|  | /* | 
|  | * 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); | 
|  | }); | 
|  | }); | 
|  | } | 
|  |  | 
|  | 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); | 
|  | }); | 
|  | } | 
|  | } |