -408000.718215] AUTODETECT spr round 4 (radius: 20)
[08:12:31 -392035.103651] AUTODETECT spr round 5 (radius: 25)
[08:17:57 -382393.490870] SPR radius for FAST iterations: 25 (autodetect)
[08:17:57 -382393.490870] Model parameter optimization (eps = 3.000000)
[08:18:19 -382235.482058] FAST spr round 1 (radius: 25)
[08:21:05 -335044.181979] FAST spr round 2 (radius: 25)
[08:23:12 -332560.721290] FAST spr round 3 (radius: 25)
[08:25:06 -332388.045356] FAST spr round 4 (radius: 25)
[08:26:45 -332368.810912] FAST spr round 5 (radius: 25)
[08:28:20 -332368.810879] Model parameter optimization (eps = 1.000000)
[08:28:35 -332366.743308] SLOW spr round 1 (radius: 5)
[08:30:55 -332313.029265] SLOW spr round 2 (radius: 5)
[08:33:04 -332311.131924] SLOW spr round 3 (radius: 5)
[08:35:09 -332311.131800] SLOW spr round 4 (radius: 10)
[08:37:20 -332311.131797] SLOW spr round 5 (radius: 15)
[08:41:27 -332303.609744] SLOW spr round 6 (radius: 5)
[08:44:23 -332303.120399] SLOW spr round 7 (radius: 5)
[08:46:52 -332303.120391] SLOW spr round 8 (radius: 10)
[08:49:06 -332303.120391] SLOW spr round 9 (radius: 15)
[08:53:02 -332303.120391] SLOW spr round 10 (radius: 20)
[09:00:06 -332303.120391] SLOW spr round 11 (radius: 25)
[09:00:34] [worker #1] ML tree search #14, logLikelihood: -332314.280543
[09:10:43 -332303.120391] Model parameter optimization (eps = 0.100000)

[09:10:48] [worker #0] ML tree search #15, logLikelihood: -332303.072635

[09:10:48 -1041438.979611] Initial branch length optimization
[09:10:52 -917780.706146] Model parameter optimization (eps = 10.000000)
[09:11:29 -913452.344831] AUTODETECT spr round 1 (radius: 5)
[09:13:57 -679827.910440] AUTODETECT spr round 2 (radius: 10)
[09:16:34 -479861.551324] AUTODETECT spr round 3 (radius: 15)
[09:19:30 -420181.740896] AUTODETECT spr round 4 (radius: 20)
[09:23:21 -390002.436640] AUTODETECT spr round 5 (radius: 25)
[09:28:31 -383137.794840] SPR radius for FAST iterations: 25 (autodetect)
[09:28:31 -383137.794840] Model parameter optimization (eps = 3.000000)
[09:28:53 -382975.868938] FAST spr round 1 (radius: 25)
[09:31:43 -334518.625813] FAST spr round 2 (radius: 25)
[09:33:51 -332759.803481] FAST spr round 3 (radius: 25)
[09:35:48 -332512.715638] FAST spr round 4 (radius: 25)
[09:37:31 -332497.306971] FAST spr round 5 (radius: 25)
[09:39:09 -332487.058778] FAST spr round 6 (radius: 25)
[09:40:46 -332486.765468] FAST spr round 7 (radius: 25)
[09:42:21 -332486.764736] Model parameter optimization (eps = 1.000000)
[09:42:32 -332485.209452] SLOW spr round 1 (radius: 5)
[09:44:52 -332361.655828] SLOW spr round 2 (radius: 5)
[09:47:01 -332359.602023] SLOW spr round 3 (radius: 5)
[09:49:07 -332359.601999] SLOW spr round 4 (radius: 10)
[09:51:26 -332357.034177] SLOW spr round 5 (radius: 5)
[09:54:18 -332352.530950] SLOW spr round 6 (radius: 5)
[09:56:42 -332352.530943] SLOW spr round 7 (radius: 10)
[09:58:57 -332352.530943] SLOW spr round 8 (radius: 15)
[10:03:01 -332352.530943] SLOW spr round 9 (radius: 20)
[10:10:18 -332319.458116] SLOW spr round 10 (radius: 5)
[10:11:52] [worker #1] ML tree search #16, logLikelihood: -332403.994427
[10:13:19 -332319.458101] SLOW spr round 11 (radius: 10)
[10:15:53 -332319.458101] SLOW spr round 12 (radius: 15)
[10:19:46 -332319.458101] SLOW spr round 13 (radius: 20)
[10:27:18 -332319.458101] SLOW spr round 14 (radius: 25)
[10:38:09 -332319.458101] Model parameter optimization (eps = 0.100000)

[10:38:19] [worker #0] ML tree search #17, logLikelihood: -332319.249077

[10:38:20 -1041202.338026] Initial branch length optimization
[10:38:23 -916082.671847] Model parameter optimization (eps = 10.000000)
[10:38:59 -911955.029007] AUTODETECT spr round 1 (radius: 5)
[10:41:26 -679365.335876] AUTODETECT spr round 2 (radius: 10)
[10:44:00 -475614.583668] AUTODETECT spr round 3 (radius: 15)
[10:46:50 -399140.272728] AUTODETECT spr round 4 (radius: 20)
[10:49:59 -387830.176706] AUTODETECT spr round 5 (radius: 25)
[10:54:16 -385974.531538] SPR radius for FAST iterations: 25 (autodetect)
[10:54:16 -385974.531538] Model parameter optimization (eps = 3.000000)
[10:54:24 -385966.870350] FAST spr round 1 (radius: 25)
[10:57:13 -334367.557122] FAST spr round 2 (radius: 25)
[10:59:22 -332936.564889] FAST spr round 3 (radius: 25)
[11:01:17 -332741.644391] FAST spr round 4 (radius: 25)
[11:02:57 -332732.377373] FAST spr round 5 (radius: 25)
[11:04:33 -332732.377268] Model parameter optimization (eps = 1.000000)
[11:04:50 -332627.284217] SLOW spr round 1 (radius: 5)
[11:07:14 -332521.955474] SLOW spr round 2 (radius: 5)
[11:09:25 -332514.962082] SLOW spr round 3 (radius: 5)
[11:11:31 -332513.666964] SLOW spr round 4 (radius: 5)
[11:12:07] [worker #1] ML tree search #18, logLikelihood: -332322.254751
[11:13:37 -332513.666926] SLOW spr round 5 (radius: 10)
[11:15:52 -332494.907238] SLOW spr round 6 (radius: 5)
[11:18:48 -332420.131671] SLOW spr round 7 (radius: 5)
[11:21:13 -332420.131669] SLOW spr round 8 (radius: 10)
[11:23:28 -332420.131669] SLOW spr round 9 (radius: 15)
[11:27:29 -332393.286225] SLOW spr round 10 (radius: 5)
[11:30:31 -332301.644176] SLOW spr round 11 (radius: 5)
[11:33:02 -332301.284376] SLOW spr round 12 (radius: 5)
[11:35:18 -332301.284373] SLOW spr round 13 (radius: 10)
[11:37:32 -332301.284373] SLOW spr round 14 (radius: 15)
[11:41:34 -332301.284373] SLOW spr round 15 (radius: 20)
[11:48:57 -332301.284373] SLOW spr round 16 (radius: 25)
[12:00:02 -332301.284373] Model parameter optimization (eps = 0.100000)

[12:00:15] [worker #0] ML tree search #19, logLikelihood: -332300.168874

[12:11:58] [worker #1] ML tree search #20, logLikelihood: -332307.901156

Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.170831,0.515617) (0.286057,0.472361) (0.306642,0.970989) (0.236470,2.025831) 
   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: -332295.432769

AIC score: 668600.865539 / AICc score: 8712660.865539 / BIC score: 677586.427683
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=653).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 39 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9UN74/3_mltree/Q9UN74.raxml.log

Analysis started: 05-Jul-2021 21:08:16 / finished: 06-Jul-2021 09:20:15

Elapsed time: 43918.668 seconds

Consumed energy: 3792.430 Wh (= 19 km in an electric car, or 95 km with an e-scooter!)