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 16-Jul-2021 23:07:59 as follows: raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/2_msa/Q5JRA6_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/3_mltree/Q5JRA6 --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/Q5JRA6/2_msa/Q5JRA6_trimmed_msa.fasta [00:00:00] Loaded alignment with 336 taxa and 495 sites WARNING: Sequences tr_A0A2I3HNE5_A0A2I3HNE5_NOMLE_61853 and tr_H2P131_H2P131_PONAB_9601 are exactly identical! WARNING: Sequences tr_H2R939_H2R939_PANTR_9598 and sp_Q9NRC9_OTOR_HUMAN_9606 are exactly identical! WARNING: Sequences tr_H2R939_H2R939_PANTR_9598 and tr_A0A2R9C0E7_A0A2R9C0E7_PANPA_9597 are exactly identical! WARNING: Sequences sp_Q16674_MIA_HUMAN_9606 and tr_A0A2R9CEG9_A0A2R9CEG9_PANPA_9597 are exactly identical! WARNING: Sequences tr_F7GL98_F7GL98_MACMU_9544 and tr_A0A2K6BBA5_A0A2K6BBA5_MACNE_9545 are exactly identical! WARNING: Sequences tr_G7PH06_G7PH06_MACFA_9541 and tr_A0A096NVL9_A0A096NVL9_PAPAN_9555 are exactly identical! WARNING: Sequences tr_G7PH06_G7PH06_MACFA_9541 and tr_A0A0D9RGX7_A0A0D9RGX7_CHLSB_60711 are exactly identical! WARNING: Sequences tr_G7PH06_G7PH06_MACFA_9541 and tr_A0A2K5MB18_A0A2K5MB18_CERAT_9531 are exactly identical! WARNING: Sequences tr_G7PH06_G7PH06_MACFA_9541 and tr_A0A2K6BYM2_A0A2K6BYM2_MACNE_9545 are exactly identical! WARNING: Sequences tr_G7PH06_G7PH06_MACFA_9541 and tr_A0A2K6A814_A0A2K6A814_MANLE_9568 are exactly identical! WARNING: Sequences tr_A0A096MYZ3_A0A096MYZ3_PAPAN_9555 and tr_A0A2K6BQC7_A0A2K6BQC7_MACNE_9545 are exactly identical! WARNING: Sequences tr_A0A226N8A2_A0A226N8A2_CALSU_9009 and tr_A0A226PS01_A0A226PS01_COLVI_9014 are exactly identical! WARNING: Sequences tr_A0A2Y9PWT7_A0A2Y9PWT7_DELLE_9749 and tr_A0A2Y9F524_A0A2Y9F524_PHYCD_9755 are exactly identical! WARNING: Sequences tr_A0A2Y9PWT7_A0A2Y9PWT7_DELLE_9749 and tr_A0A384AWW5_A0A384AWW5_BALAS_310752 are exactly identical! WARNING: Duplicate sequences found: 14 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/Q5JRA6/3_mltree/Q5JRA6.raxml.reduced.phy Alignment comprises 1 partitions and 495 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 495 / 495 Gaps: 48.11 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/3_mltree/Q5JRA6.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 336 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 71 / 5680 [00:00:00] Data distribution: max. searches per worker: 20 Starting ML tree search with 20 distinct starting trees [00:00:00 -151083.550925] Initial branch length optimization [00:00:00 -125220.829800] Model parameter optimization (eps = 10.000000) [00:00:14 -124209.608427] AUTODETECT spr round 1 (radius: 5) [00:00:28 -82075.574547] AUTODETECT spr round 2 (radius: 10) [00:00:45 -65304.648999] AUTODETECT spr round 3 (radius: 15) [00:01:06 -59877.829744] AUTODETECT spr round 4 (radius: 20) [00:01:33 -56015.753219] AUTODETECT spr round 5 (radius: 25) [00:01:57 -55995.132648] SPR radius for FAST iterations: 25 (autodetect) [00:01:57 -55995.132648] Model parameter optimization (eps = 3.000000) [00:02:08 -55851.973338] FAST spr round 1 (radius: 25) [00:02:27 -51800.964092] FAST spr round 2 (radius: 25) [00:02:44 -51535.114609] FAST spr round 3 (radius: 25) [00:03:00 -51408.461752] FAST spr round 4 (radius: 25) [00:03:15 -51389.373059] FAST spr round 5 (radius: 25) [00:03:28 -51389.372946] Model parameter optimization (eps = 1.000000) [00:03:35 -51383.067674] SLOW spr round 1 (radius: 5) [00:03:57 -51334.627797] SLOW spr round 2 (radius: 5) [00:04:19 -51315.665373] SLOW spr round 3 (radius: 5) [00:04:39 -51314.711449] SLOW spr round 4 (radius: 5) [00:04:59 -51314.543633] SLOW spr round 5 (radius: 5) [00:05:20 -51225.840001] SLOW spr round 6 (radius: 5) [00:05:41 -51218.464231] SLOW spr round 7 (radius: 5) [00:06:00 -51218.463994] SLOW spr round 8 (radius: 10) [00:06:19 -51218.267591] SLOW spr round 9 (radius: 5) [00:06:46 -51218.267580] SLOW spr round 10 (radius: 10) [00:07:10 -51218.267580] SLOW spr round 11 (radius: 15) [00:07:41 -51218.267580] SLOW spr round 12 (radius: 20) [00:08:32 -51218.267580] SLOW spr round 13 (radius: 25) [00:09:44 -51218.267580] Model parameter optimization (eps = 0.100000) [00:09:48] ML tree search #1, logLikelihood: -51218.106009 [00:09:48 -151541.701500] Initial branch length optimization [00:09:49 -124277.051865] Model parameter optimization (eps = 10.000000) [00:09:59 -123447.828732] AUTODETECT spr round 1 (radius: 5) [00:10:13 -83712.943452] AUTODETECT spr round 2 (radius: 10) [00:10:30 -62573.059037] AUTODETECT spr round 3 (radius: 15) [00:10:52 -56975.417611] AUTODETECT spr round 4 (radius: 20) [00:11:19 -55489.364335] AUTODETECT spr round 5 (radius: 25) [00:11:43 -55462.609594] SPR radius for FAST iterations: 25 (autodetect) [00:11:43 -55462.609594] Model parameter optimization (eps = 3.000000) [00:11:54 -55333.041430] FAST spr round 1 (radius: 25) [00:12:15 -51698.448462] FAST spr round 2 (radius: 25) [00:12:33 -51391.974360] FAST spr round 3 (radius: 25) [00:12:47 -51361.456769] FAST spr round 4 (radius: 25) [00:13:00 -51355.938645] FAST spr round 5 (radius: 25) [00:13:13 -51353.109356] FAST spr round 6 (radius: 25) [00:13:27 -51336.765404] FAST spr round 7 (radius: 25) [00:13:39 -51336.476543] FAST spr round 8 (radius: 25) [00:13:54 -51254.128916] FAST spr round 9 (radius: 25) [00:14:07 -51252.007412] FAST spr round 10 (radius: 25) [00:14:19 -51251.455538] FAST spr round 11 (radius: 25) [00:14:31 -51251.455533] Model parameter optimization (eps = 1.000000) [00:14:37 -51249.629923] SLOW spr round 1 (radius: 5) [00:15:00 -51225.366366] SLOW spr round 2 (radius: 5) [00:15:20 -51223.716819] SLOW spr round 3 (radius: 5) [00:15:39 -51223.716227] SLOW spr round 4 (radius: 10) [00:15:59 -51223.505067] SLOW spr round 5 (radius: 5) [00:16:26 -51223.505007] SLOW spr round 6 (radius: 10) [00:16:50 -51223.504978] SLOW spr round 7 (radius: 15) [00:17:21 -51223.504961] SLOW spr round 8 (radius: 20) [00:18:12 -51223.504951] SLOW spr round 9 (radius: 25) [00:19:20 -51223.504946] Model parameter optimization (eps = 0.100000) [00:19:22] ML tree search #2, logLikelihood: -51223.486791 [00:19:22 -153196.003289] Initial branch length optimization [00:19:23 -126374.138441] Model parameter optimization (eps = 10.000000) [00:19:39 -125468.305164] AUTODETECT spr round 1 (radius: 5) [00:19:54 -90222.692624] AUTODETECT spr round 2 (radius: 10) [00:20:11 -70933.641107] AUTODETECT spr round 3 (radius: 15) [00:20:32 -60423.513577] AUTODETECT spr round 4 (radius: 20) [00:20:58 -58202.467953] AUTODETECT spr round 5 (radius: 25) [00:21:27 -57726.623429] SPR radius for FAST iterations: 25 (autodetect) [00:21:27 -57726.623429] Model parameter optimization (eps = 3.000000) [00:21:38 -57480.412068] FAST spr round 1 (radius: 25) [00:21:59 -51976.134245] FAST spr round 2 (radius: 25) [00:22:17 -51541.806343] FAST spr round 3 (radius: 25) [00:22:33 -51449.574508] FAST spr round 4 (radius: 25) [00:22:47 -51431.386965] FAST spr round 5 (radius: 25) [00:23:01 -51394.437499] FAST spr round 6 (radius: 25) [00:23:14 -51394.436660] Model parameter optimization (eps = 1.000000) [00:23:22 -51392.305053] SLOW spr round 1 (radius: 5) [00:23:45 -51371.863170] SLOW spr round 2 (radius: 5) [00:24:07 -51230.283712] SLOW spr round 3 (radius: 5) [00:24:29 -51226.378060] SLOW spr round 4 (radius: 5) [00:24:50 -51220.935466] SLOW spr round 5 (radius: 5) [00:25:10 -51219.235622] SLOW spr round 6 (radius: 5) [00:25:31 -51216.717290] SLOW spr round 7 (radius: 5) [00:25:51 -51216.322891] SLOW spr round 8 (radius: 5) [00:26:10 -51216.322683] SLOW spr round 9 (radius: 10) [00:26:30 -51215.237474] SLOW spr round 10 (radius: 5) [00:26:57 -51215.237292] SLOW spr round 11 (radius: 10) [00:27:21 -51215.033101] SLOW spr round 12 (radius: 5) [00:27:47 -51215.033090] SLOW spr round 13 (radius: 10) [00:28:10 -51215.033090] SLOW spr round 14 (radius: 15) [00:28:41 -51215.033090] SLOW spr round 15 (radius: 20) [00:29:31 -51215.033090] SLOW spr round 16 (radius: 25) [00:30:40 -51215.033090] Model parameter optimization (eps = 0.100000) [00:30:45] ML tree search #3, logLikelihood: -51214.866834 [00:30:45 -153568.262718] Initial branch length optimization [00:30:46 -126533.053525] Model parameter optimization (eps = 10.000000) [00:31:01 -125580.588981] AUTODETECT spr round 1 (radius: 5) [00:31:15 -87412.134649] AUTODETECT spr round 2 (radius: 10) [00:31:32 -65408.708823] AUTODETECT spr round 3 (radius: 15) [00:31:53 -57531.881929] AUTODETECT spr round 4 (radius: 20) [00:32:18 -55622.397834] AUTODETECT spr round 5 (radius: 25) [00:32:45 -55605.817298] SPR radius for FAST iterations: 25 (autodetect) [00:32:45 -55605.817298] Model parameter optimization (eps = 3.000000) [00:32:57 -55461.936957] FAST spr round 1 (radius: 25) [00:33:17 -51610.677379] FAST spr round 2 (radius: 25) [00:33:35 -51444.103317] FAST spr round 3 (radius: 25) [00:33:51 -51426.145871] FAST spr round 4 (radius: 25) [00:34:05 -51421.763343] FAST spr round 5 (radius: 25) [00:34:19 -51413.263371] FAST spr round 6 (radius: 25) [00:34:32 -51413.261418] Model parameter optimization (eps = 1.000000) [00:34:38 -51407.337163] SLOW spr round 1 (radius: 5) [00:35:00 -51380.669751] SLOW spr round 2 (radius: 5) [00:35:22 -51377.224812] SLOW spr round 3 (radius: 5) [00:35:44 -51377.054051] SLOW spr round 4 (radius: 5) [00:36:06 -51372.731535] SLOW spr round 5 (radius: 5) [00:36:26 -51372.728956] SLOW spr round 6 (radius: 10) [00:36:47 -51361.783586] SLOW spr round 7 (radius: 5) [00:37:16 -51359.780889] SLOW spr round 8 (radius: 5) [00:37:40 -51358.071702] SLOW spr round 9 (radius: 5) [00:38:02 -51357.874996] SLOW spr round 10 (radius: 5) [00:38:24 -51355.936591] SLOW spr round 11 (radius: 5) [00:38:45 -51354.748881] SLOW spr round 12 (radius: 5) [00:39:06 -51354.573491] SLOW spr round 13 (radius: 5) [00:39:26 -51354.525344] SLOW spr round 14 (radius: 10) [00:39:46 -51350.929610] SLOW spr round 15 (radius: 5) [00:40:15 -51348.918950] SLOW spr round 16 (radius: 5) [00:40:38 -51348.840635] SLOW spr round 17 (radius: 10) [00:41:00 -51348.635580] SLOW spr round 18 (radius: 5) [00:41:26 -51348.634991] SLOW spr round 19 (radius: 10) [00:41:50 -51348.634670] SLOW spr round 20 (radius: 15) [00:42:19 -51348.634491] SLOW spr round 21 (radius: 20) [00:42:58 -51348.634388] SLOW spr round 22 (radius: 25) [00:43:51 -51348.634328] Model parameter optimization (eps = 0.100000) [00:43:54] ML tree search #4, logLikelihood: -51348.429541 [00:43:54 -148952.952863] Initial branch length optimization [00:43:55 -124694.230253] Model parameter optimization (eps = 10.000000) [00:44:09 -123681.820475] AUTODETECT spr round 1 (radius: 5) [00:44:23 -84465.203527] AUTODETECT spr round 2 (radius: 10) [00:44:40 -66376.667545] AUTODETECT spr round 3 (radius: 15) [00:45:00 -57024.491155] AUTODETECT spr round 4 (radius: 20) [00:45:20 -54553.600133] AUTODETECT spr round 5 (radius: 25) [00:45:41 -54476.918853] SPR radius for FAST iterations: 25 (autodetect) [00:45:41 -54476.918853] Model parameter optimization (eps = 3.000000) [00:45:53 -54389.069914] FAST spr round 1 (radius: 25) [00:46:13 -51529.878270] FAST spr round 2 (radius: 25) [00:46:31 -51426.189997] FAST spr round 3 (radius: 25) [00:46:46 -51393.494968] FAST spr round 4 (radius: 25) [00:47:00 -51391.912783] FAST spr round 5 (radius: 25) [00:47:13 -51391.850044] Model parameter optimization (eps = 1.000000) [00:47:19 -51390.325975] SLOW spr round 1 (radius: 5) [00:47:41 -51358.048767] SLOW spr round 2 (radius: 5) [00:48:03 -51231.935586] SLOW spr round 3 (radius: 5) [00:48:24 -51222.471746] SLOW spr round 4 (radius: 5) [00:48:44 -51218.749749] SLOW spr round 5 (radius: 5) [00:49:05 -51218.460631] SLOW spr round 6 (radius: 5) [00:49:24 -51218.460442] SLOW spr round 7 (radius: 10) [00:49:45 -51214.709165] SLOW spr round 8 (radius: 5) [00:50:13 -51211.418197] SLOW spr round 9 (radius: 5) [00:50:36 -51211.417979] SLOW spr round 10 (radius: 10) [00:50:58 -51211.417967] SLOW spr round 11 (radius: 15) [00:51:31 -51211.417955] SLOW spr round 12 (radius: 20) [00:52:17 -51211.417943] SLOW spr round 13 (radius: 25) [00:53:26 -51211.417931] Model parameter optimization (eps = 0.100000) [00:53:29] ML tree search #5, logLikelihood: -51211.328921 [00:53:29 -150436.659859] Initial branch length optimization [00:53:30 -123634.359260] Model parameter optimization (eps = 10.000000) [00:53:40 -122777.255554] AUTODETECT spr round 1 (radius: 5) [00:53:55 -83346.388765] AUTODETECT spr round 2 (radius: 10) [00:54:13 -63038.812663] AUTODETECT spr round 3 (radius: 15) [00:54:33 -56490.271908] AUTODETECT spr round 4 (radius: 20) [00:54:57 -55715.772073] AUTODETECT spr round 5 (radius: 25) [00:55:22 -55678.232264] SPR radius for FAST iterations: 25 (autodetect) [00:55:22 -55678.232264] Model parameter optimization (eps = 3.000000) [00:55:33 -55575.186099] FAST spr round 1 (radius: 25) [00:55:53 -51812.834235] FAST spr round 2 (radius: 25) [00:56:10 -51587.469070] FAST spr round 3 (radius: 25) [00:56:27 -51495.203294] FAST spr round 4 (radius: 25) [00:56:43 -51478.018063] FAST spr round 5 (radius: 25) [00:56:59 -51447.563453] FAST spr round 6 (radius: 25) [00:57:14 -51367.879074] FAST spr round 7 (radius: 25) [00:57:27 -51357.619919] FAST spr round 8 (radius: 25) [00:57:40 -51356.652847] FAST spr round 9 (radius: 25) [00:57:53 -51356.469707] FAST spr round 10 (radius: 25) [00:58:06 -51356.413337] Model parameter optimization (eps = 1.000000) [00:58:16 -51353.617386] SLOW spr round 1 (radius: 5) [00:58:38 -51231.506027] SLOW spr round 2 (radius: 5) [00:59:00 -51218.178523] SLOW spr round 3 (radius: 5) [00:59:21 -51215.773449] SLOW spr round 4 (radius: 5) [00:59:41 -51214.923472] SLOW spr round 5 (radius: 5) [01:00:00 -51214.923402] SLOW spr round 6 (radius: 10) [01:00:20 -51214.923399] SLOW spr round 7 (radius: 15) [01:00:57 -51214.923398] SLOW spr round 8 (radius: 20) [01:01:42 -51214.923398] SLOW spr round 9 (radius: 25) [01:02:56 -51214.923398] Model parameter optimization (eps = 0.100000) [01:02:58] ML tree search #6, logLikelihood: -51214.835217 [01:02:58 -151087.620947] Initial branch length optimization [01:02:59 -125429.894860] Model parameter optimization (eps = 10.000000) [01:03:10 -124559.773720] AUTODETECT spr round 1 (radius: 5) [01:03:24 -81911.615364] AUTODETECT spr round 2 (radius: 10) [01:03:41 -62276.437051] AUTODETECT spr round 3 (radius: 15) [01:04:01 -56821.812955] AUTODETECT spr round 4 (radius: 20) [01:04:25 -55706.568450] AUTODETECT spr round 5 (radius: 25) [01:04:52 -55136.666099] SPR radius for FAST iterations: 25 (autodetect) [01:04:52 -55136.666099] Model parameter optimization (eps = 3.000000) [01:05:02 -55032.189502] FAST spr round 1 (radius: 25) [01:05:23 -51730.643998] FAST spr round 2 (radius: 25) [01:05:41 -51412.003819] FAST spr round 3 (radius: 25) [01:05:56 -51398.933783] FAST spr round 4 (radius: 25) [01:06:11 -51389.882599] FAST spr round 5 (radius: 25) [01:06:25 -51377.767533] FAST spr round 6 (radius: 25) [01:06:39 -51375.892082] FAST spr round 7 (radius: 25) [01:06:52 -51370.770654] FAST spr round 8 (radius: 25) [01:07:06 -51368.255098] FAST spr round 9 (radius: 25) [01:07:19 -51366.706904] FAST spr round 10 (radius: 25) [01:07:33 -51366.703381] Model parameter optimization (eps = 1.000000) [01:07:42 -51363.120693] SLOW spr round 1 (radius: 5) [01:08:06 -51323.224174] SLOW spr round 2 (radius: 5) [01:08:30 -51312.941589] SLOW spr round 3 (radius: 5) [01:08:53 -51224.093476] SLOW spr round 4 (radius: 5) [01:09:14 -51216.899506] SLOW spr round 5 (radius: 5) [01:09:34 -51216.899337] SLOW spr round 6 (radius: 10) [01:09:54 -51216.421228] SLOW spr round 7 (radius: 5) [01:10:21 -51216.421122] SLOW spr round 8 (radius: 10) [01:10:47 -51216.421103] SLOW spr round 9 (radius: 15) [01:11:18 -51216.421085] SLOW spr round 10 (radius: 20) [01:12:09 -51216.421067] SLOW spr round 11 (radius: 25) [01:13:22 -51216.421047] Model parameter optimization (eps = 0.100000) [01:13:28] ML tree search #7, logLikelihood: -51214.998213 [01:13:28 -152052.593208] Initial branch length optimization [01:13:28 -125139.398992] Model parameter optimization (eps = 10.000000) [01:13:40 -124246.353631] AUTODETECT spr round 1 (radius: 5) [01:13:55 -82432.823636] AUTODETECT spr round 2 (radius: 10) [01:14:12 -60895.885339] AUTODETECT spr round 3 (radius: 15) [01:14:34 -56435.421538] AUTODETECT spr round 4 (radius: 20) [01:14:59 -54831.900505] AUTODETECT spr round 5 (radius: 25) [01:15:28 -54823.140156] SPR radius for FAST iterations: 25 (autodetect) [01:15:28 -54823.140156] Model parameter optimization (eps = 3.000000) [01:15:38 -54688.577900] FAST spr round 1 (radius: 25) [01:15:59 -51499.908323] FAST spr round 2 (radius: 25) [01:16:15 -51413.992646] FAST spr round 3 (radius: 25) [01:16:30 -51394.019373] FAST spr round 4 (radius: 25) [01:16:44 -51389.628897] FAST spr round 5 (radius: 25) [01:16:59 -51382.079087] FAST spr round 6 (radius: 25) [01:17:12 -51381.858048] FAST spr round 7 (radius: 25) [01:17:26 -51381.809969] Model parameter optimization (eps = 1.000000) [01:17:32 -51378.390003] SLOW spr round 1 (radius: 5) [01:17:53 -51356.027506] SLOW spr round 2 (radius: 5) [01:18:15 -51352.796794] SLOW spr round 3 (radius: 5) [01:18:36 -51351.927472] SLOW spr round 4 (radius: 5) [01:18:57 -51351.926405] SLOW spr round 5 (radius: 10) [01:19:18 -51349.836138] SLOW spr round 6 (radius: 5) [01:19:45 -51348.938188] SLOW spr round 7 (radius: 5) [01:20:10 -51345.649977] SLOW spr round 8 (radius: 5) [01:20:32 -51345.649609] SLOW spr round 9 (radius: 10) [01:20:52 -51345.649504] SLOW spr round 10 (radius: 15) [01:21:26 -51345.649440] SLOW spr round 11 (radius: 20) [01:22:10 -51345.649393] SLOW spr round 12 (radius: 25) [01:23:20 -51345.649358] Model parameter optimization (eps = 0.100000) [01:23:25] ML tree search #8, logLikelihood: -51345.463768 [01:23:25 -152176.957665] Initial branch length optimization [01:23:26 -126083.684282] Model parameter optimization (eps = 10.000000) [01:23:37 -124761.519715] AUTODETECT spr round 1 (radius: 5) [01:23:51 -85548.850855] AUTODETECT spr round 2 (radius: 10) [01:24:08 -65268.189215] AUTODETECT spr round 3 (radius: 15) [01:24:27 -58401.322144] AUTODETECT spr round 4 (radius: 20) [01:24:48 -56978.365762] AUTODETECT spr round 5 (radius: 25) [01:25:18 -56821.622300] SPR radius for FAST iterations: 25 (autodetect) [01:25:18 -56821.622300] Model parameter optimization (eps = 3.000000) [01:25:29 -56649.177743] FAST spr round 1 (radius: 25) [01:25:49 -51739.827752] FAST spr round 2 (radius: 25) [01:26:07 -51510.356811] FAST spr round 3 (radius: 25) [01:26:23 -51489.766539] FAST spr round 4 (radius: 25) [01:26:36 -51488.667957] FAST spr round 5 (radius: 25) [01:26:49 -51487.838451] FAST spr round 6 (radius: 25) [01:27:02 -51483.473648] FAST spr round 7 (radius: 25) [01:27:15 -51483.025300] FAST spr round 8 (radius: 25) [01:27:28 -51481.769301] FAST spr round 9 (radius: 25) [01:27:40 -51481.767719] Model parameter optimization (eps = 1.000000) [01:27:49 -51473.129358] SLOW spr round 1 (radius: 5) [01:28:11 -51391.112954] SLOW spr round 2 (radius: 5) [01:28:35 -51366.549654] SLOW spr round 3 (radius: 5) [01:28:57 -51360.986177] SLOW spr round 4 (radius: 5) [01:29:18 -51356.492903] SLOW spr round 5 (radius: 5) [01:29:39 -51345.742625] SLOW spr round 6 (radius: 5) [01:30:01 -51249.745644] SLOW spr round 7 (radius: 5) [01:30:22 -51228.390560] SLOW spr round 8 (radius: 5) [01:30:43 -51225.967120] SLOW spr round 9 (radius: 5) [01:31:02 -51225.966425] SLOW spr round 10 (radius: 10) [01:31:21 -51225.767047] SLOW spr round 11 (radius: 5) [01:31:48 -51225.767036] SLOW spr round 12 (radius: 10) [01:32:12 -51225.767036] SLOW spr round 13 (radius: 15) [01:32:42 -51225.767036] SLOW spr round 14 (radius: 20) [01:33:31 -51225.767036] SLOW spr round 15 (radius: 25) [01:34:38 -51225.767036] Model parameter optimization (eps = 0.100000) [01:34:43] ML tree search #9, logLikelihood: -51225.608736 [01:34:43 -153261.534039] Initial branch length optimization [01:34:44 -126564.059080] Model parameter optimization (eps = 10.000000) [01:34:58 -125466.491108] AUTODETECT spr round 1 (radius: 5) [01:35:12 -84390.038762] AUTODETECT spr round 2 (radius: 10) [01:35:29 -61785.966417] AUTODETECT spr round 3 (radius: 15) [01:35:51 -56853.459006] AUTODETECT spr round 4 (radius: 20) [01:36:16 -56460.003967] AUTODETECT spr round 5 (radius: 25) [01:36:44 -56434.086832] SPR radius for FAST iterations: 25 (autodetect) [01:36:44 -56434.086832] Model parameter optimization (eps = 3.000000) [01:36:55 -56075.553113] FAST spr round 1 (radius: 25) [01:37:15 -51620.431044] FAST spr round 2 (radius: 25) [01:37:31 -51373.426742] FAST spr round 3 (radius: 25) [01:37:47 -51350.805635] FAST spr round 4 (radius: 25) [01:38:00 -51349.955003] FAST spr round 5 (radius: 25) [01:38:13 -51349.807898] FAST spr round 6 (radius: 25) [01:38:25 -51349.806462] Model parameter optimization (eps = 1.000000) [01:38:31 -51346.521294] SLOW spr round 1 (radius: 5) [01:38:52 -51329.140781] SLOW spr round 2 (radius: 5) [01:39:13 -51274.334739] SLOW spr round 3 (radius: 5) [01:39:34 -51269.877238] SLOW spr round 4 (radius: 5) [01:39:55 -51262.697700] SLOW spr round 5 (radius: 5) [01:40:16 -51227.864274] SLOW spr round 6 (radius: 5) [01:40:36 -51226.251723] SLOW spr round 7 (radius: 5) [01:40:57 -51220.815177] SLOW spr round 8 (radius: 5) [01:41:17 -51217.021115] SLOW spr round 9 (radius: 5) [01:41:37 -51217.021007] SLOW spr round 10 (radius: 10) [01:41:57 -51215.635548] SLOW spr round 11 (radius: 5) [01:42:23 -51213.554297] SLOW spr round 12 (radius: 5) [01:42:46 -51212.886222] SLOW spr round 13 (radius: 5) [01:43:07 -51212.886135] SLOW spr round 14 (radius: 10) [01:43:27 -51212.886128] SLOW spr round 15 (radius: 15) [01:44:01 -51212.886127] SLOW spr round 16 (radius: 20) [01:44:45 -51212.886127] SLOW spr round 17 (radius: 25) [01:45:53 -51212.886126] Model parameter optimization (eps = 0.100000) [01:45:57] ML tree search #10, logLikelihood: -51212.516428 [01:45:57 -153426.586683] Initial branch length optimization [01:45:58 -126199.298761] Model parameter optimization (eps = 10.000000) [01:46:08 -125235.118201] AUTODETECT spr round 1 (radius: 5) [01:46:22 -86193.209509] AUTODETECT spr round 2 (radius: 10) [01:46:39 -64963.736381] AUTODETECT spr round 3 (radius: 15) [01:46:59 -57640.966451] AUTODETECT spr round 4 (radius: 20) [01:47:24 -56547.662747] AUTODETECT spr round 5 (radius: 25) [01:47:50 -56416.980745] SPR radius for FAST iterations: 25 (autodetect) [01:47:50 -56416.980745] Model parameter optimization (eps = 3.000000) [01:48:02 -56161.508645] FAST spr round 1 (radius: 25) [01:48:22 -51757.856796] FAST spr round 2 (radius: 25) [01:48:39 -51471.532682] FAST spr round 3 (radius: 25) [01:48:54 -51426.750992] FAST spr round 4 (radius: 25) [01:49:09 -51414.605687] FAST spr round 5 (radius: 25) [01:49:23 -51388.207694] FAST spr round 6 (radius: 25) [01:49:37 -51383.736344] FAST spr round 7 (radius: 25) [01:49:50 -51376.828682] FAST spr round 8 (radius: 25) [01:50:02 -51376.827226] Model parameter optimization (eps = 1.000000) [01:50:08 -51374.582092] SLOW spr round 1 (radius: 5) [01:50:30 -51354.278473] SLOW spr round 2 (radius: 5) [01:50:52 -51349.324367] SLOW spr round 3 (radius: 5) [01:51:13 -51339.935142] SLOW spr round 4 (radius: 5) [01:51:34 -51337.747646] SLOW spr round 5 (radius: 5) [01:51:55 -51337.094664] SLOW spr round 6 (radius: 5) [01:52:15 -51334.901914] SLOW spr round 7 (radius: 5) [01:52:36 -51333.937292] SLOW spr round 8 (radius: 5) [01:52:57 -51332.483715] SLOW spr round 9 (radius: 5) [01:53:18 -51233.102634] SLOW spr round 10 (radius: 5) [01:53:38 -51228.752540] SLOW spr round 11 (radius: 5) [01:53:58 -51228.751847] SLOW spr round 12 (radius: 10) [01:54:18 -51219.789014] SLOW spr round 13 (radius: 5) [01:54:45 -51216.070364] SLOW spr round 14 (radius: 5) [01:55:08 -51213.906038] SLOW spr round 15 (radius: 5) [01:55:29 -51213.485014] SLOW spr round 16 (radius: 5) [01:55:49 -51213.480672] SLOW spr round 17 (radius: 10) [01:56:09 -51213.480160] SLOW spr round 18 (radius: 15) [01:56:44 -51213.480053] SLOW spr round 19 (radius: 20) [01:57:30 -51213.479992] SLOW spr round 20 (radius: 25) [01:58:42 -51213.479935] Model parameter optimization (eps = 0.100000) [01:58:45] ML tree search #11, logLikelihood: -51213.400890 [01:58:45 -150884.493163] Initial branch length optimization [01:58:45 -124458.860892] Model parameter optimization (eps = 10.000000) [01:58:59 -123467.435297] AUTODETECT spr round 1 (radius: 5) [01:59:13 -87621.840995] AUTODETECT spr round 2 (radius: 10) [01:59:30 -64106.270103] AUTODETECT spr round 3 (radius: 15) [01:59:50 -57586.580831] AUTODETECT spr round 4 (radius: 20) [02:00:12 -56239.563818] AUTODETECT spr round 5 (radius: 25) [02:00:35 -55797.124113] SPR radius for FAST iterations: 25 (autodetect) [02:00:35 -55797.124113] Model parameter optimization (eps = 3.000000) [02:00:48 -55608.726476] FAST spr round 1 (radius: 25) [02:01:09 -52394.007642] FAST spr round 2 (radius: 25) [02:01:27 -51867.899247] FAST spr round 3 (radius: 25) [02:01:43 -51556.804057] FAST spr round 4 (radius: 25) [02:01:59 -51471.488591] FAST spr round 5 (radius: 25) [02:02:13 -51455.666199] FAST spr round 6 (radius: 25) [02:02:27 -51438.068207] FAST spr round 7 (radius: 25) [02:02:44 -51375.740019] FAST spr round 8 (radius: 25) [02:02:58 -51349.539217] FAST spr round 9 (radius: 25) [02:03:11 -51341.990964] FAST spr round 10 (radius: 25) [02:03:25 -51341.843355] FAST spr round 11 (radius: 25) [02:03:37 -51341.842981] Model parameter optimization (eps = 1.000000) [02:03:45 -51336.948588] SLOW spr round 1 (radius: 5) [02:04:07 -51242.530987] SLOW spr round 2 (radius: 5) [02:04:29 -51237.872272] SLOW spr round 3 (radius: 5) [02:04:49 -51237.869765] SLOW spr round 4 (radius: 10) [02:05:09 -51234.709145] SLOW spr round 5 (radius: 5) [02:05:36 -51234.708785] SLOW spr round 6 (radius: 10) [02:06:01 -51225.397603] SLOW spr round 7 (radius: 5) [02:06:28 -51219.431681] SLOW spr round 8 (radius: 5) [02:06:51 -51219.431511] SLOW spr round 9 (radius: 10) [02:07:12 -51219.431496] SLOW spr round 10 (radius: 15) [02:07:45 -51219.431494] SLOW spr round 11 (radius: 20) [02:08:35 -51219.431494] SLOW spr round 12 (radius: 25) [02:09:46 -51219.431494] Model parameter optimization (eps = 0.100000) [02:09:52] ML tree search #12, logLikelihood: -51218.999312 [02:09:52 -153505.165547] Initial branch length optimization [02:09:53 -125661.513507] Model parameter optimization (eps = 10.000000) [02:10:04 -124564.263373] AUTODETECT spr round 1 (radius: 5) [02:10:19 -87554.327383] AUTODETECT spr round 2 (radius: 10) [02:10:36 -66956.780366] AUTODETECT spr round 3 (radius: 15) [02:10:57 -59559.704162] AUTODETECT spr round 4 (radius: 20) [02:11:21 -56942.489729] AUTODETECT spr round 5 (radius: 25) [02:11:46 -56864.818729] SPR radius for FAST iterations: 25 (autodetect) [02:11:46 -56864.818729] Model parameter optimization (eps = 3.000000) [02:11:57 -56674.036657] FAST spr round 1 (radius: 25) [02:12:17 -51816.852432] FAST spr round 2 (radius: 25) [02:12:34 -51443.330395] FAST spr round 3 (radius: 25) [02:12:51 -51380.104307] FAST spr round 4 (radius: 25) [02:13:06 -51370.329107] FAST spr round 5 (radius: 25) [02:13:21 -51354.505769] FAST spr round 6 (radius: 25) [02:13:35 -51346.067005] FAST spr round 7 (radius: 25) [02:13:48 -51345.571993] FAST spr round 8 (radius: 25) [02:14:01 -51344.310992] FAST spr round 9 (radius: 25) [02:14:14 -51344.308328] Model parameter optimization (eps = 1.000000) [02:14:19 -51340.954768] SLOW spr round 1 (radius: 5) [02:14:41 -51237.473149] SLOW spr round 2 (radius: 5) [02:15:03 -51223.744519] SLOW spr round 3 (radius: 5) [02:15:23 -51219.449402] SLOW spr round 4 (radius: 5) [02:15:44 -51219.111172] SLOW spr round 5 (radius: 5) [02:16:04 -51219.037091] SLOW spr round 6 (radius: 10) [02:16:24 -51218.233703] SLOW spr round 7 (radius: 5) [02:16:51 -51218.233616] SLOW spr round 8 (radius: 10) [02:17:16 -51218.233542] SLOW spr round 9 (radius: 15) [02:17:47 -51218.233465] SLOW spr round 10 (radius: 20) [02:18:35 -51218.233431] SLOW spr round 11 (radius: 25) [02:19:42 -51218.233431] Model parameter optimization (eps = 0.100000) [02:19:46] ML tree search #13, logLikelihood: -51218.131283 [02:19:46 -151013.851024] Initial branch length optimization [02:19:47 -125159.865027] Model parameter optimization (eps = 10.000000) [02:19:59 -124041.480378] AUTODETECT spr round 1 (radius: 5) [02:20:13 -81800.732027] AUTODETECT spr round 2 (radius: 10) [02:20:31 -65648.356811] AUTODETECT spr round 3 (radius: 15) [02:20:52 -58886.300567] AUTODETECT spr round 4 (radius: 20) [02:21:17 -56467.732640] AUTODETECT spr round 5 (radius: 25) [02:21:43 -56467.522288] SPR radius for FAST iterations: 25 (autodetect) [02:21:43 -56467.522288] Model parameter optimization (eps = 3.000000) [02:21:54 -56226.376034] FAST spr round 1 (radius: 25) [02:22:15 -51649.107469] FAST spr round 2 (radius: 25) [02:22:34 -51420.677275] FAST spr round 3 (radius: 25) [02:22:49 -51411.786410] FAST spr round 4 (radius: 25) [02:23:02 -51411.452013] FAST spr round 5 (radius: 25) [02:23:15 -51411.451475] Model parameter optimization (eps = 1.000000) [02:23:20 -51409.650318] SLOW spr round 1 (radius: 5) [02:23:45 -51367.516016] SLOW spr round 2 (radius: 5) [02:24:08 -51358.863197] SLOW spr round 3 (radius: 5) [02:24:31 -51337.997945] SLOW spr round 4 (radius: 5) [02:24:53 -51287.209961] SLOW spr round 5 (radius: 5) [02:25:15 -51228.886078] SLOW spr round 6 (radius: 5) [02:25:35 -51227.671803] SLOW spr round 7 (radius: 5) [02:25:57 -51217.317862] SLOW spr round 8 (radius: 5) [02:26:17 -51217.316672] SLOW spr round 9 (radius: 10) [02:26:37 -51214.199620] SLOW spr round 10 (radius: 5) [02:27:04 -51214.199618] SLOW spr round 11 (radius: 10) [02:27:29 -51213.977297] SLOW spr round 12 (radius: 5) [02:27:55 -51213.977288] SLOW spr round 13 (radius: 10) [02:28:18 -51213.977288] SLOW spr round 14 (radius: 15) [02:28:50 -51213.977288] SLOW spr round 15 (radius: 20) [02:29:40 -51213.977288] SLOW spr round 16 (radius: 25) [02:30:51 -51213.977288] Model parameter optimization (eps = 0.100000) [02:30:56] ML tree search #14, logLikelihood: -51213.714755 [02:30:56 -154101.057319] Initial branch length optimization [02:30:57 -126282.535533] Model parameter optimization (eps = 10.000000) [02:31:13 -125434.745102] AUTODETECT spr round 1 (radius: 5) [02:31:27 -83330.018187] AUTODETECT spr round 2 (radius: 10) [02:31:44 -63300.664803] AUTODETECT spr round 3 (radius: 15) [02:32:05 -56253.468957] AUTODETECT spr round 4 (radius: 20) [02:32:28 -55310.151221] AUTODETECT spr round 5 (radius: 25) [02:32:52 -55101.144285] SPR radius for FAST iterations: 25 (autodetect) [02:32:53 -55101.144285] Model parameter optimization (eps = 3.000000) [02:33:03 -54971.528126] FAST spr round 1 (radius: 25) [02:33:25 -51525.293868] FAST spr round 2 (radius: 25) [02:33:43 -51434.326959] FAST spr round 3 (radius: 25) [02:33:58 -51409.407895] FAST spr round 4 (radius: 25) [02:34:12 -51405.435932] FAST spr round 5 (radius: 25) [02:34:25 -51405.435088] Model parameter optimization (eps = 1.000000) [02:34:31 -51402.197985] SLOW spr round 1 (radius: 5) [02:34:56 -51381.130731] SLOW spr round 2 (radius: 5) [02:35:19 -51357.783199] SLOW spr round 3 (radius: 5) [02:35:43 -51330.743035] SLOW spr round 4 (radius: 5) [02:36:06 -51305.612794] SLOW spr round 5 (radius: 5) [02:36:28 -51245.043848] SLOW spr round 6 (radius: 5) [02:36:50 -51241.007766] SLOW spr round 7 (radius: 5) [02:37:10 -51241.005184] SLOW spr round 8 (radius: 10) [02:37:30 -51235.938826] SLOW spr round 9 (radius: 5) [02:37:57 -51235.938743] SLOW spr round 10 (radius: 10) [02:38:23 -51226.627880] SLOW spr round 11 (radius: 5) [02:38:50 -51220.548808] SLOW spr round 12 (radius: 5) [02:39:12 -51220.547915] SLOW spr round 13 (radius: 10) [02:39:34 -51220.337565] SLOW spr round 14 (radius: 5) [02:40:01 -51220.337556] SLOW spr round 15 (radius: 10) [02:40:25 -51220.337556] SLOW spr round 16 (radius: 15) [02:40:57 -51220.337556] SLOW spr round 17 (radius: 20) [02:41:50 -51220.337556] SLOW spr round 18 (radius: 25) [02:43:03 -51220.337556] Model parameter optimization (eps = 0.100000) [02:43:09] ML tree search #15, logLikelihood: -51220.201178 [02:43:09 -155352.231615] Initial branch length optimization [02:43:09 -126951.900589] Model parameter optimization (eps = 10.000000) [02:43:20 -126054.109823] AUTODETECT spr round 1 (radius: 5) [02:43:34 -83840.705778] AUTODETECT spr round 2 (radius: 10) [02:43:51 -63208.557372] AUTODETECT spr round 3 (radius: 15) [02:44:16 -56255.664382] AUTODETECT spr round 4 (radius: 20) [02:44:47 -55204.377986] AUTODETECT spr round 5 (radius: 25) [02:45:17 -55155.230546] SPR radius for FAST iterations: 25 (autodetect) [02:45:17 -55155.230546] Model parameter optimization (eps = 3.000000) [02:45:29 -54970.063425] FAST spr round 1 (radius: 25) [02:45:49 -51895.151922] FAST spr round 2 (radius: 25) [02:46:07 -51554.924398] FAST spr round 3 (radius: 25) [02:46:23 -51525.656999] FAST spr round 4 (radius: 25) [02:46:37 -51520.058192] FAST spr round 5 (radius: 25) [02:46:50 -51519.488274] FAST spr round 6 (radius: 25) [02:47:02 -51519.487144] Model parameter optimization (eps = 1.000000) [02:47:09 -51516.585544] SLOW spr round 1 (radius: 5) [02:47:34 -51442.114160] SLOW spr round 2 (radius: 5) [02:47:56 -51356.756738] SLOW spr round 3 (radius: 5) [02:48:18 -51297.939820] SLOW spr round 4 (radius: 5) [02:48:39 -51276.465303] SLOW spr round 5 (radius: 5) [02:49:01 -51232.465491] SLOW spr round 6 (radius: 5) [02:49:22 -51230.781280] SLOW spr round 7 (radius: 5) [02:49:43 -51219.989891] SLOW spr round 8 (radius: 5) [02:50:04 -51219.988854] SLOW spr round 9 (radius: 10) [02:50:24 -51216.640049] SLOW spr round 10 (radius: 5) [02:50:51 -51214.584596] SLOW spr round 11 (radius: 5) [02:51:14 -51213.808145] SLOW spr round 12 (radius: 5) [02:51:35 -51213.808059] SLOW spr round 13 (radius: 10) [02:51:55 -51213.808057] SLOW spr round 14 (radius: 15) [02:52:29 -51213.808057] SLOW spr round 15 (radius: 20) [02:53:12 -51213.808057] SLOW spr round 16 (radius: 25) [02:54:20 -51213.808057] Model parameter optimization (eps = 0.100000) [02:54:24] ML tree search #16, logLikelihood: -51213.394384 [02:54:25 -151936.971686] Initial branch length optimization [02:54:25 -124993.949650] Model parameter optimization (eps = 10.000000) [02:54:35 -124011.525888] AUTODETECT spr round 1 (radius: 5) [02:54:48 -87881.183386] AUTODETECT spr round 2 (radius: 10) [02:55:04 -69038.366131] AUTODETECT spr round 3 (radius: 15) [02:55:24 -58490.832327] AUTODETECT spr round 4 (radius: 20) [02:55:44 -55903.826908] AUTODETECT spr round 5 (radius: 25) [02:56:07 -55632.769145] SPR radius for FAST iterations: 25 (autodetect) [02:56:07 -55632.769145] Model parameter optimization (eps = 3.000000) [02:56:17 -55503.671022] FAST spr round 1 (radius: 25) [02:56:38 -51540.082261] FAST spr round 2 (radius: 25) [02:56:54 -51384.627428] FAST spr round 3 (radius: 25) [02:57:09 -51374.483941] FAST spr round 4 (radius: 25) [02:57:23 -51374.231662] FAST spr round 5 (radius: 25) [02:57:35 -51374.230238] Model parameter optimization (eps = 1.000000) [02:57:43 -51369.708927] SLOW spr round 1 (radius: 5) [02:58:05 -51357.602307] SLOW spr round 2 (radius: 5) [02:58:27 -51356.788545] SLOW spr round 3 (radius: 5) [02:58:51 -51323.248046] SLOW spr round 4 (radius: 5) [02:59:13 -51299.884440] SLOW spr round 5 (radius: 5) [02:59:33 -51234.322343] SLOW spr round 6 (radius: 5) [02:59:54 -51220.715820] SLOW spr round 7 (radius: 5) [03:00:15 -51212.837126] SLOW spr round 8 (radius: 5) [03:00:35 -51212.834948] SLOW spr round 9 (radius: 10) [03:00:54 -51212.834803] SLOW spr round 10 (radius: 15) [03:01:31 -51212.834789] SLOW spr round 11 (radius: 20) [03:02:16 -51212.834784] SLOW spr round 12 (radius: 25) [03:03:29 -51212.834780] Model parameter optimization (eps = 0.100000) [03:03:34] ML tree search #17, logLikelihood: -51212.719449 [03:03:34 -153558.473313] Initial branch length optimization [03:03:34 -125328.300459] Model parameter optimization (eps = 10.000000) [03:03:45 -124460.762724] AUTODETECT spr round 1 (radius: 5) [03:04:00 -86818.880964] AUTODETECT spr round 2 (radius: 10) [03:04:18 -63899.023080] AUTODETECT spr round 3 (radius: 15) [03:04:37 -57717.355554] AUTODETECT spr round 4 (radius: 20) [03:05:01 -56891.236403] AUTODETECT spr round 5 (radius: 25) [03:05:28 -56230.863803] SPR radius for FAST iterations: 25 (autodetect) [03:05:28 -56230.863803] Model parameter optimization (eps = 3.000000) [03:05:39 -56021.536812] FAST spr round 1 (radius: 25) [03:06:00 -51910.469497] FAST spr round 2 (radius: 25) [03:06:18 -51512.996253] FAST spr round 3 (radius: 25) [03:06:34 -51398.228342] FAST spr round 4 (radius: 25) [03:06:50 -51385.264381] FAST spr round 5 (radius: 25) [03:07:03 -51384.855848] FAST spr round 6 (radius: 25) [03:07:15 -51384.842564] Model parameter optimization (eps = 1.000000) [03:07:22 -51376.984722] SLOW spr round 1 (radius: 5) [03:07:45 -51363.485664] SLOW spr round 2 (radius: 5) [03:08:07 -51358.368620] SLOW spr round 3 (radius: 5) [03:08:28 -51299.255516] SLOW spr round 4 (radius: 5) [03:08:50 -51229.894096] SLOW spr round 5 (radius: 5) [03:09:11 -51219.143424] SLOW spr round 6 (radius: 5) [03:09:30 -51219.142493] SLOW spr round 7 (radius: 10) [03:09:49 -51218.927727] SLOW spr round 8 (radius: 5) [03:10:15 -51218.927718] SLOW spr round 9 (radius: 10) [03:10:39 -51218.927718] SLOW spr round 10 (radius: 15) [03:11:10 -51218.927718] SLOW spr round 11 (radius: 20) [03:11:56 -51218.927718] SLOW spr round 12 (radius: 25) [03:13:01 -51218.927718] Model parameter optimization (eps = 0.100000) [03:13:05] ML tree search #18, logLikelihood: -51218.803691 [03:13:06 -149524.142305] Initial branch length optimization [03:13:06 -124197.083388] Model parameter optimization (eps = 10.000000) [03:13:18 -123261.775951] AUTODETECT spr round 1 (radius: 5) [03:13:32 -87630.923823] AUTODETECT spr round 2 (radius: 10) [03:13:50 -67148.615766] AUTODETECT spr round 3 (radius: 15) [03:14:11 -57640.527356] AUTODETECT spr round 4 (radius: 20) [03:14:35 -56706.793054] AUTODETECT spr round 5 (radius: 25) [03:15:01 -56372.683337] SPR radius for FAST iterations: 25 (autodetect) [03:15:01 -56372.683337] Model parameter optimization (eps = 3.000000) [03:15:14 -56196.250699] FAST spr round 1 (radius: 25) [03:15:36 -51585.269871] FAST spr round 2 (radius: 25) [03:15:54 -51423.634140] FAST spr round 3 (radius: 25) [03:16:10 -51381.811798] FAST spr round 4 (radius: 25) [03:16:24 -51374.585916] FAST spr round 5 (radius: 25) [03:16:38 -51374.372210] FAST spr round 6 (radius: 25) [03:16:51 -51374.325753] Model parameter optimization (eps = 1.000000) [03:16:57 -51371.071876] SLOW spr round 1 (radius: 5) [03:17:19 -51354.118105] SLOW spr round 2 (radius: 5) [03:17:41 -51352.563028] SLOW spr round 3 (radius: 5) [03:18:01 -51352.561454] SLOW spr round 4 (radius: 10) [03:18:22 -51345.532289] SLOW spr round 5 (radius: 5) [03:18:50 -51342.436896] SLOW spr round 6 (radius: 5) [03:19:14 -51341.321719] SLOW spr round 7 (radius: 5) [03:19:36 -51340.894425] SLOW spr round 8 (radius: 5) [03:19:57 -51340.721281] SLOW spr round 9 (radius: 5) [03:20:17 -51340.305501] SLOW spr round 10 (radius: 5) [03:20:39 -51337.725741] SLOW spr round 11 (radius: 5) [03:21:00 -51336.148459] SLOW spr round 12 (radius: 5) [03:21:21 -51325.874261] SLOW spr round 13 (radius: 5) [03:21:43 -51237.545092] SLOW spr round 14 (radius: 5) [03:22:03 -51235.883672] SLOW spr round 15 (radius: 5) [03:22:24 -51233.362329] SLOW spr round 16 (radius: 5) [03:22:44 -51233.362079] SLOW spr round 17 (radius: 10) [03:23:04 -51224.368130] SLOW spr round 18 (radius: 5) [03:23:31 -51219.274971] SLOW spr round 19 (radius: 5) [03:23:55 -51218.404296] SLOW spr round 20 (radius: 5) [03:24:15 -51218.404118] SLOW spr round 21 (radius: 10) [03:24:35 -51218.404108] SLOW spr round 22 (radius: 15) [03:25:10 -51218.404107] SLOW spr round 23 (radius: 20) [03:25:55 -51218.404107] SLOW spr round 24 (radius: 25) [03:27:02 -51218.404107] Model parameter optimization (eps = 0.100000) [03:27:07] ML tree search #19, logLikelihood: -51218.191563 [03:27:07 -152937.016141] Initial branch length optimization [03:27:08 -126506.220689] Model parameter optimization (eps = 10.000000) [03:27:20 -125351.738661] AUTODETECT spr round 1 (radius: 5) [03:27:34 -87054.915303] AUTODETECT spr round 2 (radius: 10) [03:27:51 -64401.902157] AUTODETECT spr round 3 (radius: 15) [03:28:10 -56640.161796] AUTODETECT spr round 4 (radius: 20) [03:28:31 -54957.536219] AUTODETECT spr round 5 (radius: 25) [03:28:53 -54870.657202] SPR radius for FAST iterations: 25 (autodetect) [03:28:53 -54870.657202] Model parameter optimization (eps = 3.000000) [03:29:04 -54651.451711] FAST spr round 1 (radius: 25) [03:29:24 -51459.712957] FAST spr round 2 (radius: 25) [03:29:42 -51259.784670] FAST spr round 3 (radius: 25) [03:29:56 -51249.293565] FAST spr round 4 (radius: 25) [03:30:10 -51244.302726] FAST spr round 5 (radius: 25) [03:30:23 -51239.462139] FAST spr round 6 (radius: 25) [03:30:35 -51236.733606] FAST spr round 7 (radius: 25) [03:30:48 -51236.733158] Model parameter optimization (eps = 1.000000) [03:30:54 -51234.576133] SLOW spr round 1 (radius: 5) [03:31:15 -51218.985788] SLOW spr round 2 (radius: 5) [03:31:35 -51217.252723] SLOW spr round 3 (radius: 5) [03:31:55 -51217.252308] SLOW spr round 4 (radius: 10) [03:32:14 -51216.228049] SLOW spr round 5 (radius: 5) [03:32:41 -51216.227688] SLOW spr round 6 (radius: 10) [03:33:05 -51216.023041] SLOW spr round 7 (radius: 5) [03:33:31 -51216.023032] SLOW spr round 8 (radius: 10) [03:33:54 -51216.023032] SLOW spr round 9 (radius: 15) [03:34:25 -51216.023032] SLOW spr round 10 (radius: 20) [03:35:13 -51216.023032] SLOW spr round 11 (radius: 25) [03:36:23 -51216.023032] Model parameter optimization (eps = 0.100000) [03:36:25] ML tree search #20, logLikelihood: -51216.009084 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.105633,0.617064) (0.087766,1.207896) (0.481667,0.751405) (0.324933,1.436842) 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: -51211.328921 AIC score: 103772.657842 / AICc score: 1016372.657842 / BIC score: 106610.734332 Free parameters (model + branch lengths): 675 WARNING: Number of free parameters (K=675) is larger than alignment size (n=495). 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/Q5JRA6/3_mltree/Q5JRA6.raxml.bestTree All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/3_mltree/Q5JRA6.raxml.mlTrees Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/3_mltree/Q5JRA6.raxml.bestModel Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q5JRA6/3_mltree/Q5JRA6.raxml.log Analysis started: 16-Jul-2021 23:07:59 / finished: 17-Jul-2021 02:44:25 Elapsed time: 12985.660 seconds