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 23-Jun-2021 00:20:11 as follows:

raxml-ng --msa /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/2_msa/P07202_trimmed_msa.fasta --data-type AA --model LG4X --prefix /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202 --seed 2 --threads 8 --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 (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/2_msa/P07202_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 627 sites

WARNING: Sequences tr_B4Q8U8_B4Q8U8_DROSI_7240 and tr_B4I5H5_B4I5H5_DROSE_7238 are exactly identical!
WARNING: Sequences tr_F1NN41_F1NN41_CHICK_9031 and tr_G1NMG8_G1NMG8_MELGA_9103 are exactly identical!
WARNING: Sequences tr_F1NN41_F1NN41_CHICK_9031 and tr_A0A226NDW2_A0A226NDW2_CALSU_9009 are exactly identical!
WARNING: Sequences tr_F1NN41_F1NN41_CHICK_9031 and tr_A0A226NW71_A0A226NW71_COLVI_9014 are exactly identical!
WARNING: Sequences tr_Q29A85_Q29A85_DROPS_46245 and tr_B4G2M3_B4G2M3_DROPE_7234 are exactly identical!
WARNING: Sequences tr_K7D7S6_K7D7S6_PANTR_9598 and sp_Q92626_PXDN_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_K7D7S6_K7D7S6_PANTR_9598 and tr_A0A2R9CID3_A0A2R9CID3_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A158NFQ1_A0A158NFQ1_ATTCE_12957 and tr_A0A195BDL5_A0A195BDL5_9HYME_520822 are exactly identical!
WARNING: Sequences tr_A0A158Q1M0_A0A158Q1M0_BRUMA_6279 and tr_A0A0R3QNF6_A0A0R3QNF6_9BILA_42155 are exactly identical!
WARNING: Sequences tr_F7H275_F7H275_MACMU_9544 and tr_A0A2K6D1Z9_A0A2K6D1Z9_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A287AZ10_A0A287AZ10_PIG_9823 and sp_P09933_PERT_PIG_9823 are exactly identical!
WARNING: Sequences tr_A0A0D9R3L2_A0A0D9R3L2_CHLSB_60711 and tr_A0A2K5L809_A0A2K5L809_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A0D9R3L2_A0A0D9R3L2_CHLSB_60711 and tr_A0A2K5Y397_A0A2K5Y397_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A0V1CAW2_A0A0V1CAW2_TRIBR_45882 and tr_A0A0V0W403_A0A0V0W403_9BILA_92179 are exactly identical!
WARNING: Sequences tr_A0A0V1CAW2_A0A0V1CAW2_TRIBR_45882 and tr_A0A0V1KP06_A0A0V1KP06_9BILA_6335 are exactly identical!
WARNING: Sequences tr_A0A0V1CTB7_A0A0V1CTB7_TRIBR_45882 and tr_A0A0V0UHI9_A0A0V0UHI9_9BILA_144512 are exactly identical!
WARNING: Sequences tr_A0A0V1N1I9_A0A0V1N1I9_9BILA_268474 and tr_A0A0V1HU92_A0A0V1HU92_9BILA_268475 are exactly identical!
WARNING: Sequences tr_A0A0V1N9Q9_A0A0V1N9Q9_9BILA_268474 and tr_A0A0V1I8M9_A0A0V1I8M9_9BILA_268475 are exactly identical!
WARNING: Sequences tr_A0A1S3IIM0_A0A1S3IIM0_LINUN_7574 and tr_A0A1S3IIZ2_A0A1S3IIZ2_LINUN_7574 are exactly identical!
WARNING: Sequences tr_A0A1I7T302_A0A1I7T302_9PELO_1561998 and tr_A0A1I7T303_A0A1I7T303_9PELO_1561998 are exactly identical!
WARNING: Sequences tr_A0A3Q0CZY8_A0A3Q0CZY8_MESAU_10036 and sp_Q8R481_PERL_MESAU_10036 are exactly identical!
WARNING: Duplicate sequences found: 21

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.reduced.phy

Alignment comprises 1 partitions and 627 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 627 / 627
Gaps: 6.03 %
Invariant sites: 0.16 %


NOTE: Binary MSA file created: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.rba

Parallelization scheme autoconfig: 2 worker(s) x 4 thread(s)

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

[00:00:00] Generating 20 random starting tree(s) with 1001 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 157 / 12560
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1108521.729516] Initial branch length optimization
[00:00:06 -934654.114250] Model parameter optimization (eps = 10.000000)
[00:00:50 -932574.562328] AUTODETECT spr round 1 (radius: 5)
[00:04:08 -691214.459607] AUTODETECT spr round 2 (radius: 10)
[00:07:30 -481186.118093] AUTODETECT spr round 3 (radius: 15)
[00:11:13 -403608.622765] AUTODETECT spr round 4 (radius: 20)
[00:15:29 -377046.335540] AUTODETECT spr round 5 (radius: 25)
[00:20:12 -373675.878279] SPR radius for FAST iterations: 25 (autodetect)
[00:20:12 -373675.878279] Model parameter optimization (eps = 3.000000)
[00:20:23 -373668.307185] FAST spr round 1 (radius: 25)
[00:24:22 -334927.480092] FAST spr round 2 (radius: 25)
[00:27:22 -333420.596870] FAST spr round 3 (radius: 25)
[00:29:56 -333361.459004] FAST spr round 4 (radius: 25)
[00:32:14 -333349.658416] FAST spr round 5 (radius: 25)
[00:34:31 -333348.109750] FAST spr round 6 (radius: 25)
[00:36:52 -333342.383608] FAST spr round 7 (radius: 25)
[00:39:00 -333342.383602] Model parameter optimization (eps = 1.000000)
[00:39:27 -333080.944296] SLOW spr round 1 (radius: 5)
[00:42:29 -332978.082022] SLOW spr round 2 (radius: 5)
[00:45:21 -332968.165067] SLOW spr round 3 (radius: 5)
[00:48:05 -332968.165062] SLOW spr round 4 (radius: 10)
[00:50:49 -332968.165059] SLOW spr round 5 (radius: 15)
[00:55:54 -332968.165057] SLOW spr round 6 (radius: 20)
[01:03:49 -332968.165054] SLOW spr round 7 (radius: 25)
[01:14:41 -332968.165051] Model parameter optimization (eps = 0.100000)

[01:14:51] [worker #0] ML tree search #1, logLikelihood: -332967.603995

[01:14:51 -1114023.789733] Initial branch length optimization
[01:14:56 -937528.465102] Model parameter optimization (eps = 10.000000)
[01:15:44 -935411.677784] AUTODETECT spr round 1 (radius: 5)
[01:18:48 -692472.962280] AUTODETECT spr round 2 (radius: 10)
[01:22:02 -505771.818875] AUTODETECT spr round 3 (radius: 15)
[01:25:47 -404877.937949] AUTODETECT spr round 4 (radius: 20)
[01:28:45] [worker #1] ML tree search #2, logLikelihood: -332961.147504
[01:30:17 -380671.427238] AUTODETECT spr round 5 (radius: 25)
[01:35:04 -378281.514392] SPR radius for FAST iterations: 25 (autodetect)
[01:35:04 -378281.514392] Model parameter optimization (eps = 3.000000)
[01:35:31 -378024.022950] FAST spr round 1 (radius: 25)
[01:40:06 -335055.051951] FAST spr round 2 (radius: 25)
[01:43:05 -333120.281282] FAST spr round 3 (radius: 25)
[01:45:36 -333068.641215] FAST spr round 4 (radius: 25)
[01:47:53 -333054.478245] FAST spr round 5 (radius: 25)
[01:50:06 -333052.075305] FAST spr round 6 (radius: 25)
[01:52:15 -333052.075201] Model parameter optimization (eps = 1.000000)
[01:52:22 -333051.147111] SLOW spr round 1 (radius: 5)
[01:55:27 -332975.827052] SLOW spr round 2 (radius: 5)
[01:58:17 -332975.312842] SLOW spr round 3 (radius: 5)
[02:01:03 -332975.312693] SLOW spr round 4 (radius: 10)
[02:03:54 -332971.378567] SLOW spr round 5 (radius: 5)
[02:07:20 -332970.046093] SLOW spr round 6 (radius: 5)
[02:10:19 -332970.045985] SLOW spr round 7 (radius: 10)
[02:13:13 -332970.045984] SLOW spr round 8 (radius: 15)
[02:18:05 -332970.045983] SLOW spr round 9 (radius: 20)
[02:25:31 -332970.045983] SLOW spr round 10 (radius: 25)
[02:35:24 -332970.045983] Model parameter optimization (eps = 0.100000)

[02:35:40] [worker #0] ML tree search #3, logLikelihood: -332967.536814

[02:35:40 -1108714.086145] Initial branch length optimization
[02:35:46] [worker #1] ML tree search #4, logLikelihood: -332976.781720
[02:35:47 -935452.369533] Model parameter optimization (eps = 10.000000)
[02:36:34 -933284.382169] AUTODETECT spr round 1 (radius: 5)
[02:39:38 -695496.287846] AUTODETECT spr round 2 (radius: 10)
[02:42:52 -511958.567641] AUTODETECT spr round 3 (radius: 15)
[02:46:35 -423606.494474] AUTODETECT spr round 4 (radius: 20)
[02:51:23 -393937.136442] AUTODETECT spr round 5 (radius: 25)
[02:57:36 -389802.223135] SPR radius for FAST iterations: 25 (autodetect)
[02:57:36 -389802.223135] Model parameter optimization (eps = 3.000000)
[02:58:04 -389484.212199] FAST spr round 1 (radius: 25)
[03:02:31 -335197.098795] FAST spr round 2 (radius: 25)
[03:05:34 -333178.990496] FAST spr round 3 (radius: 25)
[03:08:16 -333093.326327] FAST spr round 4 (radius: 25)
[03:10:33 -333083.003452] FAST spr round 5 (radius: 25)
[03:12:46 -333073.342152] FAST spr round 6 (radius: 25)
[03:14:56 -333073.342130] Model parameter optimization (eps = 1.000000)
[03:15:15 -333068.572910] SLOW spr round 1 (radius: 5)
[03:18:23 -332983.480093] SLOW spr round 2 (radius: 5)
[03:21:13 -332976.167757] SLOW spr round 3 (radius: 5)
[03:23:56 -332974.709270] SLOW spr round 4 (radius: 5)
[03:26:33 -332974.709238] SLOW spr round 5 (radius: 10)
[03:29:14 -332974.709215] SLOW spr round 6 (radius: 15)
[03:34:19 -332974.709193] SLOW spr round 7 (radius: 20)
[03:41:56 -332974.709170] SLOW spr round 8 (radius: 25)
[03:52:26 -332974.709147] Model parameter optimization (eps = 0.100000)

[03:52:38] [worker #0] ML tree search #5, logLikelihood: -332974.602520

[03:52:38 -1112261.225990] Initial branch length optimization
[03:52:43 -936715.659997] Model parameter optimization (eps = 10.000000)
[03:53:28 -934644.065881] AUTODETECT spr round 1 (radius: 5)
[03:56:31 -696292.180680] AUTODETECT spr round 2 (radius: 10)
[03:59:48 -511504.084803] AUTODETECT spr round 3 (radius: 15)
[04:02:14] [worker #1] ML tree search #6, logLikelihood: -332962.261928
[04:03:30 -435235.405437] AUTODETECT spr round 4 (radius: 20)
[04:08:26 -403108.736353] AUTODETECT spr round 5 (radius: 25)
[04:13:19 -387749.736743] SPR radius for FAST iterations: 25 (autodetect)
[04:13:19 -387749.736743] Model parameter optimization (eps = 3.000000)
[04:13:53 -387446.402004] FAST spr round 1 (radius: 25)
[04:17:58 -335755.644170] FAST spr round 2 (radius: 25)
[04:20:57 -333261.316439] FAST spr round 3 (radius: 25)
[04:23:33 -333117.292271] FAST spr round 4 (radius: 25)
[04:25:56 -333044.783130] FAST spr round 5 (radius: 25)
[04:28:07 -333041.622699] FAST spr round 6 (radius: 25)
[04:30:13 -333041.622679] Model parameter optimization (eps = 1.000000)
[04:30:28 -333037.753687] SLOW spr round 1 (radius: 5)
[04:33:30 -332961.527054] SLOW spr round 2 (radius: 5)
[04:36:18 -332959.676206] SLOW spr round 3 (radius: 5)
[04:38:59 -332959.676061] SLOW spr round 4 (radius: 10)
[04:41:46 -332959.676061] SLOW spr round 5 (radius: 15)
[04:46:44 -332959.676061] SLOW spr round 6 (radius: 20)
[04:54:30 -332959.676061] SLOW spr round 7 (radius: 25)
[05:05:02 -332959.676061] Model parameter optimization (eps = 0.100000)

[05:05:15] [worker #0] ML tree search #7, logLikelihood: -332959.543662

[05:05:16 -1108538.270752] Initial branch length optimization
[05:05:21 -932533.488515] Model parameter optimization (eps = 10.000000)
[05:06:03 -930548.009830] AUTODETECT spr round 1 (radius: 5)
[05:09:06 -705052.605231] AUTODETECT spr round 2 (radius: 10)
[05:12:26 -529394.212115] AUTODETECT spr round 3 (radius: 15)
[05:16:21 -415832.450820] AUTODETECT spr round 4 (radius: 20)
[05:18:47] [worker #1] ML tree search #8, logLikelihood: -332953.733005
[05:21:31 -387422.584533] AUTODETECT spr round 5 (radius: 25)
[05:28:01 -385774.221070] SPR radius for FAST iterations: 25 (autodetect)
[05:28:01 -385774.221070] Model parameter optimization (eps = 3.000000)
[05:28:33 -385480.894107] FAST spr round 1 (radius: 25)
[05:33:06 -335010.358148] FAST spr round 2 (radius: 25)
[05:36:09 -333211.993206] FAST spr round 3 (radius: 25)
[05:38:52 -333079.852666] FAST spr round 4 (radius: 25)
[05:41:04 -333078.551545] FAST spr round 5 (radius: 25)
[05:43:14 -333078.551545] Model parameter optimization (eps = 1.000000)
[05:43:28 -333074.650162] SLOW spr round 1 (radius: 5)
[05:46:30 -332995.619105] SLOW spr round 2 (radius: 5)
[05:49:20 -332994.516076] SLOW spr round 3 (radius: 5)
[05:52:03 -332994.516056] SLOW spr round 4 (radius: 10)
[05:54:54 -332986.337913] SLOW spr round 5 (radius: 5)
[05:58:23 -332971.039519] SLOW spr round 6 (radius: 5)
[06:01:30 -332971.039101] SLOW spr round 7 (radius: 10)
[06:04:27 -332971.039098] SLOW spr round 8 (radius: 15)
[06:09:40 -332971.039098] SLOW spr round 9 (radius: 20)
[06:17:40 -332971.039098] SLOW spr round 10 (radius: 25)
[06:27:32] [worker #1] ML tree search #10, logLikelihood: -332963.126684
[06:28:23 -332971.039098] Model parameter optimization (eps = 0.100000)

[06:28:31] [worker #0] ML tree search #9, logLikelihood: -332971.031404

[06:28:31 -1107380.673647] Initial branch length optimization
[06:28:37 -929548.775561] Model parameter optimization (eps = 10.000000)
[06:29:21 -927586.569080] AUTODETECT spr round 1 (radius: 5)
[06:32:33 -691979.961084] AUTODETECT spr round 2 (radius: 10)
[06:35:58 -498051.449324] AUTODETECT spr round 3 (radius: 15)
[06:39:45 -414051.326367] AUTODETECT spr round 4 (radius: 20)
[06:44:26 -378046.643540] AUTODETECT spr round 5 (radius: 25)
[06:49:48 -374593.588675] SPR radius for FAST iterations: 25 (autodetect)
[06:49:48 -374593.588675] Model parameter optimization (eps = 3.000000)
[06:50:24 -374334.694491] FAST spr round 1 (radius: 25)
[06:54:37 -334580.091743] FAST spr round 2 (radius: 25)
[06:57:28 -333222.307550] FAST spr round 3 (radius: 25)
[07:00:02 -333128.044791] FAST spr round 4 (radius: 25)
[07:02:22 -333088.715942] FAST spr round 5 (radius: 25)
[07:04:35 -333081.141865] FAST spr round 6 (radius: 25)
[07:06:46 -333081.141774] Model parameter optimization (eps = 1.000000)
[07:07:09 -333074.662833] SLOW spr round 1 (radius: 5)
[07:10:12 -333007.342446] SLOW spr round 2 (radius: 5)
[07:13:06 -333002.036605] SLOW spr round 3 (radius: 5)
[07:15:53 -333001.641376] SLOW spr round 4 (radius: 5)
[07:18:36 -333001.641342] SLOW spr round 5 (radius: 10)
[07:21:20 -333001.641338] SLOW spr round 6 (radius: 15)
[07:26:25 -333001.641335] SLOW spr round 7 (radius: 20)
[07:34:05 -333001.641332] SLOW spr round 8 (radius: 25)
[07:44:51 -333001.641329] Model parameter optimization (eps = 0.100000)

[07:45:09] [worker #0] ML tree search #11, logLikelihood: -332999.875124

[07:45:09 -1110945.023094] Initial branch length optimization
[07:45:15 -936693.567691] Model parameter optimization (eps = 10.000000)
[07:46:00 -934546.716752] AUTODETECT spr round 1 (radius: 5)
[07:48:21] [worker #1] ML tree search #12, logLikelihood: -332964.274837
[07:49:07 -701266.257024] AUTODETECT spr round 2 (radius: 10)
[07:52:28 -510002.136172] AUTODETECT spr round 3 (radius: 15)
[07:56:08 -432410.596921] AUTODETECT spr round 4 (radius: 20)
[08:00:31 -400229.836602] AUTODETECT spr round 5 (radius: 25)
[08:05:36 -382373.366497] SPR radius for FAST iterations: 25 (autodetect)
[08:05:36 -382373.366497] Model parameter optimization (eps = 3.000000)
[08:06:09 -382198.273721] FAST spr round 1 (radius: 25)
[08:10:16 -335434.866021] FAST spr round 2 (radius: 25)
[08:13:05 -333190.574177] FAST spr round 3 (radius: 25)
[08:15:42 -333071.236563] FAST spr round 4 (radius: 25)
[08:17:58 -333069.317108] FAST spr round 5 (radius: 25)
[08:20:09 -333069.317108] Model parameter optimization (eps = 1.000000)
[08:20:28 -333062.607542] SLOW spr round 1 (radius: 5)
[08:23:42 -332964.299296] SLOW spr round 2 (radius: 5)
[08:26:37 -332956.054612] SLOW spr round 3 (radius: 5)
[08:29:23 -332956.054568] SLOW spr round 4 (radius: 10)
[08:32:15 -332953.912028] SLOW spr round 5 (radius: 5)
[08:35:47 -332950.166430] SLOW spr round 6 (radius: 5)
[08:38:53 -332948.154315] SLOW spr round 7 (radius: 5)
[08:41:44 -332947.675155] SLOW spr round 8 (radius: 5)
[08:44:30 -332947.674739] SLOW spr round 9 (radius: 10)
[08:47:18 -332947.674727] SLOW spr round 10 (radius: 15)
[08:52:25 -332947.674727] SLOW spr round 11 (radius: 20)
[09:00:18 -332947.674727] SLOW spr round 12 (radius: 25)
[09:07:13] [worker #1] ML tree search #14, logLikelihood: -332959.420842
[09:10:54 -332947.674727] Model parameter optimization (eps = 0.100000)

[09:11:13] [worker #0] ML tree search #13, logLikelihood: -332942.139868

[09:11:14 -1103845.324017] Initial branch length optimization
[09:11:19 -932086.861398] Model parameter optimization (eps = 10.000000)
[09:12:03 -929991.990648] AUTODETECT spr round 1 (radius: 5)
[09:15:07 -688479.678243] AUTODETECT spr round 2 (radius: 10)
[09:18:28 -518419.326417] AUTODETECT spr round 3 (radius: 15)
[09:22:21 -420952.392929] AUTODETECT spr round 4 (radius: 20)
[09:27:27 -387845.346021] AUTODETECT spr round 5 (radius: 25)
[09:33:13 -384732.133627] SPR radius for FAST iterations: 25 (autodetect)
[09:33:13 -384732.133627] Model parameter optimization (eps = 3.000000)
[09:33:23 -384725.358540] FAST spr round 1 (radius: 25)
[09:37:23 -335611.479910] FAST spr round 2 (radius: 25)
[09:40:17 -333517.218508] FAST spr round 3 (radius: 25)
[09:42:45 -333393.749349] FAST spr round 4 (radius: 25)
[09:45:00 -333370.833784] FAST spr round 5 (radius: 25)
[09:47:12 -333369.519876] FAST spr round 6 (radius: 25)
[09:49:21 -333369.518902] Model parameter optimization (eps = 1.000000)
[09:49:49 -333174.744311] SLOW spr round 1 (radius: 5)
[09:52:54 -333032.370287] SLOW spr round 2 (radius: 5)
[09:55:43 -333021.965222] SLOW spr round 3 (radius: 5)
[09:58:25 -333020.724920] SLOW spr round 4 (radius: 5)
[10:01:07 -333015.855691] SLOW spr round 5 (radius: 5)
[10:03:47 -333012.280823] SLOW spr round 6 (radius: 5)
[10:06:25 -333012.280780] SLOW spr round 7 (radius: 10)
[10:09:13 -333011.640296] SLOW spr round 8 (radius: 5)
[10:12:37 -333010.054779] SLOW spr round 9 (radius: 5)
[10:15:37 -333009.526002] SLOW spr round 10 (radius: 5)
[10:18:25 -333009.525880] SLOW spr round 11 (radius: 10)
[10:21:17 -333003.431526] SLOW spr round 12 (radius: 5)
[10:24:40 -333001.955942] SLOW spr round 13 (radius: 5)
[10:27:06] [worker #1] ML tree search #16, logLikelihood: -332969.805131
[10:27:43 -332993.791911] SLOW spr round 14 (radius: 5)
[10:30:39 -332991.787002] SLOW spr round 15 (radius: 5)
[10:33:26 -332991.786759] SLOW spr round 16 (radius: 10)
[10:36:16 -332991.348511] SLOW spr round 17 (radius: 5)
[10:39:43 -332989.002717] SLOW spr round 18 (radius: 5)
[10:42:45 -332987.022795] SLOW spr round 19 (radius: 5)
[10:45:35 -332985.292556] SLOW spr round 20 (radius: 5)
[10:48:17 -332985.292430] SLOW spr round 21 (radius: 10)
[10:51:04 -332985.292408] SLOW spr round 22 (radius: 15)
[10:56:20 -332985.292386] SLOW spr round 23 (radius: 20)
[11:04:23 -332985.292364] SLOW spr round 24 (radius: 25)
[11:15:17 -332985.292341] Model parameter optimization (eps = 0.100000)

[11:15:27] [worker #0] ML tree search #15, logLikelihood: -332985.197771

[11:15:27 -1107116.056842] Initial branch length optimization
[11:15:34 -931713.019213] Model parameter optimization (eps = 10.000000)
[11:16:18 -929632.792030] AUTODETECT spr round 1 (radius: 5)
[11:19:21 -688924.687435] AUTODETECT spr round 2 (radius: 10)
[11:22:43 -498208.464575] AUTODETECT spr round 3 (radius: 15)
[11:26:26 -402278.717170] AUTODETECT spr round 4 (radius: 20)
[11:30:40 -383677.081720] AUTODETECT spr round 5 (radius: 25)
[11:36:13 -378609.356111] SPR radius for FAST iterations: 25 (autodetect)
[11:36:13 -378609.356111] Model parameter optimization (eps = 3.000000)
[11:36:23 -378603.121411] FAST spr round 1 (radius: 25)
[11:40:24 -334874.918321] FAST spr round 2 (radius: 25)
[11:43:09 -333316.081221] FAST spr round 3 (radius: 25)
[11:45:28] [worker #1] ML tree search #18, logLikelihood: -332948.624691
[11:45:33 -333264.472319] FAST spr round 4 (radius: 25)
[11:47:51 -333239.289389] FAST spr round 5 (radius: 25)
[11:50:02 -333239.289354] Model parameter optimization (eps = 1.000000)
[11:50:35 -333064.683698] SLOW spr round 1 (radius: 5)
[11:53:40 -332974.131448] SLOW spr round 2 (radius: 5)
[11:56:34 -332970.686407] SLOW spr round 3 (radius: 5)
[11:59:20 -332970.686253] SLOW spr round 4 (radius: 10)
[12:02:09 -332966.089256] SLOW spr round 5 (radius: 5)
[12:05:38 -332961.891836] SLOW spr round 6 (radius: 5)
[12:08:39 -332961.891733] SLOW spr round 7 (radius: 10)
[12:11:33 -332961.891717] SLOW spr round 8 (radius: 15)
[12:16:26 -332961.891702] SLOW spr round 9 (radius: 20)
[12:24:14 -332961.891686] SLOW spr round 10 (radius: 25)
[12:34:43 -332961.891671] Model parameter optimization (eps = 0.100000)

[12:34:48] [worker #0] ML tree search #17, logLikelihood: -332961.872481

[12:34:48 -1106398.991104] Initial branch length optimization
[12:34:53 -933428.304234] Model parameter optimization (eps = 10.000000)
[12:35:34 -931401.013748] AUTODETECT spr round 1 (radius: 5)
[12:38:34 -687737.396187] AUTODETECT spr round 2 (radius: 10)
[12:41:46 -498701.793800] AUTODETECT spr round 3 (radius: 15)
[12:45:30 -431307.644198] AUTODETECT spr round 4 (radius: 20)
[12:49:51 -413153.400796] AUTODETECT spr round 5 (radius: 25)
[12:55:19 -399386.727767] SPR radius for FAST iterations: 25 (autodetect)
[12:55:19 -399386.727767] Model parameter optimization (eps = 3.000000)
[12:55:56 -399119.135722] FAST spr round 1 (radius: 25)
[13:00:21 -335474.721570] FAST spr round 2 (radius: 25)
[13:03:16 -333214.464872] FAST spr round 3 (radius: 25)
[13:05:53 -333075.327602] FAST spr round 4 (radius: 25)
[13:08:07 -333064.454287] FAST spr round 5 (radius: 25)
[13:10:19 -333058.102993] FAST spr round 6 (radius: 25)
[13:12:26 -333058.102990] Model parameter optimization (eps = 1.000000)
[13:12:44 -333053.622630] SLOW spr round 1 (radius: 5)
[13:15:43 -332984.493654] SLOW spr round 2 (radius: 5)
[13:18:29 -332975.811889] SLOW spr round 3 (radius: 5)
[13:21:08 -332975.811882] SLOW spr round 4 (radius: 10)
[13:22:57] [worker #1] ML tree search #20, logLikelihood: -332967.116385
[13:23:53 -332975.238250] SLOW spr round 5 (radius: 5)
[13:27:13 -332975.238246] SLOW spr round 6 (radius: 10)
[13:30:19 -332975.238243] SLOW spr round 7 (radius: 15)
[13:34:51 -332975.238240] SLOW spr round 8 (radius: 20)
[13:43:03 -332975.238237] SLOW spr round 9 (radius: 25)
[13:53:51 -332975.238234] Model parameter optimization (eps = 0.100000)

[13:54:06] [worker #0] ML tree search #19, logLikelihood: -332974.790221


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.146192,0.288038) (0.258342,0.501681) (0.337604,0.937487) (0.257862,1.984728) 
   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: -332942.139868

AIC score: 669894.279737 / AICc score: 8713954.279737 / BIC score: 678798.377551
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=627).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.bestTree
All ML trees saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.mlTrees
Optimized model saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.bestModel

Execution log saved to: /cta/users/eakkoyun/WORKFOLDER/PROD/run_040621/phylogeny-snakemake/results/P07202/3_mltree/P07202.raxml.log

Analysis started: 23-Jun-2021 00:20:11 / finished: 23-Jun-2021 14:14:18

Elapsed time: 50046.980 seconds