const std = @import("../std.zig"); const math = std.math; const expect = std.testing.expect; const isNan = math.isNan; const isInf = math.isInf; const inf = math.inf; const nan = math.nan; const floatEpsAt = math.floatEpsAt; const floatEps = math.floatEps; const floatMin = math.floatMin; const floatMax = math.floatMax; /// Returns sqrt(x * x + y * y), avoiding unnecessary overflow and underflow. /// /// Special Cases: /// /// | x | y | hypot | /// |-------|-------|-------| /// | +-inf | any | +inf | /// | any | +-inf | +inf | /// | nan | fin | nan | /// | fin | nan | nan | pub fn hypot(x: anytype, y: anytype) @TypeOf(x, y) { const T = @TypeOf(x, y); switch (@typeInfo(T)) { .float => {}, .comptime_float => return @sqrt(x * x + y * y), else => @compileError("hypot not implemented for " ++ @typeName(T)), } const lower = @sqrt(floatMin(T)); const upper = @sqrt(floatMax(T) / 2); const incre = @sqrt(floatEps(T) / 2); const scale = floatEpsAt(T, incre); const hypfn = if (emulateFma(T)) hypotUnfused else hypotFused; var major: T = x; var minor: T = y; if (isInf(major) or isInf(minor)) return inf(T); if (isNan(major) or isNan(minor)) return nan(T); if (T == f16) return @floatCast(@sqrt(@mulAdd(f32, x, x, @as(f32, y) * y))); if (T == f32) return @floatCast(@sqrt(@mulAdd(f64, x, x, @as(f64, y) * y))); major = @abs(major); minor = @abs(minor); if (minor > major) { const tempo = major; major = minor; minor = tempo; } if (major * incre >= minor) return major; if (major > upper) return hypfn(T, major * scale, minor * scale) / scale; if (minor < lower) return hypfn(T, major / scale, minor / scale) * scale; return hypfn(T, major, minor); } inline fn emulateFma(comptime T: type) bool { // If @mulAdd lowers to the software implementation, // hypotUnfused should be used in place of hypotFused. // This takes an educated guess, but ideally we should // properly detect at comptime when that fallback will // occur. return (T == f128 or T == f80); } inline fn hypotFused(comptime F: type, x: F, y: F) F { const r = @sqrt(@mulAdd(F, x, x, y * y)); const rr = r * r; const xx = x * x; const z = @mulAdd(F, -y, y, rr - xx) + @mulAdd(F, r, r, -rr) - @mulAdd(F, x, x, -xx); return r - z / (2 * r); } inline fn hypotUnfused(comptime F: type, x: F, y: F) F { const r = @sqrt(x * x + y * y); if (r <= 2 * y) { // 30deg or steeper const dx = r - y; const z = x * (2 * dx - x) + (dx - 2 * (x - y)) * dx; return r - z / (2 * r); } else { // shallower than 30 deg const dy = r - x; const z = 2 * dy * (x - 2 * y) + (4 * dy - y) * y + dy * dy; return r - z / (2 * r); } } const hypot_test_cases = .{ .{ 0.0, -1.2, 1.2 }, .{ 0.2, -0.34, 0.3944616584663203993612799816649560759946493601889826495362 }, .{ 0.8923, 2.636890, 2.7837722899152509525110650481670176852603253522923737962880 }, .{ 1.5, 5.25, 5.4600824169603887033229768686452745953332522619323580787836 }, .{ 37.45, 159.835, 164.16372840856167640478217141034363907565754072954443805164 }, .{ 89.123, 382.028905, 392.28687638576315875933966414927490685367196874260165618371 }, .{ 123123.234375, 529428.707813, 543556.88524707706887251269205923830745438413088753096759371 }, }; test hypot { try expect(hypot(0.3, 0.4) == 0.5); } test "hypot.correct" { inline for (.{ f16, f32, f64, f128 }) |T| { inline for (hypot_test_cases) |v| { const a: T, const b: T, const c: T = v; try expect(math.approxEqRel(T, hypot(a, b), c, @sqrt(floatEps(T)))); } } } test "hypot.precise" { inline for (.{ f16, f32, f64 }) |T| { // f128 seems to be 5 ulp inline for (hypot_test_cases) |v| { const a: T, const b: T, const c: T = v; try expect(math.approxEqRel(T, hypot(a, b), c, floatEps(T))); } } } test "hypot.special" { @setEvalBranchQuota(2000); inline for (.{ f16, f32, f64, f128 }) |T| { try expect(math.isNan(hypot(nan(T), 0.0))); try expect(math.isNan(hypot(0.0, nan(T)))); try expect(math.isPositiveInf(hypot(inf(T), 0.0))); try expect(math.isPositiveInf(hypot(0.0, inf(T)))); try expect(math.isPositiveInf(hypot(inf(T), nan(T)))); try expect(math.isPositiveInf(hypot(nan(T), inf(T)))); try expect(math.isPositiveInf(hypot(-inf(T), 0.0))); try expect(math.isPositiveInf(hypot(0.0, -inf(T)))); try expect(math.isPositiveInf(hypot(-inf(T), nan(T)))); try expect(math.isPositiveInf(hypot(nan(T), -inf(T)))); } }