Trait num_traits::float::Float
source · [−]pub trait Float: Num + Copy + NumCast + PartialOrd + Neg<Output = Self> {
Show 59 methods
fn nan() -> Self;
fn infinity() -> Self;
fn neg_infinity() -> Self;
fn neg_zero() -> Self;
fn min_value() -> Self;
fn min_positive_value() -> Self;
fn max_value() -> Self;
fn is_nan(self) -> bool;
fn is_infinite(self) -> bool;
fn is_finite(self) -> bool;
fn is_normal(self) -> bool;
fn classify(self) -> FpCategory;
fn floor(self) -> Self;
fn ceil(self) -> Self;
fn round(self) -> Self;
fn trunc(self) -> Self;
fn fract(self) -> Self;
fn abs(self) -> Self;
fn signum(self) -> Self;
fn is_sign_positive(self) -> bool;
fn is_sign_negative(self) -> bool;
fn mul_add(self, a: Self, b: Self) -> Self;
fn recip(self) -> Self;
fn powi(self, n: i32) -> Self;
fn powf(self, n: Self) -> Self;
fn sqrt(self) -> Self;
fn exp(self) -> Self;
fn exp2(self) -> Self;
fn ln(self) -> Self;
fn log(self, base: Self) -> Self;
fn log2(self) -> Self;
fn log10(self) -> Self;
fn max(self, other: Self) -> Self;
fn min(self, other: Self) -> Self;
fn abs_sub(self, other: Self) -> Self;
fn cbrt(self) -> Self;
fn hypot(self, other: Self) -> Self;
fn sin(self) -> Self;
fn cos(self) -> Self;
fn tan(self) -> Self;
fn asin(self) -> Self;
fn acos(self) -> Self;
fn atan(self) -> Self;
fn atan2(self, other: Self) -> Self;
fn sin_cos(self) -> (Self, Self);
fn exp_m1(self) -> Self;
fn ln_1p(self) -> Self;
fn sinh(self) -> Self;
fn cosh(self) -> Self;
fn tanh(self) -> Self;
fn asinh(self) -> Self;
fn acosh(self) -> Self;
fn atanh(self) -> Self;
fn integer_decode(self) -> (u64, i16, i8);
fn epsilon() -> Self { ... }
fn is_subnormal(self) -> bool { ... }
fn to_degrees(self) -> Self { ... }
fn to_radians(self) -> Self { ... }
fn copysign(self, sign: Self) -> Self { ... }
}
Expand description
Generic trait for floating point numbers
This trait is only available with the std
feature, or with the libm
feature otherwise.
Required Methods
Returns the NaN
value.
use num_traits::Float;
let nan: f32 = Float::nan();
assert!(nan.is_nan());
Returns the infinite value.
use num_traits::Float;
use std::f32;
let infinity: f32 = Float::infinity();
assert!(infinity.is_infinite());
assert!(!infinity.is_finite());
assert!(infinity > f32::MAX);
fn neg_infinity() -> Self
fn neg_infinity() -> Self
Returns the negative infinite value.
use num_traits::Float;
use std::f32;
let neg_infinity: f32 = Float::neg_infinity();
assert!(neg_infinity.is_infinite());
assert!(!neg_infinity.is_finite());
assert!(neg_infinity < f32::MIN);
Returns -0.0
.
use num_traits::{Zero, Float};
let inf: f32 = Float::infinity();
let zero: f32 = Zero::zero();
let neg_zero: f32 = Float::neg_zero();
assert_eq!(zero, neg_zero);
assert_eq!(7.0f32/inf, zero);
assert_eq!(zero * 10.0, zero);
Returns the smallest finite value that this type can represent.
use num_traits::Float;
use std::f64;
let x: f64 = Float::min_value();
assert_eq!(x, f64::MIN);
fn min_positive_value() -> Self
fn min_positive_value() -> Self
Returns the smallest positive, normalized value that this type can represent.
use num_traits::Float;
use std::f64;
let x: f64 = Float::min_positive_value();
assert_eq!(x, f64::MIN_POSITIVE);
Returns the largest finite value that this type can represent.
use num_traits::Float;
use std::f64;
let x: f64 = Float::max_value();
assert_eq!(x, f64::MAX);
Returns true
if this value is NaN
and false otherwise.
use num_traits::Float;
use std::f64;
let nan = f64::NAN;
let f = 7.0;
assert!(nan.is_nan());
assert!(!f.is_nan());
fn is_infinite(self) -> bool
fn is_infinite(self) -> bool
Returns true
if this value is positive infinity or negative infinity and
false otherwise.
use num_traits::Float;
use std::f32;
let f = 7.0f32;
let inf: f32 = Float::infinity();
let neg_inf: f32 = Float::neg_infinity();
let nan: f32 = f32::NAN;
assert!(!f.is_infinite());
assert!(!nan.is_infinite());
assert!(inf.is_infinite());
assert!(neg_inf.is_infinite());
Returns true
if this number is neither infinite nor NaN
.
use num_traits::Float;
use std::f32;
let f = 7.0f32;
let inf: f32 = Float::infinity();
let neg_inf: f32 = Float::neg_infinity();
let nan: f32 = f32::NAN;
assert!(f.is_finite());
assert!(!nan.is_finite());
assert!(!inf.is_finite());
assert!(!neg_inf.is_finite());
Returns true
if the number is neither zero, infinite,
subnormal, or NaN
.
use num_traits::Float;
use std::f32;
let min = f32::MIN_POSITIVE; // 1.17549435e-38f32
let max = f32::MAX;
let lower_than_min = 1.0e-40_f32;
let zero = 0.0f32;
assert!(min.is_normal());
assert!(max.is_normal());
assert!(!zero.is_normal());
assert!(!f32::NAN.is_normal());
assert!(!f32::INFINITY.is_normal());
// Values between `0` and `min` are Subnormal.
assert!(!lower_than_min.is_normal());
fn classify(self) -> FpCategory
fn classify(self) -> FpCategory
Returns the floating point category of the number. If only one property is going to be tested, it is generally faster to use the specific predicate instead.
use num_traits::Float;
use std::num::FpCategory;
use std::f32;
let num = 12.4f32;
let inf = f32::INFINITY;
assert_eq!(num.classify(), FpCategory::Normal);
assert_eq!(inf.classify(), FpCategory::Infinite);
Returns the largest integer less than or equal to a number.
use num_traits::Float;
let f = 3.99;
let g = 3.0;
assert_eq!(f.floor(), 3.0);
assert_eq!(g.floor(), 3.0);
Returns the smallest integer greater than or equal to a number.
use num_traits::Float;
let f = 3.01;
let g = 4.0;
assert_eq!(f.ceil(), 4.0);
assert_eq!(g.ceil(), 4.0);
Returns the nearest integer to a number. Round half-way cases away from
0.0
.
use num_traits::Float;
let f = 3.3;
let g = -3.3;
assert_eq!(f.round(), 3.0);
assert_eq!(g.round(), -3.0);
Return the integer part of a number.
use num_traits::Float;
let f = 3.3;
let g = -3.7;
assert_eq!(f.trunc(), 3.0);
assert_eq!(g.trunc(), -3.0);
Returns the fractional part of a number.
use num_traits::Float;
let x = 3.5;
let y = -3.5;
let abs_difference_x = (x.fract() - 0.5).abs();
let abs_difference_y = (y.fract() - (-0.5)).abs();
assert!(abs_difference_x < 1e-10);
assert!(abs_difference_y < 1e-10);
Computes the absolute value of self
. Returns Float::nan()
if the
number is Float::nan()
.
use num_traits::Float;
use std::f64;
let x = 3.5;
let y = -3.5;
let abs_difference_x = (x.abs() - x).abs();
let abs_difference_y = (y.abs() - (-y)).abs();
assert!(abs_difference_x < 1e-10);
assert!(abs_difference_y < 1e-10);
assert!(f64::NAN.abs().is_nan());
Returns a number that represents the sign of self
.
1.0
if the number is positive,+0.0
orFloat::infinity()
-1.0
if the number is negative,-0.0
orFloat::neg_infinity()
Float::nan()
if the number isFloat::nan()
use num_traits::Float;
use std::f64;
let f = 3.5;
assert_eq!(f.signum(), 1.0);
assert_eq!(f64::NEG_INFINITY.signum(), -1.0);
assert!(f64::NAN.signum().is_nan());
fn is_sign_positive(self) -> bool
fn is_sign_positive(self) -> bool
Returns true
if self
is positive, including +0.0
,
Float::infinity()
, and Float::nan()
.
use num_traits::Float;
use std::f64;
let nan: f64 = f64::NAN;
let neg_nan: f64 = -f64::NAN;
let f = 7.0;
let g = -7.0;
assert!(f.is_sign_positive());
assert!(!g.is_sign_positive());
assert!(nan.is_sign_positive());
assert!(!neg_nan.is_sign_positive());
fn is_sign_negative(self) -> bool
fn is_sign_negative(self) -> bool
Returns true
if self
is negative, including -0.0
,
Float::neg_infinity()
, and -Float::nan()
.
use num_traits::Float;
use std::f64;
let nan: f64 = f64::NAN;
let neg_nan: f64 = -f64::NAN;
let f = 7.0;
let g = -7.0;
assert!(!f.is_sign_negative());
assert!(g.is_sign_negative());
assert!(!nan.is_sign_negative());
assert!(neg_nan.is_sign_negative());
Fused multiply-add. Computes (self * a) + b
with only one rounding
error, yielding a more accurate result than an unfused multiply-add.
Using mul_add
can be more performant than an unfused multiply-add if
the target architecture has a dedicated fma
CPU instruction.
use num_traits::Float;
let m = 10.0;
let x = 4.0;
let b = 60.0;
// 100.0
let abs_difference = (m.mul_add(x, b) - (m*x + b)).abs();
assert!(abs_difference < 1e-10);
Take the reciprocal (inverse) of a number, 1/x
.
use num_traits::Float;
let x = 2.0;
let abs_difference = (x.recip() - (1.0/x)).abs();
assert!(abs_difference < 1e-10);
Raise a number to an integer power.
Using this function is generally faster than using powf
use num_traits::Float;
let x = 2.0;
let abs_difference = (x.powi(2) - x*x).abs();
assert!(abs_difference < 1e-10);
Raise a number to a floating point power.
use num_traits::Float;
let x = 2.0;
let abs_difference = (x.powf(2.0) - x*x).abs();
assert!(abs_difference < 1e-10);
Take the square root of a number.
Returns NaN if self
is a negative number.
use num_traits::Float;
let positive = 4.0;
let negative = -4.0;
let abs_difference = (positive.sqrt() - 2.0).abs();
assert!(abs_difference < 1e-10);
assert!(negative.sqrt().is_nan());
Returns e^(self)
, (the exponential function).
use num_traits::Float;
let one = 1.0;
// e^1
let e = one.exp();
// ln(e) - 1 == 0
let abs_difference = (e.ln() - 1.0).abs();
assert!(abs_difference < 1e-10);
Returns 2^(self)
.
use num_traits::Float;
let f = 2.0;
// 2^2 - 4 == 0
let abs_difference = (f.exp2() - 4.0).abs();
assert!(abs_difference < 1e-10);
Returns the natural logarithm of the number.
use num_traits::Float;
let one = 1.0;
// e^1
let e = one.exp();
// ln(e) - 1 == 0
let abs_difference = (e.ln() - 1.0).abs();
assert!(abs_difference < 1e-10);
Returns the logarithm of the number with respect to an arbitrary base.
use num_traits::Float;
let ten = 10.0;
let two = 2.0;
// log10(10) - 1 == 0
let abs_difference_10 = (ten.log(10.0) - 1.0).abs();
// log2(2) - 1 == 0
let abs_difference_2 = (two.log(2.0) - 1.0).abs();
assert!(abs_difference_10 < 1e-10);
assert!(abs_difference_2 < 1e-10);
Returns the base 2 logarithm of the number.
use num_traits::Float;
let two = 2.0;
// log2(2) - 1 == 0
let abs_difference = (two.log2() - 1.0).abs();
assert!(abs_difference < 1e-10);
Returns the base 10 logarithm of the number.
use num_traits::Float;
let ten = 10.0;
// log10(10) - 1 == 0
let abs_difference = (ten.log10() - 1.0).abs();
assert!(abs_difference < 1e-10);
Returns the maximum of the two numbers.
use num_traits::Float;
let x = 1.0;
let y = 2.0;
assert_eq!(x.max(y), y);
Returns the minimum of the two numbers.
use num_traits::Float;
let x = 1.0;
let y = 2.0;
assert_eq!(x.min(y), x);
The positive difference of two numbers.
- If
self <= other
:0:0
- Else:
self - other
use num_traits::Float;
let x = 3.0;
let y = -3.0;
let abs_difference_x = (x.abs_sub(1.0) - 2.0).abs();
let abs_difference_y = (y.abs_sub(1.0) - 0.0).abs();
assert!(abs_difference_x < 1e-10);
assert!(abs_difference_y < 1e-10);
Take the cubic root of a number.
use num_traits::Float;
let x = 8.0;
// x^(1/3) - 2 == 0
let abs_difference = (x.cbrt() - 2.0).abs();
assert!(abs_difference < 1e-10);
Calculate the length of the hypotenuse of a right-angle triangle given
legs of length x
and y
.
use num_traits::Float;
let x = 2.0;
let y = 3.0;
// sqrt(x^2 + y^2)
let abs_difference = (x.hypot(y) - (x.powi(2) + y.powi(2)).sqrt()).abs();
assert!(abs_difference < 1e-10);
Computes the sine of a number (in radians).
use num_traits::Float;
use std::f64;
let x = f64::consts::PI/2.0;
let abs_difference = (x.sin() - 1.0).abs();
assert!(abs_difference < 1e-10);
Computes the cosine of a number (in radians).
use num_traits::Float;
use std::f64;
let x = 2.0*f64::consts::PI;
let abs_difference = (x.cos() - 1.0).abs();
assert!(abs_difference < 1e-10);
Computes the tangent of a number (in radians).
use num_traits::Float;
use std::f64;
let x = f64::consts::PI/4.0;
let abs_difference = (x.tan() - 1.0).abs();
assert!(abs_difference < 1e-14);
Computes the arcsine of a number. Return value is in radians in the range [-pi/2, pi/2] or NaN if the number is outside the range [-1, 1].
use num_traits::Float;
use std::f64;
let f = f64::consts::PI / 2.0;
// asin(sin(pi/2))
let abs_difference = (f.sin().asin() - f64::consts::PI / 2.0).abs();
assert!(abs_difference < 1e-10);
Computes the arccosine of a number. Return value is in radians in the range [0, pi] or NaN if the number is outside the range [-1, 1].
use num_traits::Float;
use std::f64;
let f = f64::consts::PI / 4.0;
// acos(cos(pi/4))
let abs_difference = (f.cos().acos() - f64::consts::PI / 4.0).abs();
assert!(abs_difference < 1e-10);
Computes the arctangent of a number. Return value is in radians in the range [-pi/2, pi/2];
use num_traits::Float;
let f = 1.0;
// atan(tan(1))
let abs_difference = (f.tan().atan() - 1.0).abs();
assert!(abs_difference < 1e-10);
Computes the four quadrant arctangent of self
(y
) and other
(x
).
x = 0
,y = 0
:0
x >= 0
:arctan(y/x)
->[-pi/2, pi/2]
y >= 0
:arctan(y/x) + pi
->(pi/2, pi]
y < 0
:arctan(y/x) - pi
->(-pi, -pi/2)
use num_traits::Float;
use std::f64;
let pi = f64::consts::PI;
// All angles from horizontal right (+x)
// 45 deg counter-clockwise
let x1 = 3.0;
let y1 = -3.0;
// 135 deg clockwise
let x2 = -3.0;
let y2 = 3.0;
let abs_difference_1 = (y1.atan2(x1) - (-pi/4.0)).abs();
let abs_difference_2 = (y2.atan2(x2) - 3.0*pi/4.0).abs();
assert!(abs_difference_1 < 1e-10);
assert!(abs_difference_2 < 1e-10);
fn sin_cos(self) -> (Self, Self)
fn sin_cos(self) -> (Self, Self)
Simultaneously computes the sine and cosine of the number, x
. Returns
(sin(x), cos(x))
.
use num_traits::Float;
use std::f64;
let x = f64::consts::PI/4.0;
let f = x.sin_cos();
let abs_difference_0 = (f.0 - x.sin()).abs();
let abs_difference_1 = (f.1 - x.cos()).abs();
assert!(abs_difference_0 < 1e-10);
assert!(abs_difference_0 < 1e-10);
Returns e^(self) - 1
in a way that is accurate even if the
number is close to zero.
use num_traits::Float;
let x = 7.0;
// e^(ln(7)) - 1
let abs_difference = (x.ln().exp_m1() - 6.0).abs();
assert!(abs_difference < 1e-10);
Returns ln(1+n)
(natural logarithm) more accurately than if
the operations were performed separately.
use num_traits::Float;
use std::f64;
let x = f64::consts::E - 1.0;
// ln(1 + (e - 1)) == ln(e) == 1
let abs_difference = (x.ln_1p() - 1.0).abs();
assert!(abs_difference < 1e-10);
Hyperbolic sine function.
use num_traits::Float;
use std::f64;
let e = f64::consts::E;
let x = 1.0;
let f = x.sinh();
// Solving sinh() at 1 gives `(e^2-1)/(2e)`
let g = (e*e - 1.0)/(2.0*e);
let abs_difference = (f - g).abs();
assert!(abs_difference < 1e-10);
Hyperbolic cosine function.
use num_traits::Float;
use std::f64;
let e = f64::consts::E;
let x = 1.0;
let f = x.cosh();
// Solving cosh() at 1 gives this result
let g = (e*e + 1.0)/(2.0*e);
let abs_difference = (f - g).abs();
// Same result
assert!(abs_difference < 1.0e-10);
Hyperbolic tangent function.
use num_traits::Float;
use std::f64;
let e = f64::consts::E;
let x = 1.0;
let f = x.tanh();
// Solving tanh() at 1 gives `(1 - e^(-2))/(1 + e^(-2))`
let g = (1.0 - e.powi(-2))/(1.0 + e.powi(-2));
let abs_difference = (f - g).abs();
assert!(abs_difference < 1.0e-10);
Inverse hyperbolic sine function.
use num_traits::Float;
let x = 1.0;
let f = x.sinh().asinh();
let abs_difference = (f - x).abs();
assert!(abs_difference < 1.0e-10);
Inverse hyperbolic cosine function.
use num_traits::Float;
let x = 1.0;
let f = x.cosh().acosh();
let abs_difference = (f - x).abs();
assert!(abs_difference < 1.0e-10);
Inverse hyperbolic tangent function.
use num_traits::Float;
use std::f64;
let e = f64::consts::E;
let f = e.tanh().atanh();
let abs_difference = (f - e).abs();
assert!(abs_difference < 1.0e-10);
fn integer_decode(self) -> (u64, i16, i8)
fn integer_decode(self) -> (u64, i16, i8)
Returns the mantissa, base 2 exponent, and sign as integers, respectively.
The original number can be recovered by sign * mantissa * 2 ^ exponent
.
use num_traits::Float;
let num = 2.0f32;
// (8388608, -22, 1)
let (mantissa, exponent, sign) = Float::integer_decode(num);
let sign_f = sign as f32;
let mantissa_f = mantissa as f32;
let exponent_f = num.powf(exponent as f32);
// 1 * 8388608 * 2^(-22) == 2
let abs_difference = (sign_f * mantissa_f * exponent_f - num).abs();
assert!(abs_difference < 1e-10);
Provided Methods
Returns epsilon, a small positive value.
use num_traits::Float;
use std::f64;
let x: f64 = Float::epsilon();
assert_eq!(x, f64::EPSILON);
Panics
The default implementation will panic if f32::EPSILON
cannot
be cast to Self
.
fn is_subnormal(self) -> bool
fn is_subnormal(self) -> bool
Returns true
if the number is subnormal.
use num_traits::Float;
use std::f64;
let min = f64::MIN_POSITIVE; // 2.2250738585072014e-308_f64
let max = f64::MAX;
let lower_than_min = 1.0e-308_f64;
let zero = 0.0_f64;
assert!(!min.is_subnormal());
assert!(!max.is_subnormal());
assert!(!zero.is_subnormal());
assert!(!f64::NAN.is_subnormal());
assert!(!f64::INFINITY.is_subnormal());
// Values between `0` and `min` are Subnormal.
assert!(lower_than_min.is_subnormal());
fn to_degrees(self) -> Self
fn to_degrees(self) -> Self
Converts radians to degrees.
use std::f64::consts;
let angle = consts::PI;
let abs_difference = (angle.to_degrees() - 180.0).abs();
assert!(abs_difference < 1e-10);
fn to_radians(self) -> Self
fn to_radians(self) -> Self
Converts degrees to radians.
use std::f64::consts;
let angle = 180.0_f64;
let abs_difference = (angle.to_radians() - consts::PI).abs();
assert!(abs_difference < 1e-10);
Returns a number composed of the magnitude of self
and the sign of
sign
.
Equal to self
if the sign of self
and sign
are the same, otherwise
equal to -self
. If self
is a NAN
, then a NAN
with the sign of
sign
is returned.
Examples
use num_traits::Float;
let f = 3.5_f32;
assert_eq!(f.copysign(0.42), 3.5_f32);
assert_eq!(f.copysign(-0.42), -3.5_f32);
assert_eq!((-f).copysign(0.42), 3.5_f32);
assert_eq!((-f).copysign(-0.42), -3.5_f32);
assert!(f32::nan().copysign(1.0).is_nan());