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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))));
}
}
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