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

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

RAxML-NG was called at 02-Jul-2021 05:49:02 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/2_msa/Q9P0N5_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5 --seed 2 --threads 1 --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), NONE/sequential

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/2_msa/Q9P0N5_trimmed_msa.fasta
[00:00:00] Loaded alignment with 304 taxa and 73 sites

WARNING: Sequences tr_B4QXZ1_B4QXZ1_DROSI_7240 and tr_Q8INQ3_Q8INQ3_DROME_7227 are exactly identical!
WARNING: Sequences tr_B4QXZ1_B4QXZ1_DROSI_7240 and tr_B4HL26_B4HL26_DROSE_7238 are exactly identical!
WARNING: Sequences tr_B4QXZ2_B4QXZ2_DROSI_7240 and tr_Q9VHN0_Q9VHN0_DROME_7227 are exactly identical!
WARNING: Sequences tr_B4QXZ2_B4QXZ2_DROSI_7240 and tr_B4HL27_B4HL27_DROSE_7238 are exactly identical!
WARNING: Sequences sp_Q9CQC4_TM216_MOUSE_10090 and sp_B6ID01_TM216_RAT_10116 are exactly identical!
WARNING: Sequences sp_Q9CQC4_TM216_MOUSE_10090 and tr_A0A1U8BMM6_A0A1U8BMM6_MESAU_10036 are exactly identical!
WARNING: Sequences tr_W5JM41_W5JM41_ANODA_43151 and tr_Q7PS73_Q7PS73_ANOGA_7165 are exactly identical!
WARNING: Sequences tr_M3YRV2_M3YRV2_MUSPF_9669 and tr_M3WGL0_M3WGL0_FELCA_9685 are exactly identical!
WARNING: Sequences tr_M3YRV2_M3YRV2_MUSPF_9669 and tr_A0A3Q0DM96_A0A3Q0DM96_TARSY_1868482 are exactly identical!
WARNING: Sequences tr_M3YRV2_M3YRV2_MUSPF_9669 and tr_A0A2U3ZQF5_A0A2U3ZQF5_ODORO_9708 are exactly identical!
WARNING: Sequences tr_M3YRV2_M3YRV2_MUSPF_9669 and tr_A0A2U3XFW7_A0A2U3XFW7_LEPWE_9713 are exactly identical!
WARNING: Sequences tr_M3YRV2_M3YRV2_MUSPF_9669 and tr_A0A2Y9JQT0_A0A2Y9JQT0_ENHLU_391180 are exactly identical!
WARNING: Sequences tr_B4JHZ9_B4JHZ9_DROGR_7222 and tr_B4LZG4_B4LZG4_DROVI_7244 are exactly identical!
WARNING: Sequences tr_B4JHZ9_B4JHZ9_DROGR_7222 and tr_B4K5C3_B4K5C3_DROMO_7230 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_H2RCE3_H2RCE3_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and sp_Q9P0N5_TM216_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_F7C005_F7C005_MACMU_9544 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_F7HCW2_F7HCW2_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_G7PPY1_G7PPY1_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_A0A096MZE7_A0A096MZE7_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_A0A0D9R270_A0A0D9R270_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_A0A2K5LVH9_A0A2K5LVH9_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_A0A2K6D2G1_A0A2K6D2G1_MACNE_9545 are exactly identical!
WARNING: Sequences tr_G1QQ30_G1QQ30_NOMLE_61853 and tr_A0A2K5XMH3_A0A2K5XMH3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G3RDS3_G3RDS3_GORGO_9595 and tr_H2NCB4_H2NCB4_PONAB_9601 are exactly identical!
WARNING: Sequences tr_B5DWH6_B5DWH6_DROPS_46245 and tr_B4GMZ5_B4GMZ5_DROPE_7234 are exactly identical!
WARNING: Sequences tr_Q294K4_Q294K4_DROPS_46245 and tr_B4GMZ4_B4GMZ4_DROPE_7234 are exactly identical!
WARNING: Sequences tr_H2Q2V6_H2Q2V6_PANTR_9598 and tr_A0A2R9AM91_A0A2R9AM91_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A088A385_A0A088A385_APIME_7460 and tr_A0A2A3EA86_A0A2A3EA86_APICC_94128 are exactly identical!
WARNING: Sequences tr_A0A158NL48_A0A158NL48_ATTCE_12957 and tr_F4WFW7_F4WFW7_ACREC_103372 are exactly identical!
WARNING: Sequences tr_A0A158NL48_A0A158NL48_ATTCE_12957 and tr_A0A151XBI1_A0A151XBI1_9HYME_64791 are exactly identical!
WARNING: Sequences tr_A0A158NL48_A0A158NL48_ATTCE_12957 and tr_A0A195BG05_A0A195BG05_9HYME_520822 are exactly identical!
WARNING: Sequences tr_I3NH65_I3NH65_ICTTR_43179 and tr_A0A384DFB5_A0A384DFB5_URSMA_29073 are exactly identical!
WARNING: Sequences tr_A0A0K0J662_A0A0K0J662_BRUMA_6279 and tr_A0A0N4T6K7_A0A0N4T6K7_BRUPA_6280 are exactly identical!
WARNING: Sequences tr_A0A0K0J662_A0A0K0J662_BRUMA_6279 and tr_A0A0R3QTV2_A0A0R3QTV2_9BILA_42155 are exactly identical!
WARNING: Sequences tr_A0A1D5QFL8_A0A1D5QFL8_MACMU_9544 and tr_G8F5N1_G8F5N1_MACFA_9541 are exactly identical!
WARNING: Sequences tr_A0A1D5QFL8_A0A1D5QFL8_MACMU_9544 and tr_A0A096MRI5_A0A096MRI5_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_A0A1D5QFL8_A0A1D5QFL8_MACMU_9544 and tr_A0A2K6E9F9_A0A2K6E9F9_MACNE_9545 are exactly identical!
WARNING: Sequences tr_K7G9B3_K7G9B3_PELSI_13735 and tr_A0A151NYD1_A0A151NYD1_ALLMI_8496 are exactly identical!
WARNING: Sequences tr_K7G9B3_K7G9B3_PELSI_13735 and tr_A0A3Q0GX02_A0A3Q0GX02_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_H0Z7Y6_H0Z7Y6_TAEGU_59729 and tr_A0A218UUM1_A0A218UUM1_9PASE_299123 are exactly identical!
WARNING: Sequences tr_A0A1B8XTW8_A0A1B8XTW8_XENTR_8364 and tr_F7CLR6_F7CLR6_XENTR_8364 are exactly identical!
WARNING: Sequences tr_A0A151NXA9_A0A151NXA9_ALLMI_8496 and tr_A0A1U8D6F3_A0A1U8D6F3_ALLSI_38654 are exactly identical!
WARNING: Sequences tr_A0A194RQF2_A0A194RQF2_PAPMA_76193 and tr_A0A194PRE9_A0A194PRE9_PAPXU_66420 are exactly identical!
WARNING: Sequences tr_A0A091VWI2_A0A091VWI2_NIPNI_128390 and tr_A0A087RAL8_A0A087RAL8_APTFO_9233 are exactly identical!
WARNING: Sequences tr_A0A2I0LHN2_A0A2I0LHN2_COLLI_8932 and tr_A0A1V4JPL8_A0A1V4JPL8_PATFA_372326 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V0WQ05_A0A0V0WQ05_9BILA_92179 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V0UWJ1_A0A0V0UWJ1_9BILA_181606 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V1KQ69_A0A0V1KQ69_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V0ZGH8_A0A0V0ZGH8_9BILA_990121 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V1P0J8_A0A0V1P0J8_9BILA_92180 are exactly identical!
WARNING: Sequences tr_A0A0V1CPL4_A0A0V1CPL4_TRIBR_45882 and tr_A0A0V0TPP3_A0A0V0TPP3_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A1S3IQM8_A0A1S3IQM8_LINUN_7574 and tr_A0A1S3IS64_A0A1S3IS64_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A1S3SWQ9_A0A1S3SWQ9_SALSA_8030 and tr_B9EMX2_B9EMX2_SALSA_8030 are exactly identical!
WARNING: Sequences tr_A0A226M5M1_A0A226M5M1_COLVI_9014 and tr_A0A226NV41_A0A226NV41_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2U4CM81_A0A2U4CM81_TURTR_9739 and tr_A0A2Y9MGH5_A0A2Y9MGH5_DELLE_9749 are exactly identical!
WARNING: Duplicate sequences found: 56

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.reduced.phy

Alignment comprises 1 partitions and 73 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 73 / 73
Gaps: 1.23 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.rba

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

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

[00:00:00] Generating 20 random starting tree(s) with 304 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 73 / 5840
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -43565.506549] Initial branch length optimization
[00:00:00 -34245.387220] Model parameter optimization (eps = 10.000000)
[00:00:10 -33989.350989] AUTODETECT spr round 1 (radius: 5)
[00:00:19 -24013.302158] AUTODETECT spr round 2 (radius: 10)
[00:00:32 -17172.358791] AUTODETECT spr round 3 (radius: 15)
[00:00:45 -15404.655475] AUTODETECT spr round 4 (radius: 20)
[00:01:02 -14848.120474] AUTODETECT spr round 5 (radius: 25)
[00:01:17 -14840.948987] SPR radius for FAST iterations: 25 (autodetect)
[00:01:17 -14840.948987] Model parameter optimization (eps = 3.000000)
[00:01:25 -14723.224842] FAST spr round 1 (radius: 25)
[00:01:37 -13537.585444] FAST spr round 2 (radius: 25)
[00:01:48 -13422.117753] FAST spr round 3 (radius: 25)
[00:01:56 -13407.365601] FAST spr round 4 (radius: 25)
[00:02:05 -13405.637907] FAST spr round 5 (radius: 25)
[00:02:13 -13404.778008] FAST spr round 6 (radius: 25)
[00:02:21 -13404.775032] Model parameter optimization (eps = 1.000000)
[00:02:25 -13402.421275] SLOW spr round 1 (radius: 5)
[00:02:38 -13400.408128] SLOW spr round 2 (radius: 5)
[00:02:51 -13400.243386] SLOW spr round 3 (radius: 5)
[00:03:03 -13399.380061] SLOW spr round 4 (radius: 5)
[00:03:15 -13399.380011] SLOW spr round 5 (radius: 10)
[00:03:27 -13398.148055] SLOW spr round 6 (radius: 5)
[00:03:44 -13398.147842] SLOW spr round 7 (radius: 10)
[00:03:58 -13398.147817] SLOW spr round 8 (radius: 15)
[00:04:17 -13398.147814] SLOW spr round 9 (radius: 20)
[00:04:45 -13398.147814] SLOW spr round 10 (radius: 25)
[00:05:09 -13398.147814] Model parameter optimization (eps = 0.100000)

[00:05:12] ML tree search #1, logLikelihood: -13396.744912

[00:05:12 -42942.109103] Initial branch length optimization
[00:05:12 -33962.187901] Model parameter optimization (eps = 10.000000)
[00:05:22 -33601.098349] AUTODETECT spr round 1 (radius: 5)
[00:05:32 -24492.763524] AUTODETECT spr round 2 (radius: 10)
[00:05:43 -19418.003168] AUTODETECT spr round 3 (radius: 15)
[00:05:57 -16082.997103] AUTODETECT spr round 4 (radius: 20)
[00:06:13 -15592.662794] AUTODETECT spr round 5 (radius: 25)
[00:06:30 -15520.156909] SPR radius for FAST iterations: 25 (autodetect)
[00:06:30 -15520.156909] Model parameter optimization (eps = 3.000000)
[00:06:40 -15465.810539] FAST spr round 1 (radius: 25)
[00:06:51 -13598.320104] FAST spr round 2 (radius: 25)
[00:07:02 -13426.005210] FAST spr round 3 (radius: 25)
[00:07:11 -13410.918864] FAST spr round 4 (radius: 25)
[00:07:19 -13409.588848] FAST spr round 5 (radius: 25)
[00:07:27 -13409.588443] Model parameter optimization (eps = 1.000000)
[00:07:31 -13407.459341] SLOW spr round 1 (radius: 5)
[00:07:44 -13405.509577] SLOW spr round 2 (radius: 5)
[00:07:56 -13403.919510] SLOW spr round 3 (radius: 5)
[00:08:08 -13403.919503] SLOW spr round 4 (radius: 10)
[00:08:20 -13402.165430] SLOW spr round 5 (radius: 5)
[00:08:37 -13401.773756] SLOW spr round 6 (radius: 5)
[00:08:50 -13401.773297] SLOW spr round 7 (radius: 10)
[00:09:03 -13401.773297] SLOW spr round 8 (radius: 15)
[00:09:22 -13400.799134] SLOW spr round 9 (radius: 5)
[00:09:40 -13399.972359] SLOW spr round 10 (radius: 5)
[00:09:54 -13399.972262] SLOW spr round 11 (radius: 10)
[00:10:07 -13399.972257] SLOW spr round 12 (radius: 15)
[00:10:26 -13399.972256] SLOW spr round 13 (radius: 20)
[00:10:51 -13399.972256] SLOW spr round 14 (radius: 25)
[00:11:14 -13399.972256] Model parameter optimization (eps = 0.100000)

[00:11:17] ML tree search #2, logLikelihood: -13398.491561

[00:11:17 -42903.900958] Initial branch length optimization
[00:11:18 -33725.114228] Model parameter optimization (eps = 10.000000)
[00:11:27 -33506.389775] AUTODETECT spr round 1 (radius: 5)
[00:11:36 -25338.587452] AUTODETECT spr round 2 (radius: 10)
[00:11:49 -19807.325930] AUTODETECT spr round 3 (radius: 15)
[00:12:05 -15499.142939] AUTODETECT spr round 4 (radius: 20)
[00:12:20 -15192.645572] AUTODETECT spr round 5 (radius: 25)
[00:12:40 -15001.842071] SPR radius for FAST iterations: 25 (autodetect)
[00:12:40 -15001.842071] Model parameter optimization (eps = 3.000000)
[00:12:50 -14877.953882] FAST spr round 1 (radius: 25)
[00:13:00 -13594.986042] FAST spr round 2 (radius: 25)
[00:13:10 -13417.066957] FAST spr round 3 (radius: 25)
[00:13:19 -13400.599521] FAST spr round 4 (radius: 25)
[00:13:27 -13400.599179] Model parameter optimization (eps = 1.000000)
[00:13:31 -13398.366675] SLOW spr round 1 (radius: 5)
[00:13:44 -13396.282874] SLOW spr round 2 (radius: 5)
[00:13:57 -13395.301776] SLOW spr round 3 (radius: 5)
[00:14:09 -13395.300566] SLOW spr round 4 (radius: 10)
[00:14:21 -13395.300507] SLOW spr round 5 (radius: 15)
[00:14:41 -13395.300502] SLOW spr round 6 (radius: 20)
[00:15:08 -13395.300502] SLOW spr round 7 (radius: 25)
[00:15:32 -13395.300502] Model parameter optimization (eps = 0.100000)

[00:15:36] ML tree search #3, logLikelihood: -13394.240834

[00:15:37 -43568.257702] Initial branch length optimization
[00:15:37 -34216.636847] Model parameter optimization (eps = 10.000000)
[00:15:48 -34059.937761] AUTODETECT spr round 1 (radius: 5)
[00:15:58 -25020.393725] AUTODETECT spr round 2 (radius: 10)
[00:16:09 -20369.613675] AUTODETECT spr round 3 (radius: 15)
[00:16:23 -15240.748273] AUTODETECT spr round 4 (radius: 20)
[00:16:40 -15180.832654] AUTODETECT spr round 5 (radius: 25)
[00:16:59 -15180.805510] SPR radius for FAST iterations: 20 (autodetect)
[00:16:59 -15180.805510] Model parameter optimization (eps = 3.000000)
[00:17:06 -15039.412021] FAST spr round 1 (radius: 20)
[00:17:16 -13560.161031] FAST spr round 2 (radius: 20)
[00:17:25 -13426.822677] FAST spr round 3 (radius: 20)
[00:17:34 -13414.601287] FAST spr round 4 (radius: 20)
[00:17:43 -13410.334161] FAST spr round 5 (radius: 20)
[00:17:50 -13410.333995] Model parameter optimization (eps = 1.000000)
[00:17:55 -13407.343270] SLOW spr round 1 (radius: 5)
[00:18:07 -13405.581342] SLOW spr round 2 (radius: 5)
[00:18:19 -13405.580497] SLOW spr round 3 (radius: 10)
[00:18:31 -13405.336949] SLOW spr round 4 (radius: 5)
[00:18:48 -13405.336942] SLOW spr round 5 (radius: 10)
[00:19:02 -13405.336942] SLOW spr round 6 (radius: 15)
[00:19:22 -13405.336941] SLOW spr round 7 (radius: 20)
[00:19:48 -13405.336941] SLOW spr round 8 (radius: 25)
[00:20:12 -13405.336941] Model parameter optimization (eps = 0.100000)

[00:20:13] ML tree search #4, logLikelihood: -13405.333672

[00:20:13 -42975.718145] Initial branch length optimization
[00:20:14 -33685.746125] Model parameter optimization (eps = 10.000000)
[00:20:30 -33402.221251] AUTODETECT spr round 1 (radius: 5)
[00:20:40 -24108.908668] AUTODETECT spr round 2 (radius: 10)
[00:20:52 -18537.520599] AUTODETECT spr round 3 (radius: 15)
[00:21:09 -15813.901464] AUTODETECT spr round 4 (radius: 20)
[00:21:28 -15550.629074] AUTODETECT spr round 5 (radius: 25)
[00:21:43 -15540.578193] SPR radius for FAST iterations: 25 (autodetect)
[00:21:43 -15540.578193] Model parameter optimization (eps = 3.000000)
[00:21:51 -15408.768000] FAST spr round 1 (radius: 25)
[00:22:03 -13609.594865] FAST spr round 2 (radius: 25)
[00:22:14 -13434.845418] FAST spr round 3 (radius: 25)
[00:22:24 -13406.472853] FAST spr round 4 (radius: 25)
[00:22:32 -13405.885422] FAST spr round 5 (radius: 25)
[00:22:39 -13405.883233] Model parameter optimization (eps = 1.000000)
[00:22:44 -13403.835361] SLOW spr round 1 (radius: 5)
[00:22:57 -13399.826912] SLOW spr round 2 (radius: 5)
[00:23:10 -13395.743536] SLOW spr round 3 (radius: 5)
[00:23:22 -13395.741648] SLOW spr round 4 (radius: 10)
[00:23:33 -13395.741646] SLOW spr round 5 (radius: 15)
[00:23:53 -13395.741646] SLOW spr round 6 (radius: 20)
[00:24:17 -13395.741646] SLOW spr round 7 (radius: 25)
[00:24:40 -13395.741646] Model parameter optimization (eps = 0.100000)

[00:24:41] ML tree search #5, logLikelihood: -13395.737613

[00:24:41 -43420.461657] Initial branch length optimization
[00:24:42 -33928.975123] Model parameter optimization (eps = 10.000000)
[00:24:50 -33712.626923] AUTODETECT spr round 1 (radius: 5)
[00:25:00 -24636.224604] AUTODETECT spr round 2 (radius: 10)
[00:25:11 -20240.484180] AUTODETECT spr round 3 (radius: 15)
[00:25:26 -17337.102967] AUTODETECT spr round 4 (radius: 20)
[00:25:43 -16489.299123] AUTODETECT spr round 5 (radius: 25)
[00:26:02 -16422.274225] SPR radius for FAST iterations: 25 (autodetect)
[00:26:02 -16422.274225] Model parameter optimization (eps = 3.000000)
[00:26:11 -16193.609840] FAST spr round 1 (radius: 25)
[00:26:23 -13607.523516] FAST spr round 2 (radius: 25)
[00:26:34 -13394.866980] FAST spr round 3 (radius: 25)
[00:26:42 -13383.477389] FAST spr round 4 (radius: 25)
[00:26:50 -13383.477341] Model parameter optimization (eps = 1.000000)
[00:26:54 -13379.167576] SLOW spr round 1 (radius: 5)
[00:27:08 -13375.059731] SLOW spr round 2 (radius: 5)
[00:27:21 -13372.263667] SLOW spr round 3 (radius: 5)
[00:27:33 -13372.263304] SLOW spr round 4 (radius: 10)
[00:27:45 -13372.263252] SLOW spr round 5 (radius: 15)
[00:28:08 -13372.263244] SLOW spr round 6 (radius: 20)
[00:28:35 -13372.263240] SLOW spr round 7 (radius: 25)
[00:29:00 -13372.263238] Model parameter optimization (eps = 0.100000)

[00:29:01] ML tree search #6, logLikelihood: -13372.195153

[00:29:01 -43020.748953] Initial branch length optimization
[00:29:02 -33950.463459] Model parameter optimization (eps = 10.000000)
[00:29:12 -33692.658824] AUTODETECT spr round 1 (radius: 5)
[00:29:22 -24327.866997] AUTODETECT spr round 2 (radius: 10)
[00:29:33 -18949.042650] AUTODETECT spr round 3 (radius: 15)
[00:29:47 -15205.811195] AUTODETECT spr round 4 (radius: 20)
[00:30:02 -15128.113171] AUTODETECT spr round 5 (radius: 25)
[00:30:15 -15119.456595] SPR radius for FAST iterations: 25 (autodetect)
[00:30:15 -15119.456595] Model parameter optimization (eps = 3.000000)
[00:30:27 -14983.605978] FAST spr round 1 (radius: 25)
[00:30:40 -13511.351547] FAST spr round 2 (radius: 25)
[00:30:50 -13419.946175] FAST spr round 3 (radius: 25)
[00:30:59 -13403.793495] FAST spr round 4 (radius: 25)
[00:31:07 -13402.606614] FAST spr round 5 (radius: 25)
[00:31:15 -13402.595133] Model parameter optimization (eps = 1.000000)
[00:31:18 -13401.308781] SLOW spr round 1 (radius: 5)
[00:31:31 -13400.602054] SLOW spr round 2 (radius: 5)
[00:31:43 -13400.601781] SLOW spr round 3 (radius: 10)
[00:31:55 -13400.601774] SLOW spr round 4 (radius: 15)
[00:32:14 -13400.601774] SLOW spr round 5 (radius: 20)
[00:32:38 -13400.601774] SLOW spr round 6 (radius: 25)
[00:33:03 -13400.601774] Model parameter optimization (eps = 0.100000)

[00:33:05] ML tree search #7, logLikelihood: -13400.600018

[00:33:05 -42701.478675] Initial branch length optimization
[00:33:05 -33858.142009] Model parameter optimization (eps = 10.000000)
[00:33:14 -33595.281867] AUTODETECT spr round 1 (radius: 5)
[00:33:24 -24776.429147] AUTODETECT spr round 2 (radius: 10)
[00:33:36 -18809.123546] AUTODETECT spr round 3 (radius: 15)
[00:33:52 -15336.201367] AUTODETECT spr round 4 (radius: 20)
[00:34:10 -14553.392732] AUTODETECT spr round 5 (radius: 25)
[00:34:27 -14538.598176] SPR radius for FAST iterations: 25 (autodetect)
[00:34:27 -14538.598176] Model parameter optimization (eps = 3.000000)
[00:34:33 -14477.119665] FAST spr round 1 (radius: 25)
[00:34:45 -13471.834233] FAST spr round 2 (radius: 25)
[00:34:55 -13416.154667] FAST spr round 3 (radius: 25)
[00:35:03 -13413.595094] FAST spr round 4 (radius: 25)
[00:35:11 -13413.594349] Model parameter optimization (eps = 1.000000)
[00:35:16 -13410.046555] SLOW spr round 1 (radius: 5)
[00:35:30 -13398.715583] SLOW spr round 2 (radius: 5)
[00:35:42 -13398.312206] SLOW spr round 3 (radius: 5)
[00:35:54 -13398.311705] SLOW spr round 4 (radius: 10)
[00:36:06 -13397.086009] SLOW spr round 5 (radius: 5)
[00:36:24 -13395.360262] SLOW spr round 6 (radius: 5)
[00:36:38 -13394.926890] SLOW spr round 7 (radius: 5)
[00:36:51 -13394.926637] SLOW spr round 8 (radius: 10)
[00:37:03 -13394.926634] SLOW spr round 9 (radius: 15)
[00:37:25 -13394.926634] SLOW spr round 10 (radius: 20)
[00:37:51 -13394.926634] SLOW spr round 11 (radius: 25)
[00:38:14 -13394.926634] Model parameter optimization (eps = 0.100000)

[00:38:17] ML tree search #8, logLikelihood: -13394.667887

[00:38:17 -42645.958977] Initial branch length optimization
[00:38:17 -33500.065303] Model parameter optimization (eps = 10.000000)
[00:38:32 -33273.537863] AUTODETECT spr round 1 (radius: 5)
[00:38:41 -23862.988465] AUTODETECT spr round 2 (radius: 10)
[00:38:53 -18923.188906] AUTODETECT spr round 3 (radius: 15)
[00:39:07 -17153.049977] AUTODETECT spr round 4 (radius: 20)
[00:39:24 -16472.160282] AUTODETECT spr round 5 (radius: 25)
[00:39:42 -16101.646046] SPR radius for FAST iterations: 25 (autodetect)
[00:39:42 -16101.646046] Model parameter optimization (eps = 3.000000)
[00:39:49 -15933.385833] FAST spr round 1 (radius: 25)
[00:40:01 -13669.344734] FAST spr round 2 (radius: 25)
[00:40:13 -13393.318421] FAST spr round 3 (radius: 25)
[00:40:22 -13378.033185] FAST spr round 4 (radius: 25)
[00:40:31 -13377.741633] FAST spr round 5 (radius: 25)
[00:40:38 -13377.741610] Model parameter optimization (eps = 1.000000)
[00:40:43 -13373.059415] SLOW spr round 1 (radius: 5)
[00:40:56 -13369.734473] SLOW spr round 2 (radius: 5)
[00:41:08 -13369.734199] SLOW spr round 3 (radius: 10)
[00:41:21 -13369.734175] SLOW spr round 4 (radius: 15)
[00:41:42 -13369.734171] SLOW spr round 5 (radius: 20)
[00:42:09 -13369.734170] SLOW spr round 6 (radius: 25)
[00:42:35 -13369.734170] Model parameter optimization (eps = 0.100000)

[00:42:37] ML tree search #9, logLikelihood: -13369.699182

[00:42:37 -43137.320769] Initial branch length optimization
[00:42:38 -33944.026230] Model parameter optimization (eps = 10.000000)
[00:42:47 -33712.893531] AUTODETECT spr round 1 (radius: 5)
[00:42:57 -24441.367165] AUTODETECT spr round 2 (radius: 10)
[00:43:09 -18918.839638] AUTODETECT spr round 3 (radius: 15)
[00:43:23 -15891.117037] AUTODETECT spr round 4 (radius: 20)
[00:43:40 -15483.728001] AUTODETECT spr round 5 (radius: 25)
[00:43:57 -15471.074269] SPR radius for FAST iterations: 25 (autodetect)
[00:43:57 -15471.074269] Model parameter optimization (eps = 3.000000)
[00:44:05 -15313.615103] FAST spr round 1 (radius: 25)
[00:44:17 -13555.657824] FAST spr round 2 (radius: 25)
[00:44:28 -13415.622837] FAST spr round 3 (radius: 25)
[00:44:36 -13401.116869] FAST spr round 4 (radius: 25)
[00:44:44 -13401.103627] Model parameter optimization (eps = 1.000000)
[00:44:48 -13399.773883] SLOW spr round 1 (radius: 5)
[00:45:02 -13396.772055] SLOW spr round 2 (radius: 5)
[00:45:14 -13396.706469] SLOW spr round 3 (radius: 10)
[00:45:27 -13396.706455] SLOW spr round 4 (radius: 15)
[00:45:47 -13396.706455] SLOW spr round 5 (radius: 20)
[00:46:13 -13396.706455] SLOW spr round 6 (radius: 25)
[00:46:38 -13396.706455] Model parameter optimization (eps = 0.100000)

[00:46:39] ML tree search #10, logLikelihood: -13396.686356

[00:46:39 -42734.225057] Initial branch length optimization
[00:46:39 -34010.066839] Model parameter optimization (eps = 10.000000)
[00:46:46 -33860.416483] AUTODETECT spr round 1 (radius: 5)
[00:46:56 -24076.803768] AUTODETECT spr round 2 (radius: 10)
[00:47:08 -18330.489648] AUTODETECT spr round 3 (radius: 15)
[00:47:21 -15747.711060] AUTODETECT spr round 4 (radius: 20)
[00:47:38 -15204.378000] AUTODETECT spr round 5 (radius: 25)
[00:47:56 -15187.037599] SPR radius for FAST iterations: 25 (autodetect)
[00:47:56 -15187.037599] Model parameter optimization (eps = 3.000000)
[00:48:03 -14961.567760] FAST spr round 1 (radius: 25)
[00:48:15 -13542.538972] FAST spr round 2 (radius: 25)
[00:48:25 -13412.738864] FAST spr round 3 (radius: 25)
[00:48:34 -13407.207694] FAST spr round 4 (radius: 25)
[00:48:42 -13403.944508] FAST spr round 5 (radius: 25)
[00:48:50 -13403.944045] Model parameter optimization (eps = 1.000000)
[00:48:53 -13400.881871] SLOW spr round 1 (radius: 5)
[00:49:06 -13399.451161] SLOW spr round 2 (radius: 5)
[00:49:19 -13399.449141] SLOW spr round 3 (radius: 10)
[00:49:31 -13399.120650] SLOW spr round 4 (radius: 5)
[00:49:48 -13399.120648] SLOW spr round 5 (radius: 10)
[00:50:01 -13399.120648] SLOW spr round 6 (radius: 15)
[00:50:21 -13399.120648] SLOW spr round 7 (radius: 20)
[00:50:46 -13399.120648] SLOW spr round 8 (radius: 25)
[00:51:10 -13399.120648] Model parameter optimization (eps = 0.100000)

[00:51:10] ML tree search #11, logLikelihood: -13399.118890

[00:51:10 -43234.485459] Initial branch length optimization
[00:51:11 -33610.025078] Model parameter optimization (eps = 10.000000)
[00:51:21 -33387.704326] AUTODETECT spr round 1 (radius: 5)
[00:51:30 -24320.068328] AUTODETECT spr round 2 (radius: 10)
[00:51:42 -18388.347290] AUTODETECT spr round 3 (radius: 15)
[00:51:57 -15497.968829] AUTODETECT spr round 4 (radius: 20)
[00:52:17 -15198.268728] AUTODETECT spr round 5 (radius: 25)
[00:52:40 -15110.862612] SPR radius for FAST iterations: 25 (autodetect)
[00:52:40 -15110.862612] Model parameter optimization (eps = 3.000000)
[00:52:45 -15059.788307] FAST spr round 1 (radius: 25)
[00:52:56 -13701.508043] FAST spr round 2 (radius: 25)
[00:53:06 -13480.975321] FAST spr round 3 (radius: 25)
[00:53:15 -13424.253780] FAST spr round 4 (radius: 25)
[00:53:23 -13424.246763] Model parameter optimization (eps = 1.000000)
[00:53:27 -13423.112443] SLOW spr round 1 (radius: 5)
[00:53:40 -13420.409925] SLOW spr round 2 (radius: 5)
[00:53:53 -13420.409290] SLOW spr round 3 (radius: 10)
[00:54:05 -13420.031800] SLOW spr round 4 (radius: 5)
[00:54:22 -13420.031773] SLOW spr round 5 (radius: 10)
[00:54:36 -13420.031767] SLOW spr round 6 (radius: 15)
[00:54:57 -13420.031765] SLOW spr round 7 (radius: 20)
[00:55:26 -13418.860450] SLOW spr round 8 (radius: 5)
[00:55:45 -13418.676507] SLOW spr round 9 (radius: 5)
[00:56:00 -13418.676484] SLOW spr round 10 (radius: 10)
[00:56:13 -13418.676484] SLOW spr round 11 (radius: 15)
[00:56:34 -13418.676484] SLOW spr round 12 (radius: 20)
[00:57:03 -13417.494326] SLOW spr round 13 (radius: 5)
[00:57:21 -13417.494249] SLOW spr round 14 (radius: 10)
[00:57:36 -13417.494245] SLOW spr round 15 (radius: 15)
[00:57:57 -13417.494245] SLOW spr round 16 (radius: 20)
[00:58:25 -13417.494245] SLOW spr round 17 (radius: 25)
[00:58:50 -13417.494245] Model parameter optimization (eps = 0.100000)

[00:58:51] ML tree search #12, logLikelihood: -13417.481559

[00:58:51 -42508.245908] Initial branch length optimization
[00:58:51 -33523.800425] Model parameter optimization (eps = 10.000000)
[00:58:57 -33429.737397] AUTODETECT spr round 1 (radius: 5)
[00:59:07 -24070.407209] AUTODETECT spr round 2 (radius: 10)
[00:59:19 -18431.189738] AUTODETECT spr round 3 (radius: 15)
[00:59:34 -15492.165098] AUTODETECT spr round 4 (radius: 20)
[00:59:54 -15009.380799] AUTODETECT spr round 5 (radius: 25)
[01:00:14 -15009.378109] SPR radius for FAST iterations: 20 (autodetect)
[01:00:14 -15009.378109] Model parameter optimization (eps = 3.000000)
[01:00:21 -14874.297372] FAST spr round 1 (radius: 20)
[01:00:34 -13587.304771] FAST spr round 2 (radius: 20)
[01:00:44 -13441.815930] FAST spr round 3 (radius: 20)
[01:00:52 -13420.753390] FAST spr round 4 (radius: 20)
[01:01:01 -13419.339178] FAST spr round 5 (radius: 20)
[01:01:08 -13419.336085] Model parameter optimization (eps = 1.000000)
[01:01:12 -13410.751144] SLOW spr round 1 (radius: 5)
[01:01:26 -13405.880403] SLOW spr round 2 (radius: 5)
[01:01:39 -13402.178758] SLOW spr round 3 (radius: 5)
[01:01:52 -13402.035340] SLOW spr round 4 (radius: 5)
[01:02:04 -13402.034408] SLOW spr round 5 (radius: 10)
[01:02:16 -13401.743132] SLOW spr round 6 (radius: 5)
[01:02:33 -13401.743035] SLOW spr round 7 (radius: 10)
[01:02:47 -13401.743028] SLOW spr round 8 (radius: 15)
[01:03:06 -13401.743028] SLOW spr round 9 (radius: 20)
[01:03:31 -13401.743028] SLOW spr round 10 (radius: 25)
[01:03:55 -13401.743028] Model parameter optimization (eps = 0.100000)

[01:03:58] ML tree search #13, logLikelihood: -13399.397792

[01:03:58 -42869.024615] Initial branch length optimization
[01:03:59 -33662.227711] Model parameter optimization (eps = 10.000000)
[01:04:05 -33527.636172] AUTODETECT spr round 1 (radius: 5)
[01:04:15 -24175.639584] AUTODETECT spr round 2 (radius: 10)
[01:04:28 -17601.224598] AUTODETECT spr round 3 (radius: 15)
[01:04:44 -15364.237799] AUTODETECT spr round 4 (radius: 20)
[01:05:02 -15052.362497] AUTODETECT spr round 5 (radius: 25)
[01:05:20 -15048.209925] SPR radius for FAST iterations: 25 (autodetect)
[01:05:20 -15048.209925] Model parameter optimization (eps = 3.000000)
[01:05:28 -14903.084683] FAST spr round 1 (radius: 25)
[01:05:40 -13529.289047] FAST spr round 2 (radius: 25)
[01:05:51 -13423.611235] FAST spr round 3 (radius: 25)
[01:06:00 -13406.338478] FAST spr round 4 (radius: 25)
[01:06:07 -13405.528398] FAST spr round 5 (radius: 25)
[01:06:15 -13405.528268] Model parameter optimization (eps = 1.000000)
[01:06:17 -13405.053976] SLOW spr round 1 (radius: 5)
[01:06:31 -13398.577892] SLOW spr round 2 (radius: 5)
[01:06:43 -13398.234954] SLOW spr round 3 (radius: 5)
[01:06:54 -13398.234918] SLOW spr round 4 (radius: 10)
[01:07:06 -13398.234915] SLOW spr round 5 (radius: 15)
[01:07:27 -13398.234915] SLOW spr round 6 (radius: 20)
[01:07:51 -13398.234915] SLOW spr round 7 (radius: 25)
[01:08:14 -13398.234915] Model parameter optimization (eps = 0.100000)

[01:08:16] ML tree search #14, logLikelihood: -13398.049221

[01:08:16 -43117.031948] Initial branch length optimization
[01:08:17 -34151.978566] Model parameter optimization (eps = 10.000000)
[01:08:33 -33788.875168] AUTODETECT spr round 1 (radius: 5)
[01:08:42 -25156.937154] AUTODETECT spr round 2 (radius: 10)
[01:08:54 -20006.702501] AUTODETECT spr round 3 (radius: 15)
[01:09:09 -17556.188260] AUTODETECT spr round 4 (radius: 20)
[01:09:26 -16006.048862] AUTODETECT spr round 5 (radius: 25)
[01:09:44 -15754.876247] SPR radius for FAST iterations: 25 (autodetect)
[01:09:44 -15754.876247] Model parameter optimization (eps = 3.000000)
[01:09:50 -15707.124353] FAST spr round 1 (radius: 25)
[01:10:03 -13564.074184] FAST spr round 2 (radius: 25)
[01:10:14 -13423.822755] FAST spr round 3 (radius: 25)
[01:10:24 -13405.557831] FAST spr round 4 (radius: 25)
[01:10:32 -13399.973438] FAST spr round 5 (radius: 25)
[01:10:40 -13399.148872] FAST spr round 6 (radius: 25)
[01:10:48 -13399.148822] Model parameter optimization (eps = 1.000000)
[01:10:51 -13397.841814] SLOW spr round 1 (radius: 5)
[01:11:04 -13396.982561] SLOW spr round 2 (radius: 5)
[01:11:16 -13396.982412] SLOW spr round 3 (radius: 10)
[01:11:28 -13396.597811] SLOW spr round 4 (radius: 5)
[01:11:44 -13396.597810] SLOW spr round 5 (radius: 10)
[01:11:57 -13396.597808] SLOW spr round 6 (radius: 15)
[01:12:16 -13395.661977] SLOW spr round 7 (radius: 5)
[01:12:33 -13395.661777] SLOW spr round 8 (radius: 10)
[01:12:47 -13395.661771] SLOW spr round 9 (radius: 15)
[01:13:05 -13395.661771] SLOW spr round 10 (radius: 20)
[01:13:29 -13395.661771] SLOW spr round 11 (radius: 25)
[01:13:54 -13395.661771] Model parameter optimization (eps = 0.100000)

[01:13:56] ML tree search #15, logLikelihood: -13395.651109

[01:13:56 -42826.736978] Initial branch length optimization
[01:13:57 -33808.524889] Model parameter optimization (eps = 10.000000)
[01:14:08 -33673.122743] AUTODETECT spr round 1 (radius: 5)
[01:14:17 -24444.902858] AUTODETECT spr round 2 (radius: 10)
[01:14:30 -18643.723886] AUTODETECT spr round 3 (radius: 15)
[01:14:46 -15934.549126] AUTODETECT spr round 4 (radius: 20)
[01:15:02 -15453.391762] AUTODETECT spr round 5 (radius: 25)
[01:15:20 -15452.025220] SPR radius for FAST iterations: 25 (autodetect)
[01:15:20 -15452.025220] Model parameter optimization (eps = 3.000000)
[01:15:26 -15341.875219] FAST spr round 1 (radius: 25)
[01:15:39 -13745.056714] FAST spr round 2 (radius: 25)
[01:15:50 -13488.046850] FAST spr round 3 (radius: 25)
[01:16:00 -13426.802194] FAST spr round 4 (radius: 25)
[01:16:09 -13420.325970] FAST spr round 5 (radius: 25)
[01:16:17 -13420.325800] Model parameter optimization (eps = 1.000000)
[01:16:21 -13417.409188] SLOW spr round 1 (radius: 5)
[01:16:34 -13411.699394] SLOW spr round 2 (radius: 5)
[01:16:47 -13411.697475] SLOW spr round 3 (radius: 10)
[01:16:58 -13411.697276] SLOW spr round 4 (radius: 15)
[01:17:18 -13411.697256] SLOW spr round 5 (radius: 20)
[01:17:43 -13411.697254] SLOW spr round 6 (radius: 25)
[01:18:08 -13411.697253] Model parameter optimization (eps = 0.100000)

[01:18:11] ML tree search #16, logLikelihood: -13411.436994

[01:18:12 -42622.395792] Initial branch length optimization
[01:18:12 -34094.534903] Model parameter optimization (eps = 10.000000)
[01:18:26 -33796.466477] AUTODETECT spr round 1 (radius: 5)
[01:18:36 -24566.083633] AUTODETECT spr round 2 (radius: 10)
[01:18:48 -19318.097346] AUTODETECT spr round 3 (radius: 15)
[01:19:02 -16105.389608] AUTODETECT spr round 4 (radius: 20)
[01:19:19 -15941.131192] AUTODETECT spr round 5 (radius: 25)
[01:19:37 -15922.408538] SPR radius for FAST iterations: 25 (autodetect)
[01:19:37 -15922.408538] Model parameter optimization (eps = 3.000000)
[01:19:45 -15746.770334] FAST spr round 1 (radius: 25)
[01:19:56 -13650.200031] FAST spr round 2 (radius: 25)
[01:20:05 -13408.289914] FAST spr round 3 (radius: 25)
[01:20:14 -13382.560724] FAST spr round 4 (radius: 25)
[01:20:22 -13381.509972] FAST spr round 5 (radius: 25)
[01:20:30 -13380.928779] FAST spr round 6 (radius: 25)
[01:20:37 -13380.928758] Model parameter optimization (eps = 1.000000)
[01:20:42 -13377.198220] SLOW spr round 1 (radius: 5)
[01:20:55 -13372.293090] SLOW spr round 2 (radius: 5)
[01:21:07 -13372.283322] SLOW spr round 3 (radius: 10)
[01:21:19 -13372.283240] SLOW spr round 4 (radius: 15)
[01:21:40 -13372.283229] SLOW spr round 5 (radius: 20)
[01:22:06 -13372.283228] SLOW spr round 6 (radius: 25)
[01:22:32 -13372.283228] Model parameter optimization (eps = 0.100000)

[01:22:35] ML tree search #17, logLikelihood: -13372.103156

[01:22:35 -43244.547124] Initial branch length optimization
[01:22:36 -34009.716385] Model parameter optimization (eps = 10.000000)
[01:22:46 -33749.249596] AUTODETECT spr round 1 (radius: 5)
[01:22:55 -24905.585937] AUTODETECT spr round 2 (radius: 10)
[01:23:07 -19595.040914] AUTODETECT spr round 3 (radius: 15)
[01:23:21 -15287.454464] AUTODETECT spr round 4 (radius: 20)
[01:23:37 -14851.528511] AUTODETECT spr round 5 (radius: 25)
[01:23:55 -14837.714187] SPR radius for FAST iterations: 25 (autodetect)
[01:23:55 -14837.714187] Model parameter optimization (eps = 3.000000)
[01:24:04 -14720.136989] FAST spr round 1 (radius: 25)
[01:24:14 -13526.144276] FAST spr round 2 (radius: 25)
[01:24:23 -13425.621199] FAST spr round 3 (radius: 25)
[01:24:32 -13415.476676] FAST spr round 4 (radius: 25)
[01:24:40 -13407.801373] FAST spr round 5 (radius: 25)
[01:24:48 -13407.801330] Model parameter optimization (eps = 1.000000)
[01:24:52 -13402.636000] SLOW spr round 1 (radius: 5)
[01:25:05 -13400.726601] SLOW spr round 2 (radius: 5)
[01:25:18 -13399.681808] SLOW spr round 3 (radius: 5)
[01:25:31 -13399.600438] SLOW spr round 4 (radius: 10)
[01:25:43 -13399.600294] SLOW spr round 5 (radius: 15)
[01:26:04 -13399.600241] SLOW spr round 6 (radius: 20)
[01:26:30 -13399.600162] SLOW spr round 7 (radius: 25)
[01:26:52 -13399.600045] Model parameter optimization (eps = 0.100000)

[01:26:54] ML tree search #18, logLikelihood: -13399.572595

[01:26:54 -43068.637249] Initial branch length optimization
[01:26:54 -34105.658410] Model parameter optimization (eps = 10.000000)
[01:27:10 -33685.993776] AUTODETECT spr round 1 (radius: 5)
[01:27:20 -25087.640927] AUTODETECT spr round 2 (radius: 10)
[01:27:32 -19818.343718] AUTODETECT spr round 3 (radius: 15)
[01:27:46 -17014.389358] AUTODETECT spr round 4 (radius: 20)
[01:28:00 -15624.524702] AUTODETECT spr round 5 (radius: 25)
[01:28:16 -15579.713005] SPR radius for FAST iterations: 25 (autodetect)
[01:28:16 -15579.713005] Model parameter optimization (eps = 3.000000)
[01:28:23 -15484.525994] FAST spr round 1 (radius: 25)
[01:28:35 -13535.626544] FAST spr round 2 (radius: 25)
[01:28:45 -13431.524116] FAST spr round 3 (radius: 25)
[01:28:54 -13404.481286] FAST spr round 4 (radius: 25)
[01:29:03 -13398.105176] FAST spr round 5 (radius: 25)
[01:29:11 -13398.104648] Model parameter optimization (eps = 1.000000)
[01:29:15 -13393.985676] SLOW spr round 1 (radius: 5)
[01:29:28 -13388.925061] SLOW spr round 2 (radius: 5)
[01:29:40 -13386.763670] SLOW spr round 3 (radius: 5)
[01:29:52 -13386.763382] SLOW spr round 4 (radius: 10)
[01:30:04 -13384.289230] SLOW spr round 5 (radius: 5)
[01:30:23 -13377.441934] SLOW spr round 6 (radius: 5)
[01:30:38 -13372.493453] SLOW spr round 7 (radius: 5)
[01:30:52 -13369.945536] SLOW spr round 8 (radius: 5)
[01:31:05 -13369.699357] SLOW spr round 9 (radius: 5)
[01:31:17 -13369.699181] SLOW spr round 10 (radius: 10)
[01:31:29 -13366.738562] SLOW spr round 11 (radius: 5)
[01:31:46 -13365.085139] SLOW spr round 12 (radius: 5)
[01:32:00 -13363.000242] SLOW spr round 13 (radius: 5)
[01:32:14 -13361.455986] SLOW spr round 14 (radius: 5)
[01:32:26 -13361.453116] SLOW spr round 15 (radius: 10)
[01:32:38 -13361.451553] SLOW spr round 16 (radius: 15)
[01:32:59 -13361.450773] SLOW spr round 17 (radius: 20)
[01:33:22 -13361.450430] SLOW spr round 18 (radius: 25)
[01:33:47 -13361.450290] Model parameter optimization (eps = 0.100000)

[01:33:50] ML tree search #19, logLikelihood: -13360.915744

[01:33:50 -42938.004158] Initial branch length optimization
[01:33:51 -33697.586723] Model parameter optimization (eps = 10.000000)
[01:34:04 -33348.665882] AUTODETECT spr round 1 (radius: 5)
[01:34:13 -23973.983364] AUTODETECT spr round 2 (radius: 10)
[01:34:25 -19484.586097] AUTODETECT spr round 3 (radius: 15)
[01:34:39 -16113.380607] AUTODETECT spr round 4 (radius: 20)
[01:34:53 -14871.563200] AUTODETECT spr round 5 (radius: 25)
[01:35:07 -14664.702637] SPR radius for FAST iterations: 25 (autodetect)
[01:35:07 -14664.702637] Model parameter optimization (eps = 3.000000)
[01:35:16 -14598.487118] FAST spr round 1 (radius: 25)
[01:35:28 -13521.168470] FAST spr round 2 (radius: 25)
[01:35:38 -13436.836364] FAST spr round 3 (radius: 25)
[01:35:47 -13418.066111] FAST spr round 4 (radius: 25)
[01:35:56 -13416.807406] FAST spr round 5 (radius: 25)
[01:36:03 -13416.806207] Model parameter optimization (eps = 1.000000)
[01:36:08 -13414.231067] SLOW spr round 1 (radius: 5)
[01:36:21 -13412.360664] SLOW spr round 2 (radius: 5)
[01:36:33 -13412.357965] SLOW spr round 3 (radius: 10)
[01:36:46 -13408.479309] SLOW spr round 4 (radius: 5)
[01:37:04 -13405.897939] SLOW spr round 5 (radius: 5)
[01:37:18 -13404.791473] SLOW spr round 6 (radius: 5)
[01:37:31 -13404.791436] SLOW spr round 7 (radius: 10)
[01:37:43 -13402.753833] SLOW spr round 8 (radius: 5)
[01:38:00 -13397.643343] SLOW spr round 9 (radius: 5)
[01:38:15 -13397.123726] SLOW spr round 10 (radius: 5)
[01:38:27 -13397.122992] SLOW spr round 11 (radius: 10)
[01:38:39 -13397.122978] SLOW spr round 12 (radius: 15)
[01:38:58 -13395.826731] SLOW spr round 13 (radius: 5)
[01:39:17 -13394.870291] SLOW spr round 14 (radius: 5)
[01:39:31 -13394.870219] SLOW spr round 15 (radius: 10)
[01:39:44 -13394.870219] SLOW spr round 16 (radius: 15)
[01:40:03 -13394.870219] SLOW spr round 17 (radius: 20)
[01:40:29 -13394.870219] SLOW spr round 18 (radius: 25)
[01:40:53 -13394.870219] Model parameter optimization (eps = 0.100000)

[01:40:57] ML tree search #20, logLikelihood: -13392.701881


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.306106,1.173613) (0.342104,1.305906) (0.256753,0.703894) (0.095037,0.139600) 
   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: -13360.915744

AIC score: 27943.831488 / AICc score: 775807.831488 / BIC score: 29343.302206
Free parameters (model + branch lengths): 611

WARNING: Number of free parameters (K=611) is larger than alignment size (n=73).
         This might lead to overfitting and compromise tree inference results!


WARNING: Best ML tree contains 85 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9P0N5/3_mltree/Q9P0N5.raxml.log

Analysis started: 02-Jul-2021 05:49:02 / finished: 02-Jul-2021 07:29:59

Elapsed time: 6057.323 seconds

Consumed energy: 509.740 Wh (= 3 km in an electric car, or 13 km with an e-scooter!)