there are some nice fast computations of Julia sets in Python https://www.ibm.com/developerworks/community/blogs/jfp/entry/Fast_Computation_of_Julia_Set_in_Pyth

there are some nice fast computations of Julia sets in Python https://www.ibm.com/developerworks/community/blogs/jfp/entry/Fast_Computation_of_Julia_Set_in_Python?lang=en https://www.ibm.com/developerworks/community/blogs/jfp/entry... however one problem is always requires computing all the backwards iterates of the points. And there's never getting around that. these two ladies offer a means of approximating the Julia set using a polygon. I have no heard of this. there is a nice result by William Thurston they are using "Shapes of polyhedra and triangulations of the sphere" https://arxiv.org/abs/math/9801088 https://arxiv.org/abs/math/9801088 The theorem is exactly what the article says. They cut out this shape and fold it along the correct lines and glue along the boundary, one obtains the boundary of a convex shape.