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 11-Jul-2021 12:17:19 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/2_msa/Q5SW79_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/3_mltree/Q5SW79 --seed 2 --threads 7 --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 (7 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/2_msa/Q5SW79_trimmed_msa.fasta
[00:00:00] Loaded alignment with 540 taxa and 499 sites

WARNING: Sequences tr_A0A1D5P1X9_A0A1D5P1X9_CHICK_9031 and tr_A0A226MW96_A0A226MW96_CALSU_9009 are exactly identical!
WARNING: Sequences tr_M3YWA4_M3YWA4_MUSPF_9669 and tr_A0A2Y9JT78_A0A2Y9JT78_ENHLU_391180 are exactly identical!
WARNING: Sequences tr_A0A2I3SRG9_A0A2I3SRG9_PANTR_9598 and tr_A0A2R9BQG5_A0A2R9BQG5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6R8Z2_F6R8Z2_MACMU_9544 and tr_A0A096MXV8_A0A096MXV8_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F6Y2B1_F6Y2B1_MACMU_9544 and tr_A0A2K6E8U5_A0A2K6E8U5_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F6Y2B1_F6Y2B1_MACMU_9544 and tr_A0A2K6AJD0_A0A2K6AJD0_MANLE_9568 are exactly identical!
WARNING: Sequences tr_H6BTZ0_H6BTZ0_EXODN_858893 and tr_W9XWI8_W9XWI8_9EURO_1182542 are exactly identical!
WARNING: Sequences tr_G0NJH9_G0NJH9_CAEBE_135651 and tr_G0PCQ3_G0PCQ3_CAEBE_135651 are exactly identical!
WARNING: Sequences tr_I1RS75_I1RS75_GIBZE_229533 and tr_A0A1B8ACN0_A0A1B8ACN0_FUSPO_36050 are exactly identical!
WARNING: Sequences tr_I1RS75_I1RS75_GIBZE_229533 and tr_A0A2T4H0X4_A0A2T4H0X4_FUSCU_5516 are exactly identical!
WARNING: Sequences tr_A0A1S3Z6F4_A0A1S3Z6F4_TOBAC_4097 and tr_A0A1J6IN21_A0A1J6IN21_NICAT_49451 are exactly identical!
WARNING: Sequences tr_A0A1S3Z6F4_A0A1S3Z6F4_TOBAC_4097 and tr_A0A1U7YA21_A0A1U7YA21_NICSY_4096 are exactly identical!
WARNING: Sequences tr_A0A226NGN6_A0A226NGN6_CALSU_9009 and tr_A0A226PLD9_A0A226PLD9_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2G2YIQ3_A0A2G2YIQ3_CAPAN_4072 and tr_A0A2G3BCC1_A0A2G3BCC1_CAPCH_80379 are exactly identical!
WARNING: Sequences tr_A0A2U4A4N6_A0A2U4A4N6_TURTR_9739 and tr_A0A2Y9TJZ0_A0A2Y9TJZ0_PHYCD_9755 are exactly identical!
WARNING: Duplicate sequences found: 15

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/Q5SW79/3_mltree/Q5SW79.raxml.reduced.phy

Alignment comprises 1 partitions and 499 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 499 / 499
Gaps: 31.25 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/3_mltree/Q5SW79.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 7 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 540 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 72 / 5760
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -385052.266346] Initial branch length optimization
[00:00:01 -301127.316105] Model parameter optimization (eps = 10.000000)
[00:00:29 -300082.168205] AUTODETECT spr round 1 (radius: 5)
[00:01:02 -219952.565669] AUTODETECT spr round 2 (radius: 10)
[00:01:40 -177564.358659] AUTODETECT spr round 3 (radius: 15)
[00:02:22 -155240.184293] AUTODETECT spr round 4 (radius: 20)
[00:03:09 -137800.566351] AUTODETECT spr round 5 (radius: 25)
[00:04:01 -134071.399003] SPR radius for FAST iterations: 25 (autodetect)
[00:04:01 -134071.399003] Model parameter optimization (eps = 3.000000)
[00:04:22 -132916.251350] FAST spr round 1 (radius: 25)
[00:05:17 -120005.386409] FAST spr round 2 (radius: 25)
[00:05:57 -119522.685691] FAST spr round 3 (radius: 25)
[00:06:32 -119475.991948] FAST spr round 4 (radius: 25)
[00:07:03 -119465.839826] FAST spr round 5 (radius: 25)
[00:07:34 -119464.355867] FAST spr round 6 (radius: 25)
[00:08:03 -119464.354975] Model parameter optimization (eps = 1.000000)
[00:08:12 -119453.777565] SLOW spr round 1 (radius: 5)
[00:08:56 -119400.848631] SLOW spr round 2 (radius: 5)
[00:09:40 -119396.927388] SLOW spr round 3 (radius: 5)
[00:10:21 -119396.161468] SLOW spr round 4 (radius: 5)
[00:11:02 -119396.160662] SLOW spr round 5 (radius: 10)
[00:11:45 -119391.771798] SLOW spr round 6 (radius: 5)
[00:12:35 -119391.769372] SLOW spr round 7 (radius: 10)
[00:13:24 -119391.768425] SLOW spr round 8 (radius: 15)
[00:14:37 -119391.767592] SLOW spr round 9 (radius: 20)
[00:16:31 -119391.766771] SLOW spr round 10 (radius: 25)
[00:18:41 -119391.765948] Model parameter optimization (eps = 0.100000)

[00:18:44] ML tree search #1, logLikelihood: -119391.726705

[00:18:44 -381936.974220] Initial branch length optimization
[00:18:45 -295627.804190] Model parameter optimization (eps = 10.000000)
[00:19:06 -294487.702782] AUTODETECT spr round 1 (radius: 5)
[00:19:39 -221547.672667] AUTODETECT spr round 2 (radius: 10)
[00:20:17 -171760.721605] AUTODETECT spr round 3 (radius: 15)
[00:21:00 -145905.058719] AUTODETECT spr round 4 (radius: 20)
[00:21:52 -135998.981128] AUTODETECT spr round 5 (radius: 25)
[00:22:54 -134516.612338] SPR radius for FAST iterations: 25 (autodetect)
[00:22:54 -134516.612338] Model parameter optimization (eps = 3.000000)
[00:23:14 -133485.753724] FAST spr round 1 (radius: 25)
[00:24:07 -119825.153445] FAST spr round 2 (radius: 25)
[00:24:50 -119456.098821] FAST spr round 3 (radius: 25)
[00:25:28 -119422.165550] FAST spr round 4 (radius: 25)
[00:26:00 -119412.503146] FAST spr round 5 (radius: 25)
[00:26:30 -119412.491044] Model parameter optimization (eps = 1.000000)
[00:26:42 -119402.614974] SLOW spr round 1 (radius: 5)
[00:27:26 -119375.380990] SLOW spr round 2 (radius: 5)
[00:28:09 -119371.710756] SLOW spr round 3 (radius: 5)
[00:28:50 -119371.698401] SLOW spr round 4 (radius: 10)
[00:29:32 -119371.596895] SLOW spr round 5 (radius: 5)
[00:30:24 -119368.787585] SLOW spr round 6 (radius: 5)
[00:31:10 -119368.786986] SLOW spr round 7 (radius: 10)
[00:31:54 -119368.786986] SLOW spr round 8 (radius: 15)
[00:33:08 -119368.786986] SLOW spr round 9 (radius: 20)
[00:34:56 -119368.786986] SLOW spr round 10 (radius: 25)
[00:37:03 -119368.786986] Model parameter optimization (eps = 0.100000)

[00:37:07] ML tree search #2, logLikelihood: -119368.742545

[00:37:07 -382761.633575] Initial branch length optimization
[00:37:08 -297860.206828] Model parameter optimization (eps = 10.000000)
[00:37:30 -296854.935547] AUTODETECT spr round 1 (radius: 5)
[00:38:02 -218504.670322] AUTODETECT spr round 2 (radius: 10)
[00:38:42 -164625.237492] AUTODETECT spr round 3 (radius: 15)
[00:39:24 -143122.349689] AUTODETECT spr round 4 (radius: 20)
[00:40:16 -134352.765733] AUTODETECT spr round 5 (radius: 25)
[00:41:14 -134133.904459] SPR radius for FAST iterations: 25 (autodetect)
[00:41:14 -134133.904459] Model parameter optimization (eps = 3.000000)
[00:41:33 -133276.305130] FAST spr round 1 (radius: 25)
[00:42:23 -120290.110574] FAST spr round 2 (radius: 25)
[00:43:04 -119535.307481] FAST spr round 3 (radius: 25)
[00:43:41 -119458.358610] FAST spr round 4 (radius: 25)
[00:44:11 -119450.760713] FAST spr round 5 (radius: 25)
[00:44:41 -119450.729389] Model parameter optimization (eps = 1.000000)
[00:44:47 -119446.425246] SLOW spr round 1 (radius: 5)
[00:45:29 -119409.339842] SLOW spr round 2 (radius: 5)
[00:46:12 -119402.095095] SLOW spr round 3 (radius: 5)
[00:46:53 -119397.013898] SLOW spr round 4 (radius: 5)
[00:47:34 -119395.475319] SLOW spr round 5 (radius: 5)
[00:48:14 -119393.886164] SLOW spr round 6 (radius: 5)
[00:48:54 -119393.885268] SLOW spr round 7 (radius: 10)
[00:49:36 -119392.814898] SLOW spr round 8 (radius: 5)
[00:50:26 -119391.037034] SLOW spr round 9 (radius: 5)
[00:51:10 -119391.035401] SLOW spr round 10 (radius: 10)
[00:51:54 -119391.034802] SLOW spr round 11 (radius: 15)
[00:53:07 -119391.034198] SLOW spr round 12 (radius: 20)
[00:55:01 -119391.033589] SLOW spr round 13 (radius: 25)
[00:57:08 -119391.032975] Model parameter optimization (eps = 0.100000)

[00:57:13] ML tree search #3, logLikelihood: -119390.730239

[00:57:13 -380558.400258] Initial branch length optimization
[00:57:14 -296167.584509] Model parameter optimization (eps = 10.000000)
[00:57:34 -295098.937751] AUTODETECT spr round 1 (radius: 5)
[00:58:07 -219722.493466] AUTODETECT spr round 2 (radius: 10)
[00:58:45 -170094.369534] AUTODETECT spr round 3 (radius: 15)
[00:59:27 -149659.733721] AUTODETECT spr round 4 (radius: 20)
[01:00:17 -134235.909788] AUTODETECT spr round 5 (radius: 25)
[01:01:15 -133652.295185] SPR radius for FAST iterations: 25 (autodetect)
[01:01:15 -133652.295185] Model parameter optimization (eps = 3.000000)
[01:01:31 -132947.718128] FAST spr round 1 (radius: 25)
[01:02:23 -119862.346615] FAST spr round 2 (radius: 25)
[01:03:03 -119467.586173] FAST spr round 3 (radius: 25)
[01:03:37 -119451.676680] FAST spr round 4 (radius: 25)
[01:04:08 -119446.169672] FAST spr round 5 (radius: 25)
[01:04:38 -119444.773396] FAST spr round 6 (radius: 25)
[01:05:08 -119438.058993] FAST spr round 7 (radius: 25)
[01:05:38 -119438.058347] Model parameter optimization (eps = 1.000000)
[01:05:43 -119436.213334] SLOW spr round 1 (radius: 5)
[01:06:27 -119410.685363] SLOW spr round 2 (radius: 5)
[01:07:10 -119404.383785] SLOW spr round 3 (radius: 5)
[01:07:54 -119401.569090] SLOW spr round 4 (radius: 5)
[01:08:35 -119401.568100] SLOW spr round 5 (radius: 10)
[01:09:19 -119399.483833] SLOW spr round 6 (radius: 5)
[01:10:11 -119397.059005] SLOW spr round 7 (radius: 5)
[01:10:57 -119397.058660] SLOW spr round 8 (radius: 10)
[01:11:43 -119397.036166] SLOW spr round 9 (radius: 15)
[01:12:54 -119397.035162] SLOW spr round 10 (radius: 20)
[01:14:42 -119397.035146] SLOW spr round 11 (radius: 25)
[01:16:48 -119397.035146] Model parameter optimization (eps = 0.100000)

[01:16:52] ML tree search #4, logLikelihood: -119396.899595

[01:16:52 -380350.732921] Initial branch length optimization
[01:16:54 -296617.400851] Model parameter optimization (eps = 10.000000)
[01:17:17 -295340.777303] AUTODETECT spr round 1 (radius: 5)
[01:17:51 -224439.507873] AUTODETECT spr round 2 (radius: 10)
[01:18:31 -167149.846435] AUTODETECT spr round 3 (radius: 15)
[01:19:17 -140879.633474] AUTODETECT spr round 4 (radius: 20)
[01:20:10 -135032.697003] AUTODETECT spr round 5 (radius: 25)
[01:21:04 -131081.599526] SPR radius for FAST iterations: 25 (autodetect)
[01:21:04 -131081.599526] Model parameter optimization (eps = 3.000000)
[01:21:22 -130066.478983] FAST spr round 1 (radius: 25)
[01:22:17 -119866.630881] FAST spr round 2 (radius: 25)
[01:23:00 -119435.492173] FAST spr round 3 (radius: 25)
[01:23:35 -119410.500611] FAST spr round 4 (radius: 25)
[01:24:08 -119408.768844] FAST spr round 5 (radius: 25)
[01:24:39 -119408.767358] Model parameter optimization (eps = 1.000000)
[01:24:46 -119405.666581] SLOW spr round 1 (radius: 5)
[01:25:31 -119377.544302] SLOW spr round 2 (radius: 5)
[01:26:13 -119377.362771] SLOW spr round 3 (radius: 5)
[01:26:53 -119377.362345] SLOW spr round 4 (radius: 10)
[01:27:37 -119375.463473] SLOW spr round 5 (radius: 5)
[01:28:30 -119375.460049] SLOW spr round 6 (radius: 10)
[01:29:20 -119375.459657] SLOW spr round 7 (radius: 15)
[01:30:33 -119375.459549] SLOW spr round 8 (radius: 20)
[01:32:26 -119375.459492] SLOW spr round 9 (radius: 25)
[01:34:38 -119375.459447] Model parameter optimization (eps = 0.100000)

[01:34:42] ML tree search #5, logLikelihood: -119375.390980

[01:34:42 -385767.814030] Initial branch length optimization
[01:34:43 -303008.149442] Model parameter optimization (eps = 10.000000)
[01:35:06 -301854.812275] AUTODETECT spr round 1 (radius: 5)
[01:35:41 -219526.917920] AUTODETECT spr round 2 (radius: 10)
[01:36:20 -165462.713974] AUTODETECT spr round 3 (radius: 15)
[01:37:04 -141173.792811] AUTODETECT spr round 4 (radius: 20)
[01:38:00 -132917.009080] AUTODETECT spr round 5 (radius: 25)
[01:39:00 -132115.923930] SPR radius for FAST iterations: 25 (autodetect)
[01:39:00 -132115.923930] Model parameter optimization (eps = 3.000000)
[01:39:19 -131160.977765] FAST spr round 1 (radius: 25)
[01:40:12 -119919.753468] FAST spr round 2 (radius: 25)
[01:40:55 -119497.690379] FAST spr round 3 (radius: 25)
[01:41:33 -119461.605148] FAST spr round 4 (radius: 25)
[01:42:06 -119442.937310] FAST spr round 5 (radius: 25)
[01:42:36 -119442.909027] Model parameter optimization (eps = 1.000000)
[01:42:45 -119440.014001] SLOW spr round 1 (radius: 5)
[01:43:33 -119396.203192] SLOW spr round 2 (radius: 5)
[01:44:17 -119390.781218] SLOW spr round 3 (radius: 5)
[01:45:00 -119385.448456] SLOW spr round 4 (radius: 5)
[01:45:43 -119380.339090] SLOW spr round 5 (radius: 5)
[01:46:25 -119380.338675] SLOW spr round 6 (radius: 10)
[01:47:09 -119377.878688] SLOW spr round 7 (radius: 5)
[01:48:01 -119377.830946] SLOW spr round 8 (radius: 10)
[01:48:50 -119377.828831] SLOW spr round 9 (radius: 15)
[01:50:01 -119376.912069] SLOW spr round 10 (radius: 5)
[01:50:56 -119375.126648] SLOW spr round 11 (radius: 5)
[01:51:43 -119375.125580] SLOW spr round 12 (radius: 10)
[01:52:29 -119375.125538] SLOW spr round 13 (radius: 15)
[01:53:40 -119375.125497] SLOW spr round 14 (radius: 20)
[01:55:26 -119375.125456] SLOW spr round 15 (radius: 25)
[01:57:30 -119375.125414] Model parameter optimization (eps = 0.100000)

[01:57:35] ML tree search #6, logLikelihood: -119374.986815

[01:57:35 -384062.152943] Initial branch length optimization
[01:57:36 -297616.703391] Model parameter optimization (eps = 10.000000)
[01:57:59 -296471.134656] AUTODETECT spr round 1 (radius: 5)
[01:58:32 -219115.377007] AUTODETECT spr round 2 (radius: 10)
[01:59:09 -173239.496743] AUTODETECT spr round 3 (radius: 15)
[01:59:52 -143658.555781] AUTODETECT spr round 4 (radius: 20)
[02:00:49 -133443.748148] AUTODETECT spr round 5 (radius: 25)
[02:01:54 -132145.233871] SPR radius for FAST iterations: 25 (autodetect)
[02:01:54 -132145.233871] Model parameter optimization (eps = 3.000000)
[02:02:10 -131103.688615] FAST spr round 1 (radius: 25)
[02:03:03 -119913.225619] FAST spr round 2 (radius: 25)
[02:03:43 -119506.946692] FAST spr round 3 (radius: 25)
[02:04:19 -119473.578440] FAST spr round 4 (radius: 25)
[02:04:53 -119454.769880] FAST spr round 5 (radius: 25)
[02:05:24 -119450.965156] FAST spr round 6 (radius: 25)
[02:05:53 -119450.412713] FAST spr round 7 (radius: 25)
[02:06:22 -119450.411917] Model parameter optimization (eps = 1.000000)
[02:06:29 -119443.225237] SLOW spr round 1 (radius: 5)
[02:07:12 -119400.387654] SLOW spr round 2 (radius: 5)
[02:07:53 -119399.203255] SLOW spr round 3 (radius: 5)
[02:08:33 -119399.202325] SLOW spr round 4 (radius: 10)
[02:09:14 -119398.892444] SLOW spr round 5 (radius: 5)
[02:10:06 -119396.832297] SLOW spr round 6 (radius: 5)
[02:10:50 -119396.831076] SLOW spr round 7 (radius: 10)
[02:11:34 -119396.830235] SLOW spr round 8 (radius: 15)
[02:12:50 -119396.829561] SLOW spr round 9 (radius: 20)
[02:14:39 -119396.828882] SLOW spr round 10 (radius: 25)
[02:16:47 -119396.828197] Model parameter optimization (eps = 0.100000)

[02:16:49] ML tree search #7, logLikelihood: -119396.806812

[02:16:49 -381098.959254] Initial branch length optimization
[02:16:51 -299378.951190] Model parameter optimization (eps = 10.000000)
[02:17:07 -298270.276112] AUTODETECT spr round 1 (radius: 5)
[02:17:39 -216050.923748] AUTODETECT spr round 2 (radius: 10)
[02:18:14 -171950.811728] AUTODETECT spr round 3 (radius: 15)
[02:18:55 -151748.931834] AUTODETECT spr round 4 (radius: 20)
[02:19:41 -137500.069194] AUTODETECT spr round 5 (radius: 25)
[02:20:32 -134963.993752] SPR radius for FAST iterations: 25 (autodetect)
[02:20:32 -134963.993752] Model parameter optimization (eps = 3.000000)
[02:20:52 -133909.124402] FAST spr round 1 (radius: 25)
[02:21:42 -120259.698101] FAST spr round 2 (radius: 25)
[02:22:25 -119499.609695] FAST spr round 3 (radius: 25)
[02:23:03 -119445.533707] FAST spr round 4 (radius: 25)
[02:23:35 -119436.613252] FAST spr round 5 (radius: 25)
[02:24:05 -119436.609852] Model parameter optimization (eps = 1.000000)
[02:24:12 -119432.978539] SLOW spr round 1 (radius: 5)
[02:24:57 -119407.443056] SLOW spr round 2 (radius: 5)
[02:25:40 -119403.688551] SLOW spr round 3 (radius: 5)
[02:26:21 -119401.875660] SLOW spr round 4 (radius: 5)
[02:27:02 -119401.874858] SLOW spr round 5 (radius: 10)
[02:27:44 -119401.874112] SLOW spr round 6 (radius: 15)
[02:29:02 -119401.873362] SLOW spr round 7 (radius: 20)
[02:30:53 -119401.872605] SLOW spr round 8 (radius: 25)
[02:33:02 -119401.871842] Model parameter optimization (eps = 0.100000)

[02:33:05] ML tree search #8, logLikelihood: -119401.780563

[02:33:05 -384127.943017] Initial branch length optimization
[02:33:07 -298732.250426] Model parameter optimization (eps = 10.000000)
[02:33:29 -297718.763648] AUTODETECT spr round 1 (radius: 5)
[02:34:02 -216603.599439] AUTODETECT spr round 2 (radius: 10)
[02:34:40 -169131.492640] AUTODETECT spr round 3 (radius: 15)
[02:35:24 -143340.875810] AUTODETECT spr round 4 (radius: 20)
[02:36:19 -135770.661494] AUTODETECT spr round 5 (radius: 25)
[02:37:28 -134362.752471] SPR radius for FAST iterations: 25 (autodetect)
[02:37:28 -134362.752471] Model parameter optimization (eps = 3.000000)
[02:37:50 -133433.358822] FAST spr round 1 (radius: 25)
[02:38:46 -119842.310287] FAST spr round 2 (radius: 25)
[02:39:26 -119499.315686] FAST spr round 3 (radius: 25)
[02:40:03 -119448.319413] FAST spr round 4 (radius: 25)
[02:40:37 -119437.873972] FAST spr round 5 (radius: 25)
[02:41:09 -119431.823324] FAST spr round 6 (radius: 25)
[02:41:39 -119431.822184] Model parameter optimization (eps = 1.000000)
[02:41:46 -119428.989120] SLOW spr round 1 (radius: 5)
[02:42:31 -119402.808185] SLOW spr round 2 (radius: 5)
[02:43:15 -119394.278256] SLOW spr round 3 (radius: 5)
[02:43:58 -119393.783294] SLOW spr round 4 (radius: 5)
[02:44:39 -119393.782735] SLOW spr round 5 (radius: 10)
[02:45:22 -119393.782280] SLOW spr round 6 (radius: 15)
[02:46:39 -119393.781838] SLOW spr round 7 (radius: 20)
[02:48:32 -119393.781405] SLOW spr round 8 (radius: 25)
[02:50:41 -119393.780977] Model parameter optimization (eps = 0.100000)

[02:50:50] ML tree search #9, logLikelihood: -119393.402166

[02:50:50 -386947.011829] Initial branch length optimization
[02:50:51 -301223.569027] Model parameter optimization (eps = 10.000000)
[02:51:16 -300077.321885] AUTODETECT spr round 1 (radius: 5)
[02:51:49 -224233.007906] AUTODETECT spr round 2 (radius: 10)
[02:52:27 -180324.537664] AUTODETECT spr round 3 (radius: 15)
[02:53:10 -154041.429578] AUTODETECT spr round 4 (radius: 20)
[02:53:58 -146790.993265] AUTODETECT spr round 5 (radius: 25)
[02:54:49 -143540.721486] SPR radius for FAST iterations: 25 (autodetect)
[02:54:49 -143540.721486] Model parameter optimization (eps = 3.000000)
[02:55:11 -142139.542440] FAST spr round 1 (radius: 25)
[02:56:06 -121054.930977] FAST spr round 2 (radius: 25)
[02:56:51 -119528.254562] FAST spr round 3 (radius: 25)
[02:57:30 -119445.672686] FAST spr round 4 (radius: 25)
[02:58:03 -119428.114687] FAST spr round 5 (radius: 25)
[02:58:34 -119426.877484] FAST spr round 6 (radius: 25)
[02:59:05 -119426.017761] FAST spr round 7 (radius: 25)
[02:59:35 -119426.006271] Model parameter optimization (eps = 1.000000)
[02:59:45 -119416.913512] SLOW spr round 1 (radius: 5)
[03:00:29 -119384.329287] SLOW spr round 2 (radius: 5)
[03:01:13 -119379.700877] SLOW spr round 3 (radius: 5)
[03:01:55 -119378.820483] SLOW spr round 4 (radius: 5)
[03:02:35 -119378.819153] SLOW spr round 5 (radius: 10)
[03:03:19 -119375.506105] SLOW spr round 6 (radius: 5)
[03:04:13 -119372.813422] SLOW spr round 7 (radius: 5)
[03:05:00 -119370.696796] SLOW spr round 8 (radius: 5)
[03:05:42 -119370.692457] SLOW spr round 9 (radius: 10)
[03:06:26 -119370.692120] SLOW spr round 10 (radius: 15)
[03:07:40 -119370.692039] SLOW spr round 11 (radius: 20)
[03:09:21 -119370.691971] SLOW spr round 12 (radius: 25)
[03:11:22 -119370.691903] Model parameter optimization (eps = 0.100000)

[03:11:30] ML tree search #10, logLikelihood: -119368.768737

[03:11:30 -377618.870462] Initial branch length optimization
[03:11:31 -294809.924796] Model parameter optimization (eps = 10.000000)
[03:11:56 -293627.935172] AUTODETECT spr round 1 (radius: 5)
[03:12:29 -216860.482267] AUTODETECT spr round 2 (radius: 10)
[03:13:08 -172122.614185] AUTODETECT spr round 3 (radius: 15)
[03:13:53 -138240.002551] AUTODETECT spr round 4 (radius: 20)
[03:14:50 -132203.992223] AUTODETECT spr round 5 (radius: 25)
[03:15:53 -132153.355234] SPR radius for FAST iterations: 25 (autodetect)
[03:15:53 -132153.355234] Model parameter optimization (eps = 3.000000)
[03:16:10 -131277.333807] FAST spr round 1 (radius: 25)
[03:17:03 -120174.657838] FAST spr round 2 (radius: 25)
[03:17:46 -119494.214984] FAST spr round 3 (radius: 25)
[03:18:23 -119427.514946] FAST spr round 4 (radius: 25)
[03:18:54 -119424.036103] FAST spr round 5 (radius: 25)
[03:19:24 -119423.399781] FAST spr round 6 (radius: 25)
[03:19:54 -119423.399694] Model parameter optimization (eps = 1.000000)
[03:20:02 -119414.411723] SLOW spr round 1 (radius: 5)
[03:20:46 -119379.011392] SLOW spr round 2 (radius: 5)
[03:21:29 -119376.484553] SLOW spr round 3 (radius: 5)
[03:22:09 -119376.484242] SLOW spr round 4 (radius: 10)
[03:22:52 -119374.134017] SLOW spr round 5 (radius: 5)
[03:23:43 -119374.130856] SLOW spr round 6 (radius: 10)
[03:24:33 -119374.130651] SLOW spr round 7 (radius: 15)
[03:25:44 -119374.130592] SLOW spr round 8 (radius: 20)
[03:27:36 -119374.130546] SLOW spr round 9 (radius: 25)
[03:29:42 -119374.130502] Model parameter optimization (eps = 0.100000)

[03:29:47] ML tree search #11, logLikelihood: -119374.070017

[03:29:47 -382376.912850] Initial branch length optimization
[03:29:48 -297967.698956] Model parameter optimization (eps = 10.000000)
[03:30:03 -296771.229095] AUTODETECT spr round 1 (radius: 5)
[03:30:36 -218951.140252] AUTODETECT spr round 2 (radius: 10)
[03:31:15 -165743.716555] AUTODETECT spr round 3 (radius: 15)
[03:32:00 -142063.632497] AUTODETECT spr round 4 (radius: 20)
[03:32:46 -132616.045776] AUTODETECT spr round 5 (radius: 25)
[03:33:49 -131793.150252] SPR radius for FAST iterations: 25 (autodetect)
[03:33:49 -131793.150252] Model parameter optimization (eps = 3.000000)
[03:34:05 -130842.580511] FAST spr round 1 (radius: 25)
[03:34:56 -119902.758356] FAST spr round 2 (radius: 25)
[03:35:37 -119446.129927] FAST spr round 3 (radius: 25)
[03:36:13 -119414.362021] FAST spr round 4 (radius: 25)
[03:36:44 -119411.506918] FAST spr round 5 (radius: 25)
[03:37:13 -119411.506219] Model parameter optimization (eps = 1.000000)
[03:37:21 -119400.467289] SLOW spr round 1 (radius: 5)
[03:38:06 -119372.460327] SLOW spr round 2 (radius: 5)
[03:38:47 -119372.341719] SLOW spr round 3 (radius: 5)
[03:39:26 -119372.340479] SLOW spr round 4 (radius: 10)
[03:40:08 -119369.473567] SLOW spr round 5 (radius: 5)
[03:40:58 -119369.472848] SLOW spr round 6 (radius: 10)
[03:41:46 -119369.472708] SLOW spr round 7 (radius: 15)
[03:42:54 -119369.472619] SLOW spr round 8 (radius: 20)
[03:44:34 -119369.472550] SLOW spr round 9 (radius: 25)
[03:46:29 -119369.472495] Model parameter optimization (eps = 0.100000)

[03:46:32] ML tree search #12, logLikelihood: -119369.449893

[03:46:32 -384222.335652] Initial branch length optimization
[03:46:33 -298596.754307] Model parameter optimization (eps = 10.000000)
[03:46:48 -297477.044181] AUTODETECT spr round 1 (radius: 5)
[03:47:20 -213786.123275] AUTODETECT spr round 2 (radius: 10)
[03:47:56 -174635.911721] AUTODETECT spr round 3 (radius: 15)
[03:48:36 -150833.573241] AUTODETECT spr round 4 (radius: 20)
[03:49:24 -136052.161797] AUTODETECT spr round 5 (radius: 25)
[03:50:10 -135637.938475] SPR radius for FAST iterations: 25 (autodetect)
[03:50:10 -135637.938475] Model parameter optimization (eps = 3.000000)
[03:50:31 -134570.806287] FAST spr round 1 (radius: 25)
[03:51:21 -120006.673183] FAST spr round 2 (radius: 25)
[03:51:59 -119470.455496] FAST spr round 3 (radius: 25)
[03:52:34 -119430.974301] FAST spr round 4 (radius: 25)
[03:53:05 -119421.744145] FAST spr round 5 (radius: 25)
[03:53:33 -119420.845738] FAST spr round 6 (radius: 25)
[03:54:01 -119420.844398] Model parameter optimization (eps = 1.000000)
[03:54:08 -119407.707040] SLOW spr round 1 (radius: 5)
[03:54:51 -119387.987666] SLOW spr round 2 (radius: 5)
[03:55:32 -119383.325168] SLOW spr round 3 (radius: 5)
[03:56:12 -119383.324624] SLOW spr round 4 (radius: 10)
[03:56:52 -119383.324479] SLOW spr round 5 (radius: 15)
[03:58:04 -119383.324376] SLOW spr round 6 (radius: 20)
[03:59:45 -119383.324293] SLOW spr round 7 (radius: 25)
[04:01:48 -119383.324222] Model parameter optimization (eps = 0.100000)

[04:01:52] ML tree search #13, logLikelihood: -119383.210348

[04:01:52 -380139.415617] Initial branch length optimization
[04:01:53 -295121.107567] Model parameter optimization (eps = 10.000000)
[04:02:15 -293980.776661] AUTODETECT spr round 1 (radius: 5)
[04:02:48 -226245.581956] AUTODETECT spr round 2 (radius: 10)
[04:03:27 -170238.588968] AUTODETECT spr round 3 (radius: 15)
[04:04:09 -145273.273850] AUTODETECT spr round 4 (radius: 20)
[04:05:00 -134607.699810] AUTODETECT spr round 5 (radius: 25)
[04:05:55 -133612.270960] SPR radius for FAST iterations: 25 (autodetect)
[04:05:55 -133612.270960] Model parameter optimization (eps = 3.000000)
[04:06:16 -132862.897746] FAST spr round 1 (radius: 25)
[04:07:12 -119997.076098] FAST spr round 2 (radius: 25)
[04:07:56 -119486.022241] FAST spr round 3 (radius: 25)
[04:08:32 -119446.302739] FAST spr round 4 (radius: 25)
[04:09:05 -119443.032186] FAST spr round 5 (radius: 25)
[04:09:35 -119443.026645] Model parameter optimization (eps = 1.000000)
[04:09:43 -119434.244600] SLOW spr round 1 (radius: 5)
[04:10:27 -119406.693275] SLOW spr round 2 (radius: 5)
[04:11:10 -119403.969351] SLOW spr round 3 (radius: 5)
[04:11:51 -119403.969228] SLOW spr round 4 (radius: 10)
[04:12:36 -119402.978036] SLOW spr round 5 (radius: 5)
[04:13:27 -119402.973180] SLOW spr round 6 (radius: 10)
[04:14:17 -119402.973152] SLOW spr round 7 (radius: 15)
[04:15:29 -119402.973130] SLOW spr round 8 (radius: 20)
[04:17:20 -119402.973107] SLOW spr round 9 (radius: 25)
[04:19:26 -119402.973085] Model parameter optimization (eps = 0.100000)

[04:19:29] ML tree search #14, logLikelihood: -119402.961135

[04:19:29 -382232.905893] Initial branch length optimization
[04:19:31 -298189.241492] Model parameter optimization (eps = 10.000000)
[04:19:52 -297007.735431] AUTODETECT spr round 1 (radius: 5)
[04:20:26 -216917.817521] AUTODETECT spr round 2 (radius: 10)
[04:21:05 -170459.093242] AUTODETECT spr round 3 (radius: 15)
[04:21:50 -142780.701434] AUTODETECT spr round 4 (radius: 20)
[04:22:36 -139450.848994] AUTODETECT spr round 5 (radius: 25)
[04:23:33 -135235.760686] SPR radius for FAST iterations: 25 (autodetect)
[04:23:33 -135235.760686] Model parameter optimization (eps = 3.000000)
[04:23:52 -134159.227408] FAST spr round 1 (radius: 25)
[04:24:42 -120022.102945] FAST spr round 2 (radius: 25)
[04:25:22 -119499.328979] FAST spr round 3 (radius: 25)
[04:25:57 -119447.605408] FAST spr round 4 (radius: 25)
[04:26:27 -119439.680072] FAST spr round 5 (radius: 25)
[04:26:57 -119439.679503] Model parameter optimization (eps = 1.000000)
[04:27:06 -119433.194011] SLOW spr round 1 (radius: 5)
[04:27:51 -119406.290761] SLOW spr round 2 (radius: 5)
[04:28:34 -119398.612400] SLOW spr round 3 (radius: 5)
[04:29:15 -119398.202826] SLOW spr round 4 (radius: 5)
[04:29:55 -119398.202785] SLOW spr round 5 (radius: 10)
[04:30:39 -119396.884700] SLOW spr round 6 (radius: 5)
[04:31:32 -119396.879864] SLOW spr round 7 (radius: 10)
[04:32:22 -119396.879838] SLOW spr round 8 (radius: 15)
[04:33:36 -119396.879816] SLOW spr round 9 (radius: 20)
[04:35:27 -119396.879793] SLOW spr round 10 (radius: 25)
[04:37:33 -119396.879771] Model parameter optimization (eps = 0.100000)

[04:37:38] ML tree search #15, logLikelihood: -119396.760614

[04:37:38 -382164.702557] Initial branch length optimization
[04:37:39 -297902.839159] Model parameter optimization (eps = 10.000000)
[04:37:59 -296885.889386] AUTODETECT spr round 1 (radius: 5)
[04:38:33 -220539.602969] AUTODETECT spr round 2 (radius: 10)
[04:39:11 -166463.596576] AUTODETECT spr round 3 (radius: 15)
[04:39:56 -136223.191595] AUTODETECT spr round 4 (radius: 20)
[04:40:44 -131972.214795] AUTODETECT spr round 5 (radius: 25)
[04:41:50 -131468.953700] SPR radius for FAST iterations: 25 (autodetect)
[04:41:50 -131468.953700] Model parameter optimization (eps = 3.000000)
[04:42:08 -130647.358319] FAST spr round 1 (radius: 25)
[04:42:57 -119732.196855] FAST spr round 2 (radius: 25)
[04:43:36 -119447.309098] FAST spr round 3 (radius: 25)
[04:44:09 -119428.978898] FAST spr round 4 (radius: 25)
[04:44:41 -119428.389252] FAST spr round 5 (radius: 25)
[04:45:11 -119428.388929] Model parameter optimization (eps = 1.000000)
[04:45:19 -119420.836493] SLOW spr round 1 (radius: 5)
[04:46:03 -119396.633063] SLOW spr round 2 (radius: 5)
[04:46:44 -119396.481759] SLOW spr round 3 (radius: 5)
[04:47:25 -119396.481568] SLOW spr round 4 (radius: 10)
[04:48:08 -119390.413157] SLOW spr round 5 (radius: 5)
[04:49:02 -119385.141471] SLOW spr round 6 (radius: 5)
[04:49:49 -119382.956641] SLOW spr round 7 (radius: 5)
[04:50:31 -119382.956347] SLOW spr round 8 (radius: 10)
[04:51:15 -119382.956266] SLOW spr round 9 (radius: 15)
[04:52:28 -119382.956236] SLOW spr round 10 (radius: 20)
[04:54:14 -119382.956224] SLOW spr round 11 (radius: 25)
[04:56:19 -119382.956220] Model parameter optimization (eps = 0.100000)

[04:56:22] ML tree search #16, logLikelihood: -119382.944270

[04:56:22 -387364.178799] Initial branch length optimization
[04:56:24 -300053.185217] Model parameter optimization (eps = 10.000000)
[04:56:47 -298963.884590] AUTODETECT spr round 1 (radius: 5)
[04:57:21 -219480.869736] AUTODETECT spr round 2 (radius: 10)
[04:57:59 -182655.168980] AUTODETECT spr round 3 (radius: 15)
[04:58:41 -149193.224158] AUTODETECT spr round 4 (radius: 20)
[04:59:29 -135510.438908] AUTODETECT spr round 5 (radius: 25)
[05:00:23 -134376.754095] SPR radius for FAST iterations: 25 (autodetect)
[05:00:23 -134376.754095] Model parameter optimization (eps = 3.000000)
[05:00:41 -133284.522146] FAST spr round 1 (radius: 25)
[05:01:29 -120095.474841] FAST spr round 2 (radius: 25)
[05:02:08 -119478.788230] FAST spr round 3 (radius: 25)
[05:02:46 -119432.343387] FAST spr round 4 (radius: 25)
[05:03:17 -119424.871746] FAST spr round 5 (radius: 25)
[05:03:47 -119424.859931] Model parameter optimization (eps = 1.000000)
[05:03:54 -119417.716565] SLOW spr round 1 (radius: 5)
[05:04:36 -119396.238892] SLOW spr round 2 (radius: 5)
[05:05:18 -119389.805928] SLOW spr round 3 (radius: 5)
[05:05:59 -119388.955251] SLOW spr round 4 (radius: 5)
[05:06:39 -119388.954872] SLOW spr round 5 (radius: 10)
[05:07:21 -119385.426983] SLOW spr round 6 (radius: 5)
[05:08:12 -119384.486848] SLOW spr round 7 (radius: 5)
[05:08:57 -119382.701738] SLOW spr round 8 (radius: 5)
[05:09:38 -119382.701715] SLOW spr round 9 (radius: 10)
[05:10:21 -119382.701693] SLOW spr round 10 (radius: 15)
[05:11:37 -119382.701670] SLOW spr round 11 (radius: 20)
[05:13:26 -119382.701648] SLOW spr round 12 (radius: 25)
[05:15:31 -119382.701625] Model parameter optimization (eps = 0.100000)

[05:15:35] ML tree search #17, logLikelihood: -119382.583186

[05:15:35 -379672.896629] Initial branch length optimization
[05:15:37 -297627.592335] Model parameter optimization (eps = 10.000000)
[05:15:58 -296454.679881] AUTODETECT spr round 1 (radius: 5)
[05:16:30 -217145.900050] AUTODETECT spr round 2 (radius: 10)
[05:17:07 -163295.082114] AUTODETECT spr round 3 (radius: 15)
[05:17:50 -139409.482938] AUTODETECT spr round 4 (radius: 20)
[05:18:38 -132948.040937] AUTODETECT spr round 5 (radius: 25)
[05:19:25 -131426.225606] SPR radius for FAST iterations: 25 (autodetect)
[05:19:25 -131426.225606] Model parameter optimization (eps = 3.000000)
[05:19:45 -130413.760213] FAST spr round 1 (radius: 25)
[05:20:30 -119882.995082] FAST spr round 2 (radius: 25)
[05:21:08 -119510.051508] FAST spr round 3 (radius: 25)
[05:21:43 -119484.519275] FAST spr round 4 (radius: 25)
[05:22:16 -119472.874326] FAST spr round 5 (radius: 25)
[05:22:46 -119465.035647] FAST spr round 6 (radius: 25)
[05:23:14 -119464.223914] FAST spr round 7 (radius: 25)
[05:23:42 -119464.223536] Model parameter optimization (eps = 1.000000)
[05:23:49 -119458.367520] SLOW spr round 1 (radius: 5)
[05:24:31 -119396.769706] SLOW spr round 2 (radius: 5)
[05:25:13 -119395.309938] SLOW spr round 3 (radius: 5)
[05:25:52 -119395.309183] SLOW spr round 4 (radius: 10)
[05:26:33 -119393.602432] SLOW spr round 5 (radius: 5)
[05:27:24 -119389.673534] SLOW spr round 6 (radius: 5)
[05:28:07 -119389.666832] SLOW spr round 7 (radius: 10)
[05:28:49 -119389.665353] SLOW spr round 8 (radius: 15)
[05:29:59 -119389.665042] SLOW spr round 9 (radius: 20)
[05:31:45 -119389.664976] SLOW spr round 10 (radius: 25)
[05:33:50 -119389.664963] Model parameter optimization (eps = 0.100000)

[05:33:53] ML tree search #18, logLikelihood: -119389.608990

[05:33:53 -383727.392422] Initial branch length optimization
[05:33:55 -299367.001401] Model parameter optimization (eps = 10.000000)
[05:34:12 -298296.357093] AUTODETECT spr round 1 (radius: 5)
[05:34:44 -226404.147527] AUTODETECT spr round 2 (radius: 10)
[05:35:20 -174982.318392] AUTODETECT spr round 3 (radius: 15)
[05:36:00 -149891.298490] AUTODETECT spr round 4 (radius: 20)
[05:36:50 -144908.703083] AUTODETECT spr round 5 (radius: 25)
[05:37:45 -136171.454998] SPR radius for FAST iterations: 25 (autodetect)
[05:37:45 -136171.454998] Model parameter optimization (eps = 3.000000)
[05:38:04 -135240.385314] FAST spr round 1 (radius: 25)
[05:38:58 -120314.236623] FAST spr round 2 (radius: 25)
[05:39:40 -119490.991754] FAST spr round 3 (radius: 25)
[05:40:14 -119447.098567] FAST spr round 4 (radius: 25)
[05:40:46 -119435.874797] FAST spr round 5 (radius: 25)
[05:41:14 -119435.862792] Model parameter optimization (eps = 1.000000)
[05:41:21 -119430.514855] SLOW spr round 1 (radius: 5)
[05:42:04 -119391.782415] SLOW spr round 2 (radius: 5)
[05:42:45 -119384.910404] SLOW spr round 3 (radius: 5)
[05:43:26 -119384.424027] SLOW spr round 4 (radius: 5)
[05:44:05 -119384.422653] SLOW spr round 5 (radius: 10)
[05:44:46 -119384.334802] SLOW spr round 6 (radius: 15)
[05:46:00 -119384.334504] SLOW spr round 7 (radius: 20)
[05:47:48 -119384.334456] SLOW spr round 8 (radius: 25)
[05:49:53 -119384.334426] Model parameter optimization (eps = 0.100000)

[05:49:57] ML tree search #19, logLikelihood: -119384.206221

[05:49:57 -383689.427059] Initial branch length optimization
[05:49:59 -298984.680599] Model parameter optimization (eps = 10.000000)
[05:50:19 -297799.682229] AUTODETECT spr round 1 (radius: 5)
[05:50:51 -219463.839315] AUTODETECT spr round 2 (radius: 10)
[05:51:28 -176844.854638] AUTODETECT spr round 3 (radius: 15)
[05:52:10 -153404.130667] AUTODETECT spr round 4 (radius: 20)
[05:53:01 -135403.275143] AUTODETECT spr round 5 (radius: 25)
[05:53:53 -133601.294080] SPR radius for FAST iterations: 25 (autodetect)
[05:53:53 -133601.294080] Model parameter optimization (eps = 3.000000)
[05:54:14 -132426.889988] FAST spr round 1 (radius: 25)
[05:55:02 -120082.651645] FAST spr round 2 (radius: 25)
[05:55:41 -119529.933505] FAST spr round 3 (radius: 25)
[05:56:14 -119444.231335] FAST spr round 4 (radius: 25)
[05:56:44 -119438.476876] FAST spr round 5 (radius: 25)
[05:57:13 -119438.476734] Model parameter optimization (eps = 1.000000)
[05:57:21 -119434.162240] SLOW spr round 1 (radius: 5)
[05:58:03 -119397.903375] SLOW spr round 2 (radius: 5)
[05:58:44 -119389.586113] SLOW spr round 3 (radius: 5)
[05:59:25 -119388.201358] SLOW spr round 4 (radius: 5)
[06:00:03 -119388.201265] SLOW spr round 5 (radius: 10)
[06:00:45 -119386.365345] SLOW spr round 6 (radius: 5)
[06:01:35 -119384.374140] SLOW spr round 7 (radius: 5)
[06:02:20 -119383.664111] SLOW spr round 8 (radius: 5)
[06:03:01 -119383.663751] SLOW spr round 9 (radius: 10)
[06:03:42 -119382.679502] SLOW spr round 10 (radius: 5)
[06:04:32 -119381.521729] SLOW spr round 11 (radius: 5)
[06:05:15 -119381.521601] SLOW spr round 12 (radius: 10)
[06:05:58 -119381.521594] SLOW spr round 13 (radius: 15)
[06:07:11 -119381.521593] SLOW spr round 14 (radius: 20)
[06:09:01 -119381.521593] SLOW spr round 15 (radius: 25)
[06:11:11 -119381.521593] Model parameter optimization (eps = 0.100000)

[06:11:15] ML tree search #20, logLikelihood: -119381.198402


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.050662,0.260792) (0.056332,0.413780) (0.386387,0.704959) (0.506619,1.364124) 
   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: -119368.742545

AIC score: 240903.485090 / AICc score: 2588847.485090 / BIC score: 245465.737492
Free parameters (model + branch lengths): 1083

WARNING: Number of free parameters (K=1083) is larger than alignment size (n=499).
         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/Q5SW79/3_mltree/Q5SW79.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/3_mltree/Q5SW79.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/3_mltree/Q5SW79.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5SW79/3_mltree/Q5SW79.raxml.log

Analysis started: 11-Jul-2021 12:17:19 / finished: 11-Jul-2021 18:28:34

Elapsed time: 22275.596 seconds