Corr Curve

Curve Severity

Great for animation easing, weighting random distribution, even modeling topography.

A Corr Curve is most easily defined in two ways: by setting the x=y intercept and the curve severity or by setting the Y0 and Y1 control points. Both these methods are available in the above interactive illustration.

In addition to the high level of control it affords the user, the great strength of the Corr Curve is the computational simplicity of finding the Y value of a given X value, which means this function can be run many, many, many times per frame without lag.

I first developed the Corr Curve as a method for modeling 3D topography in which it would be computationally trivial to find the height at any point and the topography would have a step granularity equal to the float precision. This means you can zoom in and it doesn't become stair-stepped unlike, say, a triangle mesh. Since that project I have found the curve very useful for all sorts of things: animation easing, weighting random distribution, and even stitching together audio samples. This wide-ranging utility is largely due to the graceful nature of the curve and the intuitive ways it can be defined.

A Corr Curve is most easily defined in two ways: by setting the x=y intercept and the curve severity or by setting the Y0 and Y1 control points. Both these methods are available in the above interactive illustration.

In addition to the high level of control it affords the user, the great strength of the Corr Curve is the computational simplicity of finding the Y value of a given X value, which means this function can be run many, many, many times per frame without lag.

I first developed the Corr Curve as a method for modeling 3D topography in which it would be computationally trivial to find the height at any point and the topography would have a step granularity equal to the float precision. This means you can zoom in and it doesn't become stair-stepped unlike, say, a triangle mesh. Since that project I have found the curve very useful for all sorts of things: animation easing, weighting random distribution, and even stitching together audio samples. This wide-ranging utility is largely due to the graceful nature of the curve and the intuitive ways it can be defined.