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 24-Jul-2021 21:29:35 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/2_msa/Q63ZE4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/3_mltree/Q63ZE4 --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/Q63ZE4/2_msa/Q63ZE4_trimmed_msa.fasta
[00:00:00] Loaded alignment with 986 taxa and 540 sites

WARNING: Sequences tr_I6L5B4_I6L5B4_PONAB_9601 and sp_Q5R540_S22A7_PONAB_9601 are exactly identical!
WARNING: Sequences tr_A0A2I3RR00_A0A2I3RR00_PANTR_9598 and tr_A0A2R9BNG5_A0A2R9BNG5_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2J8LDW6_A0A2J8LDW6_PANTR_9598 and tr_A0A2R9C641_A0A2R9C641_PANPA_9597 are exactly identical!
WARNING: Sequences tr_H2RE17_H2RE17_PANTR_9598 and tr_A0A2R9B8J4_A0A2R9B8J4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F6TY97_F6TY97_MACMU_9544 and tr_A0A2K6AM16_A0A2K6AM16_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GJJ2_F7GJJ2_MACMU_9544 and tr_G8F3Z2_G8F3Z2_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7GJJ2_F7GJJ2_MACMU_9544 and tr_A0A2K6DXZ0_A0A2K6DXZ0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7GJL4_F7GJL4_MACMU_9544 and tr_A0A096NDC7_A0A096NDC7_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7GJL4_F7GJL4_MACMU_9544 and tr_A0A2K6D4D2_A0A2K6D4D2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7HBI4_F7HBI4_MACMU_9544 and tr_G7NYK5_G7NYK5_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7HBI4_F7HBI4_MACMU_9544 and tr_A0A2K6CY06_A0A2K6CY06_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A0D9R4F8_A0A0D9R4F8_CHLSB_60711 and tr_A0A2K6BIQ2_A0A2K6BIQ2_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2D0RLF2_A0A2D0RLF2_ICTPU_7998 and tr_A0A2D0RN14_A0A2D0RN14_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2K5M382_A0A2K5M382_CERAT_9531 and tr_A0A2K5YHU9_A0A2K5YHU9_MANLE_9568 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/Q63ZE4/3_mltree/Q63ZE4.raxml.reduced.phy

Alignment comprises 1 partitions and 540 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 540 / 540
Gaps: 15.29 %
Invariant sites: 0.00 %


NOTE: Binary MSA file already exists: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/3_mltree/Q63ZE4.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 986 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 78 / 6240
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -923397.464096] Initial branch length optimization
[00:00:03 -789871.389565] Model parameter optimization (eps = 10.000000)
[00:00:40 -783609.001449] AUTODETECT spr round 1 (radius: 5)
[00:02:30 -581950.596824] AUTODETECT spr round 2 (radius: 10)
[00:04:32 -428517.304390] AUTODETECT spr round 3 (radius: 15)
[00:06:43 -382523.137228] AUTODETECT spr round 4 (radius: 20)
[00:09:28 -353001.930811] AUTODETECT spr round 5 (radius: 25)
[00:12:16 -350892.243091] SPR radius for FAST iterations: 25 (autodetect)
[00:12:16 -350892.243091] Model parameter optimization (eps = 3.000000)
[00:12:40 -350153.173578] FAST spr round 1 (radius: 25)
[00:15:11 -311182.725013] FAST spr round 2 (radius: 25)
[00:17:18 -309557.850031] FAST spr round 3 (radius: 25)
[00:19:11 -309500.841256] FAST spr round 4 (radius: 25)
[00:20:50 -309495.145101] FAST spr round 5 (radius: 25)
[00:22:27 -309495.144375] Model parameter optimization (eps = 1.000000)
[00:22:45 -309484.193915] SLOW spr round 1 (radius: 5)
[00:24:51 -309399.284330] SLOW spr round 2 (radius: 5)
[00:26:51 -309388.309668] SLOW spr round 3 (radius: 5)
[00:28:49 -309382.567717] SLOW spr round 4 (radius: 5)
[00:30:43 -309382.567670] SLOW spr round 5 (radius: 10)
[00:32:53 -309380.854048] SLOW spr round 6 (radius: 5)
[00:35:17 -309374.648362] SLOW spr round 7 (radius: 5)
[00:37:29 -309374.193621] SLOW spr round 8 (radius: 5)
[00:39:31 -309374.192644] SLOW spr round 9 (radius: 10)
[00:41:43 -309374.192422] SLOW spr round 10 (radius: 15)
[00:45:11 -309373.853867] SLOW spr round 11 (radius: 5)
[00:47:39 -309373.792415] SLOW spr round 12 (radius: 10)
[00:50:10 -309373.790940] SLOW spr round 13 (radius: 15)
[00:53:34 -309373.790726] SLOW spr round 14 (radius: 20)
[00:58:51 -309373.790698] SLOW spr round 15 (radius: 25)
[01:05:04 -309373.790693] Model parameter optimization (eps = 0.100000)

[01:05:13] ML tree search #1, logLikelihood: -309373.405024

[01:05:13 -923175.383737] Initial branch length optimization
[01:05:15 -789271.927371] Model parameter optimization (eps = 10.000000)
[01:05:49 -783020.712503] AUTODETECT spr round 1 (radius: 5)
[01:07:46 -584810.939704] AUTODETECT spr round 2 (radius: 10)
[01:09:51 -438233.762358] AUTODETECT spr round 3 (radius: 15)
[01:12:04 -375958.489295] AUTODETECT spr round 4 (radius: 20)
[01:14:58 -348757.116252] AUTODETECT spr round 5 (radius: 25)
[01:18:04 -348303.616438] SPR radius for FAST iterations: 25 (autodetect)
[01:18:04 -348303.616438] Model parameter optimization (eps = 3.000000)
[01:18:26 -347547.352883] FAST spr round 1 (radius: 25)
[01:21:02 -310958.673979] FAST spr round 2 (radius: 25)
[01:23:10 -309578.960057] FAST spr round 3 (radius: 25)
[01:25:06 -309476.304142] FAST spr round 4 (radius: 25)
[01:26:49 -309464.911577] FAST spr round 5 (radius: 25)
[01:28:27 -309462.474836] FAST spr round 6 (radius: 25)
[01:30:01 -309462.474669] Model parameter optimization (eps = 1.000000)
[01:30:06 -309461.690554] SLOW spr round 1 (radius: 5)
[01:32:12 -309384.363659] SLOW spr round 2 (radius: 5)
[01:34:16 -309378.095352] SLOW spr round 3 (radius: 5)
[01:36:17 -309378.093943] SLOW spr round 4 (radius: 10)
[01:38:28 -309376.712700] SLOW spr round 5 (radius: 5)
[01:40:48 -309365.936852] SLOW spr round 6 (radius: 5)
[01:42:54 -309365.936729] SLOW spr round 7 (radius: 10)
[01:45:07 -309365.936691] SLOW spr round 8 (radius: 15)
[01:48:46 -309365.936678] SLOW spr round 9 (radius: 20)
[01:55:00 -309365.936673] SLOW spr round 10 (radius: 25)
[02:02:38 -309365.936671] Model parameter optimization (eps = 0.100000)

[02:02:51] ML tree search #2, logLikelihood: -309363.454827

[02:02:51 -922176.602788] Initial branch length optimization
[02:02:54 -787649.538034] Model parameter optimization (eps = 10.000000)
[02:03:27 -781629.226134] AUTODETECT spr round 1 (radius: 5)
[02:05:24 -586400.614511] AUTODETECT spr round 2 (radius: 10)
[02:07:34 -426265.082189] AUTODETECT spr round 3 (radius: 15)
[02:09:57 -373425.461230] AUTODETECT spr round 4 (radius: 20)
[02:12:49 -350392.019184] AUTODETECT spr round 5 (radius: 25)
[02:16:07 -346894.163622] SPR radius for FAST iterations: 25 (autodetect)
[02:16:08 -346894.163622] Model parameter optimization (eps = 3.000000)
[02:16:35 -346154.790923] FAST spr round 1 (radius: 25)
[02:19:27 -310888.653959] FAST spr round 2 (radius: 25)
[02:21:45 -309564.315140] FAST spr round 3 (radius: 25)
[02:23:47 -309473.913750] FAST spr round 4 (radius: 25)
[02:25:34 -309456.707318] FAST spr round 5 (radius: 25)
[02:27:16 -309456.706362] Model parameter optimization (eps = 1.000000)
[02:27:29 -309451.954214] SLOW spr round 1 (radius: 5)
[02:29:42 -309366.572210] SLOW spr round 2 (radius: 5)
[02:31:45 -309362.639213] SLOW spr round 3 (radius: 5)
[02:33:47 -309356.965872] SLOW spr round 4 (radius: 5)
[02:35:45 -309356.965001] SLOW spr round 5 (radius: 10)
[02:37:57 -309356.243891] SLOW spr round 6 (radius: 5)
[02:40:19 -309337.442009] SLOW spr round 7 (radius: 5)
[02:42:28 -309336.087363] SLOW spr round 8 (radius: 5)
[02:44:30 -309334.563741] SLOW spr round 9 (radius: 5)
[02:46:28 -309334.561732] SLOW spr round 10 (radius: 10)
[02:48:38 -309332.254635] SLOW spr round 11 (radius: 5)
[02:50:56 -309331.937631] SLOW spr round 12 (radius: 5)
[02:53:02 -309331.934786] SLOW spr round 13 (radius: 10)
[02:55:19 -309331.933910] SLOW spr round 14 (radius: 15)
[02:59:07 -309331.933661] SLOW spr round 15 (radius: 20)
[03:05:24 -309331.933591] SLOW spr round 16 (radius: 25)
[03:13:24 -309331.933571] Model parameter optimization (eps = 0.100000)

[03:13:31] ML tree search #3, logLikelihood: -309331.783376

[03:13:31 -922420.336858] Initial branch length optimization
[03:13:34 -789029.803263] Model parameter optimization (eps = 10.000000)
[03:14:10 -782895.152571] AUTODETECT spr round 1 (radius: 5)
[03:16:03 -585469.896344] AUTODETECT spr round 2 (radius: 10)
[03:18:07 -444127.499843] AUTODETECT spr round 3 (radius: 15)
[03:20:19 -384102.096221] AUTODETECT spr round 4 (radius: 20)
[03:23:01 -353335.799668] AUTODETECT spr round 5 (radius: 25)
[03:26:12 -349282.073313] SPR radius for FAST iterations: 25 (autodetect)
[03:26:12 -349282.073313] Model parameter optimization (eps = 3.000000)
[03:26:35 -348609.188398] FAST spr round 1 (radius: 25)
[03:29:28 -310705.045424] FAST spr round 2 (radius: 25)
[03:31:51 -309532.676666] FAST spr round 3 (radius: 25)
[03:33:52 -309499.105473] FAST spr round 4 (radius: 25)
[03:35:40 -309498.461153] FAST spr round 5 (radius: 25)
[03:37:22 -309498.460006] Model parameter optimization (eps = 1.000000)
[03:37:36 -309491.778401] SLOW spr round 1 (radius: 5)
[03:39:49 -309412.199908] SLOW spr round 2 (radius: 5)
[03:41:57 -309387.736389] SLOW spr round 3 (radius: 5)
[03:44:04 -309377.599924] SLOW spr round 4 (radius: 5)
[03:46:05 -309377.318394] SLOW spr round 5 (radius: 5)
[03:48:07 -309377.317825] SLOW spr round 6 (radius: 10)
[03:50:21 -309377.174863] SLOW spr round 7 (radius: 5)
[03:52:41 -309377.173435] SLOW spr round 8 (radius: 10)
[03:55:09 -309377.173356] SLOW spr round 9 (radius: 15)
[03:58:44 -309377.173345] SLOW spr round 10 (radius: 20)
[04:04:41 -309377.173343] SLOW spr round 11 (radius: 25)
[04:12:14 -309377.173342] Model parameter optimization (eps = 0.100000)

[04:12:19] ML tree search #4, logLikelihood: -309377.104295

[04:12:19 -923267.938878] Initial branch length optimization
[04:12:23 -790719.769682] Model parameter optimization (eps = 10.000000)
[04:13:01 -784530.807067] AUTODETECT spr round 1 (radius: 5)
[04:14:55 -579925.747204] AUTODETECT spr round 2 (radius: 10)
[04:17:00 -431914.528727] AUTODETECT spr round 3 (radius: 15)
[04:19:17 -364869.366271] AUTODETECT spr round 4 (radius: 20)
[04:22:09 -351067.901727] AUTODETECT spr round 5 (radius: 25)
[04:25:25 -348498.557530] SPR radius for FAST iterations: 25 (autodetect)
[04:25:25 -348498.557530] Model parameter optimization (eps = 3.000000)
[04:25:48 -347731.865686] FAST spr round 1 (radius: 25)
[04:28:32 -310964.925241] FAST spr round 2 (radius: 25)
[04:30:47 -309545.420359] FAST spr round 3 (radius: 25)
[04:32:48 -309453.892701] FAST spr round 4 (radius: 25)
[04:34:32 -309442.393433] FAST spr round 5 (radius: 25)
[04:36:10 -309440.417897] FAST spr round 6 (radius: 25)
[04:37:47 -309440.417170] Model parameter optimization (eps = 1.000000)
[04:38:01 -309437.454613] SLOW spr round 1 (radius: 5)
[04:40:07 -309367.287229] SLOW spr round 2 (radius: 5)
[04:42:10 -309360.926008] SLOW spr round 3 (radius: 5)
[04:44:11 -309355.497831] SLOW spr round 4 (radius: 5)
[04:46:10 -309352.438291] SLOW spr round 5 (radius: 5)
[04:48:06 -309351.267620] SLOW spr round 6 (radius: 5)
[04:50:03 -309351.264419] SLOW spr round 7 (radius: 10)
[04:52:17 -309349.235676] SLOW spr round 8 (radius: 5)
[04:54:42 -309347.519564] SLOW spr round 9 (radius: 5)
[04:56:53 -309347.512974] SLOW spr round 10 (radius: 10)
[04:59:12 -309347.512803] SLOW spr round 11 (radius: 15)
[05:02:55 -309347.512756] SLOW spr round 12 (radius: 20)
[05:09:00 -309347.512735] SLOW spr round 13 (radius: 25)
[05:16:42 -309347.512725] Model parameter optimization (eps = 0.100000)

[05:16:50] ML tree search #5, logLikelihood: -309347.059353

[05:16:50 -922115.434554] Initial branch length optimization
[05:16:55 -790036.288397] Model parameter optimization (eps = 10.000000)
[05:17:23 -783960.311983] AUTODETECT spr round 1 (radius: 5)
[05:19:21 -583148.568941] AUTODETECT spr round 2 (radius: 10)
[05:21:27 -434310.446278] AUTODETECT spr round 3 (radius: 15)
[05:23:40 -363846.475724] AUTODETECT spr round 4 (radius: 20)
[05:26:24 -344701.158554] AUTODETECT spr round 5 (radius: 25)
[05:29:16 -342965.809498] SPR radius for FAST iterations: 25 (autodetect)
[05:29:16 -342965.809498] Model parameter optimization (eps = 3.000000)
[05:29:35 -342331.103054] FAST spr round 1 (radius: 25)
[05:32:16 -310597.007642] FAST spr round 2 (radius: 25)
[05:34:30 -309563.486236] FAST spr round 3 (radius: 25)
[05:36:26 -309491.179077] FAST spr round 4 (radius: 25)
[05:38:08 -309489.894191] FAST spr round 5 (radius: 25)
[05:39:47 -309485.848639] FAST spr round 6 (radius: 25)
[05:41:25 -309478.158277] FAST spr round 7 (radius: 25)
[05:43:02 -309470.687768] FAST spr round 8 (radius: 25)
[05:44:38 -309468.439272] FAST spr round 9 (radius: 25)
[05:46:14 -309463.395087] FAST spr round 10 (radius: 25)
[05:47:49 -309463.393953] Model parameter optimization (eps = 1.000000)
[05:48:07 -309459.596448] SLOW spr round 1 (radius: 5)
[05:50:14 -309351.071784] SLOW spr round 2 (radius: 5)
[05:52:14 -309345.052738] SLOW spr round 3 (radius: 5)
[05:54:15 -309345.049206] SLOW spr round 4 (radius: 10)
[05:56:28 -309345.049001] SLOW spr round 5 (radius: 15)
[06:00:18 -309343.339834] SLOW spr round 6 (radius: 5)
[06:02:46 -309343.129442] SLOW spr round 7 (radius: 5)
[06:05:00 -309340.788527] SLOW spr round 8 (radius: 5)
[06:07:05 -309339.921169] SLOW spr round 9 (radius: 5)
[06:09:04 -309339.920940] SLOW spr round 10 (radius: 10)
[06:11:15 -309339.920890] SLOW spr round 11 (radius: 15)
[06:15:01 -309339.920872] SLOW spr round 12 (radius: 20)
[06:21:22 -309339.920864] SLOW spr round 13 (radius: 25)
[06:29:25 -309339.920860] Model parameter optimization (eps = 0.100000)

[06:29:34] ML tree search #6, logLikelihood: -309339.778977

[06:29:34 -924890.708261] Initial branch length optimization
[06:29:37 -791155.754055] Model parameter optimization (eps = 10.000000)
[06:30:15 -784858.604369] AUTODETECT spr round 1 (radius: 5)
[06:32:14 -582773.841458] AUTODETECT spr round 2 (radius: 10)
[06:34:23 -423254.650832] AUTODETECT spr round 3 (radius: 15)
[06:36:37 -358708.622248] AUTODETECT spr round 4 (radius: 20)
[06:39:07 -349214.942400] AUTODETECT spr round 5 (radius: 25)
[06:41:44 -347313.353260] SPR radius for FAST iterations: 25 (autodetect)
[06:41:44 -347313.353260] Model parameter optimization (eps = 3.000000)
[06:42:06 -346688.280800] FAST spr round 1 (radius: 25)
[06:44:54 -310753.714189] FAST spr round 2 (radius: 25)
[06:47:05 -309545.480551] FAST spr round 3 (radius: 25)
[06:49:04 -309466.465018] FAST spr round 4 (radius: 25)
[06:50:51 -309461.973986] FAST spr round 5 (radius: 25)
[06:52:31 -309461.464719] FAST spr round 6 (radius: 25)
[06:54:11 -309461.464084] Model parameter optimization (eps = 1.000000)
[06:54:27 -309454.441184] SLOW spr round 1 (radius: 5)
[06:56:34 -309354.778393] SLOW spr round 2 (radius: 5)
[06:58:38 -309349.719382] SLOW spr round 3 (radius: 5)
[07:00:41 -309346.548390] SLOW spr round 4 (radius: 5)
[07:02:41 -309346.548103] SLOW spr round 5 (radius: 10)
[07:04:55 -309346.548068] SLOW spr round 6 (radius: 15)
[07:08:39 -309346.548063] SLOW spr round 7 (radius: 20)
[07:14:42 -309346.548061] SLOW spr round 8 (radius: 25)
[07:22:27 -309346.548061] Model parameter optimization (eps = 0.100000)

[07:22:34] ML tree search #7, logLikelihood: -309346.513122

[07:22:34 -924851.582694] Initial branch length optimization
[07:22:37 -792167.673726] Model parameter optimization (eps = 10.000000)
[07:23:11 -785953.676555] AUTODETECT spr round 1 (radius: 5)
[07:25:04 -589486.587737] AUTODETECT spr round 2 (radius: 10)
[07:27:08 -438868.730293] AUTODETECT spr round 3 (radius: 15)
[07:29:24 -370283.123594] AUTODETECT spr round 4 (radius: 20)
[07:32:03 -347009.312503] AUTODETECT spr round 5 (radius: 25)
[07:35:13 -345883.469211] SPR radius for FAST iterations: 25 (autodetect)
[07:35:13 -345883.469211] Model parameter optimization (eps = 3.000000)
[07:35:35 -345222.654434] FAST spr round 1 (radius: 25)
[07:38:27 -311008.947623] FAST spr round 2 (radius: 25)
[07:40:44 -309604.200526] FAST spr round 3 (radius: 25)
[07:42:47 -309520.625650] FAST spr round 4 (radius: 25)
[07:44:38 -309505.698227] FAST spr round 5 (radius: 25)
[07:46:21 -309492.644290] FAST spr round 6 (radius: 25)
[07:47:57 -309491.005987] FAST spr round 7 (radius: 25)
[07:49:33 -309491.005817] Model parameter optimization (eps = 1.000000)
[07:49:49 -309488.667744] SLOW spr round 1 (radius: 5)
[07:52:00 -309341.942811] SLOW spr round 2 (radius: 5)
[07:54:09 -309328.915679] SLOW spr round 3 (radius: 5)
[07:56:14 -309325.877812] SLOW spr round 4 (radius: 5)
[07:58:17 -309325.876808] SLOW spr round 5 (radius: 10)
[08:00:32 -309325.876750] SLOW spr round 6 (radius: 15)
[08:04:23 -309325.876735] SLOW spr round 7 (radius: 20)
[08:10:49 -309325.876729] SLOW spr round 8 (radius: 25)
[08:18:48 -309325.876725] Model parameter optimization (eps = 0.100000)

[08:18:59] ML tree search #8, logLikelihood: -309325.378645

[08:18:59 -923201.192256] Initial branch length optimization
[08:19:02 -790880.730378] Model parameter optimization (eps = 10.000000)
[08:19:40 -784783.502405] AUTODETECT spr round 1 (radius: 5)
[08:21:38 -589863.008418] AUTODETECT spr round 2 (radius: 10)
[08:23:46 -443220.743578] AUTODETECT spr round 3 (radius: 15)
[08:26:05 -367151.654870] AUTODETECT spr round 4 (radius: 20)
[08:28:59 -348507.086037] AUTODETECT spr round 5 (radius: 25)
[08:32:36 -346543.849769] SPR radius for FAST iterations: 25 (autodetect)
[08:32:36 -346543.849769] Model parameter optimization (eps = 3.000000)
[08:32:56 -345761.974790] FAST spr round 1 (radius: 25)
[08:35:39 -311147.566390] FAST spr round 2 (radius: 25)
[08:37:55 -309629.742816] FAST spr round 3 (radius: 25)
[08:39:57 -309516.063167] FAST spr round 4 (radius: 25)
[08:41:46 -309499.776802] FAST spr round 5 (radius: 25)
[08:43:26 -309499.742976] Model parameter optimization (eps = 1.000000)
[08:43:40 -309495.345786] SLOW spr round 1 (radius: 5)
[08:45:49 -309380.262236] SLOW spr round 2 (radius: 5)
[08:47:55 -309366.687689] SLOW spr round 3 (radius: 5)
[08:49:57 -309364.253830] SLOW spr round 4 (radius: 5)
[08:51:56 -309364.253506] SLOW spr round 5 (radius: 10)
[08:54:08 -309357.770951] SLOW spr round 6 (radius: 5)
[08:56:32 -309355.759047] SLOW spr round 7 (radius: 5)
[08:58:41 -309350.344235] SLOW spr round 8 (radius: 5)
[09:00:42 -309348.424635] SLOW spr round 9 (radius: 5)
[09:02:39 -309348.424608] SLOW spr round 10 (radius: 10)
[09:04:44 -309348.330779] SLOW spr round 11 (radius: 15)
[09:08:26 -309348.239315] SLOW spr round 12 (radius: 20)
[09:14:29 -309348.239063] SLOW spr round 13 (radius: 25)
[09:22:14 -309348.239014] Model parameter optimization (eps = 0.100000)

[09:22:28] ML tree search #9, logLikelihood: -309347.352928

[09:22:29 -923388.244684] Initial branch length optimization
[09:22:31 -788509.929568] Model parameter optimization (eps = 10.000000)
[09:23:06 -782327.418579] AUTODETECT spr round 1 (radius: 5)
[09:25:06 -592125.134813] AUTODETECT spr round 2 (radius: 10)
[09:27:15 -431858.574750] AUTODETECT spr round 3 (radius: 15)
[09:29:26 -384976.528299] AUTODETECT spr round 4 (radius: 20)
[09:32:14 -352302.300610] AUTODETECT spr round 5 (radius: 25)
[09:35:47 -349429.545011] SPR radius for FAST iterations: 25 (autodetect)
[09:35:47 -349429.545011] Model parameter optimization (eps = 3.000000)
[09:36:11 -348888.529487] FAST spr round 1 (radius: 25)
[09:39:01 -311312.565591] FAST spr round 2 (radius: 25)
[09:41:20 -309616.781447] FAST spr round 3 (radius: 25)
[09:43:26 -309499.932044] FAST spr round 4 (radius: 25)
[09:45:15 -309472.824331] FAST spr round 5 (radius: 25)
[09:46:57 -309469.235666] FAST spr round 6 (radius: 25)
[09:48:37 -309469.234329] Model parameter optimization (eps = 1.000000)
[09:48:52 -309466.031439] SLOW spr round 1 (radius: 5)
[09:51:01 -309377.443544] SLOW spr round 2 (radius: 5)
[09:53:10 -309372.548599] SLOW spr round 3 (radius: 5)
[09:55:13 -309372.547668] SLOW spr round 4 (radius: 10)
[09:57:30 -309368.850041] SLOW spr round 5 (radius: 5)
[09:59:56 -309368.849545] SLOW spr round 6 (radius: 10)
[10:02:26 -309368.210259] SLOW spr round 7 (radius: 5)
[10:04:48 -309367.247341] SLOW spr round 8 (radius: 5)
[10:06:57 -309367.245862] SLOW spr round 9 (radius: 10)
[10:09:13 -309367.245819] SLOW spr round 10 (radius: 15)
[10:13:00 -309367.245815] SLOW spr round 11 (radius: 20)
[10:18:56 -309367.245813] SLOW spr round 12 (radius: 25)
[10:26:33 -309367.245812] Model parameter optimization (eps = 0.100000)

[10:26:38] ML tree search #10, logLikelihood: -309367.230841

[10:26:38 -927763.167049] Initial branch length optimization
[10:26:41 -793993.096470] Model parameter optimization (eps = 10.000000)
[10:27:12 -787630.198232] AUTODETECT spr round 1 (radius: 5)
[10:29:05 -578240.169461] AUTODETECT spr round 2 (radius: 10)
[10:31:09 -423213.319884] AUTODETECT spr round 3 (radius: 15)
[10:33:21 -368971.921331] AUTODETECT spr round 4 (radius: 20)
[10:35:59 -357081.677660] AUTODETECT spr round 5 (radius: 25)
[10:39:00 -350557.044406] SPR radius for FAST iterations: 25 (autodetect)
[10:39:00 -350557.044406] Model parameter optimization (eps = 3.000000)
[10:39:22 -349728.093953] FAST spr round 1 (radius: 25)
[10:41:51 -310933.368098] FAST spr round 2 (radius: 25)
[10:43:56 -309591.536193] FAST spr round 3 (radius: 25)
[10:45:48 -309526.509779] FAST spr round 4 (radius: 25)
[10:47:28 -309521.850045] FAST spr round 5 (radius: 25)
[10:49:01 -309521.850044] Model parameter optimization (eps = 1.000000)
[10:49:05 -309520.997793] SLOW spr round 1 (radius: 5)
[10:51:09 -309377.262250] SLOW spr round 2 (radius: 5)
[10:53:07 -309367.206870] SLOW spr round 3 (radius: 5)
[10:54:58 -309367.205879] SLOW spr round 4 (radius: 10)
[10:57:03 -309367.205753] SLOW spr round 5 (radius: 15)
[11:00:44 -309365.809243] SLOW spr round 6 (radius: 5)
[11:03:06 -309365.807507] SLOW spr round 7 (radius: 10)
[11:05:33 -309365.807211] SLOW spr round 8 (radius: 15)
[11:09:03 -309365.807110] SLOW spr round 9 (radius: 20)
[11:15:21 -309365.807072] SLOW spr round 10 (radius: 25)
[11:23:14 -309365.807058] Model parameter optimization (eps = 0.100000)

[11:23:18] ML tree search #11, logLikelihood: -309365.781226

[11:23:18 -923296.543455] Initial branch length optimization
[11:23:20 -791992.877020] Model parameter optimization (eps = 10.000000)
[11:23:51 -785545.201931] AUTODETECT spr round 1 (radius: 5)
[11:25:39 -600980.451494] AUTODETECT spr round 2 (radius: 10)
[11:27:37 -452300.255249] AUTODETECT spr round 3 (radius: 15)
[11:29:44 -365227.097317] AUTODETECT spr round 4 (radius: 20)
[11:32:19 -347422.137737] AUTODETECT spr round 5 (radius: 25)
[11:35:32 -346121.655805] SPR radius for FAST iterations: 25 (autodetect)
[11:35:32 -346121.655805] Model parameter optimization (eps = 3.000000)
[11:35:54 -345529.203774] FAST spr round 1 (radius: 25)
[11:38:32 -310711.171037] FAST spr round 2 (radius: 25)
[11:40:42 -309623.239178] FAST spr round 3 (radius: 25)
[11:42:38 -309517.856154] FAST spr round 4 (radius: 25)
[11:44:18 -309489.459421] FAST spr round 5 (radius: 25)
[11:45:52 -309485.256149] FAST spr round 6 (radius: 25)
[11:47:24 -309485.255586] Model parameter optimization (eps = 1.000000)
[11:47:28 -309484.542722] SLOW spr round 1 (radius: 5)
[11:49:32 -309404.439283] SLOW spr round 2 (radius: 5)
[11:51:33 -309370.062311] SLOW spr round 3 (radius: 5)
[11:53:26 -309367.368213] SLOW spr round 4 (radius: 5)
[11:55:18 -309364.269460] SLOW spr round 5 (radius: 5)
[11:57:08 -309364.269030] SLOW spr round 6 (radius: 10)
[11:59:11 -309356.987618] SLOW spr round 7 (radius: 5)
[12:01:23 -309356.985370] SLOW spr round 8 (radius: 10)
[12:03:39 -309356.984716] SLOW spr round 9 (radius: 15)
[12:07:08 -309356.984501] SLOW spr round 10 (radius: 20)
[12:13:24 -309356.984432] SLOW spr round 11 (radius: 25)
[12:21:12 -309356.984409] Model parameter optimization (eps = 0.100000)

[12:21:16] ML tree search #12, logLikelihood: -309356.959547

[12:21:16 -920661.567193] Initial branch length optimization
[12:21:20 -789736.479564] Model parameter optimization (eps = 10.000000)
[12:22:10 -783377.404948] AUTODETECT spr round 1 (radius: 5)
[12:23:58 -570086.265228] AUTODETECT spr round 2 (radius: 10)
[12:25:55 -424487.256204] AUTODETECT spr round 3 (radius: 15)
[12:27:57 -370572.258703] AUTODETECT spr round 4 (radius: 20)
[12:30:22 -346779.688518] AUTODETECT spr round 5 (radius: 25)
[12:33:09 -343389.344213] SPR radius for FAST iterations: 25 (autodetect)
[12:33:09 -343389.344213] Model parameter optimization (eps = 3.000000)
[12:33:17 -343362.413137] FAST spr round 1 (radius: 25)
[12:35:49 -311248.234397] FAST spr round 2 (radius: 25)
[12:37:52 -310039.491970] FAST spr round 3 (radius: 25)
[12:39:41 -309951.028679] FAST spr round 4 (radius: 25)
[12:41:19 -309934.211056] FAST spr round 5 (radius: 25)
[12:42:51 -309934.209949] Model parameter optimization (eps = 1.000000)
[12:43:11 -309488.229588] SLOW spr round 1 (radius: 5)
[12:45:16 -309385.919684] SLOW spr round 2 (radius: 5)
[12:47:13 -309370.918527] SLOW spr round 3 (radius: 5)
[12:49:10 -309364.269044] SLOW spr round 4 (radius: 5)
[12:51:01 -309364.268546] SLOW spr round 5 (radius: 10)
[12:53:04 -309363.399059] SLOW spr round 6 (radius: 5)
[12:55:17 -309361.487508] SLOW spr round 7 (radius: 5)
[12:57:18 -309361.487255] SLOW spr round 8 (radius: 10)
[12:59:24 -309361.487224] SLOW spr round 9 (radius: 15)
[13:02:49 -309361.487215] SLOW spr round 10 (radius: 20)
[13:08:38 -309361.487212] SLOW spr round 11 (radius: 25)
[13:16:06 -309361.487210] Model parameter optimization (eps = 0.100000)

[13:16:13] ML tree search #13, logLikelihood: -309361.287166

[13:16:13 -921653.506469] Initial branch length optimization
[13:16:17 -788527.552859] Model parameter optimization (eps = 10.000000)
[13:16:43 -782190.891321] AUTODETECT spr round 1 (radius: 5)
[13:18:31 -586520.640082] AUTODETECT spr round 2 (radius: 10)
[13:20:28 -425402.949074] AUTODETECT spr round 3 (radius: 15)
[13:22:33 -382959.434957] AUTODETECT spr round 4 (radius: 20)
[13:25:08 -355619.577682] AUTODETECT spr round 5 (radius: 25)
[13:28:18 -354923.296842] SPR radius for FAST iterations: 25 (autodetect)
[13:28:18 -354923.296842] Model parameter optimization (eps = 3.000000)
[13:28:36 -354310.490263] FAST spr round 1 (radius: 25)
[13:31:11 -311351.717713] FAST spr round 2 (radius: 25)
[13:33:16 -309584.909986] FAST spr round 3 (radius: 25)
[13:35:06 -309459.522704] FAST spr round 4 (radius: 25)
[13:36:44 -309451.414524] FAST spr round 5 (radius: 25)
[13:38:18 -309450.445708] FAST spr round 6 (radius: 25)
[13:39:48 -309450.444661] Model parameter optimization (eps = 1.000000)
[13:40:00 -309449.002129] SLOW spr round 1 (radius: 5)
[13:42:02 -309345.471244] SLOW spr round 2 (radius: 5)
[13:43:56 -309340.411875] SLOW spr round 3 (radius: 5)
[13:45:49 -309340.410991] SLOW spr round 4 (radius: 10)
[13:47:51 -309340.410598] SLOW spr round 5 (radius: 15)
[13:51:27 -309339.353752] SLOW spr round 6 (radius: 5)
[13:53:50 -309337.236758] SLOW spr round 7 (radius: 5)
[13:55:55 -309337.228609] SLOW spr round 8 (radius: 10)
[13:58:06 -309337.225776] SLOW spr round 9 (radius: 15)
[14:01:37 -309336.984275] SLOW spr round 10 (radius: 5)
[14:03:57 -309336.982771] SLOW spr round 11 (radius: 10)
[14:06:23 -309336.982705] SLOW spr round 12 (radius: 15)
[14:09:50 -309336.982684] SLOW spr round 13 (radius: 20)
[14:15:55 -309336.982675] SLOW spr round 14 (radius: 25)
[14:23:32 -309336.982672] Model parameter optimization (eps = 0.100000)

[14:23:37] ML tree search #14, logLikelihood: -309336.900087

[14:23:37 -922290.445123] Initial branch length optimization
[14:23:40 -790623.324479] Model parameter optimization (eps = 10.000000)
[14:24:10 -784353.294692] AUTODETECT spr round 1 (radius: 5)
[14:25:57 -579423.973420] AUTODETECT spr round 2 (radius: 10)
[14:27:55 -425162.111408] AUTODETECT spr round 3 (radius: 15)
[14:29:59 -367561.588606] AUTODETECT spr round 4 (radius: 20)
[14:32:35 -346400.588380] AUTODETECT spr round 5 (radius: 25)
[14:35:48 -345894.828384] SPR radius for FAST iterations: 25 (autodetect)
[14:35:48 -345894.828384] Model parameter optimization (eps = 3.000000)
[14:36:07 -345324.841155] FAST spr round 1 (radius: 25)
[14:38:44 -310550.837329] FAST spr round 2 (radius: 25)
[14:40:55 -309503.752680] FAST spr round 3 (radius: 25)
[14:42:45 -309454.795193] FAST spr round 4 (radius: 25)
[14:44:22 -309451.188105] FAST spr round 5 (radius: 25)
[14:45:58 -309447.871960] FAST spr round 6 (radius: 25)
[14:47:29 -309447.871380] Model parameter optimization (eps = 1.000000)
[14:47:41 -309444.636012] SLOW spr round 1 (radius: 5)
[14:49:43 -309359.824168] SLOW spr round 2 (radius: 5)
[14:51:40 -309352.051428] SLOW spr round 3 (radius: 5)
[14:53:34 -309351.425277] SLOW spr round 4 (radius: 5)
[14:55:24 -309351.425056] SLOW spr round 5 (radius: 10)
[14:57:27 -309350.141285] SLOW spr round 6 (radius: 5)
[14:59:40 -309339.242155] SLOW spr round 7 (radius: 5)
[15:01:41 -309339.242085] SLOW spr round 8 (radius: 10)
[15:03:48 -309339.242082] SLOW spr round 9 (radius: 15)
[15:07:25 -309339.242082] SLOW spr round 10 (radius: 20)
[15:13:35 -309339.242082] SLOW spr round 11 (radius: 25)
[15:21:20 -309339.242082] Model parameter optimization (eps = 0.100000)

[15:21:32] ML tree search #15, logLikelihood: -309338.133083

[15:21:32 -918835.923100] Initial branch length optimization
[15:21:35 -788954.261734] Model parameter optimization (eps = 10.000000)
[15:22:05 -782843.716129] AUTODETECT spr round 1 (radius: 5)
[15:23:51 -582960.373812] AUTODETECT spr round 2 (radius: 10)
[15:25:49 -418286.041412] AUTODETECT spr round 3 (radius: 15)
[15:27:53 -366619.584174] AUTODETECT spr round 4 (radius: 20)
[15:30:17 -344190.843952] AUTODETECT spr round 5 (radius: 25)
[15:33:10 -341218.514934] SPR radius for FAST iterations: 25 (autodetect)
[15:33:10 -341218.514934] Model parameter optimization (eps = 3.000000)
[15:33:34 -340545.204324] FAST spr round 1 (radius: 25)
[15:36:04 -310664.239726] FAST spr round 2 (radius: 25)
[15:38:06 -309675.208232] FAST spr round 3 (radius: 25)
[15:39:55 -309551.837709] FAST spr round 4 (radius: 25)
[15:41:35 -309532.133634] FAST spr round 5 (radius: 25)
[15:43:09 -309514.832953] FAST spr round 6 (radius: 25)
[15:44:40 -309514.832874] Model parameter optimization (eps = 1.000000)
[15:44:53 -309509.621637] SLOW spr round 1 (radius: 5)
[15:46:53 -309392.005937] SLOW spr round 2 (radius: 5)
[15:48:50 -309379.843789] SLOW spr round 3 (radius: 5)
[15:50:46 -309366.142150] SLOW spr round 4 (radius: 5)
[15:52:38 -309363.365531] SLOW spr round 5 (radius: 5)
[15:54:31 -309362.712010] SLOW spr round 6 (radius: 5)
[15:56:23 -309358.128598] SLOW spr round 7 (radius: 5)
[15:58:15 -309358.128566] SLOW spr round 8 (radius: 10)
[16:00:21 -309346.085550] SLOW spr round 9 (radius: 5)
[16:02:34 -309342.815797] SLOW spr round 10 (radius: 5)
[16:04:35 -309342.570383] SLOW spr round 11 (radius: 5)
[16:06:30 -309342.570234] SLOW spr round 12 (radius: 10)
[16:08:36 -309342.570227] SLOW spr round 13 (radius: 15)
[16:12:07 -309342.570226] SLOW spr round 14 (radius: 20)
[16:17:49 -309342.570226] SLOW spr round 15 (radius: 25)
[16:25:04 -309342.570226] Model parameter optimization (eps = 0.100000)

[16:25:14] ML tree search #16, logLikelihood: -309342.392439

[16:25:14 -923538.601127] Initial branch length optimization
[16:25:17 -790580.269466] Model parameter optimization (eps = 10.000000)
[16:25:43 -784348.669805] AUTODETECT spr round 1 (radius: 5)
[16:27:31 -581189.751049] AUTODETECT spr round 2 (radius: 10)
[16:29:30 -416653.538184] AUTODETECT spr round 3 (radius: 15)
[16:31:31 -360194.300774] AUTODETECT spr round 4 (radius: 20)
[16:34:00 -343146.145341] AUTODETECT spr round 5 (radius: 25)
[16:36:43 -341415.051645] SPR radius for FAST iterations: 25 (autodetect)
[16:36:43 -341415.051645] Model parameter optimization (eps = 3.000000)
[16:37:07 -340844.194312] FAST spr round 1 (radius: 25)
[16:39:35 -310586.391019] FAST spr round 2 (radius: 25)
[16:41:37 -309567.552318] FAST spr round 3 (radius: 25)
[16:43:24 -309491.191728] FAST spr round 4 (radius: 25)
[16:45:00 -309480.903575] FAST spr round 5 (radius: 25)
[16:46:33 -309478.151292] FAST spr round 6 (radius: 25)
[16:48:03 -309478.150377] Model parameter optimization (eps = 1.000000)
[16:48:15 -309474.603245] SLOW spr round 1 (radius: 5)
[16:50:16 -309364.112236] SLOW spr round 2 (radius: 5)
[16:52:10 -309359.864954] SLOW spr round 3 (radius: 5)
[16:54:02 -309358.296648] SLOW spr round 4 (radius: 5)
[16:55:52 -309358.296611] SLOW spr round 5 (radius: 10)
[16:57:53 -309358.296600] SLOW spr round 6 (radius: 15)
[17:01:16 -309358.296597] SLOW spr round 7 (radius: 20)
[17:06:23 -309358.296595] SLOW spr round 8 (radius: 25)
[17:12:49 -309358.296594] Model parameter optimization (eps = 0.100000)

[17:12:57] ML tree search #17, logLikelihood: -309357.849982

[17:12:57 -923535.767906] Initial branch length optimization
[17:13:00 -790461.735118] Model parameter optimization (eps = 10.000000)
[17:13:34 -784138.287205] AUTODETECT spr round 1 (radius: 5)
[17:15:21 -586060.732765] AUTODETECT spr round 2 (radius: 10)
[17:17:17 -431191.582160] AUTODETECT spr round 3 (radius: 15)
[17:19:26 -364528.576709] AUTODETECT spr round 4 (radius: 20)
[17:21:54 -351791.053244] AUTODETECT spr round 5 (radius: 25)
[17:25:03 -349045.537443] SPR radius for FAST iterations: 25 (autodetect)
[17:25:03 -349045.537443] Model parameter optimization (eps = 3.000000)
[17:25:24 -348544.770817] FAST spr round 1 (radius: 25)
[17:27:56 -310779.492007] FAST spr round 2 (radius: 25)
[17:30:01 -309617.574279] FAST spr round 3 (radius: 25)
[17:31:50 -309488.581427] FAST spr round 4 (radius: 25)
[17:33:28 -309480.851712] FAST spr round 5 (radius: 25)
[17:35:01 -309479.493795] FAST spr round 6 (radius: 25)
[17:36:31 -309479.492925] Model parameter optimization (eps = 1.000000)
[17:36:44 -309474.690587] SLOW spr round 1 (radius: 5)
[17:38:45 -309355.594330] SLOW spr round 2 (radius: 5)
[17:40:40 -309349.205030] SLOW spr round 3 (radius: 5)
[17:42:31 -309349.203205] SLOW spr round 4 (radius: 10)
[17:44:34 -309349.202778] SLOW spr round 5 (radius: 15)
[17:47:57 -309349.202662] SLOW spr round 6 (radius: 20)
[17:53:06 -309349.202629] SLOW spr round 7 (radius: 25)
[17:59:38 -309349.202619] Model parameter optimization (eps = 0.100000)

[17:59:46] ML tree search #18, logLikelihood: -309348.977439

[17:59:46 -920894.381581] Initial branch length optimization
[17:59:49 -789687.308602] Model parameter optimization (eps = 10.000000)
[18:00:16 -783617.379489] AUTODETECT spr round 1 (radius: 5)
[18:02:00 -573650.980974] AUTODETECT spr round 2 (radius: 10)
[18:03:58 -426283.432970] AUTODETECT spr round 3 (radius: 15)
[18:06:02 -364273.702303] AUTODETECT spr round 4 (radius: 20)
[18:08:25 -349300.247718] AUTODETECT spr round 5 (radius: 25)
[18:11:19 -347992.920549] SPR radius for FAST iterations: 25 (autodetect)
[18:11:19 -347992.920549] Model parameter optimization (eps = 3.000000)
[18:11:39 -347365.588570] FAST spr round 1 (radius: 25)
[18:14:06 -310919.301003] FAST spr round 2 (radius: 25)
[18:16:10 -309575.488947] FAST spr round 3 (radius: 25)
[18:18:04 -309463.052286] FAST spr round 4 (radius: 25)
[18:19:42 -309448.386764] FAST spr round 5 (radius: 25)
[18:21:14 -309443.247633] FAST spr round 6 (radius: 25)
[18:22:44 -309439.291298] FAST spr round 7 (radius: 25)
[18:24:12 -309439.290798] Model parameter optimization (eps = 1.000000)
[18:24:24 -309430.679835] SLOW spr round 1 (radius: 5)
[18:26:25 -309335.678343] SLOW spr round 2 (radius: 5)
[18:28:18 -309323.496957] SLOW spr round 3 (radius: 5)
[18:30:08 -309323.409571] SLOW spr round 4 (radius: 10)
[18:32:10 -309323.207685] SLOW spr round 5 (radius: 5)
[18:34:22 -309323.206184] SLOW spr round 6 (radius: 10)
[18:36:39 -309323.206029] SLOW spr round 7 (radius: 15)
[18:40:07 -309323.205993] SLOW spr round 8 (radius: 20)
[18:46:11 -309323.205983] SLOW spr round 9 (radius: 25)
[18:53:48 -309323.205980] Model parameter optimization (eps = 0.100000)

[18:53:55] ML tree search #19, logLikelihood: -309322.894017

[18:53:56 -924765.510254] Initial branch length optimization
[18:53:58 -790099.217064] Model parameter optimization (eps = 10.000000)
[18:54:28 -783814.756164] AUTODETECT spr round 1 (radius: 5)
[18:56:15 -578952.517419] AUTODETECT spr round 2 (radius: 10)
[18:58:10 -434412.898102] AUTODETECT spr round 3 (radius: 15)
[19:00:15 -369096.622070] AUTODETECT spr round 4 (radius: 20)
[19:03:02 -352077.206073] AUTODETECT spr round 5 (radius: 25)
[19:06:04 -346166.597962] SPR radius for FAST iterations: 25 (autodetect)
[19:06:04 -346166.597962] Model parameter optimization (eps = 3.000000)
[19:06:36 -345287.483851] FAST spr round 1 (radius: 25)
[19:09:05 -311075.493095] FAST spr round 2 (radius: 25)
[19:11:03 -309575.886578] FAST spr round 3 (radius: 25)
[19:12:51 -309474.529630] FAST spr round 4 (radius: 25)
[19:14:32 -309445.451916] FAST spr round 5 (radius: 25)
[19:16:05 -309438.861682] FAST spr round 6 (radius: 25)
[19:17:36 -309436.597569] FAST spr round 7 (radius: 25)
[19:19:05 -309436.596866] Model parameter optimization (eps = 1.000000)
[19:19:17 -309425.957104] SLOW spr round 1 (radius: 5)
[19:21:16 -309342.775153] SLOW spr round 2 (radius: 5)
[19:23:09 -309337.115837] SLOW spr round 3 (radius: 5)
[19:24:59 -309337.115355] SLOW spr round 4 (radius: 10)
[19:27:01 -309337.115307] SLOW spr round 5 (radius: 15)
[19:30:29 -309337.115291] SLOW spr round 6 (radius: 20)
[19:36:10 -309337.115284] SLOW spr round 7 (radius: 25)
[19:43:39 -309337.115281] Model parameter optimization (eps = 0.100000)

[19:43:49] ML tree search #20, logLikelihood: -309336.681534


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.216597,0.786862) (0.210849,0.973489) (0.382637,0.829763) (0.189917,1.615500) 
   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: -309322.894017

AIC score: 622595.788033 / AICc score: 8427795.788033 / BIC score: 631071.637084
Free parameters (model + branch lengths): 1975

WARNING: Number of free parameters (K=1975) is larger than alignment size (n=540).
         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/Q63ZE4/3_mltree/Q63ZE4.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/3_mltree/Q63ZE4.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/3_mltree/Q63ZE4.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_300621/phylogeny-snakemake/results/Q63ZE4/3_mltree/Q63ZE4.raxml.log

Analysis started: 24-Jul-2021 21:29:35 / finished: 25-Jul-2021 17:13:25

Elapsed time: 71030.144 seconds