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 02:44:42 as follows: raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/2_msa/Q12980_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980 --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/Q12980/2_msa/Q12980_trimmed_msa.fasta [00:00:00] Loaded alignment with 210 taxa and 586 sites WARNING: Sequences tr_B4QJJ1_B4QJJ1_DROSI_7240 and tr_B4HHA7_B4HHA7_DROSE_7238 are exactly identical! WARNING: Sequences tr_A0A087QIF2_A0A087QIF2_APTFO_9233 and tr_A0A0A0AB58_A0A0A0AB58_CHAVO_50402 are exactly identical! WARNING: Sequences tr_A0A1R1XYC2_A0A1R1XYC2_9FUNG_133412 and tr_A0A1R1Y0B3_A0A1R1Y0B3_9FUNG_133412 are exactly identical! WARNING: Duplicate sequences found: 3 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/Q12980/3_mltree/Q12980.raxml.reduced.phy Alignment comprises 1 partitions and 586 patterns Partition 0: noname Model: LG4X+R4 Alignment sites / patterns: 586 / 586 Gaps: 19.84 % Invariant sites: 0.00 % NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980.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 210 taxa [00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 84 / 6720 [00:00:00] Data distribution: max. searches per worker: 20 Starting ML tree search with 20 distinct starting trees [00:00:00 -148913.313206] Initial branch length optimization [00:00:00 -111575.048874] Model parameter optimization (eps = 10.000000) [00:00:07 -110964.328748] AUTODETECT spr round 1 (radius: 5) [00:00:13 -89361.305612] AUTODETECT spr round 2 (radius: 10) [00:00:21 -76007.398133] AUTODETECT spr round 3 (radius: 15) [00:00:31 -69492.775175] AUTODETECT spr round 4 (radius: 20) [00:00:41 -67683.727404] AUTODETECT spr round 5 (radius: 25) [00:00:50 -67657.712518] SPR radius for FAST iterations: 25 (autodetect) [00:00:50 -67657.712518] Model parameter optimization (eps = 3.000000) [00:01:01 -67348.300894] FAST spr round 1 (radius: 25) [00:01:11 -61366.066137] FAST spr round 2 (radius: 25) [00:01:20 -60940.833393] FAST spr round 3 (radius: 25) [00:01:27 -60934.069672] FAST spr round 4 (radius: 25) [00:01:34 -60931.336653] FAST spr round 5 (radius: 25) [00:01:40 -60931.335232] Model parameter optimization (eps = 1.000000) [00:01:45 -60914.500795] SLOW spr round 1 (radius: 5) [00:01:59 -60902.329148] SLOW spr round 2 (radius: 5) [00:02:10 -60902.300430] SLOW spr round 3 (radius: 10) [00:02:22 -60902.299904] SLOW spr round 4 (radius: 15) [00:02:39 -60902.299856] SLOW spr round 5 (radius: 20) [00:02:59 -60902.299841] SLOW spr round 6 (radius: 25) [00:03:18 -60902.299836] Model parameter optimization (eps = 0.100000) [00:03:20] ML tree search #1, logLikelihood: -60902.136112 [00:03:20 -149120.075342] Initial branch length optimization [00:03:21 -111254.004013] Model parameter optimization (eps = 10.000000) [00:03:28 -110658.144778] AUTODETECT spr round 1 (radius: 5) [00:03:34 -90513.585338] AUTODETECT spr round 2 (radius: 10) [00:03:42 -72905.843030] AUTODETECT spr round 3 (radius: 15) [00:03:52 -64748.574618] AUTODETECT spr round 4 (radius: 20) [00:04:04 -64051.050336] AUTODETECT spr round 5 (radius: 25) [00:04:14 -64021.908040] SPR radius for FAST iterations: 25 (autodetect) [00:04:14 -64021.908040] Model parameter optimization (eps = 3.000000) [00:04:24 -63653.029736] FAST spr round 1 (radius: 25) [00:04:34 -60990.061314] FAST spr round 2 (radius: 25) [00:04:43 -60916.226851] FAST spr round 3 (radius: 25) [00:04:50 -60914.147140] FAST spr round 4 (radius: 25) [00:04:56 -60914.146592] Model parameter optimization (eps = 1.000000) [00:04:59 -60912.790753] SLOW spr round 1 (radius: 5) [00:05:11 -60904.938673] SLOW spr round 2 (radius: 5) [00:05:23 -60904.296753] SLOW spr round 3 (radius: 5) [00:05:34 -60904.296710] SLOW spr round 4 (radius: 10) [00:05:45 -60904.296700] SLOW spr round 5 (radius: 15) [00:06:03 -60904.296695] SLOW spr round 6 (radius: 20) [00:06:24 -60904.296693] SLOW spr round 7 (radius: 25) [00:06:43 -60904.296691] Model parameter optimization (eps = 0.100000) [00:06:45] ML tree search #2, logLikelihood: -60904.175946 [00:06:45 -150029.630388] Initial branch length optimization [00:06:45 -112604.048666] Model parameter optimization (eps = 10.000000) [00:06:55 -111952.488605] AUTODETECT spr round 1 (radius: 5) [00:07:01 -88933.759593] AUTODETECT spr round 2 (radius: 10) [00:07:09 -75613.898836] AUTODETECT spr round 3 (radius: 15) [00:07:18 -69801.772651] AUTODETECT spr round 4 (radius: 20) [00:07:29 -68439.025818] AUTODETECT spr round 5 (radius: 25) [00:07:40 -68419.286207] SPR radius for FAST iterations: 25 (autodetect) [00:07:40 -68419.286207] Model parameter optimization (eps = 3.000000) [00:07:53 -68014.926449] FAST spr round 1 (radius: 25) [00:08:04 -61171.132361] FAST spr round 2 (radius: 25) [00:08:13 -60949.215006] FAST spr round 3 (radius: 25) [00:08:22 -60917.986733] FAST spr round 4 (radius: 25) [00:08:28 -60917.268543] FAST spr round 5 (radius: 25) [00:08:34 -60917.267029] Model parameter optimization (eps = 1.000000) [00:08:38 -60911.510553] SLOW spr round 1 (radius: 5) [00:08:50 -60906.274963] SLOW spr round 2 (radius: 5) [00:09:01 -60906.272091] SLOW spr round 3 (radius: 10) [00:09:13 -60906.272065] SLOW spr round 4 (radius: 15) [00:09:31 -60906.272062] SLOW spr round 5 (radius: 20) [00:09:52 -60906.272061] SLOW spr round 6 (radius: 25) [00:10:11 -60906.272060] Model parameter optimization (eps = 0.100000) [00:10:14] ML tree search #3, logLikelihood: -60906.084695 [00:10:14 -148913.091495] Initial branch length optimization [00:10:14 -112120.035049] Model parameter optimization (eps = 10.000000) [00:10:24 -111482.295143] AUTODETECT spr round 1 (radius: 5) [00:10:31 -90141.183077] AUTODETECT spr round 2 (radius: 10) [00:10:39 -75585.747586] AUTODETECT spr round 3 (radius: 15) [00:10:49 -66442.320858] AUTODETECT spr round 4 (radius: 20) [00:11:01 -66347.985755] AUTODETECT spr round 5 (radius: 25) [00:11:11 -66317.704809] SPR radius for FAST iterations: 25 (autodetect) [00:11:11 -66317.704809] Model parameter optimization (eps = 3.000000) [00:11:24 -65971.589875] FAST spr round 1 (radius: 25) [00:11:34 -61000.952275] FAST spr round 2 (radius: 25) [00:11:42 -60914.223390] FAST spr round 3 (radius: 25) [00:11:48 -60909.544822] FAST spr round 4 (radius: 25) [00:11:54 -60909.543652] Model parameter optimization (eps = 1.000000) [00:11:58 -60907.029151] SLOW spr round 1 (radius: 5) [00:12:10 -60903.374589] SLOW spr round 2 (radius: 5) [00:12:22 -60901.037888] SLOW spr round 3 (radius: 5) [00:12:33 -60901.037277] SLOW spr round 4 (radius: 10) [00:12:45 -60900.786357] SLOW spr round 5 (radius: 5) [00:13:00 -60899.611953] SLOW spr round 6 (radius: 5) [00:13:13 -60899.610758] SLOW spr round 7 (radius: 10) [00:13:25 -60899.610302] SLOW spr round 8 (radius: 15) [00:13:42 -60899.610121] SLOW spr round 9 (radius: 20) [00:14:03 -60899.610048] SLOW spr round 10 (radius: 25) [00:14:22 -60899.610018] Model parameter optimization (eps = 0.100000) [00:14:23] ML tree search #4, logLikelihood: -60899.572064 [00:14:23 -147871.069337] Initial branch length optimization [00:14:24 -111340.716509] Model parameter optimization (eps = 10.000000) [00:14:33 -110707.903812] AUTODETECT spr round 1 (radius: 5) [00:14:39 -86634.364271] AUTODETECT spr round 2 (radius: 10) [00:14:47 -71281.031505] AUTODETECT spr round 3 (radius: 15) [00:14:56 -65232.497837] AUTODETECT spr round 4 (radius: 20) [00:15:05 -65227.195506] AUTODETECT spr round 5 (radius: 25) [00:15:14 -65227.150526] SPR radius for FAST iterations: 20 (autodetect) [00:15:14 -65227.150526] Model parameter optimization (eps = 3.000000) [00:15:24 -64884.476396] FAST spr round 1 (radius: 20) [00:15:34 -61063.560525] FAST spr round 2 (radius: 20) [00:15:42 -60922.355816] FAST spr round 3 (radius: 20) [00:15:48 -60922.351850] Model parameter optimization (eps = 1.000000) [00:15:53 -60918.623879] SLOW spr round 1 (radius: 5) [00:16:06 -60910.623422] SLOW spr round 2 (radius: 5) [00:16:18 -60910.621789] SLOW spr round 3 (radius: 10) [00:16:29 -60910.621738] SLOW spr round 4 (radius: 15) [00:16:47 -60910.621721] SLOW spr round 5 (radius: 20) [00:17:07 -60910.621714] SLOW spr round 6 (radius: 25) [00:17:27 -60910.621710] Model parameter optimization (eps = 0.100000) [00:17:29] ML tree search #5, logLikelihood: -60910.435868 [00:17:29 -151302.716161] Initial branch length optimization [00:17:29 -111098.314470] Model parameter optimization (eps = 10.000000) [00:17:39 -110479.970178] AUTODETECT spr round 1 (radius: 5) [00:17:45 -83574.250838] AUTODETECT spr round 2 (radius: 10) [00:17:53 -68522.989461] AUTODETECT spr round 3 (radius: 15) [00:18:03 -65806.360160] AUTODETECT spr round 4 (radius: 20) [00:18:11 -65563.729553] AUTODETECT spr round 5 (radius: 25) [00:18:21 -65563.704925] SPR radius for FAST iterations: 20 (autodetect) [00:18:21 -65563.704925] Model parameter optimization (eps = 3.000000) [00:18:33 -65194.913576] FAST spr round 1 (radius: 20) [00:18:44 -61062.798287] FAST spr round 2 (radius: 20) [00:18:53 -60928.641646] FAST spr round 3 (radius: 20) [00:19:01 -60919.809703] FAST spr round 4 (radius: 20) [00:19:07 -60919.809377] Model parameter optimization (eps = 1.000000) [00:19:11 -60917.123313] SLOW spr round 1 (radius: 5) [00:19:24 -60904.254827] SLOW spr round 2 (radius: 5) [00:19:36 -60901.908369] SLOW spr round 3 (radius: 5) [00:19:48 -60901.908042] SLOW spr round 4 (radius: 10) [00:19:59 -60901.502601] SLOW spr round 5 (radius: 5) [00:20:14 -60900.346487] SLOW spr round 6 (radius: 5) [00:20:27 -60900.346130] SLOW spr round 7 (radius: 10) [00:20:39 -60900.346006] SLOW spr round 8 (radius: 15) [00:20:56 -60900.345956] SLOW spr round 9 (radius: 20) [00:21:17 -60900.345936] SLOW spr round 10 (radius: 25) [00:21:36 -60900.345928] Model parameter optimization (eps = 0.100000) [00:21:37] ML tree search #6, logLikelihood: -60900.266598 [00:21:37 -148669.227918] Initial branch length optimization [00:21:38 -112244.286123] Model parameter optimization (eps = 10.000000) [00:21:49 -111658.867016] AUTODETECT spr round 1 (radius: 5) [00:21:55 -86274.849899] AUTODETECT spr round 2 (radius: 10) [00:22:03 -72730.399163] AUTODETECT spr round 3 (radius: 15) [00:22:15 -67458.136088] AUTODETECT spr round 4 (radius: 20) [00:22:25 -67453.452923] AUTODETECT spr round 5 (radius: 25) [00:22:35 -67453.423136] SPR radius for FAST iterations: 20 (autodetect) [00:22:35 -67453.423136] Model parameter optimization (eps = 3.000000) [00:22:43 -67120.775770] FAST spr round 1 (radius: 20) [00:22:55 -61082.123396] FAST spr round 2 (radius: 20) [00:23:03 -61000.752434] FAST spr round 3 (radius: 20) [00:23:10 -60928.860890] FAST spr round 4 (radius: 20) [00:23:16 -60927.704451] FAST spr round 5 (radius: 20) [00:23:22 -60927.703449] Model parameter optimization (eps = 1.000000) [00:23:26 -60922.920048] SLOW spr round 1 (radius: 5) [00:23:39 -60912.616029] SLOW spr round 2 (radius: 5) [00:23:51 -60908.410024] SLOW spr round 3 (radius: 5) [00:24:02 -60908.409835] SLOW spr round 4 (radius: 10) [00:24:14 -60908.409825] SLOW spr round 5 (radius: 15) [00:24:32 -60908.409822] SLOW spr round 6 (radius: 20) [00:24:52 -60908.409820] SLOW spr round 7 (radius: 25) [00:25:11 -60908.409819] Model parameter optimization (eps = 0.100000) [00:25:13] ML tree search #7, logLikelihood: -60908.312391 [00:25:13 -146136.645821] Initial branch length optimization [00:25:13 -112486.302493] Model parameter optimization (eps = 10.000000) [00:25:23 -111874.262409] AUTODETECT spr round 1 (radius: 5) [00:25:30 -88873.373283] AUTODETECT spr round 2 (radius: 10) [00:25:38 -73855.289233] AUTODETECT spr round 3 (radius: 15) [00:25:48 -66033.397673] AUTODETECT spr round 4 (radius: 20) [00:25:58 -66027.678403] AUTODETECT spr round 5 (radius: 25) [00:26:09 -65990.324983] SPR radius for FAST iterations: 25 (autodetect) [00:26:09 -65990.324983] Model parameter optimization (eps = 3.000000) [00:26:21 -65646.125593] FAST spr round 1 (radius: 25) [00:26:30 -60975.160876] FAST spr round 2 (radius: 25) [00:26:38 -60935.799472] FAST spr round 3 (radius: 25) [00:26:45 -60934.934961] FAST spr round 4 (radius: 25) [00:26:51 -60934.934864] Model parameter optimization (eps = 1.000000) [00:26:56 -60927.643341] SLOW spr round 1 (radius: 5) [00:27:08 -60907.022678] SLOW spr round 2 (radius: 5) [00:27:20 -60905.665198] SLOW spr round 3 (radius: 5) [00:27:31 -60905.664851] SLOW spr round 4 (radius: 10) [00:27:42 -60905.664807] SLOW spr round 5 (radius: 15) [00:28:00 -60905.664795] SLOW spr round 6 (radius: 20) [00:28:22 -60905.664791] SLOW spr round 7 (radius: 25) [00:28:41 -60905.664789] Model parameter optimization (eps = 0.100000) [00:28:43] ML tree search #8, logLikelihood: -60905.534537 [00:28:43 -147080.534404] Initial branch length optimization [00:28:44 -110563.800243] Model parameter optimization (eps = 10.000000) [00:28:53 -110002.554143] AUTODETECT spr round 1 (radius: 5) [00:29:00 -90939.149477] AUTODETECT spr round 2 (radius: 10) [00:29:08 -74881.726833] AUTODETECT spr round 3 (radius: 15) [00:29:17 -68225.314710] AUTODETECT spr round 4 (radius: 20) [00:29:29 -66910.533789] AUTODETECT spr round 5 (radius: 25) [00:29:41 -66787.344572] SPR radius for FAST iterations: 25 (autodetect) [00:29:41 -66787.344572] Model parameter optimization (eps = 3.000000) [00:29:49 -66441.011066] FAST spr round 1 (radius: 25) [00:30:00 -61129.524574] FAST spr round 2 (radius: 25) [00:30:09 -60944.114005] FAST spr round 3 (radius: 25) [00:30:16 -60937.211964] FAST spr round 4 (radius: 25) [00:30:23 -60934.367093] FAST spr round 5 (radius: 25) [00:30:29 -60934.366232] Model parameter optimization (eps = 1.000000) [00:30:33 -60930.928865] SLOW spr round 1 (radius: 5) [00:30:45 -60911.417926] SLOW spr round 2 (radius: 5) [00:30:57 -60910.262340] SLOW spr round 3 (radius: 5) [00:31:09 -60910.260970] SLOW spr round 4 (radius: 10) [00:31:20 -60908.044938] SLOW spr round 5 (radius: 5) [00:31:35 -60908.044807] SLOW spr round 6 (radius: 10) [00:31:48 -60908.044797] SLOW spr round 7 (radius: 15) [00:32:05 -60908.044793] SLOW spr round 8 (radius: 20) [00:32:25 -60908.044790] SLOW spr round 9 (radius: 25) [00:32:44 -60908.044788] Model parameter optimization (eps = 0.100000) [00:32:46] ML tree search #9, logLikelihood: -60907.904156 [00:32:46 -148841.528142] Initial branch length optimization [00:32:47 -112332.746805] Model parameter optimization (eps = 10.000000) [00:32:56 -111710.030596] AUTODETECT spr round 1 (radius: 5) [00:33:02 -88816.849414] AUTODETECT spr round 2 (radius: 10) [00:33:10 -78970.149555] AUTODETECT spr round 3 (radius: 15) [00:33:20 -68984.545813] AUTODETECT spr round 4 (radius: 20) [00:33:29 -68295.568667] AUTODETECT spr round 5 (radius: 25) [00:33:39 -68091.375475] SPR radius for FAST iterations: 25 (autodetect) [00:33:39 -68091.375475] Model parameter optimization (eps = 3.000000) [00:33:47 -67795.843462] FAST spr round 1 (radius: 25) [00:33:57 -61045.907938] FAST spr round 2 (radius: 25) [00:34:06 -60943.381079] FAST spr round 3 (radius: 25) [00:34:14 -60935.295271] FAST spr round 4 (radius: 25) [00:34:20 -60935.292738] Model parameter optimization (eps = 1.000000) [00:34:25 -60919.602078] SLOW spr round 1 (radius: 5) [00:34:38 -60907.568998] SLOW spr round 2 (radius: 5) [00:34:50 -60907.567161] SLOW spr round 3 (radius: 10) [00:35:01 -60907.566971] SLOW spr round 4 (radius: 15) [00:35:19 -60907.487475] SLOW spr round 5 (radius: 20) [00:35:40 -60907.475425] SLOW spr round 6 (radius: 25) [00:35:59 -60907.468698] Model parameter optimization (eps = 0.100000) [00:36:02] ML tree search #10, logLikelihood: -60907.041550 [00:36:02 -145528.713898] Initial branch length optimization [00:36:02 -111497.867365] Model parameter optimization (eps = 10.000000) [00:36:12 -110884.115890] AUTODETECT spr round 1 (radius: 5) [00:36:18 -87164.983049] AUTODETECT spr round 2 (radius: 10) [00:36:27 -72015.937081] AUTODETECT spr round 3 (radius: 15) [00:36:37 -66217.983867] AUTODETECT spr round 4 (radius: 20) [00:36:48 -66014.224150] AUTODETECT spr round 5 (radius: 25) [00:36:59 -65898.493638] SPR radius for FAST iterations: 25 (autodetect) [00:36:59 -65898.493638] Model parameter optimization (eps = 3.000000) [00:37:08 -65584.391902] FAST spr round 1 (radius: 25) [00:37:19 -61419.727128] FAST spr round 2 (radius: 25) [00:37:28 -60968.962057] FAST spr round 3 (radius: 25) [00:37:36 -60922.188644] FAST spr round 4 (radius: 25) [00:37:42 -60917.908300] FAST spr round 5 (radius: 25) [00:37:49 -60916.648084] FAST spr round 6 (radius: 25) [00:37:55 -60916.647586] Model parameter optimization (eps = 1.000000) [00:37:58 -60912.517739] SLOW spr round 1 (radius: 5) [00:38:11 -60904.935363] SLOW spr round 2 (radius: 5) [00:38:23 -60904.932602] SLOW spr round 3 (radius: 10) [00:38:34 -60904.931655] SLOW spr round 4 (radius: 15) [00:38:51 -60904.931287] SLOW spr round 5 (radius: 20) [00:39:12 -60904.931142] SLOW spr round 6 (radius: 25) [00:39:31 -60904.931084] Model parameter optimization (eps = 0.100000) [00:39:34] ML tree search #11, logLikelihood: -60904.903162 [00:39:34 -149071.537789] Initial branch length optimization [00:39:34 -113079.302424] Model parameter optimization (eps = 10.000000) [00:39:43 -112425.782413] AUTODETECT spr round 1 (radius: 5) [00:39:49 -88984.751801] AUTODETECT spr round 2 (radius: 10) [00:39:58 -69744.249818] AUTODETECT spr round 3 (radius: 15) [00:40:08 -65048.487226] AUTODETECT spr round 4 (radius: 20) [00:40:19 -64651.589293] AUTODETECT spr round 5 (radius: 25) [00:40:31 -64651.569659] SPR radius for FAST iterations: 20 (autodetect) [00:40:31 -64651.569659] Model parameter optimization (eps = 3.000000) [00:40:42 -64240.852363] FAST spr round 1 (radius: 20) [00:40:53 -61028.740529] FAST spr round 2 (radius: 20) [00:41:02 -60936.154742] FAST spr round 3 (radius: 20) [00:41:09 -60934.026736] FAST spr round 4 (radius: 20) [00:41:15 -60933.991846] Model parameter optimization (eps = 1.000000) [00:41:19 -60929.813815] SLOW spr round 1 (radius: 5) [00:41:32 -60918.851357] SLOW spr round 2 (radius: 5) [00:41:44 -60918.847412] SLOW spr round 3 (radius: 10) [00:41:55 -60918.846573] SLOW spr round 4 (radius: 15) [00:42:13 -60918.846361] SLOW spr round 5 (radius: 20) [00:42:34 -60918.846290] SLOW spr round 6 (radius: 25) [00:42:52 -60918.846268] Model parameter optimization (eps = 0.100000) [00:42:54] ML tree search #12, logLikelihood: -60918.750671 [00:42:54 -146048.854203] Initial branch length optimization [00:42:54 -110409.326155] Model parameter optimization (eps = 10.000000) [00:43:04 -109812.411302] AUTODETECT spr round 1 (radius: 5) [00:43:10 -80081.106125] AUTODETECT spr round 2 (radius: 10) [00:43:18 -67830.569685] AUTODETECT spr round 3 (radius: 15) [00:43:27 -65134.855162] AUTODETECT spr round 4 (radius: 20) [00:43:35 -64832.006528] AUTODETECT spr round 5 (radius: 25) [00:43:45 -64826.032000] SPR radius for FAST iterations: 25 (autodetect) [00:43:45 -64826.032000] Model parameter optimization (eps = 3.000000) [00:43:56 -64524.528567] FAST spr round 1 (radius: 25) [00:44:05 -61097.157682] FAST spr round 2 (radius: 25) [00:44:13 -60942.447647] FAST spr round 3 (radius: 25) [00:44:21 -60920.523164] FAST spr round 4 (radius: 25) [00:44:28 -60919.016476] FAST spr round 5 (radius: 25) [00:44:34 -60918.243206] FAST spr round 6 (radius: 25) [00:44:40 -60918.242944] Model parameter optimization (eps = 1.000000) [00:44:43 -60914.821027] SLOW spr round 1 (radius: 5) [00:44:56 -60910.277312] SLOW spr round 2 (radius: 5) [00:45:07 -60910.277161] SLOW spr round 3 (radius: 10) [00:45:18 -60910.161758] SLOW spr round 4 (radius: 5) [00:45:33 -60908.916612] SLOW spr round 5 (radius: 5) [00:45:46 -60908.915630] SLOW spr round 6 (radius: 10) [00:45:58 -60908.915255] SLOW spr round 7 (radius: 15) [00:46:15 -60908.915106] SLOW spr round 8 (radius: 20) [00:46:37 -60908.915048] SLOW spr round 9 (radius: 25) [00:46:55 -60908.915024] Model parameter optimization (eps = 0.100000) [00:46:57] ML tree search #13, logLikelihood: -60908.814585 [00:46:57 -147907.052733] Initial branch length optimization [00:46:58 -111224.720426] Model parameter optimization (eps = 10.000000) [00:47:07 -110608.707155] AUTODETECT spr round 1 (radius: 5) [00:47:13 -88740.830851] AUTODETECT spr round 2 (radius: 10) [00:47:21 -73349.732363] AUTODETECT spr round 3 (radius: 15) [00:47:31 -64988.226761] AUTODETECT spr round 4 (radius: 20) [00:47:43 -64302.720192] AUTODETECT spr round 5 (radius: 25) [00:47:54 -64297.447706] SPR radius for FAST iterations: 25 (autodetect) [00:47:54 -64297.447706] Model parameter optimization (eps = 3.000000) [00:48:05 -63950.144116] FAST spr round 1 (radius: 25) [00:48:16 -61256.147077] FAST spr round 2 (radius: 25) [00:48:25 -60945.369714] FAST spr round 3 (radius: 25) [00:48:32 -60918.982912] FAST spr round 4 (radius: 25) [00:48:38 -60918.981754] Model parameter optimization (eps = 1.000000) [00:48:43 -60913.666809] SLOW spr round 1 (radius: 5) [00:48:55 -60908.042718] SLOW spr round 2 (radius: 5) [00:49:08 -60905.687930] SLOW spr round 3 (radius: 5) [00:49:19 -60905.687651] SLOW spr round 4 (radius: 10) [00:49:31 -60905.687621] SLOW spr round 5 (radius: 15) [00:49:48 -60905.687610] SLOW spr round 6 (radius: 20) [00:50:09 -60905.687606] SLOW spr round 7 (radius: 25) [00:50:28 -60905.687604] Model parameter optimization (eps = 0.100000) [00:50:30] ML tree search #14, logLikelihood: -60905.646296 [00:50:30 -148465.694502] Initial branch length optimization [00:50:30 -113019.579205] Model parameter optimization (eps = 10.000000) [00:50:40 -112406.545894] AUTODETECT spr round 1 (radius: 5) [00:50:46 -84463.911794] AUTODETECT spr round 2 (radius: 10) [00:50:54 -68386.906360] AUTODETECT spr round 3 (radius: 15) [00:51:03 -65182.041593] AUTODETECT spr round 4 (radius: 20) [00:51:14 -65158.753888] AUTODETECT spr round 5 (radius: 25) [00:51:23 -65152.117339] SPR radius for FAST iterations: 25 (autodetect) [00:51:23 -65152.117339] Model parameter optimization (eps = 3.000000) [00:51:34 -64839.940416] FAST spr round 1 (radius: 25) [00:51:43 -61223.552072] FAST spr round 2 (radius: 25) [00:51:51 -60994.657940] FAST spr round 3 (radius: 25) [00:51:58 -60958.516359] FAST spr round 4 (radius: 25) [00:52:05 -60925.572802] FAST spr round 5 (radius: 25) [00:52:11 -60925.572711] Model parameter optimization (eps = 1.000000) [00:52:15 -60917.196925] SLOW spr round 1 (radius: 5) [00:52:28 -60910.926927] SLOW spr round 2 (radius: 5) [00:52:40 -60909.995073] SLOW spr round 3 (radius: 5) [00:52:51 -60909.995014] SLOW spr round 4 (radius: 10) [00:53:03 -60909.524991] SLOW spr round 5 (radius: 5) [00:53:18 -60908.780094] SLOW spr round 6 (radius: 5) [00:53:31 -60908.142030] SLOW spr round 7 (radius: 5) [00:53:43 -60908.141776] SLOW spr round 8 (radius: 10) [00:53:54 -60908.141774] SLOW spr round 9 (radius: 15) [00:54:12 -60908.141773] SLOW spr round 10 (radius: 20) [00:54:33 -60908.141772] SLOW spr round 11 (radius: 25) [00:54:52 -60908.141771] Model parameter optimization (eps = 0.100000) [00:54:53] ML tree search #15, logLikelihood: -60908.137067 [00:54:53 -146283.895211] Initial branch length optimization [00:54:54 -110144.589121] Model parameter optimization (eps = 10.000000) [00:55:04 -109561.239125] AUTODETECT spr round 1 (radius: 5) [00:55:10 -89361.176271] AUTODETECT spr round 2 (radius: 10) [00:55:17 -76443.440350] AUTODETECT spr round 3 (radius: 15) [00:55:27 -71436.664383] AUTODETECT spr round 4 (radius: 20) [00:55:38 -66287.037843] AUTODETECT spr round 5 (radius: 25) [00:55:50 -66287.020212] SPR radius for FAST iterations: 20 (autodetect) [00:55:50 -66287.020212] Model parameter optimization (eps = 3.000000) [00:55:59 -65988.355861] FAST spr round 1 (radius: 20) [00:56:11 -61265.413700] FAST spr round 2 (radius: 20) [00:56:19 -60935.909144] FAST spr round 3 (radius: 20) [00:56:26 -60926.724660] FAST spr round 4 (radius: 20) [00:56:32 -60926.722367] Model parameter optimization (eps = 1.000000) [00:56:36 -60922.194699] SLOW spr round 1 (radius: 5) [00:56:50 -60907.999250] SLOW spr round 2 (radius: 5) [00:57:01 -60907.998765] SLOW spr round 3 (radius: 10) [00:57:12 -60907.998739] SLOW spr round 4 (radius: 15) [00:57:30 -60907.998730] SLOW spr round 5 (radius: 20) [00:57:52 -60907.998725] SLOW spr round 6 (radius: 25) [00:58:10 -60907.998723] Model parameter optimization (eps = 0.100000) [00:58:13] ML tree search #16, logLikelihood: -60907.741450 [00:58:13 -145409.705265] Initial branch length optimization [00:58:13 -111340.826517] Model parameter optimization (eps = 10.000000) [00:58:23 -110719.173350] AUTODETECT spr round 1 (radius: 5) [00:58:29 -85455.000169] AUTODETECT spr round 2 (radius: 10) [00:58:37 -70259.605213] AUTODETECT spr round 3 (radius: 15) [00:58:47 -65786.635647] AUTODETECT spr round 4 (radius: 20) [00:58:58 -64831.799362] AUTODETECT spr round 5 (radius: 25) [00:59:08 -64575.279653] SPR radius for FAST iterations: 25 (autodetect) [00:59:08 -64575.279653] Model parameter optimization (eps = 3.000000) [00:59:18 -64281.163192] FAST spr round 1 (radius: 25) [00:59:28 -61049.209618] FAST spr round 2 (radius: 25) [00:59:36 -60933.193445] FAST spr round 3 (radius: 25) [00:59:42 -60933.190241] Model parameter optimization (eps = 1.000000) [00:59:46 -60925.788385] SLOW spr round 1 (radius: 5) [00:59:59 -60913.859322] SLOW spr round 2 (radius: 5) [01:00:11 -60911.624174] SLOW spr round 3 (radius: 5) [01:00:23 -60911.622931] SLOW spr round 4 (radius: 10) [01:00:34 -60911.622766] SLOW spr round 5 (radius: 15) [01:00:52 -60911.622704] SLOW spr round 6 (radius: 20) [01:01:12 -60911.622679] SLOW spr round 7 (radius: 25) [01:01:31 -60911.622669] Model parameter optimization (eps = 0.100000) [01:01:34] ML tree search #17, logLikelihood: -60911.484713 [01:01:34 -148516.099648] Initial branch length optimization [01:01:34 -111925.610398] Model parameter optimization (eps = 10.000000) [01:01:44 -111302.284468] AUTODETECT spr round 1 (radius: 5) [01:01:50 -91212.129794] AUTODETECT spr round 2 (radius: 10) [01:01:58 -73777.132593] AUTODETECT spr round 3 (radius: 15) [01:02:07 -68358.938343] AUTODETECT spr round 4 (radius: 20) [01:02:18 -67338.650970] AUTODETECT spr round 5 (radius: 25) [01:02:27 -67142.215545] SPR radius for FAST iterations: 25 (autodetect) [01:02:27 -67142.215545] Model parameter optimization (eps = 3.000000) [01:02:38 -66849.226323] FAST spr round 1 (radius: 25) [01:02:48 -61266.675774] FAST spr round 2 (radius: 25) [01:02:56 -60945.326945] FAST spr round 3 (radius: 25) [01:03:04 -60932.837757] FAST spr round 4 (radius: 25) [01:03:11 -60928.770353] FAST spr round 5 (radius: 25) [01:03:17 -60928.758854] Model parameter optimization (eps = 1.000000) [01:03:23 -60918.670221] SLOW spr round 1 (radius: 5) [01:03:35 -60915.120057] SLOW spr round 2 (radius: 5) [01:03:47 -60909.219329] SLOW spr round 3 (radius: 5) [01:03:59 -60909.218105] SLOW spr round 4 (radius: 10) [01:04:10 -60909.217684] SLOW spr round 5 (radius: 15) [01:04:28 -60909.217519] SLOW spr round 6 (radius: 20) [01:04:49 -60909.217453] SLOW spr round 7 (radius: 25) [01:05:08 -60909.217427] Model parameter optimization (eps = 0.100000) [01:05:10] ML tree search #18, logLikelihood: -60909.144805 [01:05:10 -147590.587958] Initial branch length optimization [01:05:11 -112701.447811] Model parameter optimization (eps = 10.000000) [01:05:18 -112081.581427] AUTODETECT spr round 1 (radius: 5) [01:05:24 -86549.885425] AUTODETECT spr round 2 (radius: 10) [01:05:33 -73738.251465] AUTODETECT spr round 3 (radius: 15) [01:05:41 -71544.548251] AUTODETECT spr round 4 (radius: 20) [01:05:51 -67815.086050] AUTODETECT spr round 5 (radius: 25) [01:06:02 -67191.532752] SPR radius for FAST iterations: 25 (autodetect) [01:06:02 -67191.532752] Model parameter optimization (eps = 3.000000) [01:06:12 -66883.076335] FAST spr round 1 (radius: 25) [01:06:24 -61098.481639] FAST spr round 2 (radius: 25) [01:06:33 -60924.869018] FAST spr round 3 (radius: 25) [01:06:39 -60921.975067] FAST spr round 4 (radius: 25) [01:06:46 -60917.167486] FAST spr round 5 (radius: 25) [01:06:52 -60917.167340] Model parameter optimization (eps = 1.000000) [01:06:57 -60910.756015] SLOW spr round 1 (radius: 5) [01:07:09 -60904.905379] SLOW spr round 2 (radius: 5) [01:07:21 -60903.978387] SLOW spr round 3 (radius: 5) [01:07:32 -60903.978321] SLOW spr round 4 (radius: 10) [01:07:44 -60903.978303] SLOW spr round 5 (radius: 15) [01:08:02 -60903.978293] SLOW spr round 6 (radius: 20) [01:08:23 -60903.978287] SLOW spr round 7 (radius: 25) [01:08:43 -60903.978284] Model parameter optimization (eps = 0.100000) [01:08:44] ML tree search #19, logLikelihood: -60903.957250 [01:08:44 -146104.204679] Initial branch length optimization [01:08:44 -110187.914935] Model parameter optimization (eps = 10.000000) [01:08:54 -109573.013082] AUTODETECT spr round 1 (radius: 5) [01:09:00 -86218.055866] AUTODETECT spr round 2 (radius: 10) [01:09:08 -71209.747805] AUTODETECT spr round 3 (radius: 15) [01:09:19 -64503.245732] AUTODETECT spr round 4 (radius: 20) [01:09:29 -64065.551103] AUTODETECT spr round 5 (radius: 25) [01:09:39 -64065.509461] SPR radius for FAST iterations: 20 (autodetect) [01:09:39 -64065.509461] Model parameter optimization (eps = 3.000000) [01:09:49 -63705.696416] FAST spr round 1 (radius: 20) [01:09:59 -61042.573136] FAST spr round 2 (radius: 20) [01:10:07 -60929.785793] FAST spr round 3 (radius: 20) [01:10:13 -60921.973948] FAST spr round 4 (radius: 20) [01:10:19 -60921.973905] Model parameter optimization (eps = 1.000000) [01:10:23 -60918.850135] SLOW spr round 1 (radius: 5) [01:10:35 -60903.734235] SLOW spr round 2 (radius: 5) [01:10:47 -60903.733136] SLOW spr round 3 (radius: 10) [01:10:59 -60903.732826] SLOW spr round 4 (radius: 15) [01:11:16 -60903.732704] SLOW spr round 5 (radius: 20) [01:11:37 -60903.732655] SLOW spr round 6 (radius: 25) [01:11:56 -60903.732634] Model parameter optimization (eps = 0.100000) [01:11:59] ML tree search #20, logLikelihood: -60903.516483 Optimized model parameters: Partition 0: noname Rate heterogeneity: FREE (4 cats, mean), weights&rates: (0.158582,0.495860) (0.149871,0.448909) (0.354324,0.727348) (0.337223,1.768475) 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: -60899.572064 AIC score: 122645.144128 / AICc score: 124859.366351 / BIC score: 124495.058399 Free parameters (model + branch lengths): 423 Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980.raxml.bestTree All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980.raxml.mlTrees Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980.raxml.bestModel Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q12980/3_mltree/Q12980.raxml.log Analysis started: 11-Jul-2021 02:44:42 / finished: 11-Jul-2021 03:56:41 Elapsed time: 4319.319 seconds