== VARIABLES == genes = best genes selected mute = temporary mutated genes == GENES == 1 - branch lengths for each depth. 2 - Angles at which branches split apart for each depth. 3 - Branch divisors for each depth, what the previous branch length is divided by to get the next branch's length. 4 - Branch thicknesses for each depth. 5 - Branch colors for each depth. == INSTRUCTIONS == Evolve the tree as you wish, saving genes you like and discarding bad ones.data:image/png;base64,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 VARIABLES == genes = best genes selected mute = temporary mutated genes == GENES == 1 - branch lengths for each depth. 2 - Angles at which branches split apart for each depth. 3 - Branch divisors for each depth, what the previous branch length is divided by to get the next branch's length. 4 - Branch thicknesses for each depth. 5 - Branch colors for each depth. == INSTRUCTIONS == Evolve the tree as you wish, saving genes you like and discarding bad ones.
2045201210data:image/png;base64,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15.423358255483842,35.3990399841501,65.70138508480595,59.03516234958686,49.237353616287066,62.55512097596451,53.1691513293703,51.75026059239997,86.0886070390468920.28468043023886,85.3095080024698,30.345255919507327,61.38445584460051,50.05240699730375,55.19517983407416,50.84022534087622,77.82195715886984,71.039676859575412.4562091525321494,1.952817575043089,2.962826500450708,1.5799584915644147,2.918905509612175,2.6204003288314404,1.4021284804555163,2.6550528953663854,2.24211564106015445.073627754358668,9.737598378239898,9.588960057845048,3.083779083536476,7.409948724856297,5.950116909069134,3.557187758287329,8.638556679107905,2.221871770795013753,43,48,24052,24,47,2246,51,7,18328,61,36,2232,0,56,13441,17,4,17910,39,34,19749,42,58,23057,55,30,15814.662417855194137,33.48453731787407,64.40993346982523,58.258467236202804,50.91739197530234,60.64529572759863,55.001538338657866,52.161951808972596,85.669899184158419.87603287778236,86.10324702773214,29.702337375075242,60.88696312174769,49.1428567780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