mirror of
https://github.com/thorvg/thorvg.git
synced 2025-06-07 13:13:23 +00:00
140 lines
No EOL
5.1 KiB
C++
140 lines
No EOL
5.1 KiB
C++
/*
|
|
* Copyright (c) 2023 - 2025 the ThorVG project. All rights reserved.
|
|
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to deal
|
|
* in the Software without restriction, including without limitation the rights
|
|
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
|
* copies of the Software, and to permit persons to whom the Software is
|
|
* furnished to do so, subject to the following conditions:
|
|
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
* SOFTWARE.
|
|
*/
|
|
|
|
/* This Source Code Form is subject to the terms of the Mozilla Public
|
|
* License, v. 2.0. If a copy of the MPL was not distributed with this
|
|
* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
|
|
|
|
#include <string.h>
|
|
#include "tvgCommon.h"
|
|
#include "tvgMath.h"
|
|
#include "tvgLottieInterpolator.h"
|
|
|
|
|
|
/************************************************************************/
|
|
/* Internal Class Implementation */
|
|
/************************************************************************/
|
|
|
|
#define NEWTON_MIN_SLOPE 0.02f
|
|
#define NEWTON_ITERATIONS 4
|
|
#define SUBDIVISION_PRECISION 0.0000001f
|
|
#define SUBDIVISION_MAX_ITERATIONS 10
|
|
|
|
|
|
static inline float _constA(float aA1, float aA2) { return 1.0f - 3.0f * aA2 + 3.0f * aA1; }
|
|
static inline float _constB(float aA1, float aA2) { return 3.0f * aA2 - 6.0f * aA1; }
|
|
static inline float _constC(float aA1) { return 3.0f * aA1; }
|
|
|
|
|
|
static inline float _getSlope(float t, float aA1, float aA2)
|
|
{
|
|
return 3.0f * _constA(aA1, aA2) * t * t + 2.0f * _constB(aA1, aA2) * t + _constC(aA1);
|
|
}
|
|
|
|
|
|
static inline float _calcBezier(float t, float aA1, float aA2)
|
|
{
|
|
return ((_constA(aA1, aA2) * t + _constB(aA1, aA2)) * t + _constC(aA1)) * t;
|
|
}
|
|
|
|
|
|
float LottieInterpolator::getTForX(float aX)
|
|
{
|
|
//Find interval where t lies
|
|
auto intervalStart = 0.0f;
|
|
auto currentSample = &samples[1];
|
|
auto lastSample = &samples[SPLINE_TABLE_SIZE - 1];
|
|
|
|
for (; currentSample != lastSample && *currentSample <= aX; ++currentSample) {
|
|
intervalStart += SAMPLE_STEP_SIZE;
|
|
}
|
|
|
|
--currentSample; // t now lies between *currentSample and *currentSample+1
|
|
|
|
// Interpolate to provide an initial guess for t
|
|
auto dist = (aX - *currentSample) / (*(currentSample + 1) - *currentSample);
|
|
auto guessForT = intervalStart + dist * SAMPLE_STEP_SIZE;
|
|
|
|
// Check the slope to see what strategy to use. If the slope is too small
|
|
// Newton-Raphson iteration won't converge on a root so we use bisection
|
|
// instead.
|
|
auto initialSlope = _getSlope(guessForT, outTangent.x, inTangent.x);
|
|
if (initialSlope >= NEWTON_MIN_SLOPE) return NewtonRaphsonIterate(aX, guessForT);
|
|
else if (initialSlope == 0.0) return guessForT;
|
|
else return binarySubdivide(aX, intervalStart, intervalStart + SAMPLE_STEP_SIZE);
|
|
}
|
|
|
|
|
|
float LottieInterpolator::binarySubdivide(float aX, float aA, float aB)
|
|
{
|
|
float x, t;
|
|
int i = 0;
|
|
|
|
do {
|
|
t = aA + (aB - aA) / 2.0f;
|
|
x = _calcBezier(t, outTangent.x, inTangent.x) - aX;
|
|
if (x > 0.0f) aB = t;
|
|
else aA = t;
|
|
} while (fabsf(x) > SUBDIVISION_PRECISION && ++i < SUBDIVISION_MAX_ITERATIONS);
|
|
return t;
|
|
}
|
|
|
|
|
|
float LottieInterpolator::NewtonRaphsonIterate(float aX, float aGuessT)
|
|
{
|
|
// Refine guess with Newton-Raphson iteration
|
|
for (int i = 0; i < NEWTON_ITERATIONS; ++i) {
|
|
// We're trying to find where f(t) = aX,
|
|
// so we're actually looking for a root for: CalcBezier(t) - aX
|
|
auto currentX = _calcBezier(aGuessT, outTangent.x, inTangent.x) - aX;
|
|
auto currentSlope = _getSlope(aGuessT, outTangent.x, inTangent.x);
|
|
if (currentSlope == 0.0f) return aGuessT;
|
|
aGuessT -= currentX / currentSlope;
|
|
}
|
|
return aGuessT;
|
|
}
|
|
|
|
|
|
/************************************************************************/
|
|
/* External Class Implementation */
|
|
/************************************************************************/
|
|
|
|
float LottieInterpolator::progress(float t)
|
|
{
|
|
if (outTangent.x == outTangent.y && inTangent.x == inTangent.y) return t;
|
|
return _calcBezier(getTForX(t), outTangent.y, inTangent.y);
|
|
}
|
|
|
|
|
|
void LottieInterpolator::set(const char* key, Point& inTangent, Point& outTangent)
|
|
{
|
|
if (key) this->key = strdup(key);
|
|
this->inTangent = inTangent;
|
|
this->outTangent = outTangent;
|
|
|
|
if (outTangent.x == outTangent.y && inTangent.x == inTangent.y) return;
|
|
|
|
//calculates sample values
|
|
for (int i = 0; i < SPLINE_TABLE_SIZE; ++i) {
|
|
samples[i] = _calcBezier(float(i) * SAMPLE_STEP_SIZE, outTangent.x, inTangent.x);
|
|
}
|
|
} |