Using points to generate quadratic equation to interpolate data

Question

I'm trying to come up with a flexible decaying score system for a game using quadratic curves. I could probably brute force my way through it but was wondering if anyone can help me come up with something flexible or maybe there are some ready made solutions out there already!

But basically I need the ability to generate the values of a,b & c in:

y = ax^2 + bx + c

from 3 points (which i know fall on a valid quadratic curve, but are dynamic based on configurable settings and maximum times to react to an event) for example: (-1100, 0), (200, 1), (1500, 0).

So I can then plugin in values for x to generate values of Y which will determine the score I give the user.

If I could get away with a fixed quadratic equation I would but the scoring is based on how much time a user has to react to a particular event (X Axis) the y axis points will always be between 0 and 1 with 0 being minimum score and 1 being maximum score!

Let me know if you need more info!

Answer 1

You can use Lagrange polynomial interpolation, the curve is given by

y(x) = y_1 * (x-x_2)*(x-x_3)/((x_1-x_2)*(x_1-x_3))
     + y_2 * (x-x_1)*(x-x_3)/((x_2-x_1)*(x_2-x_3))
     + y_3 * (x-x_1)*(x-x_2)/((x_3-x_1)*(x_3-x_2))

If you collect the coefficients, you obtain

a = y_1/((x_1-x_2)*(x_1-x_3)) + y_2/((x_2-x_1)*(x_2-x_3)) + y_3/((x_3-x_1)*(x_3-x_2))

b = -y_1*(x_2+x_3)/((x_1-x_2)*(x_1-x_3))
    -y_2*(x_1+x_3)/((x_2-x_1)*(x_2-x_3))
    -y_3*(x_1+x_2)/((x_3-x_1)*(x_3-x_2))

c = y_1*x_2*x_3/((x_1-x_2)*(x_1-x_3))
  + y_2*x_1*x_3/((x_2-x_1)*(x_2-x_3))
  + y_3*x_1*x_2/((x_3-x_1)*(x_3-x_2))

Answer 2

you can formulate it in a matrix form: aX=b

    1 x1 x1^2
a=  1 x2 x2^2
    1 x3 x3^2

   y1
b= y2
   y3

then solve by inverting the matrix a (can be done via gauss method pretty straight forward) http://en.wikipedia.org/wiki/Gaussian_elimination

X = a^-1*b

and X in this case are the [c b a] coefficients your are looking for.