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 01-Jul-2021 16:40:20 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/2_msa/A6NHY2_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2 --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: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/2_msa/A6NHY2_trimmed_msa.fasta
[00:00:00] Loaded alignment with 1001 taxa and 825 sites

WARNING: Sequences tr_A0A2I3HLI6_A0A2I3HLI6_NOMLE_61853 and tr_A0A2I2YDH9_A0A2I2YDH9_GORGO_9595 are exactly identical!
WARNING: Sequences tr_A0A2I3HLI6_A0A2I3HLI6_NOMLE_61853 and tr_A0A2I3MIE6_A0A2I3MIE6_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_A0A2I3HLI6_A0A2I3HLI6_NOMLE_61853 and tr_A0A2K5LPM7_A0A2K5LPM7_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A2I3HLI6_A0A2I3HLI6_NOMLE_61853 and tr_A0A2K6DJR0_A0A2K6DJR0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_A0A2I3HLI6_A0A2I3HLI6_NOMLE_61853 and tr_A0A2K5YP31_A0A2K5YP31_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_G3S4C5_G3S4C5_GORGO_9595 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_H2R3U2_H2R3U2_PANTR_9598 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and sp_Q01484_ANK2_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_F7H4E0_F7H4E0_MACMU_9544 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2R8MG44_A0A2R8MG44_CALJA_9483 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_G7P649_G7P649_MACFA_9541 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A096N0E1_A0A096N0E1_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2K5MCB6_A0A2K5MCB6_CERAT_9531 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2K5YPQ5_A0A2K5YPQ5_MANLE_9568 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2R9BUB3_A0A2R9BUB3_PANPA_9597 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2U3WE70_A0A2U3WE70_ODORO_9708 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A2Y9K0E1_A0A2Y9K0E1_ENHLU_391180 are exactly identical!
WARNING: Sequences tr_G1S2U2_G1S2U2_NOMLE_61853 and tr_A0A384BYK5_A0A384BYK5_URSMA_29073 are exactly identical!
WARNING: Sequences tr_G1SZP4_G1SZP4_RABIT_9986 and tr_A0A337SR04_A0A337SR04_FELCA_9685 are exactly identical!
WARNING: Sequences tr_E2RR81_E2RR81_CANLF_9615 and tr_A0A2U3X075_A0A2U3X075_ODORO_9708 are exactly identical!
WARNING: Sequences tr_E2RR81_E2RR81_CANLF_9615 and tr_A0A2U3Y629_A0A2U3Y629_LEPWE_9713 are exactly identical!
WARNING: Sequences tr_A0A2I3TF47_A0A2I3TF47_PANTR_9598 and tr_A0A2R9CIP4_A0A2R9CIP4_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A2I3TN78_A0A2I3TN78_PANTR_9598 and tr_A0A2R9AU58_A0A2R9AU58_PANPA_9597 are exactly identical!
WARNING: Sequences tr_F7CR95_F7CR95_MONDO_13616 and tr_G3VYV3_G3VYV3_SARHA_9305 are exactly identical!
WARNING: Sequences tr_F7E5S7_F7E5S7_MACMU_9544 and tr_G7NY15_G7NY15_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7E5S7_F7E5S7_MACMU_9544 and tr_A0A0D9RCK6_A0A0D9RCK6_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_F7FYD9_F7FYD9_MACMU_9544 and tr_A0A2K6E325_A0A2K6E325_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7FYD9_F7FYD9_MACMU_9544 and tr_A0A2K5ZEM7_A0A2K5ZEM7_MANLE_9568 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_G7P687_G7P687_MACFA_9541 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_A0A096NYI5_A0A096NYI5_PAPAN_9555 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_A0A0D9S0M9_A0A0D9S0M9_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_A0A2K5MH73_A0A2K5MH73_CERAT_9531 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_A0A2K6D9V0_A0A2K6D9V0_MACNE_9545 are exactly identical!
WARNING: Sequences tr_F7H1K0_F7H1K0_MACMU_9544 and tr_A0A2K5YBY3_A0A2K5YBY3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_D2HEA0_D2HEA0_AILME_9646 and tr_A0A384BYR1_A0A384BYR1_URSMA_29073 are exactly identical!
WARNING: Sequences tr_A0A093JU25_A0A093JU25_STRCA_441894 and tr_A0A091G422_A0A091G422_9AVES_55661 are exactly identical!
WARNING: Sequences tr_A0A093JU25_A0A093JU25_STRCA_441894 and tr_A0A0A0ATJ5_A0A0A0ATJ5_CHAVO_50402 are exactly identical!
WARNING: Sequences tr_A0A151J9H4_A0A151J9H4_9HYME_471704 and tr_A0A195F701_A0A195F701_9HYME_34720 are exactly identical!
WARNING: Sequences tr_A0A226NG00_A0A226NG00_CALSU_9009 and tr_A0A226PMU1_A0A226PMU1_COLVI_9014 are exactly identical!
WARNING: Sequences tr_A0A2K5M793_A0A2K5M793_CERAT_9531 and tr_A0A2K5YVV3_A0A2K5YVV3_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2Y9F066_A0A2Y9F066_PHYCD_9755 and tr_A0A383ZBC3_A0A383ZBC3_BALAS_310752 are exactly identical!
WARNING: Duplicate sequences found: 41

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/A6NHY2/3_mltree/A6NHY2.raxml.reduced.phy

Alignment comprises 1 partitions and 825 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 825 / 825
Gaps: 29.01 %
Invariant sites: 0.00 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2.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 / 207 / 16560
[00:00:00] Data distribution: max. searches per worker: 10

Starting ML tree search with 20 distinct starting trees

[00:00:00 -1288991.617075] Initial branch length optimization
[00:00:07 -1076175.072084] Model parameter optimization (eps = 10.000000)
[00:01:01 -1073403.810443] AUTODETECT spr round 1 (radius: 5)
[00:04:28 -758950.981002] AUTODETECT spr round 2 (radius: 10)
[00:08:05 -630643.957153] AUTODETECT spr round 3 (radius: 15)
[00:12:22 -522992.333452] AUTODETECT spr round 4 (radius: 20)
[00:17:11 -480799.531999] AUTODETECT spr round 5 (radius: 25)
[00:23:03 -472083.332649] SPR radius for FAST iterations: 25 (autodetect)
[00:23:03 -472083.332649] Model parameter optimization (eps = 3.000000)
[00:23:16 -472036.872983] FAST spr round 1 (radius: 25)
[00:29:20 -441681.631641] FAST spr round 2 (radius: 25)
[00:33:56 -440107.885803] FAST spr round 3 (radius: 25)
[00:37:50 -439903.473675] FAST spr round 4 (radius: 25)
[00:40:54 -439884.037790] FAST spr round 5 (radius: 25)
[00:43:47 -439880.645008] FAST spr round 6 (radius: 25)
[00:46:32 -439880.644879] Model parameter optimization (eps = 1.000000)
[00:47:03 -439221.986610] SLOW spr round 1 (radius: 5)
[00:52:13 -439066.904626] SLOW spr round 2 (radius: 5)
[00:55:46 -439042.394730] SLOW spr round 3 (radius: 5)
[00:59:12 -439042.393246] SLOW spr round 4 (radius: 10)
[01:02:45 -439042.168821] SLOW spr round 5 (radius: 5)
[01:06:47 -439042.035142] SLOW spr round 6 (radius: 5)
[01:10:20 -439042.034256] SLOW spr round 7 (radius: 10)
[01:13:54 -439042.034253] SLOW spr round 8 (radius: 15)
[01:19:49 -439033.631334] SLOW spr round 9 (radius: 5)
[01:23:43 -439030.195243] SLOW spr round 10 (radius: 5)
[01:27:10 -439030.179720] SLOW spr round 11 (radius: 10)
[01:30:37 -439030.179132] SLOW spr round 12 (radius: 15)
[01:36:08 -439030.179089] SLOW spr round 13 (radius: 20)
[01:39:18] [worker #1] ML tree search #2, logLikelihood: -439109.847161
[01:46:11 -439030.179085] SLOW spr round 14 (radius: 25)
[01:59:18 -439030.179085] Model parameter optimization (eps = 0.100000)

[01:59:25] [worker #0] ML tree search #1, logLikelihood: -439030.151553

[01:59:25 -1297924.617681] Initial branch length optimization
[01:59:32 -1079940.362066] Model parameter optimization (eps = 10.000000)
[02:00:23 -1077071.644563] AUTODETECT spr round 1 (radius: 5)
[02:03:44 -785534.477087] AUTODETECT spr round 2 (radius: 10)
[02:07:15 -617309.418974] AUTODETECT spr round 3 (radius: 15)
[02:10:57 -501136.450305] AUTODETECT spr round 4 (radius: 20)
[02:15:08 -475435.056128] AUTODETECT spr round 5 (radius: 25)
[02:20:25 -471420.333340] SPR radius for FAST iterations: 25 (autodetect)
[02:20:25 -471420.333340] Model parameter optimization (eps = 3.000000)
[02:21:03 -470435.280977] FAST spr round 1 (radius: 25)
[02:26:40 -440823.194906] FAST spr round 2 (radius: 25)
[02:30:46 -439366.150936] FAST spr round 3 (radius: 25)
[02:34:00 -439242.226113] FAST spr round 4 (radius: 25)
[02:36:55 -439218.888794] FAST spr round 5 (radius: 25)
[02:39:38 -439207.502157] FAST spr round 6 (radius: 25)
[02:42:10 -439203.840844] FAST spr round 7 (radius: 25)
[02:44:36 -439203.839618] Model parameter optimization (eps = 1.000000)
[02:44:58 -439177.615800] SLOW spr round 1 (radius: 5)
[02:48:24 -439025.168571] SLOW spr round 2 (radius: 5)
[02:51:43 -439015.827069] SLOW spr round 3 (radius: 5)
[02:54:59 -439015.826252] SLOW spr round 4 (radius: 10)
[02:58:15 -439015.826239] SLOW spr round 5 (radius: 15)
[03:03:57 -439001.410151] SLOW spr round 6 (radius: 5)
[03:08:04 -438999.487811] SLOW spr round 7 (radius: 5)
[03:11:45 -438998.802008] SLOW spr round 8 (radius: 5)
[03:15:10 -438998.801009] SLOW spr round 9 (radius: 10)
[03:18:40 -438998.800915] SLOW spr round 10 (radius: 15)
[03:24:31 -438998.800911] SLOW spr round 11 (radius: 20)
[03:33:54 -438995.639951] SLOW spr round 12 (radius: 5)
[03:37:48 -438995.639932] SLOW spr round 13 (radius: 10)
[03:41:47 -438995.639932] SLOW spr round 14 (radius: 15)
[03:47:02 -438995.639932] SLOW spr round 15 (radius: 20)
[03:51:07] [worker #1] ML tree search #4, logLikelihood: -439046.120912
[03:56:22 -438995.639932] SLOW spr round 16 (radius: 25)
[04:08:27 -438995.639932] Model parameter optimization (eps = 0.100000)

[04:08:47] [worker #0] ML tree search #3, logLikelihood: -438994.674003

[04:08:47 -1293597.543601] Initial branch length optimization
[04:08:55 -1076575.008879] Model parameter optimization (eps = 10.000000)
[04:09:45 -1073806.879337] AUTODETECT spr round 1 (radius: 5)
[04:13:05 -782666.851007] AUTODETECT spr round 2 (radius: 10)
[04:16:43 -599895.418900] AUTODETECT spr round 3 (radius: 15)
[04:20:34 -505632.195903] AUTODETECT spr round 4 (radius: 20)
[04:25:06 -476029.100261] AUTODETECT spr round 5 (radius: 25)
[04:30:08 -471354.639779] SPR radius for FAST iterations: 25 (autodetect)
[04:30:08 -471354.639779] Model parameter optimization (eps = 3.000000)
[04:30:21 -471303.555716] FAST spr round 1 (radius: 25)
[04:35:55 -441400.838211] FAST spr round 2 (radius: 25)
[04:40:01 -440153.541783] FAST spr round 3 (radius: 25)
[04:43:21 -440040.633472] FAST spr round 4 (radius: 25)
[04:46:23 -440008.907418] FAST spr round 5 (radius: 25)
[04:49:04 -440001.805800] FAST spr round 6 (radius: 25)
[04:51:33 -439997.338612] FAST spr round 7 (radius: 25)
[04:53:59 -439997.337485] Model parameter optimization (eps = 1.000000)
[04:54:06 -439997.104163] SLOW spr round 1 (radius: 5)
[04:57:34 -439886.334711] SLOW spr round 2 (radius: 5)
[05:00:53 -439884.319766] SLOW spr round 3 (radius: 5)
[05:04:06 -439880.452326] SLOW spr round 4 (radius: 5)
[05:07:26 -439880.452285] SLOW spr round 5 (radius: 10)
[05:11:05 -439855.143070] SLOW spr round 6 (radius: 5)
[05:15:09 -439839.532495] SLOW spr round 7 (radius: 5)
[05:18:44 -439839.532245] SLOW spr round 8 (radius: 10)
[05:22:23 -439839.532234] SLOW spr round 9 (radius: 15)
[05:28:19 -439833.369938] SLOW spr round 10 (radius: 5)
[05:32:34 -439815.630073] SLOW spr round 11 (radius: 5)
[05:36:17 -439815.521134] SLOW spr round 12 (radius: 5)
[05:39:46 -439815.520115] SLOW spr round 13 (radius: 10)
[05:43:25 -439814.792867] SLOW spr round 14 (radius: 5)
[05:44:36] [worker #1] ML tree search #6, logLikelihood: -439049.097900
[05:47:23 -439814.789626] SLOW spr round 15 (radius: 10)
[05:51:22 -439814.789473] SLOW spr round 16 (radius: 15)
[05:57:04 -439814.789464] SLOW spr round 17 (radius: 20)
[06:07:25 -439814.789457] SLOW spr round 18 (radius: 25)
[06:21:10 -439814.789457] Model parameter optimization (eps = 0.100000)

[06:21:16] [worker #0] ML tree search #5, logLikelihood: -439814.774879

[06:21:16 -1297759.903847] Initial branch length optimization
[06:21:25 -1087757.985819] Model parameter optimization (eps = 10.000000)
[06:22:43 -1084882.007356] AUTODETECT spr round 1 (radius: 5)
[06:26:19 -782123.484413] AUTODETECT spr round 2 (radius: 10)
[06:30:07 -594640.599384] AUTODETECT spr round 3 (radius: 15)
[06:34:06 -517956.039373] AUTODETECT spr round 4 (radius: 20)
[06:38:18 -480513.297091] AUTODETECT spr round 5 (radius: 25)
[06:43:20 -469648.141277] SPR radius for FAST iterations: 25 (autodetect)
[06:43:20 -469648.141277] Model parameter optimization (eps = 3.000000)
[06:43:54 -468616.438256] FAST spr round 1 (radius: 25)
[06:49:55 -441296.365262] FAST spr round 2 (radius: 25)
[06:54:30 -439578.885738] FAST spr round 3 (radius: 25)
[06:58:17 -439332.704766] FAST spr round 4 (radius: 25)
[07:01:38 -439283.812829] FAST spr round 5 (radius: 25)
[07:04:47 -439265.648797] FAST spr round 6 (radius: 25)
[07:07:35 -439260.043788] FAST spr round 7 (radius: 25)
[07:10:17 -439254.490330] FAST spr round 8 (radius: 25)
[07:13:08 -439235.329758] FAST spr round 9 (radius: 25)
[07:15:57 -439221.044732] FAST spr round 10 (radius: 25)
[07:18:27 -439221.044165] Model parameter optimization (eps = 1.000000)
[07:18:47 -439211.351467] SLOW spr round 1 (radius: 5)
[07:22:32 -439093.433445] SLOW spr round 2 (radius: 5)
[07:26:03 -439077.730732] SLOW spr round 3 (radius: 5)
[07:29:31 -439073.485368] SLOW spr round 4 (radius: 5)
[07:32:54 -439073.485019] SLOW spr round 5 (radius: 10)
[07:36:35 -439052.581662] SLOW spr round 6 (radius: 5)
[07:40:51 -439043.691055] SLOW spr round 7 (radius: 5)
[07:44:32 -439041.642734] SLOW spr round 8 (radius: 5)
[07:47:58 -439041.642502] SLOW spr round 9 (radius: 10)
[07:51:30 -439040.391674] SLOW spr round 10 (radius: 5)
[07:55:31 -439032.391489] SLOW spr round 11 (radius: 5)
[07:59:03 -439032.191751] SLOW spr round 12 (radius: 5)
[08:02:25 -439032.191054] SLOW spr round 13 (radius: 10)
[08:04:36] [worker #1] ML tree search #8, logLikelihood: -439048.552167
[08:05:55 -439030.046466] SLOW spr round 14 (radius: 5)
[08:09:52 -439028.321954] SLOW spr round 15 (radius: 5)
[08:13:31 -439024.105456] SLOW spr round 16 (radius: 5)
[08:16:58 -439024.104838] SLOW spr round 17 (radius: 10)
[08:20:36 -439021.587915] SLOW spr round 18 (radius: 5)
[08:24:39 -439019.349748] SLOW spr round 19 (radius: 5)
[08:28:16 -439019.349614] SLOW spr round 20 (radius: 10)
[08:31:55 -439019.349601] SLOW spr round 21 (radius: 15)
[08:37:50 -439019.349594] SLOW spr round 22 (radius: 20)
[08:48:07 -439019.349580] SLOW spr round 23 (radius: 25)
[09:02:01 -439019.349573] Model parameter optimization (eps = 0.100000)

[09:02:18] [worker #0] ML tree search #7, logLikelihood: -439017.436477

[09:02:18 -1296545.069797] Initial branch length optimization
[09:02:26 -1078871.600104] Model parameter optimization (eps = 10.000000)
[09:03:28 -1076132.927971] AUTODETECT spr round 1 (radius: 5)
[09:06:55 -788613.173122] AUTODETECT spr round 2 (radius: 10)
[09:10:37 -609724.119178] AUTODETECT spr round 3 (radius: 15)
[09:14:39 -510094.732959] AUTODETECT spr round 4 (radius: 20)
[09:19:01 -482795.655242] AUTODETECT spr round 5 (radius: 25)
[09:24:28 -474194.455498] SPR radius for FAST iterations: 25 (autodetect)
[09:24:28 -474194.455498] Model parameter optimization (eps = 3.000000)
[09:24:41 -474132.436815] FAST spr round 1 (radius: 25)
[09:30:36 -441795.300915] FAST spr round 2 (radius: 25)
[09:34:46 -440384.732610] FAST spr round 3 (radius: 25)
[09:38:18 -440163.759829] FAST spr round 4 (radius: 25)
[09:41:25 -440102.521241] FAST spr round 5 (radius: 25)
[09:44:09 -440091.483540] FAST spr round 6 (radius: 25)
[09:46:44 -440091.483494] Model parameter optimization (eps = 1.000000)
[09:46:52 -440090.924596] SLOW spr round 1 (radius: 5)
[09:48:25] [worker #1] ML tree search #10, logLikelihood: -439893.717510
[09:50:37 -440002.473283] SLOW spr round 2 (radius: 5)
[09:54:12 -439989.208833] SLOW spr round 3 (radius: 5)
[09:57:45 -439981.416768] SLOW spr round 4 (radius: 5)
[10:01:05 -439981.416716] SLOW spr round 5 (radius: 10)
[10:04:26 -439979.501445] SLOW spr round 6 (radius: 5)
[10:08:12 -439979.500758] SLOW spr round 7 (radius: 10)
[10:11:58 -439979.500734] SLOW spr round 8 (radius: 15)
[10:17:20 -439979.500725] SLOW spr round 9 (radius: 20)
[10:27:25 -439979.500720] SLOW spr round 10 (radius: 25)
[10:40:28 -439979.500715] Model parameter optimization (eps = 0.100000)

[10:40:33] [worker #0] ML tree search #9, logLikelihood: -439979.472837

[10:40:33 -1296399.169161] Initial branch length optimization
[10:40:41 -1084605.284904] Model parameter optimization (eps = 10.000000)
[10:41:43 -1081682.643139] AUTODETECT spr round 1 (radius: 5)
[10:45:01 -774059.337064] AUTODETECT spr round 2 (radius: 10)
[10:48:28 -606803.628788] AUTODETECT spr round 3 (radius: 15)
[10:52:09 -534681.291997] AUTODETECT spr round 4 (radius: 20)
[10:56:25 -486002.760825] AUTODETECT spr round 5 (radius: 25)
[11:01:16 -479552.452980] SPR radius for FAST iterations: 25 (autodetect)
[11:01:16 -479552.452980] Model parameter optimization (eps = 3.000000)
[11:01:55 -478471.957760] FAST spr round 1 (radius: 25)
[11:07:18 -441442.105949] FAST spr round 2 (radius: 25)
[11:11:22 -439619.780970] FAST spr round 3 (radius: 25)
[11:14:45 -439290.416270] FAST spr round 4 (radius: 25)
[11:17:44 -439253.805993] FAST spr round 5 (radius: 25)
[11:20:15 -439250.269585] FAST spr round 6 (radius: 25)
[11:22:41 -439243.654348] FAST spr round 7 (radius: 25)
[11:25:01 -439243.653264] Model parameter optimization (eps = 1.000000)
[11:25:25 -439212.132427] SLOW spr round 1 (radius: 5)
[11:28:56 -439109.704131] SLOW spr round 2 (radius: 5)
[11:32:20 -439074.282502] SLOW spr round 3 (radius: 5)
[11:34:19] [worker #1] ML tree search #12, logLikelihood: -439732.102959
[11:35:40 -439069.996698] SLOW spr round 4 (radius: 5)
[11:39:04 -439064.198492] SLOW spr round 5 (radius: 5)
[11:42:17 -439062.007619] SLOW spr round 6 (radius: 5)
[11:45:27 -439062.007152] SLOW spr round 7 (radius: 10)
[11:48:47 -439054.335762] SLOW spr round 8 (radius: 5)
[11:52:28 -439053.660605] SLOW spr round 9 (radius: 5)
[11:55:47 -439053.660122] SLOW spr round 10 (radius: 10)
[11:59:08 -439053.660107] SLOW spr round 11 (radius: 15)
[12:04:25 -439047.346746] SLOW spr round 12 (radius: 5)
[12:08:14 -439047.346400] SLOW spr round 13 (radius: 10)
[12:12:08 -439047.346390] SLOW spr round 14 (radius: 15)
[12:17:18 -439047.346384] SLOW spr round 15 (radius: 20)
[12:26:33 -439046.153258] SLOW spr round 16 (radius: 5)
[12:30:29 -439045.083746] SLOW spr round 17 (radius: 5)
[12:33:59 -439045.083671] SLOW spr round 18 (radius: 10)
[12:37:27 -439045.083665] SLOW spr round 19 (radius: 15)
[12:42:41 -439045.083659] SLOW spr round 20 (radius: 20)
[12:51:53 -439044.882213] SLOW spr round 21 (radius: 5)
[12:55:52 -439044.882096] SLOW spr round 22 (radius: 10)
[13:00:03 -439044.882090] SLOW spr round 23 (radius: 15)
[13:05:25 -439044.882072] SLOW spr round 24 (radius: 20)
[13:15:01 -439044.881949] SLOW spr round 25 (radius: 25)
[13:19:28] [worker #1] ML tree search #14, logLikelihood: -439074.659706
[13:27:32 -439044.881943] Model parameter optimization (eps = 0.100000)

[13:27:44] [worker #0] ML tree search #11, logLikelihood: -439044.584306

[13:27:44 -1289952.141514] Initial branch length optimization
[13:27:51 -1079971.452323] Model parameter optimization (eps = 10.000000)
[13:28:49 -1077055.410431] AUTODETECT spr round 1 (radius: 5)
[13:32:09 -786687.684880] AUTODETECT spr round 2 (radius: 10)
[13:35:40 -624535.670760] AUTODETECT spr round 3 (radius: 15)
[13:39:35 -556074.732323] AUTODETECT spr round 4 (radius: 20)
[13:44:10 -495714.425770] AUTODETECT spr round 5 (radius: 25)
[13:49:15 -479460.814502] SPR radius for FAST iterations: 25 (autodetect)
[13:49:15 -479460.814502] Model parameter optimization (eps = 3.000000)
[13:49:31 -479408.557137] FAST spr round 1 (radius: 25)
[13:54:46 -441435.501843] FAST spr round 2 (radius: 25)
[13:58:22 -440212.994068] FAST spr round 3 (radius: 25)
[14:01:19 -440058.688053] FAST spr round 4 (radius: 25)
[14:03:56 -440017.848677] FAST spr round 5 (radius: 25)
[14:06:23 -440006.380318] FAST spr round 6 (radius: 25)
[14:08:34 -440006.379870] Model parameter optimization (eps = 1.000000)
[14:08:42 -440005.320610] SLOW spr round 1 (radius: 5)
[14:11:44 -439910.178599] SLOW spr round 2 (radius: 5)
[14:14:42 -439890.162269] SLOW spr round 3 (radius: 5)
[14:17:34 -439888.710207] SLOW spr round 4 (radius: 5)
[14:20:21 -439888.710168] SLOW spr round 5 (radius: 10)
[14:23:16 -439885.352668] SLOW spr round 6 (radius: 5)
[14:26:32 -439885.351649] SLOW spr round 7 (radius: 10)
[14:29:43 -439885.351464] SLOW spr round 8 (radius: 15)
[14:34:19 -439885.351459] SLOW spr round 9 (radius: 20)
[14:39:03] [worker #1] ML tree search #16, logLikelihood: -439070.919775
[14:42:46 -439885.351455] SLOW spr round 10 (radius: 25)
[14:53:58 -439885.351451] Model parameter optimization (eps = 0.100000)

[14:54:24] [worker #0] ML tree search #13, logLikelihood: -439082.903337

[14:54:24 -1298646.628040] Initial branch length optimization
[14:54:32 -1075839.667937] Model parameter optimization (eps = 10.000000)
[14:55:15 -1073235.962572] AUTODETECT spr round 1 (radius: 5)
[14:58:12 -782356.539350] AUTODETECT spr round 2 (radius: 10)
[15:01:15 -610701.044712] AUTODETECT spr round 3 (radius: 15)
[15:04:33 -522222.528508] AUTODETECT spr round 4 (radius: 20)
[15:07:58 -491038.562379] AUTODETECT spr round 5 (radius: 25)
[15:11:58 -473669.168135] SPR radius for FAST iterations: 25 (autodetect)
[15:11:58 -473669.168135] Model parameter optimization (eps = 3.000000)
[15:12:10 -473612.509224] FAST spr round 1 (radius: 25)
[15:16:32 -442258.880690] FAST spr round 2 (radius: 25)
[15:19:58 -440704.692082] FAST spr round 3 (radius: 25)
[15:22:55 -440208.751126] FAST spr round 4 (radius: 25)
[15:25:41 -440180.358689] FAST spr round 5 (radius: 25)
[15:28:19 -440176.021199] FAST spr round 6 (radius: 25)
[15:30:50 -440176.020108] Model parameter optimization (eps = 1.000000)
[15:31:16 -439269.852841] SLOW spr round 1 (radius: 5)
[15:34:49 -439139.346096] SLOW spr round 2 (radius: 5)
[15:38:10 -439095.673980] SLOW spr round 3 (radius: 5)
[15:41:28 -439092.116314] SLOW spr round 4 (radius: 5)
[15:44:40 -439092.114787] SLOW spr round 5 (radius: 10)
[15:48:04 -439074.119904] SLOW spr round 6 (radius: 5)
[15:51:52 -439068.975325] SLOW spr round 7 (radius: 5)
[15:55:12 -439068.685862] SLOW spr round 8 (radius: 5)
[15:58:24 -439068.685825] SLOW spr round 9 (radius: 10)
[16:01:38 -439068.685824] SLOW spr round 10 (radius: 15)
[16:07:00 -439068.685824] SLOW spr round 11 (radius: 20)
[16:14:11] [worker #1] ML tree search #18, logLikelihood: -439907.612918
[16:15:58 -439066.452218] SLOW spr round 12 (radius: 5)
[16:19:59 -439066.452133] SLOW spr round 13 (radius: 10)
[16:24:03 -439066.452133] SLOW spr round 14 (radius: 15)
[16:29:17 -439066.452133] SLOW spr round 15 (radius: 20)
[16:38:29 -439066.199642] SLOW spr round 16 (radius: 5)
[16:42:26 -439066.199626] SLOW spr round 17 (radius: 10)
[16:46:33 -439066.199625] SLOW spr round 18 (radius: 15)
[16:51:43 -439066.199615] SLOW spr round 19 (radius: 20)
[17:00:43 -439066.199608] SLOW spr round 20 (radius: 25)
[17:12:57 -439066.199608] Model parameter optimization (eps = 0.100000)

[17:13:03] [worker #0] ML tree search #15, logLikelihood: -439066.103516

[17:13:03 -1297554.461684] Initial branch length optimization
[17:13:10 -1076085.819099] Model parameter optimization (eps = 10.000000)
[17:14:10 -1073461.415285] AUTODETECT spr round 1 (radius: 5)
[17:17:27 -790739.805373] AUTODETECT spr round 2 (radius: 10)
[17:20:56 -626271.434065] AUTODETECT spr round 3 (radius: 15)
[17:24:37 -542074.299148] AUTODETECT spr round 4 (radius: 20)
[17:28:32 -495950.739057] AUTODETECT spr round 5 (radius: 25)
[17:33:22 -477893.778704] SPR radius for FAST iterations: 25 (autodetect)
[17:33:22 -477893.778704] Model parameter optimization (eps = 3.000000)
[17:33:35 -477841.052429] FAST spr round 1 (radius: 25)
[17:38:55 -442597.124225] FAST spr round 2 (radius: 25)
[17:42:48 -440315.499196] FAST spr round 3 (radius: 25)
[17:46:03 -440077.988795] FAST spr round 4 (radius: 25)
[17:46:05] [worker #1] ML tree search #20, logLikelihood: -439089.960530
[17:48:58 -440003.402217] FAST spr round 5 (radius: 25)
[17:51:37 -439988.101764] FAST spr round 6 (radius: 25)
[17:53:58 -439987.696903] FAST spr round 7 (radius: 25)
[17:56:20 -439987.695650] Model parameter optimization (eps = 1.000000)
[17:56:32 -439986.603147] SLOW spr round 1 (radius: 5)
[18:00:08 -439863.121543] SLOW spr round 2 (radius: 5)
[18:03:23 -439851.638794] SLOW spr round 3 (radius: 5)
[18:06:29 -439851.638619] SLOW spr round 4 (radius: 10)
[18:09:50 -439831.412994] SLOW spr round 5 (radius: 5)
[18:13:34 -439824.225814] SLOW spr round 6 (radius: 5)
[18:16:54 -439824.225230] SLOW spr round 7 (radius: 10)
[18:20:15 -439823.012838] SLOW spr round 8 (radius: 5)
[18:23:57 -439821.023621] SLOW spr round 9 (radius: 5)
[18:27:13 -439821.022728] SLOW spr round 10 (radius: 10)
[18:30:31 -439821.022696] SLOW spr round 11 (radius: 15)
[18:35:49 -439821.022691] SLOW spr round 12 (radius: 20)
[18:45:21 -439821.022691] SLOW spr round 13 (radius: 25)
[18:58:17 -439821.022691] Model parameter optimization (eps = 0.100000)

[18:58:22] [worker #0] ML tree search #17, logLikelihood: -439821.015603

[18:58:22 -1304238.063665] Initial branch length optimization
[18:58:29 -1087332.782122] Model parameter optimization (eps = 10.000000)
[18:59:29 -1084211.952711] AUTODETECT spr round 1 (radius: 5)
[19:02:46 -765992.170859] AUTODETECT spr round 2 (radius: 10)
[19:06:14 -603583.127874] AUTODETECT spr round 3 (radius: 15)
[19:09:56 -510652.103395] AUTODETECT spr round 4 (radius: 20)
[19:13:57 -477889.211574] AUTODETECT spr round 5 (radius: 25)
[19:18:45 -474871.982572] SPR radius for FAST iterations: 25 (autodetect)
[19:18:45 -474871.982572] Model parameter optimization (eps = 3.000000)
[19:18:59 -474816.543105] FAST spr round 1 (radius: 25)
[19:24:47 -441648.284104] FAST spr round 2 (radius: 25)
[19:28:57 -440222.451049] FAST spr round 3 (radius: 25)
[19:32:13 -440063.357445] FAST spr round 4 (radius: 25)
[19:34:57 -440032.515742] FAST spr round 5 (radius: 25)
[19:37:24 -440031.689992] FAST spr round 6 (radius: 25)
[19:39:47 -440031.687635] Model parameter optimization (eps = 1.000000)
[19:39:54 -440030.755832] SLOW spr round 1 (radius: 5)
[19:43:18 -439914.557028] SLOW spr round 2 (radius: 5)
[19:46:32 -439908.308101] SLOW spr round 3 (radius: 5)
[19:49:41 -439906.818827] SLOW spr round 4 (radius: 5)
[19:52:44 -439906.818273] SLOW spr round 5 (radius: 10)
[19:55:57 -439900.066016] SLOW spr round 6 (radius: 5)
[19:59:42 -439892.255703] SLOW spr round 7 (radius: 5)
[20:02:58 -439892.187997] SLOW spr round 8 (radius: 10)
[20:06:21 -439887.235430] SLOW spr round 9 (radius: 5)
[20:09:55 -439886.042745] SLOW spr round 10 (radius: 5)
[20:13:16 -439881.233051] SLOW spr round 11 (radius: 5)
[20:16:21 -439880.363603] SLOW spr round 12 (radius: 5)
[20:19:22 -439880.363548] SLOW spr round 13 (radius: 10)
[20:22:34 -439880.363540] SLOW spr round 14 (radius: 15)
[20:27:53 -439880.363534] SLOW spr round 15 (radius: 20)
[20:36:42 -439880.363515] SLOW spr round 16 (radius: 25)
[20:48:20 -439880.363509] Model parameter optimization (eps = 0.100000)

[20:48:23] [worker #0] ML tree search #19, logLikelihood: -439880.362938


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.098834,0.467517) (0.100914,0.388660) (0.442787,0.858503) (0.357465,1.495078) 
   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: -438994.674003

AIC score: 881999.348005 / AICc score: 8926059.348005 / BIC score: 891453.691695
Free parameters (model + branch lengths): 2005

WARNING: Number of free parameters (K=2005) is larger than alignment size (n=825).
         This might lead to overfitting and compromise tree inference results!


Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/A6NHY2/3_mltree/A6NHY2.raxml.log

Analysis started: 01-Jul-2021 16:40:20 / finished: 02-Jul-2021 13:28:44

Elapsed time: 74903.321 seconds

Consumed energy: 6947.486 Wh (= 35 km in an electric car, or 174 km with an e-scooter!)