core/num/f16.rs
1//! Constants for the `f16` half-precision floating point type.
2//!
3//! *[See also the `f16` primitive type][f16].*
4//!
5//! Mathematically significant numbers are provided in the `consts` sub-module.
6//!
7//! For the constants defined directly in this module
8//! (as distinct from those defined in the `consts` sub-module),
9//! new code should instead use the associated constants
10//! defined directly on the `f16` type.
11
12#![unstable(feature = "f16", issue = "116909")]
13
14#[cfg(not(feature = "ferrocene_subset"))]
15use crate::convert::FloatToInt;
16use crate::num::FpCategory;
17#[cfg(not(feature = "ferrocene_subset"))]
18#[cfg(not(test))]
19use crate::num::libm;
20#[cfg(not(feature = "ferrocene_subset"))]
21use crate::panic::const_assert;
22use crate::{intrinsics, mem};
23
24/// Basic mathematical constants.
25#[unstable(feature = "f16", issue = "116909")]
26#[rustc_diagnostic_item = "f16_consts_mod"]
27pub mod consts {
28 // FIXME: replace with mathematical constants from cmath.
29
30 /// Archimedes' constant (π)
31 #[unstable(feature = "f16", issue = "116909")]
32 pub const PI: f16 = 3.14159265358979323846264338327950288_f16;
33
34 /// The full circle constant (τ)
35 ///
36 /// Equal to 2π.
37 #[unstable(feature = "f16", issue = "116909")]
38 pub const TAU: f16 = 6.28318530717958647692528676655900577_f16;
39
40 /// The golden ratio (φ)
41 #[unstable(feature = "f16", issue = "116909")]
42 pub const GOLDEN_RATIO: f16 = 1.618033988749894848204586834365638118_f16;
43
44 /// The Euler-Mascheroni constant (γ)
45 #[unstable(feature = "f16", issue = "116909")]
46 pub const EULER_GAMMA: f16 = 0.577215664901532860606512090082402431_f16;
47
48 /// π/2
49 #[unstable(feature = "f16", issue = "116909")]
50 pub const FRAC_PI_2: f16 = 1.57079632679489661923132169163975144_f16;
51
52 /// π/3
53 #[unstable(feature = "f16", issue = "116909")]
54 pub const FRAC_PI_3: f16 = 1.04719755119659774615421446109316763_f16;
55
56 /// π/4
57 #[unstable(feature = "f16", issue = "116909")]
58 pub const FRAC_PI_4: f16 = 0.785398163397448309615660845819875721_f16;
59
60 /// π/6
61 #[unstable(feature = "f16", issue = "116909")]
62 pub const FRAC_PI_6: f16 = 0.52359877559829887307710723054658381_f16;
63
64 /// π/8
65 #[unstable(feature = "f16", issue = "116909")]
66 pub const FRAC_PI_8: f16 = 0.39269908169872415480783042290993786_f16;
67
68 /// 1/π
69 #[unstable(feature = "f16", issue = "116909")]
70 pub const FRAC_1_PI: f16 = 0.318309886183790671537767526745028724_f16;
71
72 /// 1/sqrt(π)
73 #[unstable(feature = "f16", issue = "116909")]
74 // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
75 pub const FRAC_1_SQRT_PI: f16 = 0.564189583547756286948079451560772586_f16;
76
77 /// 1/sqrt(2π)
78 #[doc(alias = "FRAC_1_SQRT_TAU")]
79 #[unstable(feature = "f16", issue = "116909")]
80 // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
81 pub const FRAC_1_SQRT_2PI: f16 = 0.398942280401432677939946059934381868_f16;
82
83 /// 2/π
84 #[unstable(feature = "f16", issue = "116909")]
85 pub const FRAC_2_PI: f16 = 0.636619772367581343075535053490057448_f16;
86
87 /// 2/sqrt(π)
88 #[unstable(feature = "f16", issue = "116909")]
89 pub const FRAC_2_SQRT_PI: f16 = 1.12837916709551257389615890312154517_f16;
90
91 /// sqrt(2)
92 #[unstable(feature = "f16", issue = "116909")]
93 pub const SQRT_2: f16 = 1.41421356237309504880168872420969808_f16;
94
95 /// 1/sqrt(2)
96 #[unstable(feature = "f16", issue = "116909")]
97 pub const FRAC_1_SQRT_2: f16 = 0.707106781186547524400844362104849039_f16;
98
99 /// sqrt(3)
100 #[unstable(feature = "f16", issue = "116909")]
101 // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
102 pub const SQRT_3: f16 = 1.732050807568877293527446341505872367_f16;
103
104 /// 1/sqrt(3)
105 #[unstable(feature = "f16", issue = "116909")]
106 // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
107 pub const FRAC_1_SQRT_3: f16 = 0.577350269189625764509148780501957456_f16;
108
109 /// Euler's number (e)
110 #[unstable(feature = "f16", issue = "116909")]
111 pub const E: f16 = 2.71828182845904523536028747135266250_f16;
112
113 /// log<sub>2</sub>(10)
114 #[unstable(feature = "f16", issue = "116909")]
115 pub const LOG2_10: f16 = 3.32192809488736234787031942948939018_f16;
116
117 /// log<sub>2</sub>(e)
118 #[unstable(feature = "f16", issue = "116909")]
119 pub const LOG2_E: f16 = 1.44269504088896340735992468100189214_f16;
120
121 /// log<sub>10</sub>(2)
122 #[unstable(feature = "f16", issue = "116909")]
123 pub const LOG10_2: f16 = 0.301029995663981195213738894724493027_f16;
124
125 /// log<sub>10</sub>(e)
126 #[unstable(feature = "f16", issue = "116909")]
127 pub const LOG10_E: f16 = 0.434294481903251827651128918916605082_f16;
128
129 /// ln(2)
130 #[unstable(feature = "f16", issue = "116909")]
131 pub const LN_2: f16 = 0.693147180559945309417232121458176568_f16;
132
133 /// ln(10)
134 #[unstable(feature = "f16", issue = "116909")]
135 pub const LN_10: f16 = 2.30258509299404568401799145468436421_f16;
136}
137
138#[doc(test(attr(feature(cfg_target_has_reliable_f16_f128), allow(internal_features))))]
139impl f16 {
140 /// The radix or base of the internal representation of `f16`.
141 #[unstable(feature = "f16", issue = "116909")]
142 pub const RADIX: u32 = 2;
143
144 /// Number of significant digits in base 2.
145 ///
146 /// Note that the size of the mantissa in the bitwise representation is one
147 /// smaller than this since the leading 1 is not stored explicitly.
148 #[unstable(feature = "f16", issue = "116909")]
149 pub const MANTISSA_DIGITS: u32 = 11;
150
151 /// Approximate number of significant digits in base 10.
152 ///
153 /// This is the maximum <i>x</i> such that any decimal number with <i>x</i>
154 /// significant digits can be converted to `f16` and back without loss.
155 ///
156 /// Equal to floor(log<sub>10</sub> 2<sup>[`MANTISSA_DIGITS`] − 1</sup>).
157 ///
158 /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS
159 #[unstable(feature = "f16", issue = "116909")]
160 pub const DIGITS: u32 = 3;
161
162 /// [Machine epsilon] value for `f16`.
163 ///
164 /// This is the difference between `1.0` and the next larger representable number.
165 ///
166 /// Equal to 2<sup>1 − [`MANTISSA_DIGITS`]</sup>.
167 ///
168 /// [Machine epsilon]: https://en.wikipedia.org/wiki/Machine_epsilon
169 /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS
170 #[unstable(feature = "f16", issue = "116909")]
171 #[rustc_diagnostic_item = "f16_epsilon"]
172 pub const EPSILON: f16 = 9.7656e-4_f16;
173
174 /// Smallest finite `f16` value.
175 ///
176 /// Equal to −[`MAX`].
177 ///
178 /// [`MAX`]: f16::MAX
179 #[unstable(feature = "f16", issue = "116909")]
180 pub const MIN: f16 = -6.5504e+4_f16;
181 /// Smallest positive normal `f16` value.
182 ///
183 /// Equal to 2<sup>[`MIN_EXP`] − 1</sup>.
184 ///
185 /// [`MIN_EXP`]: f16::MIN_EXP
186 #[unstable(feature = "f16", issue = "116909")]
187 pub const MIN_POSITIVE: f16 = 6.1035e-5_f16;
188 /// Largest finite `f16` value.
189 ///
190 /// Equal to
191 /// (1 − 2<sup>−[`MANTISSA_DIGITS`]</sup>) 2<sup>[`MAX_EXP`]</sup>.
192 ///
193 /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS
194 /// [`MAX_EXP`]: f16::MAX_EXP
195 #[unstable(feature = "f16", issue = "116909")]
196 pub const MAX: f16 = 6.5504e+4_f16;
197
198 /// One greater than the minimum possible *normal* power of 2 exponent
199 /// for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).
200 ///
201 /// This corresponds to the exact minimum possible *normal* power of 2 exponent
202 /// for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition).
203 /// In other words, all normal numbers representable by this type are
204 /// greater than or equal to 0.5 × 2<sup><i>MIN_EXP</i></sup>.
205 #[unstable(feature = "f16", issue = "116909")]
206 pub const MIN_EXP: i32 = -13;
207 /// One greater than the maximum possible power of 2 exponent
208 /// for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).
209 ///
210 /// This corresponds to the exact maximum possible power of 2 exponent
211 /// for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition).
212 /// In other words, all numbers representable by this type are
213 /// strictly less than 2<sup><i>MAX_EXP</i></sup>.
214 #[unstable(feature = "f16", issue = "116909")]
215 pub const MAX_EXP: i32 = 16;
216
217 /// Minimum <i>x</i> for which 10<sup><i>x</i></sup> is normal.
218 ///
219 /// Equal to ceil(log<sub>10</sub> [`MIN_POSITIVE`]).
220 ///
221 /// [`MIN_POSITIVE`]: f16::MIN_POSITIVE
222 #[unstable(feature = "f16", issue = "116909")]
223 pub const MIN_10_EXP: i32 = -4;
224 /// Maximum <i>x</i> for which 10<sup><i>x</i></sup> is normal.
225 ///
226 /// Equal to floor(log<sub>10</sub> [`MAX`]).
227 ///
228 /// [`MAX`]: f16::MAX
229 #[unstable(feature = "f16", issue = "116909")]
230 pub const MAX_10_EXP: i32 = 4;
231
232 /// Not a Number (NaN).
233 ///
234 /// Note that IEEE 754 doesn't define just a single NaN value; a plethora of bit patterns are
235 /// considered to be NaN. Furthermore, the standard makes a difference between a "signaling" and
236 /// a "quiet" NaN, and allows inspecting its "payload" (the unspecified bits in the bit pattern)
237 /// and its sign. See the [specification of NaN bit patterns](f32#nan-bit-patterns) for more
238 /// info.
239 ///
240 /// This constant is guaranteed to be a quiet NaN (on targets that follow the Rust assumptions
241 /// that the quiet/signaling bit being set to 1 indicates a quiet NaN). Beyond that, nothing is
242 /// guaranteed about the specific bit pattern chosen here: both payload and sign are arbitrary.
243 /// The concrete bit pattern may change across Rust versions and target platforms.
244 #[allow(clippy::eq_op)]
245 #[rustc_diagnostic_item = "f16_nan"]
246 #[unstable(feature = "f16", issue = "116909")]
247 pub const NAN: f16 = 0.0_f16 / 0.0_f16;
248
249 /// Infinity (∞).
250 #[unstable(feature = "f16", issue = "116909")]
251 pub const INFINITY: f16 = 1.0_f16 / 0.0_f16;
252
253 /// Negative infinity (−∞).
254 #[unstable(feature = "f16", issue = "116909")]
255 pub const NEG_INFINITY: f16 = -1.0_f16 / 0.0_f16;
256
257 /// Sign bit
258 #[cfg(not(feature = "ferrocene_subset"))]
259 pub(crate) const SIGN_MASK: u16 = 0x8000;
260
261 /// Exponent mask
262 pub(crate) const EXP_MASK: u16 = 0x7c00;
263
264 /// Mantissa mask
265 pub(crate) const MAN_MASK: u16 = 0x03ff;
266
267 /// Minimum representable positive value (min subnormal)
268 #[cfg(not(feature = "ferrocene_subset"))]
269 const TINY_BITS: u16 = 0x1;
270
271 /// Minimum representable negative value (min negative subnormal)
272 #[cfg(not(feature = "ferrocene_subset"))]
273 const NEG_TINY_BITS: u16 = Self::TINY_BITS | Self::SIGN_MASK;
274
275 /// Returns `true` if this value is NaN.
276 ///
277 /// ```
278 /// #![feature(f16)]
279 /// # #[cfg(target_has_reliable_f16)] {
280 ///
281 /// let nan = f16::NAN;
282 /// let f = 7.0_f16;
283 ///
284 /// assert!(nan.is_nan());
285 /// assert!(!f.is_nan());
286 /// # }
287 /// ```
288 #[cfg(not(feature = "ferrocene_subset"))]
289 #[inline]
290 #[must_use]
291 #[unstable(feature = "f16", issue = "116909")]
292 #[allow(clippy::eq_op)] // > if you intended to check if the operand is NaN, use `.is_nan()` instead :)
293 pub const fn is_nan(self) -> bool {
294 self != self
295 }
296
297 /// Returns `true` if this value is positive infinity or negative infinity, and
298 /// `false` otherwise.
299 ///
300 /// ```
301 /// #![feature(f16)]
302 /// # #[cfg(target_has_reliable_f16)] {
303 ///
304 /// let f = 7.0f16;
305 /// let inf = f16::INFINITY;
306 /// let neg_inf = f16::NEG_INFINITY;
307 /// let nan = f16::NAN;
308 ///
309 /// assert!(!f.is_infinite());
310 /// assert!(!nan.is_infinite());
311 ///
312 /// assert!(inf.is_infinite());
313 /// assert!(neg_inf.is_infinite());
314 /// # }
315 /// ```
316 #[cfg(not(feature = "ferrocene_subset"))]
317 #[inline]
318 #[must_use]
319 #[unstable(feature = "f16", issue = "116909")]
320 pub const fn is_infinite(self) -> bool {
321 (self == f16::INFINITY) | (self == f16::NEG_INFINITY)
322 }
323
324 /// Returns `true` if this number is neither infinite nor NaN.
325 ///
326 /// ```
327 /// #![feature(f16)]
328 /// # #[cfg(target_has_reliable_f16)] {
329 ///
330 /// let f = 7.0f16;
331 /// let inf: f16 = f16::INFINITY;
332 /// let neg_inf: f16 = f16::NEG_INFINITY;
333 /// let nan: f16 = f16::NAN;
334 ///
335 /// assert!(f.is_finite());
336 ///
337 /// assert!(!nan.is_finite());
338 /// assert!(!inf.is_finite());
339 /// assert!(!neg_inf.is_finite());
340 /// # }
341 /// ```
342 #[cfg(not(feature = "ferrocene_subset"))]
343 #[inline]
344 #[must_use]
345 #[unstable(feature = "f16", issue = "116909")]
346 #[rustc_const_unstable(feature = "f16", issue = "116909")]
347 pub const fn is_finite(self) -> bool {
348 // There's no need to handle NaN separately: if self is NaN,
349 // the comparison is not true, exactly as desired.
350 self.abs() < Self::INFINITY
351 }
352
353 /// Returns `true` if the number is [subnormal].
354 ///
355 /// ```
356 /// #![feature(f16)]
357 /// # #[cfg(target_has_reliable_f16)] {
358 ///
359 /// let min = f16::MIN_POSITIVE; // 6.1035e-5
360 /// let max = f16::MAX;
361 /// let lower_than_min = 1.0e-7_f16;
362 /// let zero = 0.0_f16;
363 ///
364 /// assert!(!min.is_subnormal());
365 /// assert!(!max.is_subnormal());
366 ///
367 /// assert!(!zero.is_subnormal());
368 /// assert!(!f16::NAN.is_subnormal());
369 /// assert!(!f16::INFINITY.is_subnormal());
370 /// // Values between `0` and `min` are Subnormal.
371 /// assert!(lower_than_min.is_subnormal());
372 /// # }
373 /// ```
374 /// [subnormal]: https://en.wikipedia.org/wiki/Denormal_number
375 #[cfg(not(feature = "ferrocene_subset"))]
376 #[inline]
377 #[must_use]
378 #[unstable(feature = "f16", issue = "116909")]
379 pub const fn is_subnormal(self) -> bool {
380 matches!(self.classify(), FpCategory::Subnormal)
381 }
382
383 /// Returns `true` if the number is neither zero, infinite, [subnormal], or NaN.
384 ///
385 /// ```
386 /// #![feature(f16)]
387 /// # #[cfg(target_has_reliable_f16)] {
388 ///
389 /// let min = f16::MIN_POSITIVE; // 6.1035e-5
390 /// let max = f16::MAX;
391 /// let lower_than_min = 1.0e-7_f16;
392 /// let zero = 0.0_f16;
393 ///
394 /// assert!(min.is_normal());
395 /// assert!(max.is_normal());
396 ///
397 /// assert!(!zero.is_normal());
398 /// assert!(!f16::NAN.is_normal());
399 /// assert!(!f16::INFINITY.is_normal());
400 /// // Values between `0` and `min` are Subnormal.
401 /// assert!(!lower_than_min.is_normal());
402 /// # }
403 /// ```
404 /// [subnormal]: https://en.wikipedia.org/wiki/Denormal_number
405 #[cfg(not(feature = "ferrocene_subset"))]
406 #[inline]
407 #[must_use]
408 #[unstable(feature = "f16", issue = "116909")]
409 pub const fn is_normal(self) -> bool {
410 matches!(self.classify(), FpCategory::Normal)
411 }
412
413 /// Returns the floating point category of the number. If only one property
414 /// is going to be tested, it is generally faster to use the specific
415 /// predicate instead.
416 ///
417 /// ```
418 /// #![feature(f16)]
419 /// # #[cfg(target_has_reliable_f16)] {
420 ///
421 /// use std::num::FpCategory;
422 ///
423 /// let num = 12.4_f16;
424 /// let inf = f16::INFINITY;
425 ///
426 /// assert_eq!(num.classify(), FpCategory::Normal);
427 /// assert_eq!(inf.classify(), FpCategory::Infinite);
428 /// # }
429 /// ```
430 #[inline]
431 #[unstable(feature = "f16", issue = "116909")]
432 pub const fn classify(self) -> FpCategory {
433 let b = self.to_bits();
434 match (b & Self::MAN_MASK, b & Self::EXP_MASK) {
435 (0, Self::EXP_MASK) => FpCategory::Infinite,
436 (_, Self::EXP_MASK) => FpCategory::Nan,
437 (0, 0) => FpCategory::Zero,
438 (_, 0) => FpCategory::Subnormal,
439 _ => FpCategory::Normal,
440 }
441 }
442
443 /// Returns `true` if `self` has a positive sign, including `+0.0`, NaNs with
444 /// positive sign bit and positive infinity.
445 ///
446 /// Note that IEEE 754 doesn't assign any meaning to the sign bit in case of
447 /// a NaN, and as Rust doesn't guarantee that the bit pattern of NaNs are
448 /// conserved over arithmetic operations, the result of `is_sign_positive` on
449 /// a NaN might produce an unexpected or non-portable result. See the [specification
450 /// of NaN bit patterns](f32#nan-bit-patterns) for more info. Use `self.signum() == 1.0`
451 /// if you need fully portable behavior (will return `false` for all NaNs).
452 ///
453 /// ```
454 /// #![feature(f16)]
455 /// # #[cfg(target_has_reliable_f16)] {
456 ///
457 /// let f = 7.0_f16;
458 /// let g = -7.0_f16;
459 ///
460 /// assert!(f.is_sign_positive());
461 /// assert!(!g.is_sign_positive());
462 /// # }
463 /// ```
464 #[cfg(not(feature = "ferrocene_subset"))]
465 #[inline]
466 #[must_use]
467 #[unstable(feature = "f16", issue = "116909")]
468 pub const fn is_sign_positive(self) -> bool {
469 !self.is_sign_negative()
470 }
471
472 /// Returns `true` if `self` has a negative sign, including `-0.0`, NaNs with
473 /// negative sign bit and negative infinity.
474 ///
475 /// Note that IEEE 754 doesn't assign any meaning to the sign bit in case of
476 /// a NaN, and as Rust doesn't guarantee that the bit pattern of NaNs are
477 /// conserved over arithmetic operations, the result of `is_sign_negative` on
478 /// a NaN might produce an unexpected or non-portable result. See the [specification
479 /// of NaN bit patterns](f32#nan-bit-patterns) for more info. Use `self.signum() == -1.0`
480 /// if you need fully portable behavior (will return `false` for all NaNs).
481 ///
482 /// ```
483 /// #![feature(f16)]
484 /// # #[cfg(target_has_reliable_f16)] {
485 ///
486 /// let f = 7.0_f16;
487 /// let g = -7.0_f16;
488 ///
489 /// assert!(!f.is_sign_negative());
490 /// assert!(g.is_sign_negative());
491 /// # }
492 /// ```
493 #[cfg(not(feature = "ferrocene_subset"))]
494 #[inline]
495 #[must_use]
496 #[unstable(feature = "f16", issue = "116909")]
497 pub const fn is_sign_negative(self) -> bool {
498 // IEEE754 says: isSignMinus(x) is true if and only if x has negative sign. isSignMinus
499 // applies to zeros and NaNs as well.
500 // SAFETY: This is just transmuting to get the sign bit, it's fine.
501 (self.to_bits() & (1 << 15)) != 0
502 }
503
504 /// Returns the least number greater than `self`.
505 ///
506 /// Let `TINY` be the smallest representable positive `f16`. Then,
507 /// - if `self.is_nan()`, this returns `self`;
508 /// - if `self` is [`NEG_INFINITY`], this returns [`MIN`];
509 /// - if `self` is `-TINY`, this returns -0.0;
510 /// - if `self` is -0.0 or +0.0, this returns `TINY`;
511 /// - if `self` is [`MAX`] or [`INFINITY`], this returns [`INFINITY`];
512 /// - otherwise the unique least value greater than `self` is returned.
513 ///
514 /// The identity `x.next_up() == -(-x).next_down()` holds for all non-NaN `x`. When `x`
515 /// is finite `x == x.next_up().next_down()` also holds.
516 ///
517 /// ```rust
518 /// #![feature(f16)]
519 /// # #[cfg(target_has_reliable_f16)] {
520 ///
521 /// // f16::EPSILON is the difference between 1.0 and the next number up.
522 /// assert_eq!(1.0f16.next_up(), 1.0 + f16::EPSILON);
523 /// // But not for most numbers.
524 /// assert!(0.1f16.next_up() < 0.1 + f16::EPSILON);
525 /// assert_eq!(4356f16.next_up(), 4360.0);
526 /// # }
527 /// ```
528 ///
529 /// This operation corresponds to IEEE-754 `nextUp`.
530 ///
531 /// [`NEG_INFINITY`]: Self::NEG_INFINITY
532 /// [`INFINITY`]: Self::INFINITY
533 /// [`MIN`]: Self::MIN
534 /// [`MAX`]: Self::MAX
535 #[cfg(not(feature = "ferrocene_subset"))]
536 #[inline]
537 #[doc(alias = "nextUp")]
538 #[unstable(feature = "f16", issue = "116909")]
539 pub const fn next_up(self) -> Self {
540 // Some targets violate Rust's assumption of IEEE semantics, e.g. by flushing
541 // denormals to zero. This is in general unsound and unsupported, but here
542 // we do our best to still produce the correct result on such targets.
543 let bits = self.to_bits();
544 if self.is_nan() || bits == Self::INFINITY.to_bits() {
545 return self;
546 }
547
548 let abs = bits & !Self::SIGN_MASK;
549 let next_bits = if abs == 0 {
550 Self::TINY_BITS
551 } else if bits == abs {
552 bits + 1
553 } else {
554 bits - 1
555 };
556 Self::from_bits(next_bits)
557 }
558
559 /// Returns the greatest number less than `self`.
560 ///
561 /// Let `TINY` be the smallest representable positive `f16`. Then,
562 /// - if `self.is_nan()`, this returns `self`;
563 /// - if `self` is [`INFINITY`], this returns [`MAX`];
564 /// - if `self` is `TINY`, this returns 0.0;
565 /// - if `self` is -0.0 or +0.0, this returns `-TINY`;
566 /// - if `self` is [`MIN`] or [`NEG_INFINITY`], this returns [`NEG_INFINITY`];
567 /// - otherwise the unique greatest value less than `self` is returned.
568 ///
569 /// The identity `x.next_down() == -(-x).next_up()` holds for all non-NaN `x`. When `x`
570 /// is finite `x == x.next_down().next_up()` also holds.
571 ///
572 /// ```rust
573 /// #![feature(f16)]
574 /// # #[cfg(target_has_reliable_f16)] {
575 ///
576 /// let x = 1.0f16;
577 /// // Clamp value into range [0, 1).
578 /// let clamped = x.clamp(0.0, 1.0f16.next_down());
579 /// assert!(clamped < 1.0);
580 /// assert_eq!(clamped.next_up(), 1.0);
581 /// # }
582 /// ```
583 ///
584 /// This operation corresponds to IEEE-754 `nextDown`.
585 ///
586 /// [`NEG_INFINITY`]: Self::NEG_INFINITY
587 /// [`INFINITY`]: Self::INFINITY
588 /// [`MIN`]: Self::MIN
589 /// [`MAX`]: Self::MAX
590 #[cfg(not(feature = "ferrocene_subset"))]
591 #[inline]
592 #[doc(alias = "nextDown")]
593 #[unstable(feature = "f16", issue = "116909")]
594 pub const fn next_down(self) -> Self {
595 // Some targets violate Rust's assumption of IEEE semantics, e.g. by flushing
596 // denormals to zero. This is in general unsound and unsupported, but here
597 // we do our best to still produce the correct result on such targets.
598 let bits = self.to_bits();
599 if self.is_nan() || bits == Self::NEG_INFINITY.to_bits() {
600 return self;
601 }
602
603 let abs = bits & !Self::SIGN_MASK;
604 let next_bits = if abs == 0 {
605 Self::NEG_TINY_BITS
606 } else if bits == abs {
607 bits - 1
608 } else {
609 bits + 1
610 };
611 Self::from_bits(next_bits)
612 }
613
614 /// Takes the reciprocal (inverse) of a number, `1/x`.
615 ///
616 /// ```
617 /// #![feature(f16)]
618 /// # #[cfg(target_has_reliable_f16)] {
619 ///
620 /// let x = 2.0_f16;
621 /// let abs_difference = (x.recip() - (1.0 / x)).abs();
622 ///
623 /// assert!(abs_difference <= f16::EPSILON);
624 /// # }
625 /// ```
626 #[cfg(not(feature = "ferrocene_subset"))]
627 #[inline]
628 #[unstable(feature = "f16", issue = "116909")]
629 #[must_use = "this returns the result of the operation, without modifying the original"]
630 pub const fn recip(self) -> Self {
631 1.0 / self
632 }
633
634 /// Converts radians to degrees.
635 ///
636 /// # Unspecified precision
637 ///
638 /// The precision of this function is non-deterministic. This means it varies by platform,
639 /// Rust version, and can even differ within the same execution from one invocation to the next.
640 ///
641 /// # Examples
642 ///
643 /// ```
644 /// #![feature(f16)]
645 /// # #[cfg(target_has_reliable_f16)] {
646 ///
647 /// let angle = std::f16::consts::PI;
648 ///
649 /// let abs_difference = (angle.to_degrees() - 180.0).abs();
650 /// assert!(abs_difference <= 0.5);
651 /// # }
652 /// ```
653 #[cfg(not(feature = "ferrocene_subset"))]
654 #[inline]
655 #[unstable(feature = "f16", issue = "116909")]
656 #[must_use = "this returns the result of the operation, without modifying the original"]
657 pub const fn to_degrees(self) -> Self {
658 // Use a literal to avoid double rounding, consts::PI is already rounded,
659 // and dividing would round again.
660 const PIS_IN_180: f16 = 57.2957795130823208767981548141051703_f16;
661 self * PIS_IN_180
662 }
663
664 /// Converts degrees to radians.
665 ///
666 /// # Unspecified precision
667 ///
668 /// The precision of this function is non-deterministic. This means it varies by platform,
669 /// Rust version, and can even differ within the same execution from one invocation to the next.
670 ///
671 /// # Examples
672 ///
673 /// ```
674 /// #![feature(f16)]
675 /// # #[cfg(target_has_reliable_f16)] {
676 ///
677 /// let angle = 180.0f16;
678 ///
679 /// let abs_difference = (angle.to_radians() - std::f16::consts::PI).abs();
680 ///
681 /// assert!(abs_difference <= 0.01);
682 /// # }
683 /// ```
684 #[cfg(not(feature = "ferrocene_subset"))]
685 #[inline]
686 #[unstable(feature = "f16", issue = "116909")]
687 #[must_use = "this returns the result of the operation, without modifying the original"]
688 pub const fn to_radians(self) -> f16 {
689 // Use a literal to avoid double rounding, consts::PI is already rounded,
690 // and dividing would round again.
691 const RADS_PER_DEG: f16 = 0.017453292519943295769236907684886_f16;
692 self * RADS_PER_DEG
693 }
694
695 /// Returns the maximum of the two numbers, ignoring NaN.
696 ///
697 /// If exactly one of the arguments is NaN (quiet or signaling), then the other argument is
698 /// returned. If both arguments are NaN, the return value is NaN, with the bit pattern picked
699 /// using the usual [rules for arithmetic operations](f32#nan-bit-patterns). If the inputs
700 /// compare equal (such as for the case of `+0.0` and `-0.0`), either input may be returned
701 /// non-deterministically.
702 ///
703 /// The handling of NaNs follows the IEEE 754-2019 semantics for `maximumNumber`, treating all
704 /// NaNs the same way to ensure the operation is associative. The handling of signed zeros
705 /// follows the IEEE 754-2008 semantics for `maxNum`.
706 ///
707 /// ```
708 /// #![feature(f16)]
709 /// # #[cfg(target_has_reliable_f16)] {
710 ///
711 /// let x = 1.0f16;
712 /// let y = 2.0f16;
713 ///
714 /// assert_eq!(x.max(y), y);
715 /// assert_eq!(x.max(f16::NAN), x);
716 /// # }
717 /// ```
718 #[cfg(not(feature = "ferrocene_subset"))]
719 #[inline]
720 #[unstable(feature = "f16", issue = "116909")]
721 #[rustc_const_unstable(feature = "f16", issue = "116909")]
722 #[must_use = "this returns the result of the comparison, without modifying either input"]
723 pub const fn max(self, other: f16) -> f16 {
724 intrinsics::maxnumf16(self, other)
725 }
726
727 /// Returns the minimum of the two numbers, ignoring NaN.
728 ///
729 /// If exactly one of the arguments is NaN (quiet or signaling), then the other argument is
730 /// returned. If both arguments are NaN, the return value is NaN, with the bit pattern picked
731 /// using the usual [rules for arithmetic operations](f32#nan-bit-patterns). If the inputs
732 /// compare equal (such as for the case of `+0.0` and `-0.0`), either input may be returned
733 /// non-deterministically.
734 ///
735 /// The handling of NaNs follows the IEEE 754-2019 semantics for `minimumNumber`, treating all
736 /// NaNs the same way to ensure the operation is associative. The handling of signed zeros
737 /// follows the IEEE 754-2008 semantics for `minNum`.
738 ///
739 /// ```
740 /// #![feature(f16)]
741 /// # #[cfg(target_has_reliable_f16)] {
742 ///
743 /// let x = 1.0f16;
744 /// let y = 2.0f16;
745 ///
746 /// assert_eq!(x.min(y), x);
747 /// assert_eq!(x.min(f16::NAN), x);
748 /// # }
749 /// ```
750 #[cfg(not(feature = "ferrocene_subset"))]
751 #[inline]
752 #[unstable(feature = "f16", issue = "116909")]
753 #[rustc_const_unstable(feature = "f16", issue = "116909")]
754 #[must_use = "this returns the result of the comparison, without modifying either input"]
755 pub const fn min(self, other: f16) -> f16 {
756 intrinsics::minnumf16(self, other)
757 }
758
759 /// Returns the maximum of the two numbers, propagating NaN.
760 ///
761 /// If at least one of the arguments is NaN, the return value is NaN, with the bit pattern
762 /// picked using the usual [rules for arithmetic operations](f32#nan-bit-patterns). Furthermore,
763 /// `-0.0` is considered to be less than `+0.0`, making this function fully deterministic for
764 /// non-NaN inputs.
765 ///
766 /// This is in contrast to [`f16::max`] which only returns NaN when *both* arguments are NaN,
767 /// and which does not reliably order `-0.0` and `+0.0`.
768 ///
769 /// This follows the IEEE 754-2019 semantics for `maximum`.
770 ///
771 /// ```
772 /// #![feature(f16)]
773 /// #![feature(float_minimum_maximum)]
774 /// # #[cfg(target_has_reliable_f16)] {
775 ///
776 /// let x = 1.0f16;
777 /// let y = 2.0f16;
778 ///
779 /// assert_eq!(x.maximum(y), y);
780 /// assert!(x.maximum(f16::NAN).is_nan());
781 /// # }
782 /// ```
783 #[cfg(not(feature = "ferrocene_subset"))]
784 #[inline]
785 #[unstable(feature = "f16", issue = "116909")]
786 // #[unstable(feature = "float_minimum_maximum", issue = "91079")]
787 #[must_use = "this returns the result of the comparison, without modifying either input"]
788 pub const fn maximum(self, other: f16) -> f16 {
789 intrinsics::maximumf16(self, other)
790 }
791
792 /// Returns the minimum of the two numbers, propagating NaN.
793 ///
794 /// If at least one of the arguments is NaN, the return value is NaN, with the bit pattern
795 /// picked using the usual [rules for arithmetic operations](f32#nan-bit-patterns). Furthermore,
796 /// `-0.0` is considered to be less than `+0.0`, making this function fully deterministic for
797 /// non-NaN inputs.
798 ///
799 /// This is in contrast to [`f16::min`] which only returns NaN when *both* arguments are NaN,
800 /// and which does not reliably order `-0.0` and `+0.0`.
801 ///
802 /// This follows the IEEE 754-2019 semantics for `minimum`.
803 ///
804 /// ```
805 /// #![feature(f16)]
806 /// #![feature(float_minimum_maximum)]
807 /// # #[cfg(target_has_reliable_f16)] {
808 ///
809 /// let x = 1.0f16;
810 /// let y = 2.0f16;
811 ///
812 /// assert_eq!(x.minimum(y), x);
813 /// assert!(x.minimum(f16::NAN).is_nan());
814 /// # }
815 /// ```
816 #[cfg(not(feature = "ferrocene_subset"))]
817 #[inline]
818 #[unstable(feature = "f16", issue = "116909")]
819 // #[unstable(feature = "float_minimum_maximum", issue = "91079")]
820 #[must_use = "this returns the result of the comparison, without modifying either input"]
821 pub const fn minimum(self, other: f16) -> f16 {
822 intrinsics::minimumf16(self, other)
823 }
824
825 /// Calculates the midpoint (average) between `self` and `rhs`.
826 ///
827 /// This returns NaN when *either* argument is NaN or if a combination of
828 /// +inf and -inf is provided as arguments.
829 ///
830 /// # Examples
831 ///
832 /// ```
833 /// #![feature(f16)]
834 /// # #[cfg(target_has_reliable_f16)] {
835 ///
836 /// assert_eq!(1f16.midpoint(4.0), 2.5);
837 /// assert_eq!((-5.5f16).midpoint(8.0), 1.25);
838 /// # }
839 /// ```
840 #[cfg(not(feature = "ferrocene_subset"))]
841 #[inline]
842 #[doc(alias = "average")]
843 #[unstable(feature = "f16", issue = "116909")]
844 #[rustc_const_unstable(feature = "f16", issue = "116909")]
845 pub const fn midpoint(self, other: f16) -> f16 {
846 const HI: f16 = f16::MAX / 2.;
847
848 let (a, b) = (self, other);
849 let abs_a = a.abs();
850 let abs_b = b.abs();
851
852 if abs_a <= HI && abs_b <= HI {
853 // Overflow is impossible
854 (a + b) / 2.
855 } else {
856 (a / 2.) + (b / 2.)
857 }
858 }
859
860 /// Rounds toward zero and converts to any primitive integer type,
861 /// assuming that the value is finite and fits in that type.
862 ///
863 /// ```
864 /// #![feature(f16)]
865 /// # #[cfg(target_has_reliable_f16)] {
866 ///
867 /// let value = 4.6_f16;
868 /// let rounded = unsafe { value.to_int_unchecked::<u16>() };
869 /// assert_eq!(rounded, 4);
870 ///
871 /// let value = -128.9_f16;
872 /// let rounded = unsafe { value.to_int_unchecked::<i8>() };
873 /// assert_eq!(rounded, i8::MIN);
874 /// # }
875 /// ```
876 ///
877 /// # Safety
878 ///
879 /// The value must:
880 ///
881 /// * Not be `NaN`
882 /// * Not be infinite
883 /// * Be representable in the return type `Int`, after truncating off its fractional part
884 #[cfg(not(feature = "ferrocene_subset"))]
885 #[inline]
886 #[unstable(feature = "f16", issue = "116909")]
887 #[must_use = "this returns the result of the operation, without modifying the original"]
888 pub unsafe fn to_int_unchecked<Int>(self) -> Int
889 where
890 Self: FloatToInt<Int>,
891 {
892 // SAFETY: the caller must uphold the safety contract for
893 // `FloatToInt::to_int_unchecked`.
894 unsafe { FloatToInt::<Int>::to_int_unchecked(self) }
895 }
896
897 /// Raw transmutation to `u16`.
898 ///
899 /// This is currently identical to `transmute::<f16, u16>(self)` on all platforms.
900 ///
901 /// See [`from_bits`](#method.from_bits) for some discussion of the
902 /// portability of this operation (there are almost no issues).
903 ///
904 /// Note that this function is distinct from `as` casting, which attempts to
905 /// preserve the *numeric* value, and not the bitwise value.
906 ///
907 /// ```
908 /// #![feature(f16)]
909 /// # #[cfg(target_has_reliable_f16)] {
910 ///
911 /// assert_ne!((1f16).to_bits(), 1f16 as u16); // to_bits() is not casting!
912 /// assert_eq!((12.5f16).to_bits(), 0x4a40);
913 /// # }
914 /// ```
915 #[inline]
916 #[unstable(feature = "f16", issue = "116909")]
917 #[must_use = "this returns the result of the operation, without modifying the original"]
918 #[allow(unnecessary_transmutes)]
919 pub const fn to_bits(self) -> u16 {
920 // SAFETY: `u16` is a plain old datatype so we can always transmute to it.
921 unsafe { mem::transmute(self) }
922 }
923
924 /// Raw transmutation from `u16`.
925 ///
926 /// This is currently identical to `transmute::<u16, f16>(v)` on all platforms.
927 /// It turns out this is incredibly portable, for two reasons:
928 ///
929 /// * Floats and Ints have the same endianness on all supported platforms.
930 /// * IEEE 754 very precisely specifies the bit layout of floats.
931 ///
932 /// However there is one caveat: prior to the 2008 version of IEEE 754, how
933 /// to interpret the NaN signaling bit wasn't actually specified. Most platforms
934 /// (notably x86 and ARM) picked the interpretation that was ultimately
935 /// standardized in 2008, but some didn't (notably MIPS). As a result, all
936 /// signaling NaNs on MIPS are quiet NaNs on x86, and vice-versa.
937 ///
938 /// Rather than trying to preserve signaling-ness cross-platform, this
939 /// implementation favors preserving the exact bits. This means that
940 /// any payloads encoded in NaNs will be preserved even if the result of
941 /// this method is sent over the network from an x86 machine to a MIPS one.
942 ///
943 /// If the results of this method are only manipulated by the same
944 /// architecture that produced them, then there is no portability concern.
945 ///
946 /// If the input isn't NaN, then there is no portability concern.
947 ///
948 /// If you don't care about signalingness (very likely), then there is no
949 /// portability concern.
950 ///
951 /// Note that this function is distinct from `as` casting, which attempts to
952 /// preserve the *numeric* value, and not the bitwise value.
953 ///
954 /// ```
955 /// #![feature(f16)]
956 /// # #[cfg(target_has_reliable_f16)] {
957 ///
958 /// let v = f16::from_bits(0x4a40);
959 /// assert_eq!(v, 12.5);
960 /// # }
961 /// ```
962 #[inline]
963 #[must_use]
964 #[unstable(feature = "f16", issue = "116909")]
965 #[allow(unnecessary_transmutes)]
966 pub const fn from_bits(v: u16) -> Self {
967 // It turns out the safety issues with sNaN were overblown! Hooray!
968 // SAFETY: `u16` is a plain old datatype so we can always transmute from it.
969 unsafe { mem::transmute(v) }
970 }
971
972 /// Returns the memory representation of this floating point number as a byte array in
973 /// big-endian (network) byte order.
974 ///
975 /// See [`from_bits`](Self::from_bits) for some discussion of the
976 /// portability of this operation (there are almost no issues).
977 ///
978 /// # Examples
979 ///
980 /// ```
981 /// #![feature(f16)]
982 /// # #[cfg(target_has_reliable_f16)] {
983 ///
984 /// let bytes = 12.5f16.to_be_bytes();
985 /// assert_eq!(bytes, [0x4a, 0x40]);
986 /// # }
987 /// ```
988 #[cfg(not(feature = "ferrocene_subset"))]
989 #[inline]
990 #[unstable(feature = "f16", issue = "116909")]
991 #[must_use = "this returns the result of the operation, without modifying the original"]
992 pub const fn to_be_bytes(self) -> [u8; 2] {
993 self.to_bits().to_be_bytes()
994 }
995
996 /// Returns the memory representation of this floating point number as a byte array in
997 /// little-endian byte order.
998 ///
999 /// See [`from_bits`](Self::from_bits) for some discussion of the
1000 /// portability of this operation (there are almost no issues).
1001 ///
1002 /// # Examples
1003 ///
1004 /// ```
1005 /// #![feature(f16)]
1006 /// # #[cfg(target_has_reliable_f16)] {
1007 ///
1008 /// let bytes = 12.5f16.to_le_bytes();
1009 /// assert_eq!(bytes, [0x40, 0x4a]);
1010 /// # }
1011 /// ```
1012 #[cfg(not(feature = "ferrocene_subset"))]
1013 #[inline]
1014 #[unstable(feature = "f16", issue = "116909")]
1015 #[must_use = "this returns the result of the operation, without modifying the original"]
1016 pub const fn to_le_bytes(self) -> [u8; 2] {
1017 self.to_bits().to_le_bytes()
1018 }
1019
1020 /// Returns the memory representation of this floating point number as a byte array in
1021 /// native byte order.
1022 ///
1023 /// As the target platform's native endianness is used, portable code
1024 /// should use [`to_be_bytes`] or [`to_le_bytes`], as appropriate, instead.
1025 ///
1026 /// [`to_be_bytes`]: f16::to_be_bytes
1027 /// [`to_le_bytes`]: f16::to_le_bytes
1028 ///
1029 /// See [`from_bits`](Self::from_bits) for some discussion of the
1030 /// portability of this operation (there are almost no issues).
1031 ///
1032 /// # Examples
1033 ///
1034 /// ```
1035 /// #![feature(f16)]
1036 /// # #[cfg(target_has_reliable_f16)] {
1037 ///
1038 /// let bytes = 12.5f16.to_ne_bytes();
1039 /// assert_eq!(
1040 /// bytes,
1041 /// if cfg!(target_endian = "big") {
1042 /// [0x4a, 0x40]
1043 /// } else {
1044 /// [0x40, 0x4a]
1045 /// }
1046 /// );
1047 /// # }
1048 /// ```
1049 #[cfg(not(feature = "ferrocene_subset"))]
1050 #[inline]
1051 #[unstable(feature = "f16", issue = "116909")]
1052 #[must_use = "this returns the result of the operation, without modifying the original"]
1053 pub const fn to_ne_bytes(self) -> [u8; 2] {
1054 self.to_bits().to_ne_bytes()
1055 }
1056
1057 /// Creates a floating point value from its representation as a byte array in big endian.
1058 ///
1059 /// See [`from_bits`](Self::from_bits) for some discussion of the
1060 /// portability of this operation (there are almost no issues).
1061 ///
1062 /// # Examples
1063 ///
1064 /// ```
1065 /// #![feature(f16)]
1066 /// # #[cfg(target_has_reliable_f16)] {
1067 ///
1068 /// let value = f16::from_be_bytes([0x4a, 0x40]);
1069 /// assert_eq!(value, 12.5);
1070 /// # }
1071 /// ```
1072 #[cfg(not(feature = "ferrocene_subset"))]
1073 #[inline]
1074 #[must_use]
1075 #[unstable(feature = "f16", issue = "116909")]
1076 pub const fn from_be_bytes(bytes: [u8; 2]) -> Self {
1077 Self::from_bits(u16::from_be_bytes(bytes))
1078 }
1079
1080 /// Creates a floating point value from its representation as a byte array in little endian.
1081 ///
1082 /// See [`from_bits`](Self::from_bits) for some discussion of the
1083 /// portability of this operation (there are almost no issues).
1084 ///
1085 /// # Examples
1086 ///
1087 /// ```
1088 /// #![feature(f16)]
1089 /// # #[cfg(target_has_reliable_f16)] {
1090 ///
1091 /// let value = f16::from_le_bytes([0x40, 0x4a]);
1092 /// assert_eq!(value, 12.5);
1093 /// # }
1094 /// ```
1095 #[cfg(not(feature = "ferrocene_subset"))]
1096 #[inline]
1097 #[must_use]
1098 #[unstable(feature = "f16", issue = "116909")]
1099 pub const fn from_le_bytes(bytes: [u8; 2]) -> Self {
1100 Self::from_bits(u16::from_le_bytes(bytes))
1101 }
1102
1103 /// Creates a floating point value from its representation as a byte array in native endian.
1104 ///
1105 /// As the target platform's native endianness is used, portable code
1106 /// likely wants to use [`from_be_bytes`] or [`from_le_bytes`], as
1107 /// appropriate instead.
1108 ///
1109 /// [`from_be_bytes`]: f16::from_be_bytes
1110 /// [`from_le_bytes`]: f16::from_le_bytes
1111 ///
1112 /// See [`from_bits`](Self::from_bits) for some discussion of the
1113 /// portability of this operation (there are almost no issues).
1114 ///
1115 /// # Examples
1116 ///
1117 /// ```
1118 /// #![feature(f16)]
1119 /// # #[cfg(target_has_reliable_f16)] {
1120 ///
1121 /// let value = f16::from_ne_bytes(if cfg!(target_endian = "big") {
1122 /// [0x4a, 0x40]
1123 /// } else {
1124 /// [0x40, 0x4a]
1125 /// });
1126 /// assert_eq!(value, 12.5);
1127 /// # }
1128 /// ```
1129 #[cfg(not(feature = "ferrocene_subset"))]
1130 #[inline]
1131 #[must_use]
1132 #[unstable(feature = "f16", issue = "116909")]
1133 pub const fn from_ne_bytes(bytes: [u8; 2]) -> Self {
1134 Self::from_bits(u16::from_ne_bytes(bytes))
1135 }
1136
1137 /// Returns the ordering between `self` and `other`.
1138 ///
1139 /// Unlike the standard partial comparison between floating point numbers,
1140 /// this comparison always produces an ordering in accordance to
1141 /// the `totalOrder` predicate as defined in the IEEE 754 (2008 revision)
1142 /// floating point standard. The values are ordered in the following sequence:
1143 ///
1144 /// - negative quiet NaN
1145 /// - negative signaling NaN
1146 /// - negative infinity
1147 /// - negative numbers
1148 /// - negative subnormal numbers
1149 /// - negative zero
1150 /// - positive zero
1151 /// - positive subnormal numbers
1152 /// - positive numbers
1153 /// - positive infinity
1154 /// - positive signaling NaN
1155 /// - positive quiet NaN.
1156 ///
1157 /// The ordering established by this function does not always agree with the
1158 /// [`PartialOrd`] and [`PartialEq`] implementations of `f16`. For example,
1159 /// they consider negative and positive zero equal, while `total_cmp`
1160 /// doesn't.
1161 ///
1162 /// The interpretation of the signaling NaN bit follows the definition in
1163 /// the IEEE 754 standard, which may not match the interpretation by some of
1164 /// the older, non-conformant (e.g. MIPS) hardware implementations.
1165 ///
1166 /// # Example
1167 ///
1168 /// ```
1169 /// #![feature(f16)]
1170 /// # #[cfg(target_has_reliable_f16)] {
1171 ///
1172 /// struct GoodBoy {
1173 /// name: &'static str,
1174 /// weight: f16,
1175 /// }
1176 ///
1177 /// let mut bois = vec![
1178 /// GoodBoy { name: "Pucci", weight: 0.1 },
1179 /// GoodBoy { name: "Woofer", weight: 99.0 },
1180 /// GoodBoy { name: "Yapper", weight: 10.0 },
1181 /// GoodBoy { name: "Chonk", weight: f16::INFINITY },
1182 /// GoodBoy { name: "Abs. Unit", weight: f16::NAN },
1183 /// GoodBoy { name: "Floaty", weight: -5.0 },
1184 /// ];
1185 ///
1186 /// bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));
1187 ///
1188 /// // `f16::NAN` could be positive or negative, which will affect the sort order.
1189 /// if f16::NAN.is_sign_negative() {
1190 /// bois.into_iter().map(|b| b.weight)
1191 /// .zip([f16::NAN, -5.0, 0.1, 10.0, 99.0, f16::INFINITY].iter())
1192 /// .for_each(|(a, b)| assert_eq!(a.to_bits(), b.to_bits()))
1193 /// } else {
1194 /// bois.into_iter().map(|b| b.weight)
1195 /// .zip([-5.0, 0.1, 10.0, 99.0, f16::INFINITY, f16::NAN].iter())
1196 /// .for_each(|(a, b)| assert_eq!(a.to_bits(), b.to_bits()))
1197 /// }
1198 /// # }
1199 /// ```
1200 #[cfg(not(feature = "ferrocene_subset"))]
1201 #[inline]
1202 #[must_use]
1203 #[unstable(feature = "f16", issue = "116909")]
1204 #[rustc_const_unstable(feature = "const_cmp", issue = "143800")]
1205 pub const fn total_cmp(&self, other: &Self) -> crate::cmp::Ordering {
1206 let mut left = self.to_bits() as i16;
1207 let mut right = other.to_bits() as i16;
1208
1209 // In case of negatives, flip all the bits except the sign
1210 // to achieve a similar layout as two's complement integers
1211 //
1212 // Why does this work? IEEE 754 floats consist of three fields:
1213 // Sign bit, exponent and mantissa. The set of exponent and mantissa
1214 // fields as a whole have the property that their bitwise order is
1215 // equal to the numeric magnitude where the magnitude is defined.
1216 // The magnitude is not normally defined on NaN values, but
1217 // IEEE 754 totalOrder defines the NaN values also to follow the
1218 // bitwise order. This leads to order explained in the doc comment.
1219 // However, the representation of magnitude is the same for negative
1220 // and positive numbers – only the sign bit is different.
1221 // To easily compare the floats as signed integers, we need to
1222 // flip the exponent and mantissa bits in case of negative numbers.
1223 // We effectively convert the numbers to "two's complement" form.
1224 //
1225 // To do the flipping, we construct a mask and XOR against it.
1226 // We branchlessly calculate an "all-ones except for the sign bit"
1227 // mask from negative-signed values: right shifting sign-extends
1228 // the integer, so we "fill" the mask with sign bits, and then
1229 // convert to unsigned to push one more zero bit.
1230 // On positive values, the mask is all zeros, so it's a no-op.
1231 left ^= (((left >> 15) as u16) >> 1) as i16;
1232 right ^= (((right >> 15) as u16) >> 1) as i16;
1233
1234 left.cmp(&right)
1235 }
1236
1237 /// Restrict a value to a certain interval unless it is NaN.
1238 ///
1239 /// Returns `max` if `self` is greater than `max`, and `min` if `self` is
1240 /// less than `min`. Otherwise this returns `self`.
1241 ///
1242 /// Note that this function returns NaN if the initial value was NaN as
1243 /// well. If the result is zero and among the three inputs `self`, `min`, and `max` there are
1244 /// zeros with different sign, either `0.0` or `-0.0` is returned non-deterministically.
1245 ///
1246 /// # Panics
1247 ///
1248 /// Panics if `min > max`, `min` is NaN, or `max` is NaN.
1249 ///
1250 /// # Examples
1251 ///
1252 /// ```
1253 /// #![feature(f16)]
1254 /// # #[cfg(target_has_reliable_f16)] {
1255 ///
1256 /// assert!((-3.0f16).clamp(-2.0, 1.0) == -2.0);
1257 /// assert!((0.0f16).clamp(-2.0, 1.0) == 0.0);
1258 /// assert!((2.0f16).clamp(-2.0, 1.0) == 1.0);
1259 /// assert!((f16::NAN).clamp(-2.0, 1.0).is_nan());
1260 ///
1261 /// // These always returns zero, but the sign (which is ignored by `==`) is non-deterministic.
1262 /// assert!((0.0f16).clamp(-0.0, -0.0) == 0.0);
1263 /// assert!((1.0f16).clamp(-0.0, 0.0) == 0.0);
1264 /// // This is definitely a negative zero.
1265 /// assert!((-1.0f16).clamp(-0.0, 1.0).is_sign_negative());
1266 /// # }
1267 /// ```
1268 #[cfg(not(feature = "ferrocene_subset"))]
1269 #[inline]
1270 #[unstable(feature = "f16", issue = "116909")]
1271 #[must_use = "method returns a new number and does not mutate the original value"]
1272 pub const fn clamp(mut self, min: f16, max: f16) -> f16 {
1273 const_assert!(
1274 min <= max,
1275 "min > max, or either was NaN",
1276 "min > max, or either was NaN. min = {min:?}, max = {max:?}",
1277 min: f16,
1278 max: f16,
1279 );
1280
1281 if self < min {
1282 self = min;
1283 }
1284 if self > max {
1285 self = max;
1286 }
1287 self
1288 }
1289
1290 /// Clamps this number to a symmetric range centered around zero.
1291 ///
1292 /// The method clamps the number's magnitude (absolute value) to be at most `limit`.
1293 ///
1294 /// This is functionally equivalent to `self.clamp(-limit, limit)`, but is more
1295 /// explicit about the intent.
1296 ///
1297 /// # Panics
1298 ///
1299 /// Panics if `limit` is negative or NaN, as this indicates a logic error.
1300 ///
1301 /// # Examples
1302 ///
1303 /// ```
1304 /// #![feature(f16)]
1305 /// #![feature(clamp_magnitude)]
1306 /// # #[cfg(target_has_reliable_f16)] {
1307 /// assert_eq!(5.0f16.clamp_magnitude(3.0), 3.0);
1308 /// assert_eq!((-5.0f16).clamp_magnitude(3.0), -3.0);
1309 /// assert_eq!(2.0f16.clamp_magnitude(3.0), 2.0);
1310 /// assert_eq!((-2.0f16).clamp_magnitude(3.0), -2.0);
1311 /// # }
1312 /// ```
1313 #[cfg(not(feature = "ferrocene_subset"))]
1314 #[inline]
1315 #[unstable(feature = "clamp_magnitude", issue = "148519")]
1316 #[must_use = "this returns the clamped value and does not modify the original"]
1317 pub fn clamp_magnitude(self, limit: f16) -> f16 {
1318 assert!(limit >= 0.0, "limit must be non-negative");
1319 let limit = limit.abs(); // Canonicalises -0.0 to 0.0
1320 self.clamp(-limit, limit)
1321 }
1322
1323 /// Computes the absolute value of `self`.
1324 ///
1325 /// This function always returns the precise result.
1326 ///
1327 /// # Examples
1328 ///
1329 /// ```
1330 /// #![feature(f16)]
1331 /// # #[cfg(target_has_reliable_f16_math)] {
1332 ///
1333 /// let x = 3.5_f16;
1334 /// let y = -3.5_f16;
1335 ///
1336 /// assert_eq!(x.abs(), x);
1337 /// assert_eq!(y.abs(), -y);
1338 ///
1339 /// assert!(f16::NAN.abs().is_nan());
1340 /// # }
1341 /// ```
1342 #[inline]
1343 #[unstable(feature = "f16", issue = "116909")]
1344 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1345 #[must_use = "method returns a new number and does not mutate the original value"]
1346 pub const fn abs(self) -> Self {
1347 intrinsics::fabsf16(self)
1348 }
1349
1350 /// Returns a number that represents the sign of `self`.
1351 ///
1352 /// - `1.0` if the number is positive, `+0.0` or `INFINITY`
1353 /// - `-1.0` if the number is negative, `-0.0` or `NEG_INFINITY`
1354 /// - NaN if the number is NaN
1355 ///
1356 /// # Examples
1357 ///
1358 /// ```
1359 /// #![feature(f16)]
1360 /// # #[cfg(target_has_reliable_f16)] {
1361 ///
1362 /// let f = 3.5_f16;
1363 ///
1364 /// assert_eq!(f.signum(), 1.0);
1365 /// assert_eq!(f16::NEG_INFINITY.signum(), -1.0);
1366 ///
1367 /// assert!(f16::NAN.signum().is_nan());
1368 /// # }
1369 /// ```
1370 #[cfg(not(feature = "ferrocene_subset"))]
1371 #[inline]
1372 #[unstable(feature = "f16", issue = "116909")]
1373 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1374 #[must_use = "method returns a new number and does not mutate the original value"]
1375 pub const fn signum(self) -> f16 {
1376 if self.is_nan() { Self::NAN } else { 1.0_f16.copysign(self) }
1377 }
1378
1379 /// Returns a number composed of the magnitude of `self` and the sign of
1380 /// `sign`.
1381 ///
1382 /// Equal to `self` if the sign of `self` and `sign` are the same, otherwise equal to `-self`.
1383 /// If `self` is a NaN, then a NaN with the same payload as `self` and the sign bit of `sign` is
1384 /// returned.
1385 ///
1386 /// If `sign` is a NaN, then this operation will still carry over its sign into the result. Note
1387 /// that IEEE 754 doesn't assign any meaning to the sign bit in case of a NaN, and as Rust
1388 /// doesn't guarantee that the bit pattern of NaNs are conserved over arithmetic operations, the
1389 /// result of `copysign` with `sign` being a NaN might produce an unexpected or non-portable
1390 /// result. See the [specification of NaN bit patterns](primitive@f32#nan-bit-patterns) for more
1391 /// info.
1392 ///
1393 /// # Examples
1394 ///
1395 /// ```
1396 /// #![feature(f16)]
1397 /// # #[cfg(target_has_reliable_f16_math)] {
1398 ///
1399 /// let f = 3.5_f16;
1400 ///
1401 /// assert_eq!(f.copysign(0.42), 3.5_f16);
1402 /// assert_eq!(f.copysign(-0.42), -3.5_f16);
1403 /// assert_eq!((-f).copysign(0.42), 3.5_f16);
1404 /// assert_eq!((-f).copysign(-0.42), -3.5_f16);
1405 ///
1406 /// assert!(f16::NAN.copysign(1.0).is_nan());
1407 /// # }
1408 /// ```
1409 #[cfg(not(feature = "ferrocene_subset"))]
1410 #[inline]
1411 #[unstable(feature = "f16", issue = "116909")]
1412 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1413 #[must_use = "method returns a new number and does not mutate the original value"]
1414 pub const fn copysign(self, sign: f16) -> f16 {
1415 intrinsics::copysignf16(self, sign)
1416 }
1417
1418 /// Float addition that allows optimizations based on algebraic rules.
1419 ///
1420 /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1421 #[cfg(not(feature = "ferrocene_subset"))]
1422 #[must_use = "method returns a new number and does not mutate the original value"]
1423 #[unstable(feature = "float_algebraic", issue = "136469")]
1424 #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1425 #[inline]
1426 pub const fn algebraic_add(self, rhs: f16) -> f16 {
1427 intrinsics::fadd_algebraic(self, rhs)
1428 }
1429
1430 /// Float subtraction that allows optimizations based on algebraic rules.
1431 ///
1432 /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1433 #[cfg(not(feature = "ferrocene_subset"))]
1434 #[must_use = "method returns a new number and does not mutate the original value"]
1435 #[unstable(feature = "float_algebraic", issue = "136469")]
1436 #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1437 #[inline]
1438 pub const fn algebraic_sub(self, rhs: f16) -> f16 {
1439 intrinsics::fsub_algebraic(self, rhs)
1440 }
1441
1442 /// Float multiplication that allows optimizations based on algebraic rules.
1443 ///
1444 /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1445 #[cfg(not(feature = "ferrocene_subset"))]
1446 #[must_use = "method returns a new number and does not mutate the original value"]
1447 #[unstable(feature = "float_algebraic", issue = "136469")]
1448 #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1449 #[inline]
1450 pub const fn algebraic_mul(self, rhs: f16) -> f16 {
1451 intrinsics::fmul_algebraic(self, rhs)
1452 }
1453
1454 /// Float division that allows optimizations based on algebraic rules.
1455 ///
1456 /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1457 #[cfg(not(feature = "ferrocene_subset"))]
1458 #[must_use = "method returns a new number and does not mutate the original value"]
1459 #[unstable(feature = "float_algebraic", issue = "136469")]
1460 #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1461 #[inline]
1462 pub const fn algebraic_div(self, rhs: f16) -> f16 {
1463 intrinsics::fdiv_algebraic(self, rhs)
1464 }
1465
1466 /// Float remainder that allows optimizations based on algebraic rules.
1467 ///
1468 /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1469 #[cfg(not(feature = "ferrocene_subset"))]
1470 #[must_use = "method returns a new number and does not mutate the original value"]
1471 #[unstable(feature = "float_algebraic", issue = "136469")]
1472 #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1473 #[inline]
1474 pub const fn algebraic_rem(self, rhs: f16) -> f16 {
1475 intrinsics::frem_algebraic(self, rhs)
1476 }
1477}
1478
1479// Functions in this module fall into `core_float_math`
1480// #[unstable(feature = "core_float_math", issue = "137578")]
1481#[cfg(not(feature = "ferrocene_subset"))]
1482#[cfg(not(test))]
1483#[doc(test(attr(feature(cfg_target_has_reliable_f16_f128), expect(internal_features))))]
1484impl f16 {
1485 /// Returns the largest integer less than or equal to `self`.
1486 ///
1487 /// This function always returns the precise result.
1488 ///
1489 /// # Examples
1490 ///
1491 /// ```
1492 /// #![feature(f16)]
1493 /// # #[cfg(not(miri))]
1494 /// # #[cfg(target_has_reliable_f16)] {
1495 ///
1496 /// let f = 3.7_f16;
1497 /// let g = 3.0_f16;
1498 /// let h = -3.7_f16;
1499 ///
1500 /// assert_eq!(f.floor(), 3.0);
1501 /// assert_eq!(g.floor(), 3.0);
1502 /// assert_eq!(h.floor(), -4.0);
1503 /// # }
1504 /// ```
1505 #[inline]
1506 #[rustc_allow_incoherent_impl]
1507 #[unstable(feature = "f16", issue = "116909")]
1508 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1509 #[must_use = "method returns a new number and does not mutate the original value"]
1510 pub const fn floor(self) -> f16 {
1511 intrinsics::floorf16(self)
1512 }
1513
1514 /// Returns the smallest integer greater than or equal to `self`.
1515 ///
1516 /// This function always returns the precise result.
1517 ///
1518 /// # Examples
1519 ///
1520 /// ```
1521 /// #![feature(f16)]
1522 /// # #[cfg(not(miri))]
1523 /// # #[cfg(target_has_reliable_f16)] {
1524 ///
1525 /// let f = 3.01_f16;
1526 /// let g = 4.0_f16;
1527 ///
1528 /// assert_eq!(f.ceil(), 4.0);
1529 /// assert_eq!(g.ceil(), 4.0);
1530 /// # }
1531 /// ```
1532 #[inline]
1533 #[doc(alias = "ceiling")]
1534 #[rustc_allow_incoherent_impl]
1535 #[unstable(feature = "f16", issue = "116909")]
1536 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1537 #[must_use = "method returns a new number and does not mutate the original value"]
1538 pub const fn ceil(self) -> f16 {
1539 intrinsics::ceilf16(self)
1540 }
1541
1542 /// Returns the nearest integer to `self`. If a value is half-way between two
1543 /// integers, round away from `0.0`.
1544 ///
1545 /// This function always returns the precise result.
1546 ///
1547 /// # Examples
1548 ///
1549 /// ```
1550 /// #![feature(f16)]
1551 /// # #[cfg(not(miri))]
1552 /// # #[cfg(target_has_reliable_f16)] {
1553 ///
1554 /// let f = 3.3_f16;
1555 /// let g = -3.3_f16;
1556 /// let h = -3.7_f16;
1557 /// let i = 3.5_f16;
1558 /// let j = 4.5_f16;
1559 ///
1560 /// assert_eq!(f.round(), 3.0);
1561 /// assert_eq!(g.round(), -3.0);
1562 /// assert_eq!(h.round(), -4.0);
1563 /// assert_eq!(i.round(), 4.0);
1564 /// assert_eq!(j.round(), 5.0);
1565 /// # }
1566 /// ```
1567 #[inline]
1568 #[rustc_allow_incoherent_impl]
1569 #[unstable(feature = "f16", issue = "116909")]
1570 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1571 #[must_use = "method returns a new number and does not mutate the original value"]
1572 pub const fn round(self) -> f16 {
1573 intrinsics::roundf16(self)
1574 }
1575
1576 /// Returns the nearest integer to a number. Rounds half-way cases to the number
1577 /// with an even least significant digit.
1578 ///
1579 /// This function always returns the precise result.
1580 ///
1581 /// # Examples
1582 ///
1583 /// ```
1584 /// #![feature(f16)]
1585 /// # #[cfg(not(miri))]
1586 /// # #[cfg(target_has_reliable_f16)] {
1587 ///
1588 /// let f = 3.3_f16;
1589 /// let g = -3.3_f16;
1590 /// let h = 3.5_f16;
1591 /// let i = 4.5_f16;
1592 ///
1593 /// assert_eq!(f.round_ties_even(), 3.0);
1594 /// assert_eq!(g.round_ties_even(), -3.0);
1595 /// assert_eq!(h.round_ties_even(), 4.0);
1596 /// assert_eq!(i.round_ties_even(), 4.0);
1597 /// # }
1598 /// ```
1599 #[inline]
1600 #[rustc_allow_incoherent_impl]
1601 #[unstable(feature = "f16", issue = "116909")]
1602 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1603 #[must_use = "method returns a new number and does not mutate the original value"]
1604 pub const fn round_ties_even(self) -> f16 {
1605 intrinsics::round_ties_even_f16(self)
1606 }
1607
1608 /// Returns the integer part of `self`.
1609 /// This means that non-integer numbers are always truncated towards zero.
1610 ///
1611 /// This function always returns the precise result.
1612 ///
1613 /// # Examples
1614 ///
1615 /// ```
1616 /// #![feature(f16)]
1617 /// # #[cfg(not(miri))]
1618 /// # #[cfg(target_has_reliable_f16)] {
1619 ///
1620 /// let f = 3.7_f16;
1621 /// let g = 3.0_f16;
1622 /// let h = -3.7_f16;
1623 ///
1624 /// assert_eq!(f.trunc(), 3.0);
1625 /// assert_eq!(g.trunc(), 3.0);
1626 /// assert_eq!(h.trunc(), -3.0);
1627 /// # }
1628 /// ```
1629 #[inline]
1630 #[doc(alias = "truncate")]
1631 #[rustc_allow_incoherent_impl]
1632 #[unstable(feature = "f16", issue = "116909")]
1633 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1634 #[must_use = "method returns a new number and does not mutate the original value"]
1635 pub const fn trunc(self) -> f16 {
1636 intrinsics::truncf16(self)
1637 }
1638
1639 /// Returns the fractional part of `self`.
1640 ///
1641 /// This function always returns the precise result.
1642 ///
1643 /// # Examples
1644 ///
1645 /// ```
1646 /// #![feature(f16)]
1647 /// # #[cfg(not(miri))]
1648 /// # #[cfg(target_has_reliable_f16)] {
1649 ///
1650 /// let x = 3.6_f16;
1651 /// let y = -3.6_f16;
1652 /// let abs_difference_x = (x.fract() - 0.6).abs();
1653 /// let abs_difference_y = (y.fract() - (-0.6)).abs();
1654 ///
1655 /// assert!(abs_difference_x <= f16::EPSILON);
1656 /// assert!(abs_difference_y <= f16::EPSILON);
1657 /// # }
1658 /// ```
1659 #[inline]
1660 #[rustc_allow_incoherent_impl]
1661 #[unstable(feature = "f16", issue = "116909")]
1662 #[rustc_const_unstable(feature = "f16", issue = "116909")]
1663 #[must_use = "method returns a new number and does not mutate the original value"]
1664 pub const fn fract(self) -> f16 {
1665 self - self.trunc()
1666 }
1667
1668 /// Fused multiply-add. Computes `(self * a) + b` with only one rounding
1669 /// error, yielding a more accurate result than an unfused multiply-add.
1670 ///
1671 /// Using `mul_add` *may* be more performant than an unfused multiply-add if
1672 /// the target architecture has a dedicated `fma` CPU instruction. However,
1673 /// this is not always true, and will be heavily dependant on designing
1674 /// algorithms with specific target hardware in mind.
1675 ///
1676 /// # Precision
1677 ///
1678 /// The result of this operation is guaranteed to be the rounded
1679 /// infinite-precision result. It is specified by IEEE 754 as
1680 /// `fusedMultiplyAdd` and guaranteed not to change.
1681 ///
1682 /// # Examples
1683 ///
1684 /// ```
1685 /// #![feature(f16)]
1686 /// # #[cfg(not(miri))]
1687 /// # #[cfg(target_has_reliable_f16)] {
1688 ///
1689 /// let m = 10.0_f16;
1690 /// let x = 4.0_f16;
1691 /// let b = 60.0_f16;
1692 ///
1693 /// assert_eq!(m.mul_add(x, b), 100.0);
1694 /// assert_eq!(m * x + b, 100.0);
1695 ///
1696 /// let one_plus_eps = 1.0_f16 + f16::EPSILON;
1697 /// let one_minus_eps = 1.0_f16 - f16::EPSILON;
1698 /// let minus_one = -1.0_f16;
1699 ///
1700 /// // The exact result (1 + eps) * (1 - eps) = 1 - eps * eps.
1701 /// assert_eq!(one_plus_eps.mul_add(one_minus_eps, minus_one), -f16::EPSILON * f16::EPSILON);
1702 /// // Different rounding with the non-fused multiply and add.
1703 /// assert_eq!(one_plus_eps * one_minus_eps + minus_one, 0.0);
1704 /// # }
1705 /// ```
1706 #[inline]
1707 #[rustc_allow_incoherent_impl]
1708 #[unstable(feature = "f16", issue = "116909")]
1709 #[doc(alias = "fmaf16", alias = "fusedMultiplyAdd")]
1710 #[must_use = "method returns a new number and does not mutate the original value"]
1711 pub const fn mul_add(self, a: f16, b: f16) -> f16 {
1712 intrinsics::fmaf16(self, a, b)
1713 }
1714
1715 /// Calculates Euclidean division, the matching method for `rem_euclid`.
1716 ///
1717 /// This computes the integer `n` such that
1718 /// `self = n * rhs + self.rem_euclid(rhs)`.
1719 /// In other words, the result is `self / rhs` rounded to the integer `n`
1720 /// such that `self >= n * rhs`.
1721 ///
1722 /// # Precision
1723 ///
1724 /// The result of this operation is guaranteed to be the rounded
1725 /// infinite-precision result.
1726 ///
1727 /// # Examples
1728 ///
1729 /// ```
1730 /// #![feature(f16)]
1731 /// # #[cfg(not(miri))]
1732 /// # #[cfg(target_has_reliable_f16)] {
1733 ///
1734 /// let a: f16 = 7.0;
1735 /// let b = 4.0;
1736 /// assert_eq!(a.div_euclid(b), 1.0); // 7.0 > 4.0 * 1.0
1737 /// assert_eq!((-a).div_euclid(b), -2.0); // -7.0 >= 4.0 * -2.0
1738 /// assert_eq!(a.div_euclid(-b), -1.0); // 7.0 >= -4.0 * -1.0
1739 /// assert_eq!((-a).div_euclid(-b), 2.0); // -7.0 >= -4.0 * 2.0
1740 /// # }
1741 /// ```
1742 #[inline]
1743 #[rustc_allow_incoherent_impl]
1744 #[unstable(feature = "f16", issue = "116909")]
1745 #[must_use = "method returns a new number and does not mutate the original value"]
1746 pub fn div_euclid(self, rhs: f16) -> f16 {
1747 let q = (self / rhs).trunc();
1748 if self % rhs < 0.0 {
1749 return if rhs > 0.0 { q - 1.0 } else { q + 1.0 };
1750 }
1751 q
1752 }
1753
1754 /// Calculates the least nonnegative remainder of `self` when
1755 /// divided by `rhs`.
1756 ///
1757 /// In particular, the return value `r` satisfies `0.0 <= r < rhs.abs()` in
1758 /// most cases. However, due to a floating point round-off error it can
1759 /// result in `r == rhs.abs()`, violating the mathematical definition, if
1760 /// `self` is much smaller than `rhs.abs()` in magnitude and `self < 0.0`.
1761 /// This result is not an element of the function's codomain, but it is the
1762 /// closest floating point number in the real numbers and thus fulfills the
1763 /// property `self == self.div_euclid(rhs) * rhs + self.rem_euclid(rhs)`
1764 /// approximately.
1765 ///
1766 /// # Precision
1767 ///
1768 /// The result of this operation is guaranteed to be the rounded
1769 /// infinite-precision result.
1770 ///
1771 /// # Examples
1772 ///
1773 /// ```
1774 /// #![feature(f16)]
1775 /// # #[cfg(not(miri))]
1776 /// # #[cfg(target_has_reliable_f16)] {
1777 ///
1778 /// let a: f16 = 7.0;
1779 /// let b = 4.0;
1780 /// assert_eq!(a.rem_euclid(b), 3.0);
1781 /// assert_eq!((-a).rem_euclid(b), 1.0);
1782 /// assert_eq!(a.rem_euclid(-b), 3.0);
1783 /// assert_eq!((-a).rem_euclid(-b), 1.0);
1784 /// // limitation due to round-off error
1785 /// assert!((-f16::EPSILON).rem_euclid(3.0) != 0.0);
1786 /// # }
1787 /// ```
1788 #[inline]
1789 #[rustc_allow_incoherent_impl]
1790 #[doc(alias = "modulo", alias = "mod")]
1791 #[unstable(feature = "f16", issue = "116909")]
1792 #[must_use = "method returns a new number and does not mutate the original value"]
1793 pub fn rem_euclid(self, rhs: f16) -> f16 {
1794 let r = self % rhs;
1795 if r < 0.0 { r + rhs.abs() } else { r }
1796 }
1797
1798 /// Raises a number to an integer power.
1799 ///
1800 /// Using this function is generally faster than using `powf`.
1801 /// It might have a different sequence of rounding operations than `powf`,
1802 /// so the results are not guaranteed to agree.
1803 ///
1804 /// Note that this function is special in that it can return non-NaN results for NaN inputs. For
1805 /// example, `f16::powi(f16::NAN, 0)` returns `1.0`. However, if an input is a *signaling*
1806 /// NaN, then the result is non-deterministically either a NaN or the result that the
1807 /// corresponding quiet NaN would produce.
1808 ///
1809 /// # Unspecified precision
1810 ///
1811 /// The precision of this function is non-deterministic. This means it varies by platform,
1812 /// Rust version, and can even differ within the same execution from one invocation to the next.
1813 ///
1814 /// # Examples
1815 ///
1816 /// ```
1817 /// #![feature(f16)]
1818 /// # #[cfg(not(miri))]
1819 /// # #[cfg(target_has_reliable_f16)] {
1820 ///
1821 /// let x = 2.0_f16;
1822 /// let abs_difference = (x.powi(2) - (x * x)).abs();
1823 /// assert!(abs_difference <= f16::EPSILON);
1824 ///
1825 /// assert_eq!(f16::powi(f16::NAN, 0), 1.0);
1826 /// assert_eq!(f16::powi(0.0, 0), 1.0);
1827 /// # }
1828 /// ```
1829 #[inline]
1830 #[rustc_allow_incoherent_impl]
1831 #[unstable(feature = "f16", issue = "116909")]
1832 #[must_use = "method returns a new number and does not mutate the original value"]
1833 pub fn powi(self, n: i32) -> f16 {
1834 intrinsics::powif16(self, n)
1835 }
1836
1837 /// Returns the square root of a number.
1838 ///
1839 /// Returns NaN if `self` is a negative number other than `-0.0`.
1840 ///
1841 /// # Precision
1842 ///
1843 /// The result of this operation is guaranteed to be the rounded
1844 /// infinite-precision result. It is specified by IEEE 754 as `squareRoot`
1845 /// and guaranteed not to change.
1846 ///
1847 /// # Examples
1848 ///
1849 /// ```
1850 /// #![feature(f16)]
1851 /// # #[cfg(not(miri))]
1852 /// # #[cfg(target_has_reliable_f16)] {
1853 ///
1854 /// let positive = 4.0_f16;
1855 /// let negative = -4.0_f16;
1856 /// let negative_zero = -0.0_f16;
1857 ///
1858 /// assert_eq!(positive.sqrt(), 2.0);
1859 /// assert!(negative.sqrt().is_nan());
1860 /// assert!(negative_zero.sqrt() == negative_zero);
1861 /// # }
1862 /// ```
1863 #[inline]
1864 #[doc(alias = "squareRoot")]
1865 #[rustc_allow_incoherent_impl]
1866 #[unstable(feature = "f16", issue = "116909")]
1867 #[must_use = "method returns a new number and does not mutate the original value"]
1868 pub fn sqrt(self) -> f16 {
1869 intrinsics::sqrtf16(self)
1870 }
1871
1872 /// Returns the cube root of a number.
1873 ///
1874 /// # Unspecified precision
1875 ///
1876 /// The precision of this function is non-deterministic. This means it varies by platform,
1877 /// Rust version, and can even differ within the same execution from one invocation to the next.
1878 ///
1879 /// This function currently corresponds to the `cbrtf` from libc on Unix
1880 /// and Windows. Note that this might change in the future.
1881 ///
1882 /// # Examples
1883 ///
1884 /// ```
1885 /// #![feature(f16)]
1886 /// # #[cfg(not(miri))]
1887 /// # #[cfg(target_has_reliable_f16)] {
1888 ///
1889 /// let x = 8.0f16;
1890 ///
1891 /// // x^(1/3) - 2 == 0
1892 /// let abs_difference = (x.cbrt() - 2.0).abs();
1893 ///
1894 /// assert!(abs_difference <= f16::EPSILON);
1895 /// # }
1896 /// ```
1897 #[inline]
1898 #[rustc_allow_incoherent_impl]
1899 #[unstable(feature = "f16", issue = "116909")]
1900 #[must_use = "method returns a new number and does not mutate the original value"]
1901 pub fn cbrt(self) -> f16 {
1902 libm::cbrtf(self as f32) as f16
1903 }
1904}