(function(f){if(typeof exports==="object"&&typeof module!=="undefined"){module.exports=f()}else if(typeof define==="function"&&define.amd){define([],f)}else{var g;if(typeof window!=="undefined"){g=window}else if(typeof global!=="undefined"){g=global}else if(typeof self!=="undefined"){g=self}else{g=this}g.BezierEasing = f()}})(function(){var define,module,exports;return (function(){function r(e,n,t){function o(i,f){if(!n[i]){if(!e[i]){var c="function"==typeof require&&require;if(!f&&c)return c(i,!0);if(u)return u(i,!0);var a=new Error("Cannot find module '"+i+"'");throw a.code="MODULE_NOT_FOUND",a}var p=n[i]={exports:{}};e[i][0].call(p.exports,function(r){var n=e[i][1][r];return o(n||r)},p,p.exports,r,e,n,t)}return n[i].exports}for(var u="function"==typeof require&&require,i=0;i 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; } function LinearEasing (x) { return x; } module.exports = function bezier (mX1, mY1, mX2, mY2) { if (!(0 <= mX1 && mX1 <= 1 && 0 <= mX2 && mX2 <= 1)) { throw new Error('bezier x values must be in [0, 1] range'); } if (mX1 === mY1 && mX2 === mY2) { return LinearEasing; } // Precompute samples table var sampleValues = float32ArraySupported ? new Float32Array(kSplineTableSize) : new Array(kSplineTableSize); for (var i = 0; i < kSplineTableSize; ++i) { sampleValues[i] = calcBezier(i * kSampleStepSize, mX1, mX2); } function getTForX (aX) { var intervalStart = 0.0; var currentSample = 1; var lastSample = kSplineTableSize - 1; for (; currentSample !== lastSample && sampleValues[currentSample] <= aX; ++currentSample) { intervalStart += kSampleStepSize; } --currentSample; // Interpolate to provide an initial guess for t var dist = (aX - sampleValues[currentSample]) / (sampleValues[currentSample + 1] - sampleValues[currentSample]); var guessForT = intervalStart + dist * kSampleStepSize; var initialSlope = getSlope(guessForT, mX1, mX2); if (initialSlope >= NEWTON_MIN_SLOPE) { return newtonRaphsonIterate(aX, guessForT, mX1, mX2); } else if (initialSlope === 0.0) { return guessForT; } else { return binarySubdivide(aX, intervalStart, intervalStart + kSampleStepSize, mX1, mX2); } } return function BezierEasing (x) { // Because JavaScript number are imprecise, we should guarantee the extremes are right. if (x === 0) { return 0; } if (x === 1) { return 1; } return calcBezier(getTForX(x), mY1, mY2); }; }; },{}]},{},[1])(1) });