2020-05-14 01:18:46 +00:00
|
|
|
/*
|
|
|
|
* Copyright 2020 Google Inc.
|
|
|
|
*
|
|
|
|
* Use of this source code is governed by a BSD-style license that can be
|
|
|
|
* found in the LICENSE file.
|
|
|
|
*/
|
|
|
|
|
|
|
|
#include "include/utils/SkRandom.h"
|
|
|
|
#include "src/core/SkGeometry.h"
|
|
|
|
#include "src/gpu/tessellate/GrWangsFormula.h"
|
|
|
|
#include "tests/Test.h"
|
|
|
|
|
|
|
|
constexpr static int kIntolerance = 4; // 1/4 pixel max error.
|
|
|
|
|
|
|
|
const SkPoint kSerp[4] = {
|
|
|
|
{285.625f, 499.687f}, {411.625f, 808.188f}, {1064.62f, 135.688f}, {1042.63f, 585.187f}};
|
|
|
|
|
|
|
|
const SkPoint kLoop[4] = {
|
|
|
|
{635.625f, 614.687f}, {171.625f, 236.188f}, {1064.62f, 135.688f}, {516.625f, 570.187f}};
|
|
|
|
|
|
|
|
const SkPoint kQuad[4] = {
|
|
|
|
{460.625f, 557.187f}, {707.121f, 209.688f}, {779.628f, 577.687f}};
|
|
|
|
|
|
|
|
DEF_TEST(WangsFormula_nextlog2, r) {
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits<float>::infinity()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits<float>::max()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-1000.0f) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-0.1f) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits<float>::min()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits<float>::denorm_min()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(0.0f) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits<float>::denorm_min()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits<float>::min()) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(0.1f) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(1.0f) == 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(1.1f) == 1);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(2.0f) == 1);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(2.1f) == 2);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(3.0f) == 2);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(3.1f) == 2);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(4.0f) == 2);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(4.1f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(5.0f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(5.1f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(6.0f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(6.1f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(7.0f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(7.1f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(8.0f) == 3);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(8.1f) == 4);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(9.0f) == 4);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(9.1f) == 4);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits<float>::max()) == 128);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits<float>::infinity()) > 0);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits<float>::quiet_NaN()) >= 0);
|
|
|
|
|
|
|
|
for (int i = 0; i < 100; ++i) {
|
|
|
|
float pow2 = std::ldexp(1, i);
|
|
|
|
float epsilon = std::ldexp(SK_ScalarNearlyZero, i);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(pow2) == i);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(pow2 + epsilon) == i + 1);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::nextlog2(pow2 - epsilon) == i);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void for_random_matrices(SkRandom* rand, std::function<void(const SkMatrix&)> f) {
|
|
|
|
SkMatrix m;
|
|
|
|
m.setIdentity();
|
|
|
|
f(m);
|
|
|
|
|
|
|
|
for (int i = -10; i <= 30; ++i) {
|
|
|
|
for (int j = -10; j <= 30; ++j) {
|
|
|
|
m.setScaleX(std::ldexp(1 + rand->nextF(), i));
|
|
|
|
m.setSkewX(0);
|
|
|
|
m.setSkewY(0);
|
|
|
|
m.setScaleY(std::ldexp(1 + rand->nextF(), j));
|
|
|
|
f(m);
|
|
|
|
|
|
|
|
m.setScaleX(std::ldexp(1 + rand->nextF(), i));
|
|
|
|
m.setSkewX(std::ldexp(1 + rand->nextF(), (j + i) / 2));
|
|
|
|
m.setSkewY(std::ldexp(1 + rand->nextF(), (j + i) / 2));
|
|
|
|
m.setScaleY(std::ldexp(1 + rand->nextF(), j));
|
|
|
|
f(m);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
void for_random_beziers(int numPoints, SkRandom* rand, std::function<void(const SkPoint[])> f) {
|
|
|
|
SkASSERT(numPoints <= 4);
|
|
|
|
SkPoint pts[4];
|
|
|
|
for (int i = -10; i <= 30; ++i) {
|
|
|
|
for (int j = 0; j < numPoints; ++j) {
|
|
|
|
pts[j].set(std::ldexp(1 + rand->nextF(), i), std::ldexp(1 + rand->nextF(), i));
|
|
|
|
}
|
|
|
|
f(pts);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Ensure the optimized "*_log2" versions return the same value as ceil(std::log2(f)).
|
|
|
|
DEF_TEST(WangsFormula_log2, r) {
|
|
|
|
// Constructs a cubic such that the 'length' term in wang's formula == term.
|
|
|
|
//
|
|
|
|
// f = sqrt(k * length(max(abs(p0 - p1*2 + p2),
|
|
|
|
// abs(p1 - p2*2 + p3))));
|
|
|
|
auto setupCubicLengthTerm = [](int seed, SkPoint pts[], float term) {
|
|
|
|
memset(pts, 0, sizeof(SkPoint) * 4);
|
|
|
|
|
|
|
|
SkPoint term2d = (seed & 1) ?
|
|
|
|
SkPoint::Make(term, 0) : SkPoint::Make(.5f, std::sqrt(3)/2) * term;
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
if (seed & 1) {
|
|
|
|
term2d.fX = -term2d.fX;
|
|
|
|
}
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
if (seed & 1) {
|
|
|
|
std::swap(term2d.fX, term2d.fY);
|
|
|
|
}
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
switch (seed % 4) {
|
|
|
|
case 0:
|
|
|
|
pts[0] = term2d;
|
|
|
|
pts[3] = term2d * .75f;
|
|
|
|
return;
|
|
|
|
case 1:
|
|
|
|
pts[1] = term2d * -.5f;
|
|
|
|
return;
|
|
|
|
case 2:
|
|
|
|
pts[1] = term2d * -.5f;
|
|
|
|
return;
|
|
|
|
case 3:
|
|
|
|
pts[3] = term2d;
|
|
|
|
pts[0] = term2d * .75f;
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
// Constructs a quadratic such that the 'length' term in wang's formula == term.
|
|
|
|
//
|
|
|
|
// f = sqrt(k * length(p0 - p1*2 + p2));
|
|
|
|
auto setupQuadraticLengthTerm = [](int seed, SkPoint pts[], float term) {
|
|
|
|
memset(pts, 0, sizeof(SkPoint) * 3);
|
|
|
|
|
|
|
|
SkPoint term2d = (seed & 1) ?
|
|
|
|
SkPoint::Make(term, 0) : SkPoint::Make(.5f, std::sqrt(3)/2) * term;
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
if (seed & 1) {
|
|
|
|
term2d.fX = -term2d.fX;
|
|
|
|
}
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
if (seed & 1) {
|
|
|
|
std::swap(term2d.fX, term2d.fY);
|
|
|
|
}
|
|
|
|
seed >>= 1;
|
|
|
|
|
|
|
|
switch (seed % 3) {
|
|
|
|
case 0:
|
|
|
|
pts[0] = term2d;
|
|
|
|
return;
|
|
|
|
case 1:
|
|
|
|
pts[1] = term2d * -.5f;
|
|
|
|
return;
|
|
|
|
case 2:
|
|
|
|
pts[2] = term2d;
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
for (int level = 0; level < 30; ++level) {
|
|
|
|
float epsilon = std::ldexp(SK_ScalarNearlyZero, level * 2);
|
|
|
|
SkPoint pts[4];
|
|
|
|
|
|
|
|
{
|
|
|
|
// Test cubic boundaries.
|
|
|
|
// f = sqrt(k * length(max(abs(p0 - p1*2 + p2),
|
|
|
|
// abs(p1 - p2*2 + p3))));
|
|
|
|
constexpr static float k = (3 * 2) / (8 * (1.f/kIntolerance));
|
|
|
|
float x = std::ldexp(1, level * 2) / k;
|
|
|
|
setupCubicLengthTerm(level << 1, pts, x - epsilon);
|
|
|
|
REPORTER_ASSERT(r,
|
|
|
|
std::ceil(std::log2(GrWangsFormula::cubic(kIntolerance, pts))) == level);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::cubic_log2(kIntolerance, pts) == level);
|
|
|
|
setupCubicLengthTerm(level << 1, pts, x + epsilon);
|
|
|
|
REPORTER_ASSERT(r,
|
|
|
|
std::ceil(std::log2(GrWangsFormula::cubic(kIntolerance, pts))) == level + 1);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::cubic_log2(kIntolerance, pts) == level + 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
{
|
|
|
|
// Test quadratic boundaries.
|
|
|
|
// f = std::sqrt(k * Length(p0 - p1*2 + p2));
|
|
|
|
constexpr static float k = 2 / (8 * (1.f/kIntolerance));
|
|
|
|
float x = std::ldexp(1, level * 2) / k;
|
|
|
|
setupQuadraticLengthTerm(level << 1, pts, x - epsilon);
|
|
|
|
REPORTER_ASSERT(r,
|
|
|
|
std::ceil(std::log2(GrWangsFormula::quadratic(kIntolerance, pts))) == level);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::quadratic_log2(kIntolerance, pts) == level);
|
|
|
|
setupQuadraticLengthTerm(level << 1, pts, x + epsilon);
|
|
|
|
REPORTER_ASSERT(r,
|
|
|
|
std::ceil(std::log2(GrWangsFormula::quadratic(kIntolerance, pts))) == level+1);
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::quadratic_log2(kIntolerance, pts) == level + 1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
auto check_cubic_log2 = [&](const SkPoint* pts) {
|
|
|
|
float f = std::max(1.f, GrWangsFormula::cubic(kIntolerance, pts));
|
|
|
|
int f_log2 = GrWangsFormula::cubic_log2(kIntolerance, pts);
|
|
|
|
REPORTER_ASSERT(r, SkScalarCeilToInt(std::log2(f)) == f_log2);
|
|
|
|
};
|
|
|
|
|
|
|
|
auto check_quadratic_log2 = [&](const SkPoint* pts) {
|
|
|
|
float f = std::max(1.f, GrWangsFormula::quadratic(kIntolerance, pts));
|
|
|
|
int f_log2 = GrWangsFormula::quadratic_log2(kIntolerance, pts);
|
|
|
|
REPORTER_ASSERT(r, SkScalarCeilToInt(std::log2(f)) == f_log2);
|
|
|
|
};
|
|
|
|
|
|
|
|
SkRandom rand;
|
|
|
|
|
|
|
|
for_random_matrices(&rand, [&](const SkMatrix& m) {
|
|
|
|
SkPoint pts[4];
|
|
|
|
m.mapPoints(pts, kSerp, 4);
|
|
|
|
check_cubic_log2(pts);
|
|
|
|
|
|
|
|
m.mapPoints(pts, kLoop, 4);
|
|
|
|
check_cubic_log2(pts);
|
|
|
|
|
|
|
|
m.mapPoints(pts, kQuad, 3);
|
|
|
|
check_quadratic_log2(pts);
|
|
|
|
});
|
|
|
|
|
|
|
|
for_random_beziers(4, &rand, [&](const SkPoint pts[]) {
|
|
|
|
check_cubic_log2(pts);
|
|
|
|
});
|
|
|
|
|
|
|
|
for_random_beziers(3, &rand, [&](const SkPoint pts[]) {
|
|
|
|
check_quadratic_log2(pts);
|
|
|
|
});
|
|
|
|
}
|
|
|
|
|
|
|
|
// Ensure using transformations gives the same result as pre-transforming all points.
|
|
|
|
DEF_TEST(WangsFormula_vectorXforms, r) {
|
|
|
|
auto check_cubic_log2_with_transform = [&](const SkPoint* pts, const SkMatrix& m){
|
|
|
|
SkPoint ptsXformed[4];
|
|
|
|
m.mapPoints(ptsXformed, pts, 4);
|
|
|
|
int expected = GrWangsFormula::cubic_log2(kIntolerance, ptsXformed);
|
|
|
|
int actual = GrWangsFormula::cubic_log2(kIntolerance, pts, GrVectorXform(m));
|
|
|
|
REPORTER_ASSERT(r, actual == expected);
|
|
|
|
};
|
|
|
|
|
|
|
|
auto check_quadratic_log2_with_transform = [&](const SkPoint* pts, const SkMatrix& m) {
|
|
|
|
SkPoint ptsXformed[3];
|
|
|
|
m.mapPoints(ptsXformed, pts, 3);
|
|
|
|
int expected = GrWangsFormula::quadratic_log2(kIntolerance, ptsXformed);
|
|
|
|
int actual = GrWangsFormula::quadratic_log2(kIntolerance, pts, GrVectorXform(m));
|
|
|
|
REPORTER_ASSERT(r, actual == expected);
|
|
|
|
};
|
|
|
|
|
|
|
|
SkRandom rand;
|
|
|
|
|
|
|
|
for_random_matrices(&rand, [&](const SkMatrix& m) {
|
|
|
|
check_cubic_log2_with_transform(kSerp, m);
|
|
|
|
check_cubic_log2_with_transform(kLoop, m);
|
|
|
|
check_quadratic_log2_with_transform(kQuad, m);
|
|
|
|
|
|
|
|
for_random_beziers(4, &rand, [&](const SkPoint pts[]) {
|
|
|
|
check_cubic_log2_with_transform(pts, m);
|
|
|
|
});
|
|
|
|
|
|
|
|
for_random_beziers(3, &rand, [&](const SkPoint pts[]) {
|
|
|
|
check_quadratic_log2_with_transform(pts, m);
|
|
|
|
});
|
|
|
|
});
|
2020-06-04 22:44:29 +00:00
|
|
|
}
|
2020-05-14 01:18:46 +00:00
|
|
|
|
2020-06-04 22:44:29 +00:00
|
|
|
DEF_TEST(WangsFormula_worst_case_cubic, r) {
|
|
|
|
{
|
|
|
|
SkPoint worstP[] = {{0,0}, {100,100}, {0,0}, {0,0}};
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::worst_case_cubic(kIntolerance, 100, 100) ==
|
|
|
|
GrWangsFormula::cubic(kIntolerance, worstP));
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::worst_case_cubic_log2(kIntolerance, 100, 100) ==
|
|
|
|
GrWangsFormula::cubic_log2(kIntolerance, worstP));
|
|
|
|
}
|
|
|
|
{
|
|
|
|
SkPoint worstP[] = {{100,100}, {100,100}, {200,200}, {100,100}};
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::worst_case_cubic(kIntolerance, 100, 100) ==
|
|
|
|
GrWangsFormula::cubic(kIntolerance, worstP));
|
|
|
|
REPORTER_ASSERT(r, GrWangsFormula::worst_case_cubic_log2(kIntolerance, 100, 100) ==
|
|
|
|
GrWangsFormula::cubic_log2(kIntolerance, worstP));
|
|
|
|
}
|
|
|
|
auto check_worst_case_cubic = [&](const SkPoint* pts) {
|
|
|
|
SkRect bbox;
|
|
|
|
bbox.setBoundsNoCheck(pts, 4);
|
|
|
|
float worst = GrWangsFormula::worst_case_cubic(kIntolerance, bbox.width(), bbox.height());
|
|
|
|
int worst_log2 = GrWangsFormula::worst_case_cubic_log2(kIntolerance, bbox.width(),
|
|
|
|
bbox.height());
|
|
|
|
float actual = GrWangsFormula::cubic(kIntolerance, pts);
|
|
|
|
REPORTER_ASSERT(r, worst >= actual);
|
|
|
|
REPORTER_ASSERT(r, std::ceil(std::log2(std::max(1.f, worst))) == worst_log2);
|
|
|
|
SkASSERT(std::ceil(std::log2(std::max(1.f, worst))) == worst_log2);
|
|
|
|
};
|
|
|
|
SkRandom rand;
|
|
|
|
for (int i = 0; i < 100; ++i) {
|
|
|
|
for_random_beziers(4, &rand, [&](const SkPoint pts[]) {
|
|
|
|
check_worst_case_cubic(pts);
|
|
|
|
});
|
|
|
|
}
|
2020-05-14 01:18:46 +00:00
|
|
|
}
|