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