| Index: ui/gfx/geometry/cubic_bezier.cc
|
| diff --git a/ui/gfx/geometry/cubic_bezier.cc b/ui/gfx/geometry/cubic_bezier.cc
|
| index fe6dfcc7ff1af6c44033845df6dadf3232dff1db..b69596fdace3b87ad1ef2062c4566e8d009610f5 100644
|
| --- a/ui/gfx/geometry/cubic_bezier.cc
|
| +++ b/ui/gfx/geometry/cubic_bezier.cc
|
| @@ -4,136 +4,95 @@
|
|
|
| #include "ui/gfx/geometry/cubic_bezier.h"
|
|
|
| -#include <algorithm>
|
| -#include <cmath>
|
| -
|
| -#include "base/logging.h"
|
| -
|
| namespace gfx {
|
|
|
| -namespace {
|
| -
|
| static const double kBezierEpsilon = 1e-7;
|
| -static const int MAX_STEPS = 30;
|
| -
|
| -static double eval_bezier(double p1, double p2, double t) {
|
| - const double p1_times_3 = 3.0 * p1;
|
| - const double p2_times_3 = 3.0 * p2;
|
| - const double h3 = p1_times_3;
|
| - const double h1 = p1_times_3 - p2_times_3 + 1.0;
|
| - const double h2 = p2_times_3 - 6.0 * p1;
|
| - return t * (t * (t * h1 + h2) + h3);
|
| -}
|
|
|
| -static double eval_bezier_derivative(double p1, double p2, double t) {
|
| - const double h1 = 9.0 * p1 - 9.0 * p2 + 3.0;
|
| - const double h2 = 6.0 * p2 - 12.0 * p1;
|
| - const double h3 = 3.0 * p1;
|
| - return t * (t * h1 + h2) + h3;
|
| +double CubicBezier::GetDefaultEpsilon() {
|
| + return kBezierEpsilon;
|
| }
|
|
|
| -// Finds t such that eval_bezier(x1, x2, t) = x.
|
| -// There is a unique solution if x1 and x2 lie within (0, 1).
|
| -static double bezier_interp(double x1,
|
| - double x2,
|
| - double x) {
|
| - DCHECK_GE(1.0, x1);
|
| - DCHECK_LE(0.0, x1);
|
| - DCHECK_GE(1.0, x2);
|
| - DCHECK_LE(0.0, x2);
|
| -
|
| - x1 = std::min(std::max(x1, 0.0), 1.0);
|
| - x2 = std::min(std::max(x2, 0.0), 1.0);
|
| - x = std::min(std::max(x, 0.0), 1.0);
|
| -
|
| - // We're just going to do bisection for now (for simplicity), but we could
|
| - // easily do some newton steps if this turns out to be a bottleneck.
|
| - double t = 0.0;
|
| - double step = 1.0;
|
| - for (int i = 0; i < MAX_STEPS; ++i, step *= 0.5) {
|
| - const double error = eval_bezier(x1, x2, t) - x;
|
| - if (std::abs(error) < kBezierEpsilon)
|
| - break;
|
| - t += error > 0.0 ? -step : step;
|
| - }
|
| -
|
| - // We should have terminated the above loop because we got close to x, not
|
| - // because we exceeded MAX_STEPS. Do a DCHECK here to confirm.
|
| - DCHECK_GT(kBezierEpsilon, std::abs(eval_bezier(x1, x2, t) - x));
|
| -
|
| - return t;
|
| +CubicBezier::CubicBezier(double p1x, double p1y, double p2x, double p2y) {
|
| + InitCoefficients(p1x, p1y, p2x, p2y);
|
| + InitGradients(p1x, p1y, p2x, p2y);
|
| + InitRange(p1y, p2y);
|
| }
|
|
|
| -} // namespace
|
| -
|
| -CubicBezier::CubicBezier(double x1, double y1, double x2, double y2)
|
| - : x1_(x1),
|
| - y1_(y1),
|
| - x2_(x2),
|
| - y2_(y2) {
|
| - InitGradients();
|
| +void CubicBezier::InitCoefficients(double p1x,
|
| + double p1y,
|
| + double p2x,
|
| + double p2y) {
|
| + // Calculate the polynomial coefficients, implicit first and last control
|
| + // points are (0,0) and (1,1).
|
| + cx = 3.0 * p1x;
|
| + bx = 3.0 * (p2x - p1x) - cx;
|
| + ax = 1.0 - cx - bx;
|
| +
|
| + cy = 3.0 * p1y;
|
| + by = 3.0 * (p2y - p1y) - cy;
|
| + ay = 1.0 - cy - by;
|
| }
|
|
|
| -CubicBezier::~CubicBezier() {
|
| -}
|
| -
|
| -void CubicBezier::InitGradients() {
|
| - if (x1_ > 0)
|
| - start_gradient_ = y1_ / x1_;
|
| - else if (!y1_ && x2_ > 0)
|
| - start_gradient_ = y2_ / x2_;
|
| +void CubicBezier::InitGradients(double p1x,
|
| + double p1y,
|
| + double p2x,
|
| + double p2y) {
|
| + // End-point gradients are used to calculate timing function results
|
| + // outside the range [0, 1].
|
| + //
|
| + // There are three possibilities for the gradient at each end:
|
| + // (1) the closest control point is not horizontally coincident with regard to
|
| + // (0, 0) or (1, 1). In this case the line between the end point and
|
| + // the control point is tangent to the bezier at the end point.
|
| + // (2) the closest control point is coincident with the end point. In
|
| + // this case the line between the end point and the far control
|
| + // point is tangent to the bezier at the end point.
|
| + // (3) the closest control point is horizontally coincident with the end
|
| + // point, but vertically distinct. In this case the gradient at the
|
| + // end point is Infinite. However, this causes issues when
|
| + // interpolating. As a result, we break down to a simple case of
|
| + // 0 gradient under these conditions.
|
| +
|
| + if (p1x > 0)
|
| + start_gradient_ = p1y / p1x;
|
| + else if (!p1y && p2x > 0)
|
| + start_gradient_ = p2y / p2x;
|
| else
|
| start_gradient_ = 0;
|
|
|
| - if (x2_ < 1)
|
| - end_gradient_ = (y2_ - 1) / (x2_ - 1);
|
| - else if (x2_ == 1 && x1_ < 1)
|
| - end_gradient_ = (y1_ - 1) / (x1_ - 1);
|
| + if (p2x < 1)
|
| + end_gradient_ = (p2y - 1) / (p2x - 1);
|
| + else if (p2x == 1 && p1x < 1)
|
| + end_gradient_ = (p1y - 1) / (p1x - 1);
|
| else
|
| end_gradient_ = 0;
|
| }
|
|
|
| -double CubicBezier::Solve(double x) const {
|
| - if (x < 0)
|
| - return start_gradient_ * x;
|
| - if (x > 1)
|
| - return 1.0 + end_gradient_ * (x - 1.0);
|
| -
|
| - return eval_bezier(y1_, y2_, bezier_interp(x1_, x2_, x));
|
| -}
|
| -
|
| -double CubicBezier::Slope(double x) const {
|
| - double t = bezier_interp(x1_, x2_, x);
|
| - double dx_dt = eval_bezier_derivative(x1_, x2_, t);
|
| - double dy_dt = eval_bezier_derivative(y1_, y2_, t);
|
| - return dy_dt / dx_dt;
|
| -}
|
| -
|
| -void CubicBezier::Range(double* min, double* max) const {
|
| - *min = 0;
|
| - *max = 1;
|
| - if (0 <= y1_ && y1_ < 1 && 0 <= y2_ && y2_ <= 1)
|
| +void CubicBezier::InitRange(double p1y, double p2y) {
|
| + range_min_ = 0;
|
| + range_max_ = 1;
|
| + if (0 <= p1y && p1y < 1 && 0 <= p2y && p2y <= 1)
|
| return;
|
|
|
| - // Represent the function's derivative in the form at^2 + bt + c.
|
| + // Represent the function's derivative in the form at^2 + bt + c
|
| + // as in sampleCurveDerivativeY.
|
| // (Technically this is (dy/dt)*(1/3), which is suitable for finding zeros
|
| // but does not actually give the slope of the curve.)
|
| - double a = 3 * (y1_ - y2_) + 1;
|
| - double b = 2 * (y2_ - 2 * y1_);
|
| - double c = y1_;
|
| + const double a = 3.0 * ay;
|
| + const double b = 2.0 * by;
|
| + const double c = cy;
|
|
|
| // Check if the derivative is constant.
|
| - if (std::abs(a) < kBezierEpsilon &&
|
| - std::abs(b) < kBezierEpsilon)
|
| + if (std::abs(a) < kBezierEpsilon && std::abs(b) < kBezierEpsilon)
|
| return;
|
|
|
| // Zeros of the function's derivative.
|
| - double t_1 = 0;
|
| - double t_2 = 0;
|
| + double t1 = 0;
|
| + double t2 = 0;
|
|
|
| if (std::abs(a) < kBezierEpsilon) {
|
| // The function's derivative is linear.
|
| - t_1 = -c / b;
|
| + t1 = -c / b;
|
| } else {
|
| // The function's derivative is a quadratic. We find the zeros of this
|
| // quadratic using the quadratic formula.
|
| @@ -141,21 +100,21 @@ void CubicBezier::Range(double* min, double* max) const {
|
| if (discriminant < 0)
|
| return;
|
| double discriminant_sqrt = sqrt(discriminant);
|
| - t_1 = (-b + discriminant_sqrt) / (2 * a);
|
| - t_2 = (-b - discriminant_sqrt) / (2 * a);
|
| + t1 = (-b + discriminant_sqrt) / (2 * a);
|
| + t2 = (-b - discriminant_sqrt) / (2 * a);
|
| }
|
|
|
| - double sol_1 = 0;
|
| - double sol_2 = 0;
|
| + double sol1 = 0;
|
| + double sol2 = 0;
|
|
|
| - if (0 < t_1 && t_1 < 1)
|
| - sol_1 = eval_bezier(y1_, y2_, t_1);
|
| + if (0 < t1 && t1 < 1)
|
| + sol1 = SampleCurveY(t1);
|
|
|
| - if (0 < t_2 && t_2 < 1)
|
| - sol_2 = eval_bezier(y1_, y2_, t_2);
|
| + if (0 < t2 && t2 < 1)
|
| + sol2 = SampleCurveY(t2);
|
|
|
| - *min = std::min(std::min(*min, sol_1), sol_2);
|
| - *max = std::max(std::max(*max, sol_1), sol_2);
|
| + range_min_ = std::min(std::min(range_min_, sol1), sol2);
|
| + range_max_ = std::max(std::max(range_max_, sol1), sol2);
|
| }
|
|
|
| } // namespace gfx
|
|
|