osu/osu.Game/Rulesets/Objects/BezierApproximator.cs

152 lines
6.7 KiB
C#

// Copyright (c) 2007-2018 ppy Pty Ltd <contact@ppy.sh>.
// Licensed under the MIT Licence - https://raw.githubusercontent.com/ppy/osu/master/LICENCE
using System;
using System.Collections.Generic;
using OpenTK;
namespace osu.Game.Rulesets.Objects
{
public readonly ref struct BezierApproximator
{
private readonly int count;
private readonly ReadOnlySpan<Vector2> controlPoints;
private readonly Vector2[] subdivisionBuffer1;
private readonly Vector2[] subdivisionBuffer2;
private const float tolerance = 0.25f;
private const float tolerance_sq = tolerance * tolerance;
public BezierApproximator(ReadOnlySpan<Vector2> controlPoints)
{
this.controlPoints = controlPoints;
count = controlPoints.Length;
subdivisionBuffer1 = new Vector2[count];
subdivisionBuffer2 = new Vector2[count * 2 - 1];
}
/// <summary>
/// Make sure the 2nd order derivative (approximated using finite elements) is within tolerable bounds.
/// NOTE: The 2nd order derivative of a 2d curve represents its curvature, so intuitively this function
/// checks (as the name suggests) whether our approximation is _locally_ "flat". More curvy parts
/// need to have a denser approximation to be more "flat".
/// </summary>
/// <param name="controlPoints">The control points to check for flatness.</param>
/// <returns>Whether the control points are flat enough.</returns>
private static bool isFlatEnough(Vector2[] controlPoints)
{
for (int i = 1; i < controlPoints.Length - 1; i++)
if ((controlPoints[i - 1] - 2 * controlPoints[i] + controlPoints[i + 1]).LengthSquared > tolerance_sq * 4)
return false;
return true;
}
/// <summary>
/// Subdivides n control points representing a bezier curve into 2 sets of n control points, each
/// describing a bezier curve equivalent to a half of the original curve. Effectively this splits
/// the original curve into 2 curves which result in the original curve when pieced back together.
/// </summary>
/// <param name="controlPoints">The control points to split.</param>
/// <param name="l">Output: The control points corresponding to the left half of the curve.</param>
/// <param name="r">Output: The control points corresponding to the right half of the curve.</param>
private void subdivide(Vector2[] controlPoints, Vector2[] l, Vector2[] r)
{
Vector2[] midpoints = subdivisionBuffer1;
for (int i = 0; i < count; ++i)
midpoints[i] = controlPoints[i];
for (int i = 0; i < count; i++)
{
l[i] = midpoints[0];
r[count - i - 1] = midpoints[count - i - 1];
for (int j = 0; j < count - i - 1; j++)
midpoints[j] = (midpoints[j] + midpoints[j + 1]) / 2;
}
}
/// <summary>
/// This uses <a href="https://en.wikipedia.org/wiki/De_Casteljau%27s_algorithm">De Casteljau's algorithm</a> to obtain an optimal
/// piecewise-linear approximation of the bezier curve with the same amount of points as there are control points.
/// </summary>
/// <param name="controlPoints">The control points describing the bezier curve to be approximated.</param>
/// <param name="output">The points representing the resulting piecewise-linear approximation.</param>
private void approximate(Vector2[] controlPoints, List<Vector2> output)
{
Vector2[] l = subdivisionBuffer2;
Vector2[] r = subdivisionBuffer1;
subdivide(controlPoints, l, r);
for (int i = 0; i < count - 1; ++i)
l[count + i] = r[i + 1];
output.Add(controlPoints[0]);
for (int i = 1; i < count - 1; ++i)
{
int index = 2 * i;
Vector2 p = 0.25f * (l[index - 1] + 2 * l[index] + l[index + 1]);
output.Add(p);
}
}
/// <summary>
/// Creates a piecewise-linear approximation of a bezier curve, by adaptively repeatedly subdividing
/// the control points until their approximation error vanishes below a given threshold.
/// </summary>
/// <returns>A list of vectors representing the piecewise-linear approximation.</returns>
public List<Vector2> CreateBezier()
{
List<Vector2> output = new List<Vector2>();
if (count == 0)
return output;
Stack<Vector2[]> toFlatten = new Stack<Vector2[]>();
Stack<Vector2[]> freeBuffers = new Stack<Vector2[]>();
// "toFlatten" contains all the curves which are not yet approximated well enough.
// We use a stack to emulate recursion without the risk of running into a stack overflow.
// (More specifically, we iteratively and adaptively refine our curve with a
// <a href="https://en.wikipedia.org/wiki/Depth-first_search">Depth-first search</a>
// over the tree resulting from the subdivisions we make.)
toFlatten.Push(controlPoints.ToArray());
Vector2[] leftChild = subdivisionBuffer2;
while (toFlatten.Count > 0)
{
Vector2[] parent = toFlatten.Pop();
if (isFlatEnough(parent))
{
// If the control points we currently operate on are sufficiently "flat", we use
// an extension to De Casteljau's algorithm to obtain a piecewise-linear approximation
// of the bezier curve represented by our control points, consisting of the same amount
// of points as there are control points.
approximate(parent, output);
freeBuffers.Push(parent);
continue;
}
// If we do not yet have a sufficiently "flat" (in other words, detailed) approximation we keep
// subdividing the curve we are currently operating on.
Vector2[] rightChild = freeBuffers.Count > 0 ? freeBuffers.Pop() : new Vector2[count];
subdivide(parent, leftChild, rightChild);
// We re-use the buffer of the parent for one of the children, so that we save one allocation per iteration.
for (int i = 0; i < count; ++i)
parent[i] = leftChild[i];
toFlatten.Push(rightChild);
toFlatten.Push(parent);
}
output.Add(controlPoints[count - 1]);
return output;
}
}
}