/* * 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::infinity()) == 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits::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::min()) == 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(-std::numeric_limits::denorm_min()) == 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(0.0f) == 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits::denorm_min()) == 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits::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::max()) == 128); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits::infinity()) > 0); REPORTER_ASSERT(r, GrWangsFormula::nextlog2(std::numeric_limits::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 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 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); }); } }