//! Constants for the `f16` half-precision floating point type. //! //! *[See also the `f16` primitive type][f16].* //! //! Mathematically significant numbers are provided in the `consts` sub-module. //! //! For the constants defined directly in this module //! (as distinct from those defined in the `consts` sub-module), //! new code should instead use the associated constants //! defined directly on the `f16` type. #![unstable(feature = "f16", issue = "116909")] use crate::mem; /// Basic mathematical constants. #[unstable(feature = "f16", issue = "116909")] pub mod consts { // FIXME: replace with mathematical constants from cmath. /// Archimedes' constant (π) #[unstable(feature = "f16", issue = "116909")] pub const PI: f16 = 3.14159265358979323846264338327950288_f16; /// The full circle constant (τ) /// /// Equal to 2π. #[unstable(feature = "f16", issue = "116909")] pub const TAU: f16 = 6.28318530717958647692528676655900577_f16; /// The golden ratio (φ) #[unstable(feature = "f16", issue = "116909")] // Also, #[unstable(feature = "more_float_constants", issue = "103883")] pub const PHI: f16 = 1.618033988749894848204586834365638118_f16; /// The Euler-Mascheroni constant (γ) #[unstable(feature = "f16", issue = "116909")] // Also, #[unstable(feature = "more_float_constants", issue = "103883")] pub const EGAMMA: f16 = 0.577215664901532860606512090082402431_f16; /// π/2 #[unstable(feature = "f16", issue = "116909")] pub const FRAC_PI_2: f16 = 1.57079632679489661923132169163975144_f16; /// π/3 #[unstable(feature = "f16", issue = "116909")] pub const FRAC_PI_3: f16 = 1.04719755119659774615421446109316763_f16; /// π/4 #[unstable(feature = "f16", issue = "116909")] pub const FRAC_PI_4: f16 = 0.785398163397448309615660845819875721_f16; /// π/6 #[unstable(feature = "f16", issue = "116909")] pub const FRAC_PI_6: f16 = 0.52359877559829887307710723054658381_f16; /// π/8 #[unstable(feature = "f16", issue = "116909")] pub const FRAC_PI_8: f16 = 0.39269908169872415480783042290993786_f16; /// 1/π #[unstable(feature = "f16", issue = "116909")] pub const FRAC_1_PI: f16 = 0.318309886183790671537767526745028724_f16; /// 1/sqrt(π) #[unstable(feature = "f16", issue = "116909")] // Also, #[unstable(feature = "more_float_constants", issue = "103883")] pub const FRAC_1_SQRT_PI: f16 = 0.564189583547756286948079451560772586_f16; /// 2/π #[unstable(feature = "f16", issue = "116909")] pub const FRAC_2_PI: f16 = 0.636619772367581343075535053490057448_f16; /// 2/sqrt(π) #[unstable(feature = "f16", issue = "116909")] pub const FRAC_2_SQRT_PI: f16 = 1.12837916709551257389615890312154517_f16; /// sqrt(2) #[unstable(feature = "f16", issue = "116909")] pub const SQRT_2: f16 = 1.41421356237309504880168872420969808_f16; /// 1/sqrt(2) #[unstable(feature = "f16", issue = "116909")] pub const FRAC_1_SQRT_2: f16 = 0.707106781186547524400844362104849039_f16; /// sqrt(3) #[unstable(feature = "f16", issue = "116909")] // Also, #[unstable(feature = "more_float_constants", issue = "103883")] pub const SQRT_3: f16 = 1.732050807568877293527446341505872367_f16; /// 1/sqrt(3) #[unstable(feature = "f16", issue = "116909")] // Also, #[unstable(feature = "more_float_constants", issue = "103883")] pub const FRAC_1_SQRT_3: f16 = 0.577350269189625764509148780501957456_f16; /// Euler's number (e) #[unstable(feature = "f16", issue = "116909")] pub const E: f16 = 2.71828182845904523536028747135266250_f16; /// log2(10) #[unstable(feature = "f16", issue = "116909")] pub const LOG2_10: f16 = 3.32192809488736234787031942948939018_f16; /// log2(e) #[unstable(feature = "f16", issue = "116909")] pub const LOG2_E: f16 = 1.44269504088896340735992468100189214_f16; /// log10(2) #[unstable(feature = "f16", issue = "116909")] pub const LOG10_2: f16 = 0.301029995663981195213738894724493027_f16; /// log10(e) #[unstable(feature = "f16", issue = "116909")] pub const LOG10_E: f16 = 0.434294481903251827651128918916605082_f16; /// ln(2) #[unstable(feature = "f16", issue = "116909")] pub const LN_2: f16 = 0.693147180559945309417232121458176568_f16; /// ln(10) #[unstable(feature = "f16", issue = "116909")] pub const LN_10: f16 = 2.30258509299404568401799145468436421_f16; } #[cfg(not(test))] impl f16 { // FIXME(f16_f128): almost all methods in this `impl` are missing examples and a const // implementation. Add these once we can run code on all platforms and have f16/f128 in CTFE. /// The radix or base of the internal representation of `f16`. #[unstable(feature = "f16", issue = "116909")] pub const RADIX: u32 = 2; /// Number of significant digits in base 2. #[unstable(feature = "f16", issue = "116909")] pub const MANTISSA_DIGITS: u32 = 11; /// Approximate number of significant digits in base 10. /// /// This is the maximum x such that any decimal number with x /// significant digits can be converted to `f16` and back without loss. /// /// Equal to floor(log10 2[`MANTISSA_DIGITS`] − 1). /// /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS #[unstable(feature = "f16", issue = "116909")] pub const DIGITS: u32 = 3; /// [Machine epsilon] value for `f16`. /// /// This is the difference between `1.0` and the next larger representable number. /// /// Equal to 21 − [`MANTISSA_DIGITS`]. /// /// [Machine epsilon]: https://en.wikipedia.org/wiki/Machine_epsilon /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS #[unstable(feature = "f16", issue = "116909")] pub const EPSILON: f16 = 9.7656e-4_f16; /// Smallest finite `f16` value. /// /// Equal to −[`MAX`]. /// /// [`MAX`]: f16::MAX #[unstable(feature = "f16", issue = "116909")] pub const MIN: f16 = -6.5504e+4_f16; /// Smallest positive normal `f16` value. /// /// Equal to 2[`MIN_EXP`] − 1. /// /// [`MIN_EXP`]: f16::MIN_EXP #[unstable(feature = "f16", issue = "116909")] pub const MIN_POSITIVE: f16 = 6.1035e-5_f16; /// Largest finite `f16` value. /// /// Equal to /// (1 − 2−[`MANTISSA_DIGITS`]) 2[`MAX_EXP`]. /// /// [`MANTISSA_DIGITS`]: f16::MANTISSA_DIGITS /// [`MAX_EXP`]: f16::MAX_EXP #[unstable(feature = "f16", issue = "116909")] pub const MAX: f16 = 6.5504e+4_f16; /// One greater than the minimum possible normal power of 2 exponent. /// /// If x = `MIN_EXP`, then normal numbers /// ≥ 0.5 × 2x. #[unstable(feature = "f16", issue = "116909")] pub const MIN_EXP: i32 = -13; /// Maximum possible power of 2 exponent. /// /// If x = `MAX_EXP`, then normal numbers /// < 1 × 2x. #[unstable(feature = "f16", issue = "116909")] pub const MAX_EXP: i32 = 16; /// Minimum x for which 10x is normal. /// /// Equal to ceil(log10 [`MIN_POSITIVE`]). /// /// [`MIN_POSITIVE`]: f16::MIN_POSITIVE #[unstable(feature = "f16", issue = "116909")] pub const MIN_10_EXP: i32 = -4; /// Maximum x for which 10x is normal. /// /// Equal to floor(log10 [`MAX`]). /// /// [`MAX`]: f16::MAX #[unstable(feature = "f16", issue = "116909")] pub const MAX_10_EXP: i32 = 4; /// Returns `true` if this value is NaN. #[inline] #[must_use] #[unstable(feature = "f16", issue = "116909")] #[allow(clippy::eq_op)] // > if you intended to check if the operand is NaN, use `.is_nan()` instead :) pub const fn is_nan(self) -> bool { self != self } /// Returns `true` if `self` has a positive sign, including `+0.0`, NaNs with /// positive sign bit and positive infinity. Note that IEEE 754 doesn't assign any /// meaning to the sign bit in case of a NaN, and as Rust doesn't guarantee that /// the bit pattern of NaNs are conserved over arithmetic operations, the result of /// `is_sign_positive` on a NaN might produce an unexpected result in some cases. /// See [explanation of NaN as a special value](f32) for more info. /// /// ``` /// #![feature(f16)] /// /// let f = 7.0_f16; /// let g = -7.0_f16; /// /// assert!(f.is_sign_positive()); /// assert!(!g.is_sign_positive()); /// ``` #[inline] #[must_use] #[unstable(feature = "f16", issue = "116909")] pub fn is_sign_positive(self) -> bool { !self.is_sign_negative() } /// Returns `true` if `self` has a negative sign, including `-0.0`, NaNs with /// negative sign bit and negative infinity. Note that IEEE 754 doesn't assign any /// meaning to the sign bit in case of a NaN, and as Rust doesn't guarantee that /// the bit pattern of NaNs are conserved over arithmetic operations, the result of /// `is_sign_negative` on a NaN might produce an unexpected result in some cases. /// See [explanation of NaN as a special value](f32) for more info. /// /// ``` /// #![feature(f16)] /// /// let f = 7.0_f16; /// let g = -7.0_f16; /// /// assert!(!f.is_sign_negative()); /// assert!(g.is_sign_negative()); /// ``` #[inline] #[must_use] #[unstable(feature = "f16", issue = "116909")] pub fn is_sign_negative(self) -> bool { // IEEE754 says: isSignMinus(x) is true if and only if x has negative sign. isSignMinus // applies to zeros and NaNs as well. // SAFETY: This is just transmuting to get the sign bit, it's fine. (self.to_bits() & (1 << 15)) != 0 } /// Raw transmutation to `u16`. /// /// This is currently identical to `transmute::(self)` on all platforms. /// /// See [`from_bits`](#method.from_bits) for some discussion of the /// portability of this operation (there are almost no issues). /// /// Note that this function is distinct from `as` casting, which attempts to /// preserve the *numeric* value, and not the bitwise value. #[inline] #[unstable(feature = "f16", issue = "116909")] #[must_use = "this returns the result of the operation, without modifying the original"] pub fn to_bits(self) -> u16 { // SAFETY: `u16` is a plain old datatype so we can always... uh... // ...look, just pretend you forgot what you just read. // Stability concerns. unsafe { mem::transmute(self) } } /// Raw transmutation from `u16`. /// /// This is currently identical to `transmute::(v)` on all platforms. /// It turns out this is incredibly portable, for two reasons: /// /// * Floats and Ints have the same endianness on all supported platforms. /// * IEEE 754 very precisely specifies the bit layout of floats. /// /// However there is one caveat: prior to the 2008 version of IEEE 754, how /// to interpret the NaN signaling bit wasn't actually specified. Most platforms /// (notably x86 and ARM) picked the interpretation that was ultimately /// standardized in 2008, but some didn't (notably MIPS). As a result, all /// signaling NaNs on MIPS are quiet NaNs on x86, and vice-versa. /// /// Rather than trying to preserve signaling-ness cross-platform, this /// implementation favors preserving the exact bits. This means that /// any payloads encoded in NaNs will be preserved even if the result of /// this method is sent over the network from an x86 machine to a MIPS one. /// /// If the results of this method are only manipulated by the same /// architecture that produced them, then there is no portability concern. /// /// If the input isn't NaN, then there is no portability concern. /// /// If you don't care about signalingness (very likely), then there is no /// portability concern. /// /// Note that this function is distinct from `as` casting, which attempts to /// preserve the *numeric* value, and not the bitwise value. #[inline] #[must_use] #[unstable(feature = "f16", issue = "116909")] pub fn from_bits(v: u16) -> Self { // SAFETY: `u16` is a plain old datatype so we can always... uh... // ...look, just pretend you forgot what you just read. // Stability concerns. unsafe { mem::transmute(v) } } }