I need to find the distance of multiple points to a curve of the form: f(x) = a^(k^(bx))
My first option was using its derivative, using a line of the f
The distance between a point (c,d) and your curve is the minimum of the function
sqrt((c-x)^2 + (d-a^(k^(bx)))^2)
To find its minimum, we can forget about the sqrt
and look at the first derivative. Find out where it's 0 (it has to be the minimal distance, as there's no maximum distance). That gives you the x coordinate of the nearest point on the curve. To get the distance you need to calculate the y coordinate, and then calculate the distance to the point (you can just calculate the distance function at that x
, it's the same thing).
Repeat for each of your points.
The first derivative of the distance function, is, unfortunately, a kind of bitch. Using Wolfram's derivator, the result is hopefully (if I haven't made any copying errors):
dist(x)/dx = 2(b * lna * lnk * k^(bx) * a^(k^(bx)) * (a^(k^(bx)) - d) - c + x)
To find distance from point to curve it's not a simple task, for that you need to find the global of function where f(x) is the function which determine your curve.
For that goal you could use:
Simplex method
Nelder_Mead_method
gradient_descent
This methods implemented in many libraries like Solver Foundation, NMath etc.