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core/num/
f128.rs

1//! Constants for the `f128` quadruple-precision floating point type.
2//!
3//! *[See also the `f128` primitive type][f128].*
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 `f128` type.
11
12#![unstable(feature = "f128", issue = "116909")]
13
14use crate::convert::FloatToInt;
15use crate::num::FpCategory;
16use crate::panic::const_assert;
17use crate::{intrinsics, mem};
18
19/// Basic mathematical constants.
20#[unstable(feature = "f128", issue = "116909")]
21#[rustc_diagnostic_item = "f128_consts_mod"]
22pub mod consts {
23    // FIXME: replace with mathematical constants from cmath.
24
25    /// Archimedes' constant (π)
26    #[unstable(feature = "f128", issue = "116909")]
27    pub const PI: f128 = 3.14159265358979323846264338327950288419716939937510582097494_f128;
28
29    /// The full circle constant (τ)
30    ///
31    /// Equal to 2π.
32    #[unstable(feature = "f128", issue = "116909")]
33    pub const TAU: f128 = 6.28318530717958647692528676655900576839433879875021164194989_f128;
34
35    /// The golden ratio (φ)
36    #[unstable(feature = "f128", issue = "116909")]
37    pub const GOLDEN_RATIO: f128 =
38        1.61803398874989484820458683436563811772030917980576286213545_f128;
39
40    /// The Euler-Mascheroni constant (γ)
41    #[unstable(feature = "f128", issue = "116909")]
42    pub const EULER_GAMMA: f128 =
43        0.577215664901532860606512090082402431042159335939923598805767_f128;
44
45    /// π/2
46    #[unstable(feature = "f128", issue = "116909")]
47    pub const FRAC_PI_2: f128 = 1.57079632679489661923132169163975144209858469968755291048747_f128;
48
49    /// π/3
50    #[unstable(feature = "f128", issue = "116909")]
51    pub const FRAC_PI_3: f128 = 1.04719755119659774615421446109316762806572313312503527365831_f128;
52
53    /// π/4
54    #[unstable(feature = "f128", issue = "116909")]
55    pub const FRAC_PI_4: f128 = 0.785398163397448309615660845819875721049292349843776455243736_f128;
56
57    /// π/6
58    #[unstable(feature = "f128", issue = "116909")]
59    pub const FRAC_PI_6: f128 = 0.523598775598298873077107230546583814032861566562517636829157_f128;
60
61    /// π/8
62    #[unstable(feature = "f128", issue = "116909")]
63    pub const FRAC_PI_8: f128 = 0.392699081698724154807830422909937860524646174921888227621868_f128;
64
65    /// 1/π
66    #[unstable(feature = "f128", issue = "116909")]
67    pub const FRAC_1_PI: f128 = 0.318309886183790671537767526745028724068919291480912897495335_f128;
68
69    /// 1/sqrt(π)
70    #[unstable(feature = "f128", issue = "116909")]
71    // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
72    pub const FRAC_1_SQRT_PI: f128 =
73        0.564189583547756286948079451560772585844050629328998856844086_f128;
74
75    /// 1/sqrt(2π)
76    #[doc(alias = "FRAC_1_SQRT_TAU")]
77    #[unstable(feature = "f128", issue = "116909")]
78    // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
79    pub const FRAC_1_SQRT_2PI: f128 =
80        0.398942280401432677939946059934381868475858631164934657665926_f128;
81
82    /// 2/π
83    #[unstable(feature = "f128", issue = "116909")]
84    pub const FRAC_2_PI: f128 = 0.636619772367581343075535053490057448137838582961825794990669_f128;
85
86    /// 2/sqrt(π)
87    #[unstable(feature = "f128", issue = "116909")]
88    pub const FRAC_2_SQRT_PI: f128 =
89        1.12837916709551257389615890312154517168810125865799771368817_f128;
90
91    /// sqrt(2)
92    #[unstable(feature = "f128", issue = "116909")]
93    pub const SQRT_2: f128 = 1.41421356237309504880168872420969807856967187537694807317668_f128;
94
95    /// 1/sqrt(2)
96    #[unstable(feature = "f128", issue = "116909")]
97    pub const FRAC_1_SQRT_2: f128 =
98        0.707106781186547524400844362104849039284835937688474036588340_f128;
99
100    /// sqrt(3)
101    #[unstable(feature = "f128", issue = "116909")]
102    // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
103    pub const SQRT_3: f128 = 1.73205080756887729352744634150587236694280525381038062805581_f128;
104
105    /// 1/sqrt(3)
106    #[unstable(feature = "f128", issue = "116909")]
107    // Also, #[unstable(feature = "more_float_constants", issue = "146939")]
108    pub const FRAC_1_SQRT_3: f128 =
109        0.577350269189625764509148780501957455647601751270126876018602_f128;
110
111    /// Euler's number (e)
112    #[unstable(feature = "f128", issue = "116909")]
113    pub const E: f128 = 2.71828182845904523536028747135266249775724709369995957496697_f128;
114
115    /// log<sub>2</sub>(10)
116    #[unstable(feature = "f128", issue = "116909")]
117    pub const LOG2_10: f128 = 3.32192809488736234787031942948939017586483139302458061205476_f128;
118
119    /// log<sub>2</sub>(e)
120    #[unstable(feature = "f128", issue = "116909")]
121    pub const LOG2_E: f128 = 1.44269504088896340735992468100189213742664595415298593413545_f128;
122
123    /// log<sub>10</sub>(2)
124    #[unstable(feature = "f128", issue = "116909")]
125    pub const LOG10_2: f128 = 0.301029995663981195213738894724493026768189881462108541310427_f128;
126
127    /// log<sub>10</sub>(e)
128    #[unstable(feature = "f128", issue = "116909")]
129    pub const LOG10_E: f128 = 0.434294481903251827651128918916605082294397005803666566114454_f128;
130
131    /// ln(2)
132    #[unstable(feature = "f128", issue = "116909")]
133    pub const LN_2: f128 = 0.693147180559945309417232121458176568075500134360255254120680_f128;
134
135    /// ln(10)
136    #[unstable(feature = "f128", issue = "116909")]
137    pub const LN_10: f128 = 2.30258509299404568401799145468436420760110148862877297603333_f128;
138}
139
140#[doc(test(attr(feature(cfg_target_has_reliable_f16_f128), allow(internal_features))))]
141impl f128 {
142    /// The radix or base of the internal representation of `f128`.
143    #[unstable(feature = "f128", issue = "116909")]
144    pub const RADIX: u32 = 2;
145
146    /// Number of significant digits in base 2.
147    ///
148    /// Note that the size of the mantissa in the bitwise representation is one
149    /// smaller than this since the leading 1 is not stored explicitly.
150    #[unstable(feature = "f128", issue = "116909")]
151    pub const MANTISSA_DIGITS: u32 = 113;
152
153    /// Approximate number of significant digits in base 10.
154    ///
155    /// This is the maximum <i>x</i> such that any decimal number with <i>x</i>
156    /// significant digits can be converted to `f128` and back without loss.
157    ///
158    /// Equal to floor(log<sub>10</sub>&nbsp;2<sup>[`MANTISSA_DIGITS`]&nbsp;&minus;&nbsp;1</sup>).
159    ///
160    /// [`MANTISSA_DIGITS`]: f128::MANTISSA_DIGITS
161    #[unstable(feature = "f128", issue = "116909")]
162    pub const DIGITS: u32 = 33;
163
164    /// [Machine epsilon] value for `f128`.
165    ///
166    /// This is the difference between `1.0` and the next larger representable number.
167    ///
168    /// Equal to 2<sup>1&nbsp;&minus;&nbsp;[`MANTISSA_DIGITS`]</sup>.
169    ///
170    /// [Machine epsilon]: https://en.wikipedia.org/wiki/Machine_epsilon
171    /// [`MANTISSA_DIGITS`]: f128::MANTISSA_DIGITS
172    #[unstable(feature = "f128", issue = "116909")]
173    #[rustc_diagnostic_item = "f128_epsilon"]
174    pub const EPSILON: f128 = 1.92592994438723585305597794258492732e-34_f128;
175
176    /// Smallest finite `f128` value.
177    ///
178    /// Equal to &minus;[`MAX`].
179    ///
180    /// [`MAX`]: f128::MAX
181    #[unstable(feature = "f128", issue = "116909")]
182    pub const MIN: f128 = -1.18973149535723176508575932662800702e+4932_f128;
183    /// Smallest positive normal `f128` value.
184    ///
185    /// Equal to 2<sup>[`MIN_EXP`]&nbsp;&minus;&nbsp;1</sup>.
186    ///
187    /// [`MIN_EXP`]: f128::MIN_EXP
188    #[unstable(feature = "f128", issue = "116909")]
189    pub const MIN_POSITIVE: f128 = 3.36210314311209350626267781732175260e-4932_f128;
190    /// Largest finite `f128` value.
191    ///
192    /// Equal to
193    /// (1&nbsp;&minus;&nbsp;2<sup>&minus;[`MANTISSA_DIGITS`]</sup>)&nbsp;2<sup>[`MAX_EXP`]</sup>.
194    ///
195    /// [`MANTISSA_DIGITS`]: f128::MANTISSA_DIGITS
196    /// [`MAX_EXP`]: f128::MAX_EXP
197    #[unstable(feature = "f128", issue = "116909")]
198    pub const MAX: f128 = 1.18973149535723176508575932662800702e+4932_f128;
199
200    /// One greater than the minimum possible *normal* power of 2 exponent
201    /// for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).
202    ///
203    /// This corresponds to the exact minimum possible *normal* power of 2 exponent
204    /// for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition).
205    /// In other words, all normal numbers representable by this type are
206    /// greater than or equal to 0.5&nbsp;×&nbsp;2<sup><i>MIN_EXP</i></sup>.
207    #[unstable(feature = "f128", issue = "116909")]
208    pub const MIN_EXP: i32 = -16_381;
209    /// One greater than the maximum possible power of 2 exponent
210    /// for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).
211    ///
212    /// This corresponds to the exact maximum possible power of 2 exponent
213    /// for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition).
214    /// In other words, all numbers representable by this type are
215    /// strictly less than 2<sup><i>MAX_EXP</i></sup>.
216    #[unstable(feature = "f128", issue = "116909")]
217    pub const MAX_EXP: i32 = 16_384;
218
219    /// Minimum <i>x</i> for which 10<sup><i>x</i></sup> is normal.
220    ///
221    /// Equal to ceil(log<sub>10</sub>&nbsp;[`MIN_POSITIVE`]).
222    ///
223    /// [`MIN_POSITIVE`]: f128::MIN_POSITIVE
224    #[unstable(feature = "f128", issue = "116909")]
225    pub const MIN_10_EXP: i32 = -4_931;
226    /// Maximum <i>x</i> for which 10<sup><i>x</i></sup> is normal.
227    ///
228    /// Equal to floor(log<sub>10</sub>&nbsp;[`MAX`]).
229    ///
230    /// [`MAX`]: f128::MAX
231    #[unstable(feature = "f128", issue = "116909")]
232    pub const MAX_10_EXP: i32 = 4_932;
233
234    /// Not a Number (NaN).
235    ///
236    /// Note that IEEE 754 doesn't define just a single NaN value; a plethora of bit patterns are
237    /// considered to be NaN. Furthermore, the standard makes a difference between a "signaling" and
238    /// a "quiet" NaN, and allows inspecting its "payload" (the unspecified bits in the bit pattern)
239    /// and its sign. See the [specification of NaN bit patterns](f32#nan-bit-patterns) for more
240    /// info.
241    ///
242    /// This constant is guaranteed to be a quiet NaN (on targets that follow the Rust assumptions
243    /// that the quiet/signaling bit being set to 1 indicates a quiet NaN). Beyond that, nothing is
244    /// guaranteed about the specific bit pattern chosen here: both payload and sign are arbitrary.
245    /// The concrete bit pattern may change across Rust versions and target platforms.
246    #[allow(clippy::eq_op)]
247    #[rustc_diagnostic_item = "f128_nan"]
248    #[unstable(feature = "f128", issue = "116909")]
249    pub const NAN: f128 = 0.0_f128 / 0.0_f128;
250
251    /// Infinity (∞).
252    #[unstable(feature = "f128", issue = "116909")]
253    pub const INFINITY: f128 = 1.0_f128 / 0.0_f128;
254
255    /// Negative infinity (−∞).
256    #[unstable(feature = "f128", issue = "116909")]
257    pub const NEG_INFINITY: f128 = -1.0_f128 / 0.0_f128;
258
259    /// Sign bit
260    pub(crate) const SIGN_MASK: u128 = 0x8000_0000_0000_0000_0000_0000_0000_0000;
261
262    /// Exponent mask
263    pub(crate) const EXP_MASK: u128 = 0x7fff_0000_0000_0000_0000_0000_0000_0000;
264
265    /// Mantissa mask
266    pub(crate) const MAN_MASK: u128 = 0x0000_ffff_ffff_ffff_ffff_ffff_ffff_ffff;
267
268    /// Minimum representable positive value (min subnormal)
269    const TINY_BITS: u128 = 0x1;
270
271    /// Minimum representable negative value (min negative subnormal)
272    const NEG_TINY_BITS: u128 = Self::TINY_BITS | Self::SIGN_MASK;
273
274    /// Returns `true` if this value is NaN.
275    ///
276    /// ```
277    /// #![feature(f128)]
278    /// # #[cfg(target_has_reliable_f128)] {
279    ///
280    /// let nan = f128::NAN;
281    /// let f = 7.0_f128;
282    ///
283    /// assert!(nan.is_nan());
284    /// assert!(!f.is_nan());
285    /// # }
286    /// ```
287    #[inline]
288    #[must_use]
289    #[unstable(feature = "f128", issue = "116909")]
290    #[allow(clippy::eq_op)] // > if you intended to check if the operand is NaN, use `.is_nan()` instead :)
291    pub const fn is_nan(self) -> bool {
292        self != self
293    }
294
295    /// Returns `true` if this value is positive infinity or negative infinity, and
296    /// `false` otherwise.
297    ///
298    /// ```
299    /// #![feature(f128)]
300    /// # #[cfg(target_has_reliable_f128)] {
301    ///
302    /// let f = 7.0f128;
303    /// let inf = f128::INFINITY;
304    /// let neg_inf = f128::NEG_INFINITY;
305    /// let nan = f128::NAN;
306    ///
307    /// assert!(!f.is_infinite());
308    /// assert!(!nan.is_infinite());
309    ///
310    /// assert!(inf.is_infinite());
311    /// assert!(neg_inf.is_infinite());
312    /// # }
313    /// ```
314    #[inline]
315    #[must_use]
316    #[unstable(feature = "f128", issue = "116909")]
317    pub const fn is_infinite(self) -> bool {
318        (self == f128::INFINITY) | (self == f128::NEG_INFINITY)
319    }
320
321    /// Returns `true` if this number is neither infinite nor NaN.
322    ///
323    /// ```
324    /// #![feature(f128)]
325    /// # #[cfg(target_has_reliable_f128)] {
326    ///
327    /// let f = 7.0f128;
328    /// let inf: f128 = f128::INFINITY;
329    /// let neg_inf: f128 = f128::NEG_INFINITY;
330    /// let nan: f128 = f128::NAN;
331    ///
332    /// assert!(f.is_finite());
333    ///
334    /// assert!(!nan.is_finite());
335    /// assert!(!inf.is_finite());
336    /// assert!(!neg_inf.is_finite());
337    /// # }
338    /// ```
339    #[inline]
340    #[must_use]
341    #[unstable(feature = "f128", issue = "116909")]
342    #[rustc_const_unstable(feature = "f128", issue = "116909")]
343    pub const fn is_finite(self) -> bool {
344        // There's no need to handle NaN separately: if self is NaN,
345        // the comparison is not true, exactly as desired.
346        self.abs() < Self::INFINITY
347    }
348
349    /// Returns `true` if the number is [subnormal].
350    ///
351    /// ```
352    /// #![feature(f128)]
353    /// # #[cfg(target_has_reliable_f128)] {
354    ///
355    /// let min = f128::MIN_POSITIVE; // 3.362103143e-4932f128
356    /// let max = f128::MAX;
357    /// let lower_than_min = 1.0e-4960_f128;
358    /// let zero = 0.0_f128;
359    ///
360    /// assert!(!min.is_subnormal());
361    /// assert!(!max.is_subnormal());
362    ///
363    /// assert!(!zero.is_subnormal());
364    /// assert!(!f128::NAN.is_subnormal());
365    /// assert!(!f128::INFINITY.is_subnormal());
366    /// // Values between `0` and `min` are Subnormal.
367    /// assert!(lower_than_min.is_subnormal());
368    /// # }
369    /// ```
370    ///
371    /// [subnormal]: https://en.wikipedia.org/wiki/Denormal_number
372    #[inline]
373    #[must_use]
374    #[unstable(feature = "f128", issue = "116909")]
375    pub const fn is_subnormal(self) -> bool {
376        matches!(self.classify(), FpCategory::Subnormal)
377    }
378
379    /// Returns `true` if the number is neither zero, infinite, [subnormal], or NaN.
380    ///
381    /// ```
382    /// #![feature(f128)]
383    /// # #[cfg(target_has_reliable_f128)] {
384    ///
385    /// let min = f128::MIN_POSITIVE; // 3.362103143e-4932f128
386    /// let max = f128::MAX;
387    /// let lower_than_min = 1.0e-4960_f128;
388    /// let zero = 0.0_f128;
389    ///
390    /// assert!(min.is_normal());
391    /// assert!(max.is_normal());
392    ///
393    /// assert!(!zero.is_normal());
394    /// assert!(!f128::NAN.is_normal());
395    /// assert!(!f128::INFINITY.is_normal());
396    /// // Values between `0` and `min` are Subnormal.
397    /// assert!(!lower_than_min.is_normal());
398    /// # }
399    /// ```
400    ///
401    /// [subnormal]: https://en.wikipedia.org/wiki/Denormal_number
402    #[inline]
403    #[must_use]
404    #[unstable(feature = "f128", issue = "116909")]
405    pub const fn is_normal(self) -> bool {
406        matches!(self.classify(), FpCategory::Normal)
407    }
408
409    /// Returns the floating point category of the number. If only one property
410    /// is going to be tested, it is generally faster to use the specific
411    /// predicate instead.
412    ///
413    /// ```
414    /// #![feature(f128)]
415    /// # #[cfg(target_has_reliable_f128)] {
416    ///
417    /// use std::num::FpCategory;
418    ///
419    /// let num = 12.4_f128;
420    /// let inf = f128::INFINITY;
421    ///
422    /// assert_eq!(num.classify(), FpCategory::Normal);
423    /// assert_eq!(inf.classify(), FpCategory::Infinite);
424    /// # }
425    /// ```
426    #[inline]
427    #[unstable(feature = "f128", issue = "116909")]
428    pub const fn classify(self) -> FpCategory {
429        let bits = self.to_bits();
430        match (bits & Self::MAN_MASK, bits & Self::EXP_MASK) {
431            (0, Self::EXP_MASK) => FpCategory::Infinite,
432            (_, Self::EXP_MASK) => FpCategory::Nan,
433            (0, 0) => FpCategory::Zero,
434            (_, 0) => FpCategory::Subnormal,
435            _ => FpCategory::Normal,
436        }
437    }
438
439    /// Returns `true` if `self` has a positive sign, including `+0.0`, NaNs with
440    /// positive sign bit and positive infinity.
441    ///
442    /// Note that IEEE 754 doesn't assign any meaning to the sign bit in case of
443    /// a NaN, and as Rust doesn't guarantee that the bit pattern of NaNs are
444    /// conserved over arithmetic operations, the result of `is_sign_positive` on
445    /// a NaN might produce an unexpected or non-portable result. See the [specification
446    /// of NaN bit patterns](f32#nan-bit-patterns) for more info. Use `self.signum() == 1.0`
447    /// if you need fully portable behavior (will return `false` for all NaNs).
448    ///
449    /// ```
450    /// #![feature(f128)]
451    ///
452    /// let f = 7.0_f128;
453    /// let g = -7.0_f128;
454    ///
455    /// assert!(f.is_sign_positive());
456    /// assert!(!g.is_sign_positive());
457    /// ```
458    #[inline]
459    #[must_use]
460    #[unstable(feature = "f128", issue = "116909")]
461    pub const fn is_sign_positive(self) -> bool {
462        !self.is_sign_negative()
463    }
464
465    /// Returns `true` if `self` has a negative sign, including `-0.0`, NaNs with
466    /// negative sign bit and negative infinity.
467    ///
468    /// Note that IEEE 754 doesn't assign any meaning to the sign bit in case of
469    /// a NaN, and as Rust doesn't guarantee that the bit pattern of NaNs are
470    /// conserved over arithmetic operations, the result of `is_sign_negative` on
471    /// a NaN might produce an unexpected or non-portable result. See the [specification
472    /// of NaN bit patterns](f32#nan-bit-patterns) for more info. Use `self.signum() == -1.0`
473    /// if you need fully portable behavior (will return `false` for all NaNs).
474    ///
475    /// ```
476    /// #![feature(f128)]
477    ///
478    /// let f = 7.0_f128;
479    /// let g = -7.0_f128;
480    ///
481    /// assert!(!f.is_sign_negative());
482    /// assert!(g.is_sign_negative());
483    /// ```
484    #[inline]
485    #[must_use]
486    #[unstable(feature = "f128", issue = "116909")]
487    pub const fn is_sign_negative(self) -> bool {
488        // IEEE754 says: isSignMinus(x) is true if and only if x has negative sign. isSignMinus
489        // applies to zeros and NaNs as well.
490        // SAFETY: This is just transmuting to get the sign bit, it's fine.
491        (self.to_bits() & (1 << 127)) != 0
492    }
493
494    /// Returns the least number greater than `self`.
495    ///
496    /// Let `TINY` be the smallest representable positive `f128`. Then,
497    ///  - if `self.is_nan()`, this returns `self`;
498    ///  - if `self` is [`NEG_INFINITY`], this returns [`MIN`];
499    ///  - if `self` is `-TINY`, this returns -0.0;
500    ///  - if `self` is -0.0 or +0.0, this returns `TINY`;
501    ///  - if `self` is [`MAX`] or [`INFINITY`], this returns [`INFINITY`];
502    ///  - otherwise the unique least value greater than `self` is returned.
503    ///
504    /// The identity `x.next_up() == -(-x).next_down()` holds for all non-NaN `x`. When `x`
505    /// is finite `x == x.next_up().next_down()` also holds.
506    ///
507    /// ```rust
508    /// #![feature(f128)]
509    /// # #[cfg(target_has_reliable_f128)] {
510    ///
511    /// // f128::EPSILON is the difference between 1.0 and the next number up.
512    /// assert_eq!(1.0f128.next_up(), 1.0 + f128::EPSILON);
513    /// // But not for most numbers.
514    /// assert!(0.1f128.next_up() < 0.1 + f128::EPSILON);
515    /// assert_eq!(4611686018427387904f128.next_up(), 4611686018427387904.000000000000001);
516    /// # }
517    /// ```
518    ///
519    /// This operation corresponds to IEEE-754 `nextUp`.
520    ///
521    /// [`NEG_INFINITY`]: Self::NEG_INFINITY
522    /// [`INFINITY`]: Self::INFINITY
523    /// [`MIN`]: Self::MIN
524    /// [`MAX`]: Self::MAX
525    #[inline]
526    #[doc(alias = "nextUp")]
527    #[unstable(feature = "f128", issue = "116909")]
528    pub const fn next_up(self) -> Self {
529        // Some targets violate Rust's assumption of IEEE semantics, e.g. by flushing
530        // denormals to zero. This is in general unsound and unsupported, but here
531        // we do our best to still produce the correct result on such targets.
532        let bits = self.to_bits();
533        if self.is_nan() || bits == Self::INFINITY.to_bits() {
534            return self;
535        }
536
537        let abs = bits & !Self::SIGN_MASK;
538        let next_bits = if abs == 0 {
539            Self::TINY_BITS
540        } else if bits == abs {
541            bits + 1
542        } else {
543            bits - 1
544        };
545        Self::from_bits(next_bits)
546    }
547
548    /// Returns the greatest number less than `self`.
549    ///
550    /// Let `TINY` be the smallest representable positive `f128`. Then,
551    ///  - if `self.is_nan()`, this returns `self`;
552    ///  - if `self` is [`INFINITY`], this returns [`MAX`];
553    ///  - if `self` is `TINY`, this returns 0.0;
554    ///  - if `self` is -0.0 or +0.0, this returns `-TINY`;
555    ///  - if `self` is [`MIN`] or [`NEG_INFINITY`], this returns [`NEG_INFINITY`];
556    ///  - otherwise the unique greatest value less than `self` is returned.
557    ///
558    /// The identity `x.next_down() == -(-x).next_up()` holds for all non-NaN `x`. When `x`
559    /// is finite `x == x.next_down().next_up()` also holds.
560    ///
561    /// ```rust
562    /// #![feature(f128)]
563    /// # #[cfg(target_has_reliable_f128)] {
564    ///
565    /// let x = 1.0f128;
566    /// // Clamp value into range [0, 1).
567    /// let clamped = x.clamp(0.0, 1.0f128.next_down());
568    /// assert!(clamped < 1.0);
569    /// assert_eq!(clamped.next_up(), 1.0);
570    /// # }
571    /// ```
572    ///
573    /// This operation corresponds to IEEE-754 `nextDown`.
574    ///
575    /// [`NEG_INFINITY`]: Self::NEG_INFINITY
576    /// [`INFINITY`]: Self::INFINITY
577    /// [`MIN`]: Self::MIN
578    /// [`MAX`]: Self::MAX
579    #[inline]
580    #[doc(alias = "nextDown")]
581    #[unstable(feature = "f128", issue = "116909")]
582    pub const fn next_down(self) -> Self {
583        // Some targets violate Rust's assumption of IEEE semantics, e.g. by flushing
584        // denormals to zero. This is in general unsound and unsupported, but here
585        // we do our best to still produce the correct result on such targets.
586        let bits = self.to_bits();
587        if self.is_nan() || bits == Self::NEG_INFINITY.to_bits() {
588            return self;
589        }
590
591        let abs = bits & !Self::SIGN_MASK;
592        let next_bits = if abs == 0 {
593            Self::NEG_TINY_BITS
594        } else if bits == abs {
595            bits - 1
596        } else {
597            bits + 1
598        };
599        Self::from_bits(next_bits)
600    }
601
602    /// Takes the reciprocal (inverse) of a number, `1/x`.
603    ///
604    /// ```
605    /// #![feature(f128)]
606    /// # #[cfg(target_has_reliable_f128)] {
607    ///
608    /// let x = 2.0_f128;
609    /// let abs_difference = (x.recip() - (1.0 / x)).abs();
610    ///
611    /// assert!(abs_difference <= f128::EPSILON);
612    /// # }
613    /// ```
614    #[inline]
615    #[unstable(feature = "f128", issue = "116909")]
616    #[must_use = "this returns the result of the operation, without modifying the original"]
617    pub const fn recip(self) -> Self {
618        1.0 / self
619    }
620
621    /// Converts radians to degrees.
622    ///
623    /// # Unspecified precision
624    ///
625    /// The precision of this function is non-deterministic. This means it varies by platform,
626    /// Rust version, and can even differ within the same execution from one invocation to the next.
627    ///
628    /// # Examples
629    ///
630    /// ```
631    /// #![feature(f128)]
632    /// # #[cfg(target_has_reliable_f128)] {
633    ///
634    /// let angle = std::f128::consts::PI;
635    ///
636    /// let abs_difference = (angle.to_degrees() - 180.0).abs();
637    /// assert!(abs_difference <= f128::EPSILON);
638    /// # }
639    /// ```
640    #[inline]
641    #[unstable(feature = "f128", issue = "116909")]
642    #[must_use = "this returns the result of the operation, without modifying the original"]
643    pub const fn to_degrees(self) -> Self {
644        // The division here is correctly rounded with respect to the true value of 180/π.
645        // Although π is irrational and already rounded, the double rounding happens
646        // to produce correct result for f128.
647        const PIS_IN_180: f128 = 180.0 / consts::PI;
648        self * PIS_IN_180
649    }
650
651    /// Converts degrees to radians.
652    ///
653    /// # Unspecified precision
654    ///
655    /// The precision of this function is non-deterministic. This means it varies by platform,
656    /// Rust version, and can even differ within the same execution from one invocation to the next.
657    ///
658    /// # Examples
659    ///
660    /// ```
661    /// #![feature(f128)]
662    /// # #[cfg(target_has_reliable_f128)] {
663    ///
664    /// let angle = 180.0f128;
665    ///
666    /// let abs_difference = (angle.to_radians() - std::f128::consts::PI).abs();
667    ///
668    /// assert!(abs_difference <= 1e-30);
669    /// # }
670    /// ```
671    #[inline]
672    #[unstable(feature = "f128", issue = "116909")]
673    #[must_use = "this returns the result of the operation, without modifying the original"]
674    pub const fn to_radians(self) -> f128 {
675        // Use a literal to avoid double rounding, consts::PI is already rounded,
676        // and dividing would round again.
677        const RADS_PER_DEG: f128 =
678            0.0174532925199432957692369076848861271344287188854172545609719_f128;
679        self * RADS_PER_DEG
680    }
681
682    /// Returns the maximum of the two numbers, ignoring NaN.
683    ///
684    /// If exactly one of the arguments is NaN (quiet or signaling), then the other argument is
685    /// returned. If both arguments are NaN, the return value is NaN, with the bit pattern picked
686    /// using the usual [rules for arithmetic operations](f32#nan-bit-patterns). If the inputs
687    /// compare equal (such as for the case of `+0.0` and `-0.0`), either input may be returned
688    /// non-deterministically.
689    ///
690    /// The handling of NaNs follows the IEEE 754-2019 semantics for `maximumNumber`, treating all
691    /// NaNs the same way to ensure the operation is associative. The handling of signed zeros
692    /// follows the IEEE 754-2008 semantics for `maxNum`.
693    ///
694    /// ```
695    /// #![feature(f128)]
696    /// # #[cfg(target_has_reliable_f128_math)] {
697    ///
698    /// let x = 1.0f128;
699    /// let y = 2.0f128;
700    ///
701    /// assert_eq!(x.max(y), y);
702    /// assert_eq!(x.max(f128::NAN), x);
703    /// # }
704    /// ```
705    #[inline]
706    #[unstable(feature = "f128", issue = "116909")]
707    #[rustc_const_unstable(feature = "f128", issue = "116909")]
708    #[must_use = "this returns the result of the comparison, without modifying either input"]
709    pub const fn max(self, other: f128) -> f128 {
710        intrinsics::maxnumf128(self, other)
711    }
712
713    /// Returns the minimum of the two numbers, ignoring NaN.
714    ///
715    /// If exactly one of the arguments is NaN (quiet or signaling), then the other argument is
716    /// returned. If both arguments are NaN, the return value is NaN, with the bit pattern picked
717    /// using the usual [rules for arithmetic operations](f32#nan-bit-patterns). If the inputs
718    /// compare equal (such as for the case of `+0.0` and `-0.0`), either input may be returned
719    /// non-deterministically.
720    ///
721    /// The handling of NaNs follows the IEEE 754-2019 semantics for `minimumNumber`, treating all
722    /// NaNs the same way to ensure the operation is associative. The handling of signed zeros
723    /// follows the IEEE 754-2008 semantics for `minNum`.
724    ///
725    /// ```
726    /// #![feature(f128)]
727    /// # #[cfg(target_has_reliable_f128_math)] {
728    ///
729    /// let x = 1.0f128;
730    /// let y = 2.0f128;
731    ///
732    /// assert_eq!(x.min(y), x);
733    /// assert_eq!(x.min(f128::NAN), x);
734    /// # }
735    /// ```
736    #[inline]
737    #[unstable(feature = "f128", issue = "116909")]
738    #[rustc_const_unstable(feature = "f128", issue = "116909")]
739    #[must_use = "this returns the result of the comparison, without modifying either input"]
740    pub const fn min(self, other: f128) -> f128 {
741        intrinsics::minnumf128(self, other)
742    }
743
744    /// Returns the maximum of the two numbers, propagating NaN.
745    ///
746    /// If at least one of the arguments is NaN, the return value is NaN, with the bit pattern
747    /// picked using the usual [rules for arithmetic operations](f32#nan-bit-patterns). Furthermore,
748    /// `-0.0` is considered to be less than `+0.0`, making this function fully deterministic for
749    /// non-NaN inputs.
750    ///
751    /// This is in contrast to [`f128::max`] which only returns NaN when *both* arguments are NaN,
752    /// and which does not reliably order `-0.0` and `+0.0`.
753    ///
754    /// This follows the IEEE 754-2019 semantics for `maximum`.
755    ///
756    /// ```
757    /// #![feature(f128)]
758    /// #![feature(float_minimum_maximum)]
759    /// # #[cfg(target_has_reliable_f128_math)] {
760    ///
761    /// let x = 1.0f128;
762    /// let y = 2.0f128;
763    ///
764    /// assert_eq!(x.maximum(y), y);
765    /// assert!(x.maximum(f128::NAN).is_nan());
766    /// # }
767    /// ```
768    #[inline]
769    #[unstable(feature = "f128", issue = "116909")]
770    // #[unstable(feature = "float_minimum_maximum", issue = "91079")]
771    #[must_use = "this returns the result of the comparison, without modifying either input"]
772    pub const fn maximum(self, other: f128) -> f128 {
773        intrinsics::maximumf128(self, other)
774    }
775
776    /// Returns the minimum of the two numbers, propagating NaN.
777    ///
778    /// If at least one of the arguments is NaN, the return value is NaN, with the bit pattern
779    /// picked using the usual [rules for arithmetic operations](f32#nan-bit-patterns). Furthermore,
780    /// `-0.0` is considered to be less than `+0.0`, making this function fully deterministic for
781    /// non-NaN inputs.
782    ///
783    /// This is in contrast to [`f128::min`] which only returns NaN when *both* arguments are NaN,
784    /// and which does not reliably order `-0.0` and `+0.0`.
785    ///
786    /// This follows the IEEE 754-2019 semantics for `minimum`.
787    ///
788    /// ```
789    /// #![feature(f128)]
790    /// #![feature(float_minimum_maximum)]
791    /// # #[cfg(target_has_reliable_f128_math)] {
792    ///
793    /// let x = 1.0f128;
794    /// let y = 2.0f128;
795    ///
796    /// assert_eq!(x.minimum(y), x);
797    /// assert!(x.minimum(f128::NAN).is_nan());
798    /// # }
799    /// ```
800    #[inline]
801    #[unstable(feature = "f128", issue = "116909")]
802    // #[unstable(feature = "float_minimum_maximum", issue = "91079")]
803    #[must_use = "this returns the result of the comparison, without modifying either input"]
804    pub const fn minimum(self, other: f128) -> f128 {
805        intrinsics::minimumf128(self, other)
806    }
807
808    /// Calculates the midpoint (average) between `self` and `rhs`.
809    ///
810    /// This returns NaN when *either* argument is NaN or if a combination of
811    /// +inf and -inf is provided as arguments.
812    ///
813    /// # Examples
814    ///
815    /// ```
816    /// #![feature(f128)]
817    /// # #[cfg(target_has_reliable_f128)] {
818    ///
819    /// assert_eq!(1f128.midpoint(4.0), 2.5);
820    /// assert_eq!((-5.5f128).midpoint(8.0), 1.25);
821    /// # }
822    /// ```
823    #[inline]
824    #[doc(alias = "average")]
825    #[unstable(feature = "f128", issue = "116909")]
826    #[rustc_const_unstable(feature = "f128", issue = "116909")]
827    pub const fn midpoint(self, other: f128) -> f128 {
828        const HI: f128 = f128::MAX / 2.;
829
830        let (a, b) = (self, other);
831        let abs_a = a.abs();
832        let abs_b = b.abs();
833
834        if abs_a <= HI && abs_b <= HI {
835            // Overflow is impossible
836            (a + b) / 2.
837        } else {
838            (a / 2.) + (b / 2.)
839        }
840    }
841
842    /// Rounds toward zero and converts to any primitive integer type,
843    /// assuming that the value is finite and fits in that type.
844    ///
845    /// ```
846    /// #![feature(f128)]
847    /// # #[cfg(target_has_reliable_f128)] {
848    ///
849    /// let value = 4.6_f128;
850    /// let rounded = unsafe { value.to_int_unchecked::<u16>() };
851    /// assert_eq!(rounded, 4);
852    ///
853    /// let value = -128.9_f128;
854    /// let rounded = unsafe { value.to_int_unchecked::<i8>() };
855    /// assert_eq!(rounded, i8::MIN);
856    /// # }
857    /// ```
858    ///
859    /// # Safety
860    ///
861    /// The value must:
862    ///
863    /// * Not be `NaN`
864    /// * Not be infinite
865    /// * Be representable in the return type `Int`, after truncating off its fractional part
866    #[inline]
867    #[unstable(feature = "f128", issue = "116909")]
868    #[must_use = "this returns the result of the operation, without modifying the original"]
869    pub unsafe fn to_int_unchecked<Int>(self) -> Int
870    where
871        Self: FloatToInt<Int>,
872    {
873        // SAFETY: the caller must uphold the safety contract for
874        // `FloatToInt::to_int_unchecked`.
875        unsafe { FloatToInt::<Int>::to_int_unchecked(self) }
876    }
877
878    /// Raw transmutation to `u128`.
879    ///
880    /// This is currently identical to `transmute::<f128, u128>(self)` on all platforms.
881    ///
882    /// See [`from_bits`](#method.from_bits) for some discussion of the
883    /// portability of this operation (there are almost no issues).
884    ///
885    /// Note that this function is distinct from `as` casting, which attempts to
886    /// preserve the *numeric* value, and not the bitwise value.
887    ///
888    /// ```
889    /// #![feature(f128)]
890    /// # #[cfg(target_has_reliable_f128)] {
891    ///
892    /// assert_ne!((1f128).to_bits(), 1f128 as u128); // to_bits() is not casting!
893    /// assert_eq!((12.5f128).to_bits(), 0x40029000000000000000000000000000);
894    /// # }
895    /// ```
896    #[inline]
897    #[unstable(feature = "f128", issue = "116909")]
898    #[must_use = "this returns the result of the operation, without modifying the original"]
899    #[allow(unnecessary_transmutes)]
900    pub const fn to_bits(self) -> u128 {
901        // SAFETY: `u128` is a plain old datatype so we can always transmute to it.
902        unsafe { mem::transmute(self) }
903    }
904
905    /// Raw transmutation from `u128`.
906    ///
907    /// This is currently identical to `transmute::<u128, f128>(v)` on all platforms.
908    /// It turns out this is incredibly portable, for two reasons:
909    ///
910    /// * Floats and Ints have the same endianness on all supported platforms.
911    /// * IEEE 754 very precisely specifies the bit layout of floats.
912    ///
913    /// However there is one caveat: prior to the 2008 version of IEEE 754, how
914    /// to interpret the NaN signaling bit wasn't actually specified. Most platforms
915    /// (notably x86 and ARM) picked the interpretation that was ultimately
916    /// standardized in 2008, but some didn't (notably MIPS). As a result, all
917    /// signaling NaNs on MIPS are quiet NaNs on x86, and vice-versa.
918    ///
919    /// Rather than trying to preserve signaling-ness cross-platform, this
920    /// implementation favors preserving the exact bits. This means that
921    /// any payloads encoded in NaNs will be preserved even if the result of
922    /// this method is sent over the network from an x86 machine to a MIPS one.
923    ///
924    /// If the results of this method are only manipulated by the same
925    /// architecture that produced them, then there is no portability concern.
926    ///
927    /// If the input isn't NaN, then there is no portability concern.
928    ///
929    /// If you don't care about signalingness (very likely), then there is no
930    /// portability concern.
931    ///
932    /// Note that this function is distinct from `as` casting, which attempts to
933    /// preserve the *numeric* value, and not the bitwise value.
934    ///
935    /// ```
936    /// #![feature(f128)]
937    /// # #[cfg(target_has_reliable_f128)] {
938    ///
939    /// let v = f128::from_bits(0x40029000000000000000000000000000);
940    /// assert_eq!(v, 12.5);
941    /// # }
942    /// ```
943    #[inline]
944    #[must_use]
945    #[unstable(feature = "f128", issue = "116909")]
946    #[allow(unnecessary_transmutes)]
947    pub const fn from_bits(v: u128) -> Self {
948        // It turns out the safety issues with sNaN were overblown! Hooray!
949        // SAFETY: `u128` is a plain old datatype so we can always transmute from it.
950        unsafe { mem::transmute(v) }
951    }
952
953    /// Returns the memory representation of this floating point number as a byte array in
954    /// big-endian (network) byte order.
955    ///
956    /// See [`from_bits`](Self::from_bits) for some discussion of the
957    /// portability of this operation (there are almost no issues).
958    ///
959    /// # Examples
960    ///
961    /// ```
962    /// #![feature(f128)]
963    ///
964    /// let bytes = 12.5f128.to_be_bytes();
965    /// assert_eq!(
966    ///     bytes,
967    ///     [0x40, 0x02, 0x90, 0x00, 0x00, 0x00, 0x00, 0x00,
968    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
969    /// );
970    /// ```
971    #[inline]
972    #[unstable(feature = "f128", issue = "116909")]
973    #[must_use = "this returns the result of the operation, without modifying the original"]
974    pub const fn to_be_bytes(self) -> [u8; 16] {
975        self.to_bits().to_be_bytes()
976    }
977
978    /// Returns the memory representation of this floating point number as a byte array in
979    /// little-endian byte order.
980    ///
981    /// See [`from_bits`](Self::from_bits) for some discussion of the
982    /// portability of this operation (there are almost no issues).
983    ///
984    /// # Examples
985    ///
986    /// ```
987    /// #![feature(f128)]
988    ///
989    /// let bytes = 12.5f128.to_le_bytes();
990    /// assert_eq!(
991    ///     bytes,
992    ///     [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
993    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x90, 0x02, 0x40]
994    /// );
995    /// ```
996    #[inline]
997    #[unstable(feature = "f128", issue = "116909")]
998    #[must_use = "this returns the result of the operation, without modifying the original"]
999    pub const fn to_le_bytes(self) -> [u8; 16] {
1000        self.to_bits().to_le_bytes()
1001    }
1002
1003    /// Returns the memory representation of this floating point number as a byte array in
1004    /// native byte order.
1005    ///
1006    /// As the target platform's native endianness is used, portable code
1007    /// should use [`to_be_bytes`] or [`to_le_bytes`], as appropriate, instead.
1008    ///
1009    /// [`to_be_bytes`]: f128::to_be_bytes
1010    /// [`to_le_bytes`]: f128::to_le_bytes
1011    ///
1012    /// See [`from_bits`](Self::from_bits) for some discussion of the
1013    /// portability of this operation (there are almost no issues).
1014    ///
1015    /// # Examples
1016    ///
1017    /// ```
1018    /// #![feature(f128)]
1019    ///
1020    /// let bytes = 12.5f128.to_ne_bytes();
1021    /// assert_eq!(
1022    ///     bytes,
1023    ///     if cfg!(target_endian = "big") {
1024    ///         [0x40, 0x02, 0x90, 0x00, 0x00, 0x00, 0x00, 0x00,
1025    ///          0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
1026    ///     } else {
1027    ///         [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1028    ///          0x00, 0x00, 0x00, 0x00, 0x00, 0x90, 0x02, 0x40]
1029    ///     }
1030    /// );
1031    /// ```
1032    #[inline]
1033    #[unstable(feature = "f128", issue = "116909")]
1034    #[must_use = "this returns the result of the operation, without modifying the original"]
1035    pub const fn to_ne_bytes(self) -> [u8; 16] {
1036        self.to_bits().to_ne_bytes()
1037    }
1038
1039    /// Creates a floating point value from its representation as a byte array in big endian.
1040    ///
1041    /// See [`from_bits`](Self::from_bits) for some discussion of the
1042    /// portability of this operation (there are almost no issues).
1043    ///
1044    /// # Examples
1045    ///
1046    /// ```
1047    /// #![feature(f128)]
1048    /// # #[cfg(target_has_reliable_f128)] {
1049    ///
1050    /// let value = f128::from_be_bytes(
1051    ///     [0x40, 0x02, 0x90, 0x00, 0x00, 0x00, 0x00, 0x00,
1052    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
1053    /// );
1054    /// assert_eq!(value, 12.5);
1055    /// # }
1056    /// ```
1057    #[inline]
1058    #[must_use]
1059    #[unstable(feature = "f128", issue = "116909")]
1060    pub const fn from_be_bytes(bytes: [u8; 16]) -> Self {
1061        Self::from_bits(u128::from_be_bytes(bytes))
1062    }
1063
1064    /// Creates a floating point value from its representation as a byte array in little endian.
1065    ///
1066    /// See [`from_bits`](Self::from_bits) for some discussion of the
1067    /// portability of this operation (there are almost no issues).
1068    ///
1069    /// # Examples
1070    ///
1071    /// ```
1072    /// #![feature(f128)]
1073    /// # #[cfg(target_has_reliable_f128)] {
1074    ///
1075    /// let value = f128::from_le_bytes(
1076    ///     [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1077    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x90, 0x02, 0x40]
1078    /// );
1079    /// assert_eq!(value, 12.5);
1080    /// # }
1081    /// ```
1082    #[inline]
1083    #[must_use]
1084    #[unstable(feature = "f128", issue = "116909")]
1085    pub const fn from_le_bytes(bytes: [u8; 16]) -> Self {
1086        Self::from_bits(u128::from_le_bytes(bytes))
1087    }
1088
1089    /// Creates a floating point value from its representation as a byte array in native endian.
1090    ///
1091    /// As the target platform's native endianness is used, portable code
1092    /// likely wants to use [`from_be_bytes`] or [`from_le_bytes`], as
1093    /// appropriate instead.
1094    ///
1095    /// [`from_be_bytes`]: f128::from_be_bytes
1096    /// [`from_le_bytes`]: f128::from_le_bytes
1097    ///
1098    /// See [`from_bits`](Self::from_bits) for some discussion of the
1099    /// portability of this operation (there are almost no issues).
1100    ///
1101    /// # Examples
1102    ///
1103    /// ```
1104    /// #![feature(f128)]
1105    /// # #[cfg(target_has_reliable_f128)] {
1106    ///
1107    /// let value = f128::from_ne_bytes(if cfg!(target_endian = "big") {
1108    ///     [0x40, 0x02, 0x90, 0x00, 0x00, 0x00, 0x00, 0x00,
1109    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
1110    /// } else {
1111    ///     [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,
1112    ///      0x00, 0x00, 0x00, 0x00, 0x00, 0x90, 0x02, 0x40]
1113    /// });
1114    /// assert_eq!(value, 12.5);
1115    /// # }
1116    /// ```
1117    #[inline]
1118    #[must_use]
1119    #[unstable(feature = "f128", issue = "116909")]
1120    pub const fn from_ne_bytes(bytes: [u8; 16]) -> Self {
1121        Self::from_bits(u128::from_ne_bytes(bytes))
1122    }
1123
1124    /// Returns the ordering between `self` and `other`.
1125    ///
1126    /// Unlike the standard partial comparison between floating point numbers,
1127    /// this comparison always produces an ordering in accordance to
1128    /// the `totalOrder` predicate as defined in the IEEE 754 (2008 revision)
1129    /// floating point standard. The values are ordered in the following sequence:
1130    ///
1131    /// - negative quiet NaN
1132    /// - negative signaling NaN
1133    /// - negative infinity
1134    /// - negative numbers
1135    /// - negative subnormal numbers
1136    /// - negative zero
1137    /// - positive zero
1138    /// - positive subnormal numbers
1139    /// - positive numbers
1140    /// - positive infinity
1141    /// - positive signaling NaN
1142    /// - positive quiet NaN.
1143    ///
1144    /// The ordering established by this function does not always agree with the
1145    /// [`PartialOrd`] and [`PartialEq`] implementations of `f128`. For example,
1146    /// they consider negative and positive zero equal, while `total_cmp`
1147    /// doesn't.
1148    ///
1149    /// The interpretation of the signaling NaN bit follows the definition in
1150    /// the IEEE 754 standard, which may not match the interpretation by some of
1151    /// the older, non-conformant (e.g. MIPS) hardware implementations.
1152    ///
1153    /// # Example
1154    ///
1155    /// ```
1156    /// #![feature(f128)]
1157    ///
1158    /// struct GoodBoy {
1159    ///     name: &'static str,
1160    ///     weight: f128,
1161    /// }
1162    ///
1163    /// let mut bois = vec![
1164    ///     GoodBoy { name: "Pucci", weight: 0.1 },
1165    ///     GoodBoy { name: "Woofer", weight: 99.0 },
1166    ///     GoodBoy { name: "Yapper", weight: 10.0 },
1167    ///     GoodBoy { name: "Chonk", weight: f128::INFINITY },
1168    ///     GoodBoy { name: "Abs. Unit", weight: f128::NAN },
1169    ///     GoodBoy { name: "Floaty", weight: -5.0 },
1170    /// ];
1171    ///
1172    /// bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));
1173    ///
1174    /// // `f128::NAN` could be positive or negative, which will affect the sort order.
1175    /// if f128::NAN.is_sign_negative() {
1176    ///     bois.into_iter().map(|b| b.weight)
1177    ///         .zip([f128::NAN, -5.0, 0.1, 10.0, 99.0, f128::INFINITY].iter())
1178    ///         .for_each(|(a, b)| assert_eq!(a.to_bits(), b.to_bits()))
1179    /// } else {
1180    ///     bois.into_iter().map(|b| b.weight)
1181    ///         .zip([-5.0, 0.1, 10.0, 99.0, f128::INFINITY, f128::NAN].iter())
1182    ///         .for_each(|(a, b)| assert_eq!(a.to_bits(), b.to_bits()))
1183    /// }
1184    /// ```
1185    #[inline]
1186    #[must_use]
1187    #[unstable(feature = "f128", issue = "116909")]
1188    #[rustc_const_unstable(feature = "const_cmp", issue = "143800")]
1189    pub const fn total_cmp(&self, other: &Self) -> crate::cmp::Ordering {
1190        let mut left = self.to_bits() as i128;
1191        let mut right = other.to_bits() as i128;
1192
1193        // In case of negatives, flip all the bits except the sign
1194        // to achieve a similar layout as two's complement integers
1195        //
1196        // Why does this work? IEEE 754 floats consist of three fields:
1197        // Sign bit, exponent and mantissa. The set of exponent and mantissa
1198        // fields as a whole have the property that their bitwise order is
1199        // equal to the numeric magnitude where the magnitude is defined.
1200        // The magnitude is not normally defined on NaN values, but
1201        // IEEE 754 totalOrder defines the NaN values also to follow the
1202        // bitwise order. This leads to order explained in the doc comment.
1203        // However, the representation of magnitude is the same for negative
1204        // and positive numbers – only the sign bit is different.
1205        // To easily compare the floats as signed integers, we need to
1206        // flip the exponent and mantissa bits in case of negative numbers.
1207        // We effectively convert the numbers to "two's complement" form.
1208        //
1209        // To do the flipping, we construct a mask and XOR against it.
1210        // We branchlessly calculate an "all-ones except for the sign bit"
1211        // mask from negative-signed values: right shifting sign-extends
1212        // the integer, so we "fill" the mask with sign bits, and then
1213        // convert to unsigned to push one more zero bit.
1214        // On positive values, the mask is all zeros, so it's a no-op.
1215        left ^= (((left >> 127) as u128) >> 1) as i128;
1216        right ^= (((right >> 127) as u128) >> 1) as i128;
1217
1218        left.cmp(&right)
1219    }
1220
1221    /// Restrict a value to a certain interval unless it is NaN.
1222    ///
1223    /// Returns `max` if `self` is greater than `max`, and `min` if `self` is
1224    /// less than `min`. Otherwise this returns `self`.
1225    ///
1226    /// Note that this function returns NaN if the initial value was NaN as
1227    /// well. If the result is zero and among the three inputs `self`, `min`, and `max` there are
1228    /// zeros with different sign, either `0.0` or `-0.0` is returned non-deterministically.
1229    ///
1230    /// # Panics
1231    ///
1232    /// Panics if `min > max`, `min` is NaN, or `max` is NaN.
1233    ///
1234    /// # Examples
1235    ///
1236    /// ```
1237    /// #![feature(f128)]
1238    /// # #[cfg(target_has_reliable_f128)] {
1239    ///
1240    /// assert!((-3.0f128).clamp(-2.0, 1.0) == -2.0);
1241    /// assert!((0.0f128).clamp(-2.0, 1.0) == 0.0);
1242    /// assert!((2.0f128).clamp(-2.0, 1.0) == 1.0);
1243    /// assert!((f128::NAN).clamp(-2.0, 1.0).is_nan());
1244    ///
1245    /// // These always returns zero, but the sign (which is ignored by `==`) is non-deterministic.
1246    /// assert!((0.0f128).clamp(-0.0, -0.0) == 0.0);
1247    /// assert!((1.0f128).clamp(-0.0, 0.0) == 0.0);
1248    /// // This is definitely a negative zero.
1249    /// assert!((-1.0f128).clamp(-0.0, 1.0).is_sign_negative());
1250    /// # }
1251    /// ```
1252    #[inline]
1253    #[unstable(feature = "f128", issue = "116909")]
1254    #[must_use = "method returns a new number and does not mutate the original value"]
1255    pub const fn clamp(mut self, min: f128, max: f128) -> f128 {
1256        const_assert!(
1257            min <= max,
1258            "min > max, or either was NaN",
1259            "min > max, or either was NaN. min = {min:?}, max = {max:?}",
1260            min: f128,
1261            max: f128,
1262        );
1263
1264        if self < min {
1265            self = min;
1266        }
1267        if self > max {
1268            self = max;
1269        }
1270        self
1271    }
1272
1273    /// Clamps this number to a symmetric range centered around zero.
1274    ///
1275    /// The method clamps the number's magnitude (absolute value) to be at most `limit`.
1276    ///
1277    /// This is functionally equivalent to `self.clamp(-limit, limit)`, but is more
1278    /// explicit about the intent.
1279    ///
1280    /// # Panics
1281    ///
1282    /// Panics if `limit` is negative or NaN, as this indicates a logic error.
1283    ///
1284    /// # Examples
1285    ///
1286    /// ```
1287    /// #![feature(f128)]
1288    /// #![feature(clamp_magnitude)]
1289    /// # #[cfg(all(target_arch = "x86_64", target_os = "linux"))] {
1290    /// assert_eq!(5.0f128.clamp_magnitude(3.0), 3.0);
1291    /// assert_eq!((-5.0f128).clamp_magnitude(3.0), -3.0);
1292    /// assert_eq!(2.0f128.clamp_magnitude(3.0), 2.0);
1293    /// assert_eq!((-2.0f128).clamp_magnitude(3.0), -2.0);
1294    /// # }
1295    /// ```
1296    #[inline]
1297    #[unstable(feature = "clamp_magnitude", issue = "148519")]
1298    #[must_use = "this returns the clamped value and does not modify the original"]
1299    pub fn clamp_magnitude(self, limit: f128) -> f128 {
1300        assert!(limit >= 0.0, "limit must be non-negative");
1301        let limit = limit.abs(); // Canonicalises -0.0 to 0.0
1302        self.clamp(-limit, limit)
1303    }
1304
1305    /// Computes the absolute value of `self`.
1306    ///
1307    /// This function always returns the precise result.
1308    ///
1309    /// # Examples
1310    ///
1311    /// ```
1312    /// #![feature(f128)]
1313    /// # #[cfg(target_has_reliable_f128)] {
1314    ///
1315    /// let x = 3.5_f128;
1316    /// let y = -3.5_f128;
1317    ///
1318    /// assert_eq!(x.abs(), x);
1319    /// assert_eq!(y.abs(), -y);
1320    ///
1321    /// assert!(f128::NAN.abs().is_nan());
1322    /// # }
1323    /// ```
1324    #[inline]
1325    #[unstable(feature = "f128", issue = "116909")]
1326    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1327    #[must_use = "method returns a new number and does not mutate the original value"]
1328    pub const fn abs(self) -> Self {
1329        intrinsics::fabsf128(self)
1330    }
1331
1332    /// Returns a number that represents the sign of `self`.
1333    ///
1334    /// - `1.0` if the number is positive, `+0.0` or `INFINITY`
1335    /// - `-1.0` if the number is negative, `-0.0` or `NEG_INFINITY`
1336    /// - NaN if the number is NaN
1337    ///
1338    /// # Examples
1339    ///
1340    /// ```
1341    /// #![feature(f128)]
1342    /// # #[cfg(target_has_reliable_f128)] {
1343    ///
1344    /// let f = 3.5_f128;
1345    ///
1346    /// assert_eq!(f.signum(), 1.0);
1347    /// assert_eq!(f128::NEG_INFINITY.signum(), -1.0);
1348    ///
1349    /// assert!(f128::NAN.signum().is_nan());
1350    /// # }
1351    /// ```
1352    #[inline]
1353    #[unstable(feature = "f128", issue = "116909")]
1354    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1355    #[must_use = "method returns a new number and does not mutate the original value"]
1356    pub const fn signum(self) -> f128 {
1357        if self.is_nan() { Self::NAN } else { 1.0_f128.copysign(self) }
1358    }
1359
1360    /// Returns a number composed of the magnitude of `self` and the sign of
1361    /// `sign`.
1362    ///
1363    /// Equal to `self` if the sign of `self` and `sign` are the same, otherwise equal to `-self`.
1364    /// If `self` is a NaN, then a NaN with the same payload as `self` and the sign bit of `sign` is
1365    /// returned.
1366    ///
1367    /// If `sign` is a NaN, then this operation will still carry over its sign into the result. Note
1368    /// that IEEE 754 doesn't assign any meaning to the sign bit in case of a NaN, and as Rust
1369    /// doesn't guarantee that the bit pattern of NaNs are conserved over arithmetic operations, the
1370    /// result of `copysign` with `sign` being a NaN might produce an unexpected or non-portable
1371    /// result. See the [specification of NaN bit patterns](primitive@f32#nan-bit-patterns) for more
1372    /// info.
1373    ///
1374    /// # Examples
1375    ///
1376    /// ```
1377    /// #![feature(f128)]
1378    /// # #[cfg(target_has_reliable_f128)] {
1379    ///
1380    /// let f = 3.5_f128;
1381    ///
1382    /// assert_eq!(f.copysign(0.42), 3.5_f128);
1383    /// assert_eq!(f.copysign(-0.42), -3.5_f128);
1384    /// assert_eq!((-f).copysign(0.42), 3.5_f128);
1385    /// assert_eq!((-f).copysign(-0.42), -3.5_f128);
1386    ///
1387    /// assert!(f128::NAN.copysign(1.0).is_nan());
1388    /// # }
1389    /// ```
1390    #[inline]
1391    #[unstable(feature = "f128", issue = "116909")]
1392    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1393    #[must_use = "method returns a new number and does not mutate the original value"]
1394    pub const fn copysign(self, sign: f128) -> f128 {
1395        intrinsics::copysignf128(self, sign)
1396    }
1397
1398    /// Float addition that allows optimizations based on algebraic rules.
1399    ///
1400    /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1401    #[must_use = "method returns a new number and does not mutate the original value"]
1402    #[unstable(feature = "float_algebraic", issue = "136469")]
1403    #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1404    #[inline]
1405    pub const fn algebraic_add(self, rhs: f128) -> f128 {
1406        intrinsics::fadd_algebraic(self, rhs)
1407    }
1408
1409    /// Float subtraction that allows optimizations based on algebraic rules.
1410    ///
1411    /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1412    #[must_use = "method returns a new number and does not mutate the original value"]
1413    #[unstable(feature = "float_algebraic", issue = "136469")]
1414    #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1415    #[inline]
1416    pub const fn algebraic_sub(self, rhs: f128) -> f128 {
1417        intrinsics::fsub_algebraic(self, rhs)
1418    }
1419
1420    /// Float multiplication that allows optimizations based on algebraic rules.
1421    ///
1422    /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1423    #[must_use = "method returns a new number and does not mutate the original value"]
1424    #[unstable(feature = "float_algebraic", issue = "136469")]
1425    #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1426    #[inline]
1427    pub const fn algebraic_mul(self, rhs: f128) -> f128 {
1428        intrinsics::fmul_algebraic(self, rhs)
1429    }
1430
1431    /// Float division that allows optimizations based on algebraic rules.
1432    ///
1433    /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
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_div(self, rhs: f128) -> f128 {
1439        intrinsics::fdiv_algebraic(self, rhs)
1440    }
1441
1442    /// Float remainder that allows optimizations based on algebraic rules.
1443    ///
1444    /// See [algebraic operators](primitive@f32#algebraic-operators) for more info.
1445    #[must_use = "method returns a new number and does not mutate the original value"]
1446    #[unstable(feature = "float_algebraic", issue = "136469")]
1447    #[rustc_const_unstable(feature = "float_algebraic", issue = "136469")]
1448    #[inline]
1449    pub const fn algebraic_rem(self, rhs: f128) -> f128 {
1450        intrinsics::frem_algebraic(self, rhs)
1451    }
1452}
1453
1454// Functions in this module fall into `core_float_math`
1455// #[unstable(feature = "core_float_math", issue = "137578")]
1456#[cfg(not(test))]
1457#[doc(test(attr(feature(cfg_target_has_reliable_f16_f128), expect(internal_features))))]
1458impl f128 {
1459    /// Returns the largest integer less than or equal to `self`.
1460    ///
1461    /// This function always returns the precise result.
1462    ///
1463    /// # Examples
1464    ///
1465    /// ```
1466    /// #![feature(f128)]
1467    /// # #[cfg(not(miri))]
1468    /// # #[cfg(target_has_reliable_f128_math)] {
1469    ///
1470    /// let f = 3.7_f128;
1471    /// let g = 3.0_f128;
1472    /// let h = -3.7_f128;
1473    ///
1474    /// assert_eq!(f.floor(), 3.0);
1475    /// assert_eq!(g.floor(), 3.0);
1476    /// assert_eq!(h.floor(), -4.0);
1477    /// # }
1478    /// ```
1479    #[inline]
1480    #[rustc_allow_incoherent_impl]
1481    #[unstable(feature = "f128", issue = "116909")]
1482    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1483    #[must_use = "method returns a new number and does not mutate the original value"]
1484    pub const fn floor(self) -> f128 {
1485        intrinsics::floorf128(self)
1486    }
1487
1488    /// Returns the smallest integer greater than or equal to `self`.
1489    ///
1490    /// This function always returns the precise result.
1491    ///
1492    /// # Examples
1493    ///
1494    /// ```
1495    /// #![feature(f128)]
1496    /// # #[cfg(not(miri))]
1497    /// # #[cfg(target_has_reliable_f128_math)] {
1498    ///
1499    /// let f = 3.01_f128;
1500    /// let g = 4.0_f128;
1501    ///
1502    /// assert_eq!(f.ceil(), 4.0);
1503    /// assert_eq!(g.ceil(), 4.0);
1504    /// # }
1505    /// ```
1506    #[inline]
1507    #[doc(alias = "ceiling")]
1508    #[rustc_allow_incoherent_impl]
1509    #[unstable(feature = "f128", issue = "116909")]
1510    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1511    #[must_use = "method returns a new number and does not mutate the original value"]
1512    pub const fn ceil(self) -> f128 {
1513        intrinsics::ceilf128(self)
1514    }
1515
1516    /// Returns the nearest integer to `self`. If a value is half-way between two
1517    /// integers, round away from `0.0`.
1518    ///
1519    /// This function always returns the precise result.
1520    ///
1521    /// # Examples
1522    ///
1523    /// ```
1524    /// #![feature(f128)]
1525    /// # #[cfg(not(miri))]
1526    /// # #[cfg(target_has_reliable_f128_math)] {
1527    ///
1528    /// let f = 3.3_f128;
1529    /// let g = -3.3_f128;
1530    /// let h = -3.7_f128;
1531    /// let i = 3.5_f128;
1532    /// let j = 4.5_f128;
1533    ///
1534    /// assert_eq!(f.round(), 3.0);
1535    /// assert_eq!(g.round(), -3.0);
1536    /// assert_eq!(h.round(), -4.0);
1537    /// assert_eq!(i.round(), 4.0);
1538    /// assert_eq!(j.round(), 5.0);
1539    /// # }
1540    /// ```
1541    #[inline]
1542    #[rustc_allow_incoherent_impl]
1543    #[unstable(feature = "f128", issue = "116909")]
1544    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1545    #[must_use = "method returns a new number and does not mutate the original value"]
1546    pub const fn round(self) -> f128 {
1547        intrinsics::roundf128(self)
1548    }
1549
1550    /// Returns the nearest integer to a number. Rounds half-way cases to the number
1551    /// with an even least significant digit.
1552    ///
1553    /// This function always returns the precise result.
1554    ///
1555    /// # Examples
1556    ///
1557    /// ```
1558    /// #![feature(f128)]
1559    /// # #[cfg(not(miri))]
1560    /// # #[cfg(target_has_reliable_f128_math)] {
1561    ///
1562    /// let f = 3.3_f128;
1563    /// let g = -3.3_f128;
1564    /// let h = 3.5_f128;
1565    /// let i = 4.5_f128;
1566    ///
1567    /// assert_eq!(f.round_ties_even(), 3.0);
1568    /// assert_eq!(g.round_ties_even(), -3.0);
1569    /// assert_eq!(h.round_ties_even(), 4.0);
1570    /// assert_eq!(i.round_ties_even(), 4.0);
1571    /// # }
1572    /// ```
1573    #[inline]
1574    #[rustc_allow_incoherent_impl]
1575    #[unstable(feature = "f128", issue = "116909")]
1576    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1577    #[must_use = "method returns a new number and does not mutate the original value"]
1578    pub const fn round_ties_even(self) -> f128 {
1579        intrinsics::round_ties_even_f128(self)
1580    }
1581
1582    /// Returns the integer part of `self`.
1583    /// This means that non-integer numbers are always truncated towards zero.
1584    ///
1585    /// This function always returns the precise result.
1586    ///
1587    /// # Examples
1588    ///
1589    /// ```
1590    /// #![feature(f128)]
1591    /// # #[cfg(not(miri))]
1592    /// # #[cfg(target_has_reliable_f128_math)] {
1593    ///
1594    /// let f = 3.7_f128;
1595    /// let g = 3.0_f128;
1596    /// let h = -3.7_f128;
1597    ///
1598    /// assert_eq!(f.trunc(), 3.0);
1599    /// assert_eq!(g.trunc(), 3.0);
1600    /// assert_eq!(h.trunc(), -3.0);
1601    /// # }
1602    /// ```
1603    #[inline]
1604    #[doc(alias = "truncate")]
1605    #[rustc_allow_incoherent_impl]
1606    #[unstable(feature = "f128", issue = "116909")]
1607    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1608    #[must_use = "method returns a new number and does not mutate the original value"]
1609    pub const fn trunc(self) -> f128 {
1610        intrinsics::truncf128(self)
1611    }
1612
1613    /// Returns the fractional part of `self`.
1614    ///
1615    /// This function always returns the precise result.
1616    ///
1617    /// # Examples
1618    ///
1619    /// ```
1620    /// #![feature(f128)]
1621    /// # #[cfg(not(miri))]
1622    /// # #[cfg(target_has_reliable_f128_math)] {
1623    ///
1624    /// let x = 3.6_f128;
1625    /// let y = -3.6_f128;
1626    /// let abs_difference_x = (x.fract() - 0.6).abs();
1627    /// let abs_difference_y = (y.fract() - (-0.6)).abs();
1628    ///
1629    /// assert!(abs_difference_x <= f128::EPSILON);
1630    /// assert!(abs_difference_y <= f128::EPSILON);
1631    /// # }
1632    /// ```
1633    #[inline]
1634    #[rustc_allow_incoherent_impl]
1635    #[unstable(feature = "f128", issue = "116909")]
1636    #[rustc_const_unstable(feature = "f128", issue = "116909")]
1637    #[must_use = "method returns a new number and does not mutate the original value"]
1638    pub const fn fract(self) -> f128 {
1639        self - self.trunc()
1640    }
1641
1642    /// Fused multiply-add. Computes `(self * a) + b` with only one rounding
1643    /// error, yielding a more accurate result than an unfused multiply-add.
1644    ///
1645    /// Using `mul_add` *may* be more performant than an unfused multiply-add if
1646    /// the target architecture has a dedicated `fma` CPU instruction. However,
1647    /// this is not always true, and will be heavily dependant on designing
1648    /// algorithms with specific target hardware in mind.
1649    ///
1650    /// # Precision
1651    ///
1652    /// The result of this operation is guaranteed to be the rounded
1653    /// infinite-precision result. It is specified by IEEE 754 as
1654    /// `fusedMultiplyAdd` and guaranteed not to change.
1655    ///
1656    /// # Examples
1657    ///
1658    /// ```
1659    /// #![feature(f128)]
1660    /// # #[cfg(not(miri))]
1661    /// # #[cfg(target_has_reliable_f128_math)] {
1662    ///
1663    /// let m = 10.0_f128;
1664    /// let x = 4.0_f128;
1665    /// let b = 60.0_f128;
1666    ///
1667    /// assert_eq!(m.mul_add(x, b), 100.0);
1668    /// assert_eq!(m * x + b, 100.0);
1669    ///
1670    /// let one_plus_eps = 1.0_f128 + f128::EPSILON;
1671    /// let one_minus_eps = 1.0_f128 - f128::EPSILON;
1672    /// let minus_one = -1.0_f128;
1673    ///
1674    /// // The exact result (1 + eps) * (1 - eps) = 1 - eps * eps.
1675    /// assert_eq!(one_plus_eps.mul_add(one_minus_eps, minus_one), -f128::EPSILON * f128::EPSILON);
1676    /// // Different rounding with the non-fused multiply and add.
1677    /// assert_eq!(one_plus_eps * one_minus_eps + minus_one, 0.0);
1678    /// # }
1679    /// ```
1680    #[inline]
1681    #[rustc_allow_incoherent_impl]
1682    #[doc(alias = "fmaf128", alias = "fusedMultiplyAdd")]
1683    #[unstable(feature = "f128", issue = "116909")]
1684    #[must_use = "method returns a new number and does not mutate the original value"]
1685    pub const fn mul_add(self, a: f128, b: f128) -> f128 {
1686        intrinsics::fmaf128(self, a, b)
1687    }
1688
1689    /// Calculates Euclidean division, the matching method for `rem_euclid`.
1690    ///
1691    /// This computes the integer `n` such that
1692    /// `self = n * rhs + self.rem_euclid(rhs)`.
1693    /// In other words, the result is `self / rhs` rounded to the integer `n`
1694    /// such that `self >= n * rhs`.
1695    ///
1696    /// # Precision
1697    ///
1698    /// The result of this operation is guaranteed to be the rounded
1699    /// infinite-precision result.
1700    ///
1701    /// # Examples
1702    ///
1703    /// ```
1704    /// #![feature(f128)]
1705    /// # #[cfg(not(miri))]
1706    /// # #[cfg(target_has_reliable_f128_math)] {
1707    ///
1708    /// let a: f128 = 7.0;
1709    /// let b = 4.0;
1710    /// assert_eq!(a.div_euclid(b), 1.0); // 7.0 > 4.0 * 1.0
1711    /// assert_eq!((-a).div_euclid(b), -2.0); // -7.0 >= 4.0 * -2.0
1712    /// assert_eq!(a.div_euclid(-b), -1.0); // 7.0 >= -4.0 * -1.0
1713    /// assert_eq!((-a).div_euclid(-b), 2.0); // -7.0 >= -4.0 * 2.0
1714    /// # }
1715    /// ```
1716    #[inline]
1717    #[rustc_allow_incoherent_impl]
1718    #[unstable(feature = "f128", issue = "116909")]
1719    #[must_use = "method returns a new number and does not mutate the original value"]
1720    pub fn div_euclid(self, rhs: f128) -> f128 {
1721        let q = (self / rhs).trunc();
1722        if self % rhs < 0.0 {
1723            return if rhs > 0.0 { q - 1.0 } else { q + 1.0 };
1724        }
1725        q
1726    }
1727
1728    /// Calculates the least nonnegative remainder of `self` when
1729    /// divided by `rhs`.
1730    ///
1731    /// In particular, the return value `r` satisfies `0.0 <= r < rhs.abs()` in
1732    /// most cases. However, due to a floating point round-off error it can
1733    /// result in `r == rhs.abs()`, violating the mathematical definition, if
1734    /// `self` is much smaller than `rhs.abs()` in magnitude and `self < 0.0`.
1735    /// This result is not an element of the function's codomain, but it is the
1736    /// closest floating point number in the real numbers and thus fulfills the
1737    /// property `self == self.div_euclid(rhs) * rhs + self.rem_euclid(rhs)`
1738    /// approximately.
1739    ///
1740    /// # Precision
1741    ///
1742    /// The result of this operation is guaranteed to be the rounded
1743    /// infinite-precision result.
1744    ///
1745    /// # Examples
1746    ///
1747    /// ```
1748    /// #![feature(f128)]
1749    /// # #[cfg(not(miri))]
1750    /// # #[cfg(target_has_reliable_f128_math)] {
1751    ///
1752    /// let a: f128 = 7.0;
1753    /// let b = 4.0;
1754    /// assert_eq!(a.rem_euclid(b), 3.0);
1755    /// assert_eq!((-a).rem_euclid(b), 1.0);
1756    /// assert_eq!(a.rem_euclid(-b), 3.0);
1757    /// assert_eq!((-a).rem_euclid(-b), 1.0);
1758    /// // limitation due to round-off error
1759    /// assert!((-f128::EPSILON).rem_euclid(3.0) != 0.0);
1760    /// # }
1761    /// ```
1762    #[inline]
1763    #[rustc_allow_incoherent_impl]
1764    #[doc(alias = "modulo", alias = "mod")]
1765    #[unstable(feature = "f128", issue = "116909")]
1766    #[must_use = "method returns a new number and does not mutate the original value"]
1767    pub fn rem_euclid(self, rhs: f128) -> f128 {
1768        let r = self % rhs;
1769        if r < 0.0 { r + rhs.abs() } else { r }
1770    }
1771
1772    /// Raises a number to an integer power.
1773    ///
1774    /// Using this function is generally faster than using `powf`.
1775    /// It might have a different sequence of rounding operations than `powf`,
1776    /// so the results are not guaranteed to agree.
1777    ///
1778    /// Note that this function is special in that it can return non-NaN results for NaN inputs. For
1779    /// example, `f128::powi(f128::NAN, 0)` returns `1.0`. However, if an input is a *signaling*
1780    /// NaN, then the result is non-deterministically either a NaN or the result that the
1781    /// corresponding quiet NaN would produce.
1782    ///
1783    /// # Unspecified precision
1784    ///
1785    /// The precision of this function is non-deterministic. This means it varies by platform,
1786    /// Rust version, and can even differ within the same execution from one invocation to the next.
1787    ///
1788    /// # Examples
1789    ///
1790    /// ```
1791    /// #![feature(f128)]
1792    /// # #[cfg(not(miri))]
1793    /// # #[cfg(target_has_reliable_f128_math)] {
1794    ///
1795    /// let x = 2.0_f128;
1796    /// let abs_difference = (x.powi(2) - (x * x)).abs();
1797    /// assert!(abs_difference <= f128::EPSILON);
1798    ///
1799    /// assert_eq!(f128::powi(f128::NAN, 0), 1.0);
1800    /// assert_eq!(f128::powi(0.0, 0), 1.0);
1801    /// # }
1802    /// ```
1803    #[inline]
1804    #[rustc_allow_incoherent_impl]
1805    #[unstable(feature = "f128", issue = "116909")]
1806    #[must_use = "method returns a new number and does not mutate the original value"]
1807    pub fn powi(self, n: i32) -> f128 {
1808        intrinsics::powif128(self, n)
1809    }
1810
1811    /// Returns the square root of a number.
1812    ///
1813    /// Returns NaN if `self` is a negative number other than `-0.0`.
1814    ///
1815    /// # Precision
1816    ///
1817    /// The result of this operation is guaranteed to be the rounded
1818    /// infinite-precision result. It is specified by IEEE 754 as `squareRoot`
1819    /// and guaranteed not to change.
1820    ///
1821    /// # Examples
1822    ///
1823    /// ```
1824    /// #![feature(f128)]
1825    /// # #[cfg(not(miri))]
1826    /// # #[cfg(target_has_reliable_f128_math)] {
1827    ///
1828    /// let positive = 4.0_f128;
1829    /// let negative = -4.0_f128;
1830    /// let negative_zero = -0.0_f128;
1831    ///
1832    /// assert_eq!(positive.sqrt(), 2.0);
1833    /// assert!(negative.sqrt().is_nan());
1834    /// assert!(negative_zero.sqrt() == negative_zero);
1835    /// # }
1836    /// ```
1837    #[inline]
1838    #[doc(alias = "squareRoot")]
1839    #[rustc_allow_incoherent_impl]
1840    #[unstable(feature = "f128", issue = "116909")]
1841    #[must_use = "method returns a new number and does not mutate the original value"]
1842    pub fn sqrt(self) -> f128 {
1843        intrinsics::sqrtf128(self)
1844    }
1845}