158 lines
4.8 KiB
Plaintext
158 lines
4.8 KiB
Plaintext
/* eslint-disable */
|
||
const BezierFactory = (function () {
|
||
/**
|
||
* BezierEasing - use bezier curve for transition easing function
|
||
* by Gaëtan Renaudeau 2014 - 2015 – MIT License
|
||
*
|
||
* Credits: is based on Firefox's nsSMILKeySpline.cpp
|
||
* Usage:
|
||
* var spline = BezierEasing([ 0.25, 0.1, 0.25, 1.0 ])
|
||
* spline.get(x) => returns the easing value | x must be in [0, 1] range
|
||
*
|
||
*/
|
||
|
||
var ob = {};
|
||
ob.getBezierEasing = getBezierEasing;
|
||
var beziers = {};
|
||
|
||
function getBezierEasing(a, b, c, d, nm) {
|
||
var str = nm || ('bez_' + a + '_' + b + '_' + c + '_' + d).replace(/\./g, 'p');
|
||
if (beziers[str]) {
|
||
return beziers[str];
|
||
}
|
||
var bezEasing = new BezierEasing([a, b, c, d]);
|
||
beziers[str] = bezEasing;
|
||
return bezEasing;
|
||
}
|
||
|
||
// These values are established by empiricism with tests (tradeoff: performance VS precision)
|
||
var NEWTON_ITERATIONS = 4;
|
||
var NEWTON_MIN_SLOPE = 0.001;
|
||
var SUBDIVISION_PRECISION = 0.0000001;
|
||
var SUBDIVISION_MAX_ITERATIONS = 10;
|
||
|
||
var kSplineTableSize = 11;
|
||
var kSampleStepSize = 1.0 / (kSplineTableSize - 1.0);
|
||
|
||
var float32ArraySupported = typeof Float32Array === 'function';
|
||
|
||
function A(aA1, aA2) { return 1.0 - 3.0 * aA2 + 3.0 * aA1; }
|
||
function B(aA1, aA2) { return 3.0 * aA2 - 6.0 * aA1; }
|
||
function C(aA1) { return 3.0 * aA1; }
|
||
|
||
// Returns x(t) given t, x1, and x2, or y(t) given t, y1, and y2.
|
||
function calcBezier(aT, aA1, aA2) {
|
||
return ((A(aA1, aA2) * aT + B(aA1, aA2)) * aT + C(aA1)) * aT;
|
||
}
|
||
|
||
// Returns dx/dt given t, x1, and x2, or dy/dt given t, y1, and y2.
|
||
function getSlope(aT, aA1, aA2) {
|
||
return 3.0 * A(aA1, aA2) * aT * aT + 2.0 * B(aA1, aA2) * aT + C(aA1);
|
||
}
|
||
|
||
function binarySubdivide(aX, aA, aB, mX1, mX2) {
|
||
var currentX,
|
||
currentT,
|
||
i = 0;
|
||
do {
|
||
currentT = aA + (aB - aA) / 2.0;
|
||
currentX = calcBezier(currentT, mX1, mX2) - aX;
|
||
if (currentX > 0.0) {
|
||
aB = currentT;
|
||
} else {
|
||
aA = currentT;
|
||
}
|
||
} while (Math.abs(currentX) > SUBDIVISION_PRECISION && ++i < SUBDIVISION_MAX_ITERATIONS);
|
||
return currentT;
|
||
}
|
||
|
||
function newtonRaphsonIterate(aX, aGuessT, mX1, mX2) {
|
||
for (var i = 0; i < NEWTON_ITERATIONS; ++i) {
|
||
var currentSlope = getSlope(aGuessT, mX1, mX2);
|
||
if (currentSlope === 0.0) return aGuessT;
|
||
var currentX = calcBezier(aGuessT, mX1, mX2) - aX;
|
||
aGuessT -= currentX / currentSlope;
|
||
}
|
||
return aGuessT;
|
||
}
|
||
|
||
/**
|
||
* points is an array of [ mX1, mY1, mX2, mY2 ]
|
||
*/
|
||
function BezierEasing(points) {
|
||
this._p = points;
|
||
this._mSampleValues = float32ArraySupported ? new Float32Array(kSplineTableSize) : new Array(kSplineTableSize);
|
||
this._precomputed = false;
|
||
|
||
this.get = this.get.bind(this);
|
||
}
|
||
|
||
BezierEasing.prototype = {
|
||
|
||
get: function (x) {
|
||
var mX1 = this._p[0],
|
||
mY1 = this._p[1],
|
||
mX2 = this._p[2],
|
||
mY2 = this._p[3];
|
||
if (!this._precomputed) this._precompute();
|
||
if (mX1 === mY1 && mX2 === mY2) return x; // linear
|
||
// Because JavaScript number are imprecise, we should guarantee the extremes are right.
|
||
if (x === 0) return 0;
|
||
if (x === 1) return 1;
|
||
return calcBezier(this._getTForX(x), mY1, mY2);
|
||
},
|
||
|
||
// Private part
|
||
|
||
_precompute: function () {
|
||
var mX1 = this._p[0],
|
||
mY1 = this._p[1],
|
||
mX2 = this._p[2],
|
||
mY2 = this._p[3];
|
||
this._precomputed = true;
|
||
if (mX1 !== mY1 || mX2 !== mY2) { this._calcSampleValues(); }
|
||
},
|
||
|
||
_calcSampleValues: function () {
|
||
var mX1 = this._p[0],
|
||
mX2 = this._p[2];
|
||
for (var i = 0; i < kSplineTableSize; ++i) {
|
||
this._mSampleValues[i] = calcBezier(i * kSampleStepSize, mX1, mX2);
|
||
}
|
||
},
|
||
|
||
/**
|
||
* getTForX chose the fastest heuristic to determine the percentage value precisely from a given X projection.
|
||
*/
|
||
_getTForX: function (aX) {
|
||
var mX1 = this._p[0],
|
||
mX2 = this._p[2],
|
||
mSampleValues = this._mSampleValues;
|
||
|
||
var intervalStart = 0.0;
|
||
var currentSample = 1;
|
||
var lastSample = kSplineTableSize - 1;
|
||
|
||
for (; currentSample !== lastSample && mSampleValues[currentSample] <= aX; ++currentSample) {
|
||
intervalStart += kSampleStepSize;
|
||
}
|
||
--currentSample;
|
||
|
||
// Interpolate to provide an initial guess for t
|
||
var dist = (aX - mSampleValues[currentSample]) / (mSampleValues[currentSample + 1] - mSampleValues[currentSample]);
|
||
var guessForT = intervalStart + dist * kSampleStepSize;
|
||
|
||
var initialSlope = getSlope(guessForT, mX1, mX2);
|
||
if (initialSlope >= NEWTON_MIN_SLOPE) {
|
||
return newtonRaphsonIterate(aX, guessForT, mX1, mX2);
|
||
} if (initialSlope === 0.0) {
|
||
return guessForT;
|
||
}
|
||
return binarySubdivide(aX, intervalStart, intervalStart + kSampleStepSize, mX1, mX2);
|
||
},
|
||
};
|
||
|
||
return ob;
|
||
}());
|
||
|
||
export default BezierFactory; |