+David MooreBasically you set things up like any "normal"
inverse Julia plotter, then apply any mutation(s).
So, wrt the red plot:
Barring any typos...
z_[n] is the current 2d point under iteration.
c is a 2d Julia point.
________________________________d_[n].x = z_[n].x - c.x
d_[n].y = z_[n].y - c.y
z_dis_[n] = sqrt(d_[n].x^2 + d_[n].y^2)
z_radius_[n] = sqrt(z_dis_[n])
z_angle_[n] = atan2(d_[n].y, d_[n].x) / 2
________________________________Okay, we have a lot of “useful” information
here. Let's "experiment" with setting a constant P to the power of (z_dis_[n]) where (z_radius_[n]) is redefined to something like:
________________________________z_radius_[n] = pow(P, z_dis_[n])
________________________________Now, this gives us all we need in order to create the "red plot" of a given c.
IIRC, P looks nice around (0.2) for inverse Julia's with the spirals exposed via contrived very high or low probability ratios....
;^)
Can you give more detail on how the path in red is constructed? Is the blue an inverse z^2+c iteration or is it something else?Nov 4, 2014
Chris “M” ThomassonOwner+David Moore