Primitive Type f32
1.0.0 ·Expand description
A 32-bit floating point type (specifically, the “binary32” type defined in IEEE 754-2008).
This type can represent a wide range of decimal numbers, like 3.5
, 27
,
-113.75
, 0.0078125
, 34359738368
, 0
, -1
. So unlike integer types
(such as i32
), floating point types can represent non-integer numbers,
too.
However, being able to represent this wide range of numbers comes at the
cost of precision: floats can only represent some of the real numbers and
calculation with floats round to a nearby representable number. For example,
5.0
and 1.0
can be exactly represented as f32
, but 1.0 / 5.0
results
in 0.20000000298023223876953125
since 0.2
cannot be exactly represented
as f32
. Note, however, that printing floats with println
and friends will
often discard insignificant digits: println!("{}", 1.0f32 / 5.0f32)
will
print 0.2
.
Additionally, f32
can represent some special values:
- −0.0: IEEE 754 floating point numbers have a bit that indicates their sign, so −0.0 is a possible value. For comparison −0.0 = +0.0, but floating point operations can carry the sign bit through arithmetic operations. This means −0.0 × +0.0 produces −0.0 and a negative number rounded to a value smaller than a float can represent also produces −0.0.
- ∞ and
−∞: these result from calculations
like
1.0 / 0.0
. - NaN (not a number): this value results from
calculations like
(-1.0).sqrt()
. NaN has some potentially unexpected behavior:- It is not equal to any float, including itself! This is the reason
f32
doesn’t implement theEq
trait. - It is also neither smaller nor greater than any float, making it
impossible to sort by the default comparison operation, which is the
reason
f32
doesn’t implement theOrd
trait. - It is also considered infectious as almost all calculations where one of the operands is NaN will also result in NaN. The explanations on this page only explicitly document behavior on NaN operands if this default is deviated from.
- Lastly, there are multiple bit patterns that are considered NaN. Rust does not currently guarantee that the bit patterns of NaN are preserved over arithmetic operations, and they are not guaranteed to be portable or even fully deterministic! This means that there may be some surprising results upon inspecting the bit patterns, as the same calculations might produce NaNs with different bit patterns.
- It is not equal to any float, including itself! This is the reason
When a primitive operation (addition, subtraction, multiplication, or division) is performed on this type, the result is rounded according to the roundTiesToEven direction defined in IEEE 754-2008. That means:
- The result is the representable value closest to the true value, if there is a unique closest representable value.
- If the true value is exactly half-way between two representable values, the result is the one with an even least-significant binary digit.
- If the true value’s magnitude is ≥
f32::MAX
+ 2(f32::MAX_EXP
−f32::MANTISSA_DIGITS
− 1), the result is ∞ or −∞ (preserving the true value’s sign). - If the result of a sum exactly equals zero, the outcome is +0.0 unless
both arguments were negative, then it is -0.0. Subtraction
a - b
is regarded as a suma + (-b)
.
For more information on floating point numbers, see Wikipedia.
Implementations§
source§impl f32
impl f32
sourcepub fn round(self) -> f32
pub fn round(self) -> f32
Returns the nearest integer to self
. If a value is half-way between two
integers, round away from 0.0
.
This function always returns the precise result.
§Examples
let f = 3.3_f32;
let g = -3.3_f32;
let h = -3.7_f32;
let i = 3.5_f32;
let j = 4.5_f32;
assert_eq!(f.round(), 3.0);
assert_eq!(g.round(), -3.0);
assert_eq!(h.round(), -4.0);
assert_eq!(i.round(), 4.0);
assert_eq!(j.round(), 5.0);
Run1.77.0 · sourcepub fn round_ties_even(self) -> f32
pub fn round_ties_even(self) -> f32
Returns the nearest integer to a number. Rounds half-way cases to the number with an even least significant digit.
This function always returns the precise result.
§Examples
let f = 3.3_f32;
let g = -3.3_f32;
let h = 3.5_f32;
let i = 4.5_f32;
assert_eq!(f.round_ties_even(), 3.0);
assert_eq!(g.round_ties_even(), -3.0);
assert_eq!(h.round_ties_even(), 4.0);
assert_eq!(i.round_ties_even(), 4.0);
Runsourcepub fn trunc(self) -> f32
pub fn trunc(self) -> f32
Returns the integer part of self
.
This means that non-integer numbers are always truncated towards zero.
This function always returns the precise result.
§Examples
let f = 3.7_f32;
let g = 3.0_f32;
let h = -3.7_f32;
assert_eq!(f.trunc(), 3.0);
assert_eq!(g.trunc(), 3.0);
assert_eq!(h.trunc(), -3.0);
Runsourcepub fn fract(self) -> f32
pub fn fract(self) -> f32
Returns the fractional part of self
.
This function always returns the precise result.
§Examples
let x = 3.6_f32;
let y = -3.6_f32;
let abs_difference_x = (x.fract() - 0.6).abs();
let abs_difference_y = (y.fract() - (-0.6)).abs();
assert!(abs_difference_x <= f32::EPSILON);
assert!(abs_difference_y <= f32::EPSILON);
Runsourcepub fn signum(self) -> f32
pub fn signum(self) -> f32
Returns a number that represents the sign of self
.
1.0
if the number is positive,+0.0
orINFINITY
-1.0
if the number is negative,-0.0
orNEG_INFINITY
- NaN if the number is NaN
§Examples
let f = 3.5_f32;
assert_eq!(f.signum(), 1.0);
assert_eq!(f32::NEG_INFINITY.signum(), -1.0);
assert!(f32::NAN.signum().is_nan());
Run1.35.0 · sourcepub fn copysign(self, sign: f32) -> f32
pub fn copysign(self, sign: f32) -> f32
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 bit of
sign
is returned. Note, however, that conserving the sign bit on NaN
across arithmetical operations is not generally guaranteed.
See explanation of NaN as a special value for more info.
§Examples
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());
Runsourcepub fn mul_add(self, a: f32, b: f32) -> f32
pub fn mul_add(self, a: f32, b: f32) -> f32
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
may be more performant than an unfused multiply-add if
the target architecture has a dedicated fma
CPU instruction. However,
this is not always true, and will be heavily dependant on designing
algorithms with specific target hardware in mind.
§Precision
The result of this operation is guaranteed to be the rounded
infinite-precision result. It is specified by IEEE 754 as
fusedMultiplyAdd
and guaranteed not to change.
§Examples
let m = 10.0_f32;
let x = 4.0_f32;
let b = 60.0_f32;
assert_eq!(m.mul_add(x, b), 100.0);
assert_eq!(m * x + b, 100.0);
let one_plus_eps = 1.0_f32 + f32::EPSILON;
let one_minus_eps = 1.0_f32 - f32::EPSILON;
let minus_one = -1.0_f32;
// The exact result (1 + eps) * (1 - eps) = 1 - eps * eps.
assert_eq!(one_plus_eps.mul_add(one_minus_eps, minus_one), -f32::EPSILON * f32::EPSILON);
// Different rounding with the non-fused multiply and add.
assert_eq!(one_plus_eps * one_minus_eps + minus_one, 0.0);
Run1.38.0 · sourcepub fn div_euclid(self, rhs: f32) -> f32
pub fn div_euclid(self, rhs: f32) -> f32
Calculates Euclidean division, the matching method for rem_euclid
.
This computes the integer n
such that
self = n * rhs + self.rem_euclid(rhs)
.
In other words, the result is self / rhs
rounded to the integer n
such that self >= n * rhs
.
§Precision
The result of this operation is guaranteed to be the rounded infinite-precision result.
§Examples
let a: f32 = 7.0;
let b = 4.0;
assert_eq!(a.div_euclid(b), 1.0); // 7.0 > 4.0 * 1.0
assert_eq!((-a).div_euclid(b), -2.0); // -7.0 >= 4.0 * -2.0
assert_eq!(a.div_euclid(-b), -1.0); // 7.0 >= -4.0 * -1.0
assert_eq!((-a).div_euclid(-b), 2.0); // -7.0 >= -4.0 * 2.0
Run1.38.0 · sourcepub fn rem_euclid(self, rhs: f32) -> f32
pub fn rem_euclid(self, rhs: f32) -> f32
Calculates the least nonnegative remainder of self (mod rhs)
.
In particular, the return value r
satisfies 0.0 <= r < rhs.abs()
in
most cases. However, due to a floating point round-off error it can
result in r == rhs.abs()
, violating the mathematical definition, if
self
is much smaller than rhs.abs()
in magnitude and self < 0.0
.
This result is not an element of the function’s codomain, but it is the
closest floating point number in the real numbers and thus fulfills the
property self == self.div_euclid(rhs) * rhs + self.rem_euclid(rhs)
approximately.
§Precision
The result of this operation is guaranteed to be the rounded infinite-precision result.
§Examples
let a: f32 = 7.0;
let b = 4.0;
assert_eq!(a.rem_euclid(b), 3.0);
assert_eq!((-a).rem_euclid(b), 1.0);
assert_eq!(a.rem_euclid(-b), 3.0);
assert_eq!((-a).rem_euclid(-b), 1.0);
// limitation due to round-off error
assert!((-f32::EPSILON).rem_euclid(3.0) != 0.0);
Runsourcepub fn powi(self, n: i32) -> f32
pub fn powi(self, n: i32) -> f32
Raises a number to an integer power.
Using this function is generally faster than using powf
.
It might have a different sequence of rounding operations than powf
,
so the results are not guaranteed to agree.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
§Examples
let x = 2.0_f32;
let abs_difference = (x.powi(2) - (x * x)).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn sqrt(self) -> f32
pub fn sqrt(self) -> f32
Returns the square root of a number.
Returns NaN if self
is a negative number other than -0.0
.
§Precision
The result of this operation is guaranteed to be the rounded
infinite-precision result. It is specified by IEEE 754 as squareRoot
and guaranteed not to change.
§Examples
let positive = 4.0_f32;
let negative = -4.0_f32;
let negative_zero = -0.0_f32;
assert_eq!(positive.sqrt(), 2.0);
assert!(negative.sqrt().is_nan());
assert!(negative_zero.sqrt() == negative_zero);
Runsourcepub fn exp(self) -> f32
pub fn exp(self) -> f32
Returns e^(self)
, (the exponential function).
§Platform-specific precision
The precision of this function varies by platform and Rust version.
§Examples
let one = 1.0f32;
// e^1
let e = one.exp();
// ln(e) - 1 == 0
let abs_difference = (e.ln() - 1.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn ln(self) -> f32
pub fn ln(self) -> f32
Returns the natural logarithm of the number.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
§Examples
let one = 1.0f32;
// e^1
let e = one.exp();
// ln(e) - 1 == 0
let abs_difference = (e.ln() - 1.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn log(self, base: f32) -> f32
pub fn log(self, base: f32) -> f32
Returns the logarithm of the number with respect to an arbitrary base.
The result might not be correctly rounded owing to implementation details;
self.log2()
can produce more accurate results for base 2, and
self.log10()
can produce more accurate results for base 10.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
§Examples
let five = 5.0f32;
// log5(5) - 1 == 0
let abs_difference = (five.log(5.0) - 1.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn abs_sub(self, other: f32) -> f32
👎Deprecated since 1.10.0: you probably meant (self - other).abs()
: this operation is (self - other).max(0.0)
except that abs_sub
also propagates NaNs (also known as fdimf
in C). If you truly need the positive difference, consider using that expression or the C function fdimf
, depending on how you wish to handle NaN (please consider filing an issue describing your use-case too).
pub fn abs_sub(self, other: f32) -> f32
(self - other).abs()
: this operation is (self - other).max(0.0)
except that abs_sub
also propagates NaNs (also known as fdimf
in C). If you truly need the positive difference, consider using that expression or the C function fdimf
, depending on how you wish to handle NaN (please consider filing an issue describing your use-case too).The positive difference of two numbers.
- If
self <= other
:0.0
- Else:
self - other
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the fdimf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let x = 3.0f32;
let y = -3.0f32;
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 <= f32::EPSILON);
assert!(abs_difference_y <= f32::EPSILON);
Runsourcepub fn cbrt(self) -> f32
pub fn cbrt(self) -> f32
Returns the cube root of a number.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the cbrtf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let x = 8.0f32;
// x^(1/3) - 2 == 0
let abs_difference = (x.cbrt() - 2.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn hypot(self, other: f32) -> f32
pub fn hypot(self, other: f32) -> f32
Compute the distance between the origin and a point (x
, y
) on the
Euclidean plane. Equivalently, compute the length of the hypotenuse of a
right-angle triangle with other sides having length x.abs()
and
y.abs()
.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the hypotf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let x = 2.0f32;
let y = 3.0f32;
// sqrt(x^2 + y^2)
let abs_difference = (x.hypot(y) - (x.powi(2) + y.powi(2)).sqrt()).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn tan(self) -> f32
pub fn tan(self) -> f32
Computes the tangent of a number (in radians).
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the tanf
from libc on Unix and
Windows. Note that this might change in the future.
§Examples
let x = std::f32::consts::FRAC_PI_4;
let abs_difference = (x.tan() - 1.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn asin(self) -> f32
pub fn asin(self) -> f32
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].
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the asinf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let f = std::f32::consts::FRAC_PI_2;
// asin(sin(pi/2))
let abs_difference = (f.sin().asin() - std::f32::consts::FRAC_PI_2).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn acos(self) -> f32
pub fn acos(self) -> f32
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].
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the acosf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let f = std::f32::consts::FRAC_PI_4;
// acos(cos(pi/4))
let abs_difference = (f.cos().acos() - std::f32::consts::FRAC_PI_4).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn atan(self) -> f32
pub fn atan(self) -> f32
Computes the arctangent of a number. Return value is in radians in the range [-pi/2, pi/2];
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the atanf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let f = 1.0f32;
// atan(tan(1))
let abs_difference = (f.tan().atan() - 1.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn atan2(self, other: f32) -> f32
pub fn atan2(self, other: f32) -> f32
Computes the four quadrant arctangent of self
(y
) and other
(x
) in radians.
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)
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the atan2f
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
// Positive angles measured counter-clockwise
// from positive x axis
// -pi/4 radians (45 deg clockwise)
let x1 = 3.0f32;
let y1 = -3.0f32;
// 3pi/4 radians (135 deg counter-clockwise)
let x2 = -3.0f32;
let y2 = 3.0f32;
let abs_difference_1 = (y1.atan2(x1) - (-std::f32::consts::FRAC_PI_4)).abs();
let abs_difference_2 = (y2.atan2(x2) - (3.0 * std::f32::consts::FRAC_PI_4)).abs();
assert!(abs_difference_1 <= f32::EPSILON);
assert!(abs_difference_2 <= f32::EPSILON);
Runsourcepub fn sin_cos(self) -> (f32, f32)
pub fn sin_cos(self) -> (f32, f32)
Simultaneously computes the sine and cosine of the number, x
. Returns
(sin(x), cos(x))
.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the (f32::sin(x), f32::cos(x))
. Note that this might change in the future.
§Examples
let x = std::f32::consts::FRAC_PI_4;
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 <= f32::EPSILON);
assert!(abs_difference_1 <= f32::EPSILON);
Runsourcepub fn exp_m1(self) -> f32
pub fn exp_m1(self) -> f32
Returns e^(self) - 1
in a way that is accurate even if the
number is close to zero.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the expm1f
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let x = 1e-8_f32;
// for very small x, e^x is approximately 1 + x + x^2 / 2
let approx = x + x * x / 2.0;
let abs_difference = (x.exp_m1() - approx).abs();
assert!(abs_difference < 1e-10);
Runsourcepub fn ln_1p(self) -> f32
pub fn ln_1p(self) -> f32
Returns ln(1+n)
(natural logarithm) more accurately than if
the operations were performed separately.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the log1pf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let x = 1e-8_f32;
// for very small x, ln(1 + x) is approximately x - x^2 / 2
let approx = x - x * x / 2.0;
let abs_difference = (x.ln_1p() - approx).abs();
assert!(abs_difference < 1e-10);
Runsourcepub fn sinh(self) -> f32
pub fn sinh(self) -> f32
Hyperbolic sine function.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the sinhf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let e = std::f32::consts::E;
let x = 1.0f32;
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 <= f32::EPSILON);
Runsourcepub fn cosh(self) -> f32
pub fn cosh(self) -> f32
Hyperbolic cosine function.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the coshf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let e = std::f32::consts::E;
let x = 1.0f32;
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 <= f32::EPSILON);
Runsourcepub fn tanh(self) -> f32
pub fn tanh(self) -> f32
Hyperbolic tangent function.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the tanhf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
let e = std::f32::consts::E;
let x = 1.0f32;
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 <= f32::EPSILON);
Runsourcepub fn gamma(self) -> f32
🔬This is a nightly-only experimental API. (float_gamma
#99842)
pub fn gamma(self) -> f32
float_gamma
#99842)Gamma function.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the tgammaf
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
#![feature(float_gamma)]
let x = 5.0f32;
let abs_difference = (x.gamma() - 24.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn ln_gamma(self) -> (f32, i32)
🔬This is a nightly-only experimental API. (float_gamma
#99842)
pub fn ln_gamma(self) -> (f32, i32)
float_gamma
#99842)Natural logarithm of the absolute value of the gamma function
The integer part of the tuple indicates the sign of the gamma function.
§Platform-specific precision
The precision of this function varies by platform and Rust version.
This function currently corresponds to the lgamma_r
from libc on Unix
and Windows. Note that this might change in the future.
§Examples
#![feature(float_gamma)]
let x = 2.0f32;
let abs_difference = (x.ln_gamma().0 - 0.0).abs();
assert!(abs_difference <= f32::EPSILON);
Runsource§impl f32
impl f32
1.43.0 · sourcepub const MANTISSA_DIGITS: u32 = 24u32
pub const MANTISSA_DIGITS: u32 = 24u32
Number of significant digits in base 2.
1.43.0 · sourcepub const DIGITS: u32 = 6u32
pub const DIGITS: u32 = 6u32
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 f32
and back without loss.
Equal to floor(log10 2MANTISSA_DIGITS
− 1).
1.43.0 · sourcepub const EPSILON: f32 = 1.1920929E-7f32
pub const EPSILON: f32 = 1.1920929E-7f32
Machine epsilon value for f32
.
This is the difference between 1.0
and the next larger representable number.
Equal to 21 − MANTISSA_DIGITS
.
1.43.0 · sourcepub const MIN_POSITIVE: f32 = 1.17549435E-38f32
pub const MIN_POSITIVE: f32 = 1.17549435E-38f32
Smallest positive normal f32
value.
Equal to 2MIN_EXP
− 1.
1.43.0 · sourcepub const MAX: f32 = 3.40282347E+38f32
pub const MAX: f32 = 3.40282347E+38f32
Largest finite f32
value.
Equal to
(1 − 2−MANTISSA_DIGITS
) 2MAX_EXP
.
1.43.0 · sourcepub const MIN_EXP: i32 = -125i32
pub const MIN_EXP: i32 = -125i32
One greater than the minimum possible normal power of 2 exponent.
If x = MIN_EXP
, then normal numbers
≥ 0.5 × 2x.
1.43.0 · sourcepub const MAX_EXP: i32 = 128i32
pub const MAX_EXP: i32 = 128i32
Maximum possible power of 2 exponent.
If x = MAX_EXP
, then normal numbers
< 1 × 2x.
1.43.0 · sourcepub const MIN_10_EXP: i32 = -37i32
pub const MIN_10_EXP: i32 = -37i32
Minimum x for which 10x is normal.
Equal to ceil(log10 MIN_POSITIVE
).
1.43.0 · sourcepub const MAX_10_EXP: i32 = 38i32
pub const MAX_10_EXP: i32 = 38i32
Maximum x for which 10x is normal.
Equal to floor(log10 MAX
).
1.43.0 · sourcepub const NAN: f32 = NaN_f32
pub const NAN: f32 = NaN_f32
Not a Number (NaN).
Note that IEEE 754 doesn’t define just a single NaN value; a plethora of bit patterns are considered to be NaN. Furthermore, the standard makes a difference between a “signaling” and a “quiet” NaN, and allows inspecting its “payload” (the unspecified bits in the bit pattern). This constant isn’t guaranteed to equal to any specific NaN bitpattern, and the stability of its representation over Rust versions and target platforms isn’t guaranteed.
1.43.0 · sourcepub const NEG_INFINITY: f32 = -Inf_f32
pub const NEG_INFINITY: f32 = -Inf_f32
Negative infinity (−∞).
const: unstable · sourcepub fn is_nan(self) -> bool
pub fn is_nan(self) -> bool
Returns true
if this value is NaN.
let nan = f32::NAN;
let f = 7.0_f32;
assert!(nan.is_nan());
assert!(!f.is_nan());
Runconst: unstable · sourcepub fn is_infinite(self) -> bool
pub fn is_infinite(self) -> bool
Returns true
if this value is positive infinity or negative infinity, and
false
otherwise.
let f = 7.0f32;
let inf = f32::INFINITY;
let neg_inf = f32::NEG_INFINITY;
let nan = f32::NAN;
assert!(!f.is_infinite());
assert!(!nan.is_infinite());
assert!(inf.is_infinite());
assert!(neg_inf.is_infinite());
Runconst: unstable · sourcepub fn is_finite(self) -> bool
pub fn is_finite(self) -> bool
Returns true
if this number is neither infinite nor NaN.
let f = 7.0f32;
let inf = f32::INFINITY;
let neg_inf = f32::NEG_INFINITY;
let nan = f32::NAN;
assert!(f.is_finite());
assert!(!nan.is_finite());
assert!(!inf.is_finite());
assert!(!neg_inf.is_finite());
Run1.53.0 (const: unstable) · sourcepub fn is_subnormal(self) -> bool
pub fn is_subnormal(self) -> bool
Returns true
if the number is subnormal.
let min = f32::MIN_POSITIVE; // 1.17549435e-38f32
let max = f32::MAX;
let lower_than_min = 1.0e-40_f32;
let zero = 0.0_f32;
assert!(!min.is_subnormal());
assert!(!max.is_subnormal());
assert!(!zero.is_subnormal());
assert!(!f32::NAN.is_subnormal());
assert!(!f32::INFINITY.is_subnormal());
// Values between `0` and `min` are Subnormal.
assert!(lower_than_min.is_subnormal());
Runconst: unstable · sourcepub fn is_normal(self) -> bool
pub fn is_normal(self) -> bool
Returns true
if the number is neither zero, infinite,
subnormal, or NaN.
let min = f32::MIN_POSITIVE; // 1.17549435e-38f32
let max = f32::MAX;
let lower_than_min = 1.0e-40_f32;
let zero = 0.0_f32;
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());
Runconst: unstable · sourcepub fn classify(self) -> FpCategory
pub 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 std::num::FpCategory;
let num = 12.4_f32;
let inf = f32::INFINITY;
assert_eq!(num.classify(), FpCategory::Normal);
assert_eq!(inf.classify(), FpCategory::Infinite);
Runconst: unstable · sourcepub fn is_sign_positive(self) -> bool
pub fn is_sign_positive(self) -> bool
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 for more info.
let f = 7.0_f32;
let g = -7.0_f32;
assert!(f.is_sign_positive());
assert!(!g.is_sign_positive());
Runconst: unstable · sourcepub fn is_sign_negative(self) -> bool
pub fn is_sign_negative(self) -> bool
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 for more info.
let f = 7.0f32;
let g = -7.0f32;
assert!(!f.is_sign_negative());
assert!(g.is_sign_negative());
Runconst: unstable · sourcepub fn next_up(self) -> f32
🔬This is a nightly-only experimental API. (float_next_up_down
#91399)
pub fn next_up(self) -> f32
float_next_up_down
#91399)Returns the least number greater than self
.
Let TINY
be the smallest representable positive f32
. Then,
- if
self.is_nan()
, this returnsself
; - if
self
isNEG_INFINITY
, this returnsMIN
; - if
self
is-TINY
, this returns -0.0; - if
self
is -0.0 or +0.0, this returnsTINY
; - if
self
isMAX
orINFINITY
, this returnsINFINITY
; - otherwise the unique least value greater than
self
is returned.
The identity x.next_up() == -(-x).next_down()
holds for all non-NaN x
. When x
is finite x == x.next_up().next_down()
also holds.
#![feature(float_next_up_down)]
// f32::EPSILON is the difference between 1.0 and the next number up.
assert_eq!(1.0f32.next_up(), 1.0 + f32::EPSILON);
// But not for most numbers.
assert!(0.1f32.next_up() < 0.1 + f32::EPSILON);
assert_eq!(16777216f32.next_up(), 16777218.0);
Runconst: unstable · sourcepub fn next_down(self) -> f32
🔬This is a nightly-only experimental API. (float_next_up_down
#91399)
pub fn next_down(self) -> f32
float_next_up_down
#91399)Returns the greatest number less than self
.
Let TINY
be the smallest representable positive f32
. Then,
- if
self.is_nan()
, this returnsself
; - if
self
isINFINITY
, this returnsMAX
; - if
self
isTINY
, this returns 0.0; - if
self
is -0.0 or +0.0, this returns-TINY
; - if
self
isMIN
orNEG_INFINITY
, this returnsNEG_INFINITY
; - otherwise the unique greatest value less than
self
is returned.
The identity x.next_down() == -(-x).next_up()
holds for all non-NaN x
. When x
is finite x == x.next_down().next_up()
also holds.
#![feature(float_next_up_down)]
let x = 1.0f32;
// Clamp value into range [0, 1).
let clamped = x.clamp(0.0, 1.0f32.next_down());
assert!(clamped < 1.0);
assert_eq!(clamped.next_up(), 1.0);
Runsourcepub fn recip(self) -> f32
pub fn recip(self) -> f32
Takes the reciprocal (inverse) of a number, 1/x
.
let x = 2.0_f32;
let abs_difference = (x.recip() - (1.0 / x)).abs();
assert!(abs_difference <= f32::EPSILON);
Run1.7.0 · sourcepub fn to_degrees(self) -> f32
pub fn to_degrees(self) -> f32
Converts radians to degrees.
let angle = std::f32::consts::PI;
let abs_difference = (angle.to_degrees() - 180.0).abs();
assert!(abs_difference <= f32::EPSILON);
Run1.7.0 · sourcepub fn to_radians(self) -> f32
pub fn to_radians(self) -> f32
Converts degrees to radians.
let angle = 180.0f32;
let abs_difference = (angle.to_radians() - std::f32::consts::PI).abs();
assert!(abs_difference <= f32::EPSILON);
Runsourcepub fn max(self, other: f32) -> f32
pub fn max(self, other: f32) -> f32
Returns the maximum of the two numbers, ignoring NaN.
If one of the arguments is NaN, then the other argument is returned. This follows the IEEE 754-2008 semantics for maxNum, except for handling of signaling NaNs; this function handles all NaNs the same way and avoids maxNum’s problems with associativity. This also matches the behavior of libm’s fmax.
let x = 1.0f32;
let y = 2.0f32;
assert_eq!(x.max(y), y);
Runsourcepub fn min(self, other: f32) -> f32
pub fn min(self, other: f32) -> f32
Returns the minimum of the two numbers, ignoring NaN.
If one of the arguments is NaN, then the other argument is returned. This follows the IEEE 754-2008 semantics for minNum, except for handling of signaling NaNs; this function handles all NaNs the same way and avoids minNum’s problems with associativity. This also matches the behavior of libm’s fmin.
let x = 1.0f32;
let y = 2.0f32;
assert_eq!(x.min(y), x);
Runsourcepub fn maximum(self, other: f32) -> f32
🔬This is a nightly-only experimental API. (float_minimum_maximum
#91079)
pub fn maximum(self, other: f32) -> f32
float_minimum_maximum
#91079)Returns the maximum of the two numbers, propagating NaN.
This returns NaN when either argument is NaN, as opposed to
f32::max
which only returns NaN when both arguments are NaN.
#![feature(float_minimum_maximum)]
let x = 1.0f32;
let y = 2.0f32;
assert_eq!(x.maximum(y), y);
assert!(x.maximum(f32::NAN).is_nan());
RunIf one of the arguments is NaN, then NaN is returned. Otherwise this returns the greater of the two numbers. For this operation, -0.0 is considered to be less than +0.0. Note that this follows the semantics specified in IEEE 754-2019.
Also note that “propagation” of NaNs here doesn’t necessarily mean that the bitpattern of a NaN operand is conserved; see explanation of NaN as a special value for more info.
sourcepub fn minimum(self, other: f32) -> f32
🔬This is a nightly-only experimental API. (float_minimum_maximum
#91079)
pub fn minimum(self, other: f32) -> f32
float_minimum_maximum
#91079)Returns the minimum of the two numbers, propagating NaN.
This returns NaN when either argument is NaN, as opposed to
f32::min
which only returns NaN when both arguments are NaN.
#![feature(float_minimum_maximum)]
let x = 1.0f32;
let y = 2.0f32;
assert_eq!(x.minimum(y), x);
assert!(x.minimum(f32::NAN).is_nan());
RunIf one of the arguments is NaN, then NaN is returned. Otherwise this returns the lesser of the two numbers. For this operation, -0.0 is considered to be less than +0.0. Note that this follows the semantics specified in IEEE 754-2019.
Also note that “propagation” of NaNs here doesn’t necessarily mean that the bitpattern of a NaN operand is conserved; see explanation of NaN as a special value for more info.
sourcepub fn midpoint(self, other: f32) -> f32
🔬This is a nightly-only experimental API. (num_midpoint
#110840)
pub fn midpoint(self, other: f32) -> f32
num_midpoint
#110840)1.44.0 · sourcepub unsafe fn to_int_unchecked<Int>(self) -> Intwhere
f32: FloatToInt<Int>,
pub unsafe fn to_int_unchecked<Int>(self) -> Intwhere
f32: FloatToInt<Int>,
Rounds toward zero and converts to any primitive integer type, assuming that the value is finite and fits in that type.
let value = 4.6_f32;
let rounded = unsafe { value.to_int_unchecked::<u16>() };
assert_eq!(rounded, 4);
let value = -128.9_f32;
let rounded = unsafe { value.to_int_unchecked::<i8>() };
assert_eq!(rounded, i8::MIN);
Run§Safety
The value must:
- Not be
NaN
- Not be infinite
- Be representable in the return type
Int
, after truncating off its fractional part
1.20.0 (const: unstable) · sourcepub fn to_bits(self) -> u32
pub fn to_bits(self) -> u32
Raw transmutation to u32
.
This is currently identical to transmute::<f32, u32>(self)
on all platforms.
See 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.
§Examples
assert_ne!((1f32).to_bits(), 1f32 as u32); // to_bits() is not casting!
assert_eq!((12.5f32).to_bits(), 0x41480000);
Run1.20.0 (const: unstable) · sourcepub fn from_bits(v: u32) -> f32
pub fn from_bits(v: u32) -> f32
Raw transmutation from u32
.
This is currently identical to transmute::<u32, f32>(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.
§Examples
let v = f32::from_bits(0x41480000);
assert_eq!(v, 12.5);
Run1.40.0 (const: unstable) · sourcepub fn to_be_bytes(self) -> [u8; 4]
pub fn to_be_bytes(self) -> [u8; 4]
Return the memory representation of this floating point number as a byte array in big-endian (network) byte order.
See from_bits
for some discussion of the
portability of this operation (there are almost no issues).
§Examples
let bytes = 12.5f32.to_be_bytes();
assert_eq!(bytes, [0x41, 0x48, 0x00, 0x00]);
Run1.40.0 (const: unstable) · sourcepub fn to_le_bytes(self) -> [u8; 4]
pub fn to_le_bytes(self) -> [u8; 4]
Return the memory representation of this floating point number as a byte array in little-endian byte order.
See from_bits
for some discussion of the
portability of this operation (there are almost no issues).
§Examples
let bytes = 12.5f32.to_le_bytes();
assert_eq!(bytes, [0x00, 0x00, 0x48, 0x41]);
Run1.40.0 (const: unstable) · sourcepub fn to_ne_bytes(self) -> [u8; 4]
pub fn to_ne_bytes(self) -> [u8; 4]
Return the memory representation of this floating point number as a byte array in native byte order.
As the target platform’s native endianness is used, portable code
should use to_be_bytes
or to_le_bytes
, as appropriate, instead.
See from_bits
for some discussion of the
portability of this operation (there are almost no issues).
§Examples
let bytes = 12.5f32.to_ne_bytes();
assert_eq!(
bytes,
if cfg!(target_endian = "big") {
[0x41, 0x48, 0x00, 0x00]
} else {
[0x00, 0x00, 0x48, 0x41]
}
);
Run1.40.0 (const: unstable) · sourcepub fn from_ne_bytes(bytes: [u8; 4]) -> f32
pub fn from_ne_bytes(bytes: [u8; 4]) -> f32
Create a floating point value from its representation as a byte array in native endian.
As the target platform’s native endianness is used, portable code
likely wants to use from_be_bytes
or from_le_bytes
, as
appropriate instead.
See from_bits
for some discussion of the
portability of this operation (there are almost no issues).
§Examples
let value = f32::from_ne_bytes(if cfg!(target_endian = "big") {
[0x41, 0x48, 0x00, 0x00]
} else {
[0x00, 0x00, 0x48, 0x41]
});
assert_eq!(value, 12.5);
Run1.62.0 · sourcepub fn total_cmp(&self, other: &f32) -> Ordering
pub fn total_cmp(&self, other: &f32) -> Ordering
Return the ordering between self
and other
.
Unlike the standard partial comparison between floating point numbers,
this comparison always produces an ordering in accordance to
the totalOrder
predicate as defined in the IEEE 754 (2008 revision)
floating point standard. The values are ordered in the following sequence:
- negative quiet NaN
- negative signaling NaN
- negative infinity
- negative numbers
- negative subnormal numbers
- negative zero
- positive zero
- positive subnormal numbers
- positive numbers
- positive infinity
- positive signaling NaN
- positive quiet NaN.
The ordering established by this function does not always agree with the
PartialOrd
and PartialEq
implementations of f32
. For example,
they consider negative and positive zero equal, while total_cmp
doesn’t.
The interpretation of the signaling NaN bit follows the definition in the IEEE 754 standard, which may not match the interpretation by some of the older, non-conformant (e.g. MIPS) hardware implementations.
§Example
struct GoodBoy {
name: String,
weight: f32,
}
let mut bois = vec![
GoodBoy { name: "Pucci".to_owned(), weight: 0.1 },
GoodBoy { name: "Woofer".to_owned(), weight: 99.0 },
GoodBoy { name: "Yapper".to_owned(), weight: 10.0 },
GoodBoy { name: "Chonk".to_owned(), weight: f32::INFINITY },
GoodBoy { name: "Abs. Unit".to_owned(), weight: f32::NAN },
GoodBoy { name: "Floaty".to_owned(), weight: -5.0 },
];
bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));
// `f32::NAN` could be positive or negative, which will affect the sort order.
if f32::NAN.is_sign_negative() {
assert!(bois.into_iter().map(|b| b.weight)
.zip([f32::NAN, -5.0, 0.1, 10.0, 99.0, f32::INFINITY].iter())
.all(|(a, b)| a.to_bits() == b.to_bits()))
} else {
assert!(bois.into_iter().map(|b| b.weight)
.zip([-5.0, 0.1, 10.0, 99.0, f32::INFINITY, f32::NAN].iter())
.all(|(a, b)| a.to_bits() == b.to_bits()))
}
Run1.50.0 · sourcepub fn clamp(self, min: f32, max: f32) -> f32
pub fn clamp(self, min: f32, max: f32) -> f32
Restrict a value to a certain interval unless it is NaN.
Returns max
if self
is greater than max
, and min
if self
is
less than min
. Otherwise this returns self
.
Note that this function returns NaN if the initial value was NaN as well.
§Panics
Panics if min > max
, min
is NaN, or max
is NaN.
§Examples
assert!((-3.0f32).clamp(-2.0, 1.0) == -2.0);
assert!((0.0f32).clamp(-2.0, 1.0) == 0.0);
assert!((2.0f32).clamp(-2.0, 1.0) == 1.0);
assert!((f32::NAN).clamp(-2.0, 1.0).is_nan());
RunTrait Implementations§
1.22.0 · source§impl AddAssign<&f32> for f32
impl AddAssign<&f32> for f32
source§fn add_assign(&mut self, other: &f32)
fn add_assign(&mut self, other: &f32)
+=
operation. Read more1.8.0 · source§impl AddAssign for f32
impl AddAssign for f32
source§fn add_assign(&mut self, other: f32)
fn add_assign(&mut self, other: f32)
+=
operation. Read more1.22.0 · source§impl DivAssign<&f32> for f32
impl DivAssign<&f32> for f32
source§fn div_assign(&mut self, other: &f32)
fn div_assign(&mut self, other: &f32)
/=
operation. Read more1.8.0 · source§impl DivAssign for f32
impl DivAssign for f32
source§fn div_assign(&mut self, other: f32)
fn div_assign(&mut self, other: f32)
/=
operation. Read moresource§impl FromStr for f32
impl FromStr for f32
source§fn from_str(src: &str) -> Result<f32, ParseFloatError>
fn from_str(src: &str) -> Result<f32, ParseFloatError>
Converts a string in base 10 to a float. Accepts an optional decimal exponent.
This function accepts strings such as
- ‘3.14’
- ‘-3.14’
- ‘2.5E10’, or equivalently, ‘2.5e10’
- ‘2.5E-10’
- ‘5.’
- ‘.5’, or, equivalently, ‘0.5’
- ‘inf’, ‘-inf’, ‘+infinity’, ‘NaN’
Note that alphabetical characters are not case-sensitive.
Leading and trailing whitespace represent an error.
§Grammar
All strings that adhere to the following EBNF grammar when
lowercased will result in an Ok
being returned:
Float ::= Sign? ( 'inf' | 'infinity' | 'nan' | Number )
Number ::= ( Digit+ |
Digit+ '.' Digit* |
Digit* '.' Digit+ ) Exp?
Exp ::= 'e' Sign? Digit+
Sign ::= [+-]
Digit ::= [0-9]
§Arguments
- src - A string
§Return value
Err(ParseFloatError)
if the string did not represent a valid
number. Otherwise, Ok(n)
where n
is the closest
representable floating-point number to the number represented
by src
(following the same rules for rounding as for the
results of primitive operations).
§type Err = ParseFloatError
type Err = ParseFloatError
1.22.0 · source§impl MulAssign<&f32> for f32
impl MulAssign<&f32> for f32
source§fn mul_assign(&mut self, other: &f32)
fn mul_assign(&mut self, other: &f32)
*=
operation. Read more1.8.0 · source§impl MulAssign for f32
impl MulAssign for f32
source§fn mul_assign(&mut self, other: f32)
fn mul_assign(&mut self, other: f32)
*=
operation. Read moreconst: unstable · source§impl PartialEq for f32
impl PartialEq for f32
source§impl PartialOrd for f32
impl PartialOrd for f32
source§fn le(&self, other: &f32) -> bool
fn le(&self, other: &f32) -> bool
self
and other
) and is used by the <=
operator. Read moresource§impl Rem for f32
impl Rem for f32
The remainder from the division of two floats.
The remainder has the same sign as the dividend and is computed as:
x - (x / y).trunc() * y
.
§Examples
let x: f32 = 50.50;
let y: f32 = 8.125;
let remainder = x - (x / y).trunc() * y;
// The answer to both operations is 1.75
assert_eq!(x % y, remainder);
Run1.22.0 · source§impl RemAssign<&f32> for f32
impl RemAssign<&f32> for f32
source§fn rem_assign(&mut self, other: &f32)
fn rem_assign(&mut self, other: &f32)
%=
operation. Read more1.8.0 · source§impl RemAssign for f32
impl RemAssign for f32
source§fn rem_assign(&mut self, other: f32)
fn rem_assign(&mut self, other: f32)
%=
operation. Read moresource§impl SimdElement for f32
impl SimdElement for f32
1.22.0 · source§impl SubAssign<&f32> for f32
impl SubAssign<&f32> for f32
source§fn sub_assign(&mut self, other: &f32)
fn sub_assign(&mut self, other: &f32)
-=
operation. Read more1.8.0 · source§impl SubAssign for f32
impl SubAssign for f32
source§fn sub_assign(&mut self, other: f32)
fn sub_assign(&mut self, other: f32)
-=
operation. Read more