Fractal Formula as Trap Shape

From Ultrafractal Wiki

Jump to: navigation, search

Hello all,

After reading Keith's mention of the Formula + Coloring Trap method, I was curious about it. So I tried putting a Julia set onto another Julia set. It seems to work, although not always in the ways I might have expected. For instance, when I tried using a basic point trap as the coloring on the Julia trap, distance coloring (on the sub-trap) seemed to work the way I was used to, but angle coloring didn't. Applying angle coloring to the trap as a whole seemed to work better.

Trying to keep track of which-piece-is-happening-where is an interesting kind of mental gymnastics.

Anyway, here's what I've got so far. Tweaking and dissection is definitely encouraged!

Morgen



iteratedIterations {
; Tweaks OK
::oHzFEin2t3VbPOutR4vfA3/BB1PWs+Ipe/K0H69SCaa2mg4D9FgCYoViyW5klUkk9e79rvkU
 SUatltIpz12LhALwaTOzwhDJHNkzjoTrjibjyf9LfhhRbWbOO0MrFXH1iTM6+QWZRjpxjZJt
 7Ct9BG7wZb31y+Ye0T46mQXKzx14ks2mQz7Lr3iLMeDOP/PF8K4rQAgv5LfBjWWzEHVRFao5
 PfIPLy4Pa00s10osKKOr9pQIAYsHTEx+yEcY5RcNhTSJt7KTC3fIvNrKqphpu1RFNVR14i2w
 nwki2HVVlVstrRIlirDvDsyG4Y5a765DQvi8VovnjFyB47absPabRo1KktF9Pjoitk+vl9qA
 fo/LfRaZNp9iYibf0noWDm2lmljLi2TsUrbjKSiqTWdIdvpBpFrfK087o9KTKTVbaw4kQwKH
 Iyh22AbLPHSxVlPSkF6VAynfIKLv8QLVyv8FZFNZJ4Xz7dpEyKKLwv8FESOvq8sCcUtRTZeG
 pZmoYJ7/ZnVHiz5KFtg7+h6Hya/QdUVTv6luJOnYMXdcDZEDXnFz6fTLPuMvsmYT7UvT4pOK
 JjI/rRDpd3USb2WazeZKT3wIAnjjbHU/8He97u/72QV41sKMvMPPvLsMdRtl1LSJV5noWXn8
 K2XiyzHX1EaS+60VRLyeTbUdb4yNT/cxll3HzqEhu8ySCdvHdClVTosdXNuZXZOb+8cCsbWJ
 ZNToZc5+9lFsRQ6o3HGqx8q8t8Y4USHbOBI+QDuWKGeeHaRG6MU9+cAvSCq3T8w1QWjLCHJ1
 ZptiK+m4IizMoIkWX2ymgGCkh6mWclYc08R8jiTp4yNqpituc2p37iqwnNTcNt0vpzv+327+
 6t9OlMvoYEw5SPZjtMEAFiw+Hyssv0p8Xth/8I3LTV6m8y4uB2p2hvvvQTR4U0u+z4YxFOzw
 jQrQnhPeXUUWq2c9lpzwALMBogE3FEhoiuptG3GvTYpf5lSDE3PhaawJkB9hvsZa0JXVAiPy
 PywQbLMDJZHph6V0KJns4quDuC54SisiEjHNwKRYcSsXiR+zCP7yrHZP4+zhmYS/5JjPbeVa
 JhoxXn3Fd3l1kuIC5kfhR117LLb39vpCyUQRJ+47Z8JmTq5aQp8ydmAEao7Ee4jfI/VXlv+A
 sXySzihmZo7CkWU5Ju5+cGF1cNTTKpB/UJctY6YGhrFY3iCVdbiUBCKiQO9xPsO3toSVnLNF
 ElIxVKnU6i3kpQFlKLrrGJqoC5KRoKqIuekryKFaknMLTo6jVL/AaRkwljBWUpsYsxzIj+Ym
 r/4Dsl5/0f9NbWv+bNlWEqvuWy4ovkAy+746GWQhyzLuYdnZg9Pj/gjvCGgoQF62PoCT7VpP
 WAVppKQKxllKclt+RMuqRFWTX3FT9/8fpipJ9n4uUWFgsCURErl3xWf5f4xsm+z/JVOOPUE3
 xMpuiWV63ZJbxNfTN+XUyo3x+feflSc/PiOiVuppMraD/OiJ7HZhVqoRn5l4+yE4ohXdhgkf
 0jfWwzcobdPlnWrpKi8WDPjJBu+dTio6mFDZjf14okEY4NwvyRsMRBQKrA0ZKMPTdH7vqaRJ
 Zvq3kdgIgb0Q0pCqbJie4SHZ6lYmlMpLslO+u5IrAxvNvsB30aKrwVfxSP3USYa5tx+jZt74
 HVfXwsPPnOLYkncK/SN8S2AVXaoYZiTc+u2+t72hJZEiO4McMtUP2RFxYTVaF1HlmIB2mpUc
 D1jO/prgezTfgbvvWKAm39+l9sLuHcJ8ULpHZR98KsHWR9kKnHTh9MKuHQh90JkHtOPXnlR0
 l8VJmPJB99cNfMLwzQOUpfNuTfPnDyWWn43B58sqWyzSL+TtHqnzG1ltn8o5tQ98JwaEOhLu
 t0RS55OmlkHiOMbvujc6skxjL6ZHLDnGaiCK22ujZfmrpHdkemdYw159RbLyaPkMvvTx9RKp
 vwJkPYVGKa/gGtIvk5BFcbEuzd5wpbyAFRD7IwpTSM4nK0dQXLjsiE8nCRGMRF6b54gg+9lC
 Zmyua8cDCscgD071XsrVAAGMUsNovYHPLX/A7+idQjyxx1NAxZw1ZoYKKUgDqjnHnagFyyrv
 4Awocc9geA/haggBB5ichQnghyhcJZ7G4b7TFQfV8+gDCg8Bo+yvD5y7F+u2AXPeFdsP0DDQ
 0QHGqzaQBgWIyf+u8aQW91E4E4DmqC3RkAv/HYb7wbKYg/wICkMiYxlG0fyYCEEAtth28K9G
 aKIEZbbP2ng8+EEgcpjOT0CotPvSrAHP/R2G7VAHkfAxKPUDyaieQaOoPwiXJvbBhW+O2+c2
 4dLSFIEZq2E1wn3WwAAZoi3nn0rCAWkh3hKcBT1BHPyEohB+749pAbPEZS6Q58ekvP02zCNd
 0gPQhIzsgjWhheDZKnjFiY66Rj10VWE/SdkD4Y1C54oKwuaKTbzpAJjhuqTQ3lGaXaodph2l
 GaXaodph2lGaXaodph2lGaXaodph2lGaXaodph2lGaXaodph2lGaXaodph2lGaXaodph2lGa
 Xaodph2lGaXaodph2lGaXaod97PoddVXn/vAZXJ9KkAA7K6QbZ3aO20gFR1lLHHK9Ajx1zzD
 BHggD0aA2TeWeoA4E4IZFMADMXK6mA/ahzl4MamX4kTUgzuBj0wcZWYu08L1taQuoB5iGkLa
 QuoB5iGkLaQuoB5iGkLfJA5CyXDylfXByl97TZG57v/b28+P1iJ7pJ5tZLt653EYb54GSnH3
 3nZbOLEuSujetbra8prGvL74KpMcqOwtKhufYZPrVhmadKTpHS2il1ywYCKLXsBB2+hfLOPX
 quWTFZLJhI5aPSc+s4L+bSlKBKLHjyJ7QAILbP2drI7IJr5lbZ65fR6U7yeQqcNGJyXZZJN7
 TUukLjM1VPWH6IdDx6Sy1SN7J7QluSjs5v7ckaCpKryiVfZWsarzkmtYihEnIpZsjJ6Mfocd
 t4x11rjesl+QcpYXp12ElNus4oCpjqzngJ0g8RJzce8N7bIWVnDxy7dIWF3DxK4fIWJHExq4
 hIWNXE0pKlppNYp7bf+homsiwfINVKu6O4CJzxK9YuWB0pJUnmQdaCvcaCvwxMqzS4zzS4JO
 K+/mcE+fp8DSf587vEHQw+89ZhCsBW83Sfvgx3rebfP3ALf+rc/wrIvPECtv5XF+8niqOUUe
 8SvH8JZpk1/YilYmfjT+6OdgYki5D8Z5B800Ae33PYR70ICrxf8YUdW0D0f8aIPXI3oKiIly
 UjPTPMpC8Wy8ijk6IuYLzP0iNIxxdYYZQvqv6Zq+7R0vOO5So7aE/hpd2DX5FAHbk1wlGh7k
 5cB2OIgz5TThuWQXX04lhBY86kgMk76Y9rVKrrKzKap29qLeDNEXjxF68WrzbtOv168Wrzbt
 Ov168WrzbtOv168WrvcG05tWf5MovcG+K5yZ42vZFobmFAZSjs/UyChVILoP0XfnNovzG+if
 nNMr/QmdZ8Mu/R6p58V1t5g+lbW/yNrf5m1vczfBe5mB+63uZ9b3sG2CaYLohtgG2Cf1AbB3
 BIIY7GMANBXgjP/X6B7J/YA4AtAOuDXg/IHEPNxeIUA/33AL447CNyB66crpPujjTTZ8vtwt
 g63W/zpQTSG86ej3ZHG6JHW2yIcxm/DPitzczVQd5nYu5KWI/LMXJw6Gmr8fAIFlYCH=
}

Personal tools