Primitive Type f321.0.0[−]

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 unequal to any float, including itself! It is also neither smaller nor greater than any float, making it impossible to sort. Lastly, it is considered infectious as almost all calculations where one of the operands is NaN will also result in NaN.

For more information on floating point numbers, see Wikipedia.

See also the std::f32::consts module.

Implementations

Returns the largest integer less than or equal to a number.

Examples
let f = 3.7_f32;
let g = 3.0_f32;
let h = -3.7_f32;

assert_eq!(f.floor(), 3.0);
assert_eq!(g.floor(), 3.0);
assert_eq!(h.floor(), -4.0);
Run

Returns the smallest integer greater than or equal to a number.

Examples
let f = 3.01_f32;
let g = 4.0_f32;

assert_eq!(f.ceil(), 4.0);
assert_eq!(g.ceil(), 4.0);
Run

Returns the nearest integer to a number. Round half-way cases away from 0.0.

Examples
let f = 3.3_f32;
let g = -3.3_f32;

assert_eq!(f.round(), 3.0);
assert_eq!(g.round(), -3.0);
Run

Returns the integer part of a number.

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);
Run

Returns the fractional part of a number.

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);
Run

Computes the absolute value of self. Returns NAN if the number is NAN.

Examples
let x = 3.5_f32;
let y = -3.5_f32;

let abs_difference_x = (x.abs() - x).abs();
let abs_difference_y = (y.abs() - (-y)).abs();

assert!(abs_difference_x <= f32::EPSILON);
assert!(abs_difference_y <= f32::EPSILON);

assert!(f32::NAN.abs().is_nan());
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Returns a number that represents the sign of self.

  • 1.0 if the number is positive, +0.0 or INFINITY
  • -1.0 if the number is negative, -0.0 or NEG_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());
Run

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
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());
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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.

Examples
let m = 10.0_f32;
let x = 4.0_f32;
let b = 60.0_f32;

// 100.0
let abs_difference = (m.mul_add(x, b) - ((m * x) + b)).abs();

assert!(abs_difference <= f32::EPSILON);
Run

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.

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
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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) approximatively.

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);
Run

Raises a number to an integer power.

Using this function is generally faster than using powf

Examples
let x = 2.0_f32;
let abs_difference = (x.powi(2) - (x * x)).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Raises a number to a floating point power.

Examples
let x = 2.0_f32;
let abs_difference = (x.powf(2.0) - (x * x)).abs();

assert!(abs_difference <= f32::EPSILON);
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Returns the square root of a number.

Returns NaN if self is a negative number other than -0.0.

Examples
let positive = 4.0_f32;
let negative = -4.0_f32;
let negative_zero = -0.0_f32;

let abs_difference = (positive.sqrt() - 2.0).abs();

assert!(abs_difference <= f32::EPSILON);
assert!(negative.sqrt().is_nan());
assert!(negative_zero.sqrt() == negative_zero);
Run

Returns e^(self), (the exponential function).

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);
Run

Returns 2^(self).

Examples
let f = 2.0f32;

// 2^2 - 4 == 0
let abs_difference = (f.exp2() - 4.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Returns the natural logarithm of the number.

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);
Run

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.

Examples
let five = 5.0f32;

// log5(5) - 1 == 0
let abs_difference = (five.log(5.0) - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Returns the base 2 logarithm of the number.

Examples
let two = 2.0f32;

// log2(2) - 1 == 0
let abs_difference = (two.log2() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Returns the base 10 logarithm of the number.

Examples
let ten = 10.0f32;

// log10(10) - 1 == 0
let abs_difference = (ten.log10() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run
👎 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).

The positive difference of two numbers.

  • If self <= other: 0:0
  • Else: self - other
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);
Run

Returns the cube root of a number.

Examples
let x = 8.0f32;

// x^(1/3) - 2 == 0
let abs_difference = (x.cbrt() - 2.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Calculates the length of the hypotenuse of a right-angle triangle given legs of length x and y.

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);
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Computes the sine of a number (in radians).

Examples
let x = std::f32::consts::FRAC_PI_2;

let abs_difference = (x.sin() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Computes the cosine of a number (in radians).

Examples
let x = 2.0 * std::f32::consts::PI;

let abs_difference = (x.cos() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Computes the tangent of a number (in radians).

Examples
let x = std::f32::consts::FRAC_PI_4;
let abs_difference = (x.tan() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
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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].

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);
Run

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].

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);
Run

Computes the arctangent of a number. Return value is in radians in the range [-pi/2, pi/2];

Examples
let f = 1.0f32;

// atan(tan(1))
let abs_difference = (f.tan().atan() - 1.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

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)
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);
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Simultaneously computes the sine and cosine of the number, x. Returns (sin(x), cos(x)).

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);
Run

Returns e^(self) - 1 in a way that is accurate even if the number is close to zero.

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);
Run

Returns ln(1+n) (natural logarithm) more accurately than if the operations were performed separately.

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);
Run

Hyperbolic sine function.

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);
Run

Hyperbolic cosine function.

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);
Run

Hyperbolic tangent function.

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);
Run

Inverse hyperbolic sine function.

Examples
let x = 1.0f32;
let f = x.sinh().asinh();

let abs_difference = (f - x).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Inverse hyperbolic cosine function.

Examples
let x = 1.0f32;
let f = x.cosh().acosh();

let abs_difference = (f - x).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Inverse hyperbolic tangent function.

Examples
let e = std::f32::consts::E;
let f = e.tanh().atanh();

let abs_difference = (f - e).abs();

assert!(abs_difference <= 1e-5);
Run
🔬 This is a nightly-only experimental API. (float_interpolation #86269)

Linear interpolation between start and end.

This enables linear interpolation between start and end, where start is represented by self == 0.0 and end is represented by self == 1.0. This is the basis of all “transition”, “easing”, or “step” functions; if you change self from 0.0 to 1.0 at a given rate, the result will change from start to end at a similar rate.

Values below 0.0 or above 1.0 are allowed, allowing you to extrapolate values outside the range from start to end. This also is useful for transition functions which might move slightly past the end or start for a desired effect. Mathematically, the values returned are equivalent to start + self * (end - start), although we make a few specific guarantees that are useful specifically to linear interpolation.

These guarantees are:

  • If start and end are finite, the value at 0.0 is always start and the value at 1.0 is always end. (exactness)
  • If start and end are finite, the values will always move in the direction from start to end (monotonicity)
  • If self is finite and start == end, the value at any point will always be start == end. (consistency)

The radix or base of the internal representation of f32.

Number of significant digits in base 2.

Approximate number of significant digits in base 10.

Machine epsilon value for f32.

This is the difference between 1.0 and the next larger representable number.

Smallest finite f32 value.

Smallest positive normal f32 value.

Largest finite f32 value.

One greater than the minimum possible normal power of 2 exponent.

Maximum possible power of 2 exponent.

Minimum possible normal power of 10 exponent.

Maximum possible power of 10 exponent.

Not a Number (NaN).

Infinity (∞).

Negative infinity (−∞).

Returns true if this value is NaN.

let nan = f32::NAN;
let f = 7.0_f32;

assert!(nan.is_nan());
assert!(!f.is_nan());
Run

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());
Run

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());
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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());
Run

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());
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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);
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Returns true if self has a positive sign, including +0.0, NaNs with positive sign bit and positive infinity.

let f = 7.0_f32;
let g = -7.0_f32;

assert!(f.is_sign_positive());
assert!(!g.is_sign_positive());
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Returns true if self has a negative sign, including -0.0, NaNs with negative sign bit and negative infinity.

let f = 7.0f32;
let g = -7.0f32;

assert!(!f.is_sign_negative());
assert!(g.is_sign_negative());
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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);
Run

Converts radians to degrees.

let angle = std::f32::consts::PI;

let abs_difference = (angle.to_degrees() - 180.0).abs();

assert!(abs_difference <= f32::EPSILON);
Run

Converts degrees to radians.

let angle = 180.0f32;

let abs_difference = (angle.to_radians() - std::f32::consts::PI).abs();

assert!(abs_difference <= f32::EPSILON);
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Returns the maximum of the two numbers.

let x = 1.0f32;
let y = 2.0f32;

assert_eq!(x.max(y), y);
Run

If one of the arguments is NaN, then the other argument is returned.

Returns the minimum of the two numbers.

let x = 1.0f32;
let y = 2.0f32;

assert_eq!(x.min(y), x);
Run

If one of the arguments is NaN, then the other argument is returned.

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

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);
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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);
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Return the memory representation of this floating point number as a byte array in big-endian (network) byte order.

Examples
let bytes = 12.5f32.to_be_bytes();
assert_eq!(bytes, [0x41, 0x48, 0x00, 0x00]);
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Return the memory representation of this floating point number as a byte array in little-endian byte order.

Examples
let bytes = 12.5f32.to_le_bytes();
assert_eq!(bytes, [0x00, 0x00, 0x48, 0x41]);
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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.

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]
    }
);
Run

Create a floating point value from its representation as a byte array in big endian.

Examples
let value = f32::from_be_bytes([0x41, 0x48, 0x00, 0x00]);
assert_eq!(value, 12.5);
Run

Create a floating point value from its representation as a byte array in little endian.

Examples
let value = f32::from_le_bytes([0x00, 0x00, 0x48, 0x41]);
assert_eq!(value, 12.5);
Run

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.

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);
Run
🔬 This is a nightly-only experimental API. (total_cmp #72599)

Returns an ordering between self and other values. Unlike the standard partial comparison between floating point numbers, this comparison always produces an ordering in accordance to the totalOrder predicate as defined in IEEE 754 (2008 revision) floating point standard. The values are ordered in following order:

  • 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

Note that this function does not always agree with the PartialOrd and PartialEq implementations of f32. In particular, they regard negative and positive zero as equal, while total_cmp doesn’t.

Example
#![feature(total_cmp)]
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));
Run

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());
Run

Trait Implementations

The resulting type after applying the + operator.

Performs the + operation. Read more

The resulting type after applying the + operator.

Performs the + operation. Read more

The resulting type after applying the + operator.

Performs the + operation. Read more

The resulting type after applying the + operator.

Performs the + operation. Read more

Performs the += operation. Read more

Performs the += operation. Read more

Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

Formats the value using the given formatter. Read more

Returns the default value of 0.0

Formats the value using the given formatter. Read more

The resulting type after applying the / operator.

Performs the / operation. Read more

The resulting type after applying the / operator.

Performs the / operation. Read more

The resulting type after applying the / operator.

Performs the / operation. Read more

The resulting type after applying the / operator.

Performs the / operation. Read more

Performs the /= operation. Read more

Performs the /= operation. Read more

Converts i16 to f32 losslessly.

Converts i8 to f32 losslessly.

Converts u16 to f32 losslessly.

Converts u8 to f32 losslessly.

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’, ‘NaN’

Leading and trailing whitespace represent an error.

Grammar

All strings that adhere to the following EBNF grammar will result in an Ok being returned:

Float  ::= Sign? ( 'inf' | 'NaN' | Number )
Number ::= ( Digit+ |
             Digit+ '.' Digit* |
             Digit* '.' Digit+ ) Exp?
Exp    ::= [eE] 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 floating-point number represented by src.

The associated error which can be returned from parsing.

Formats the value using the given formatter.

The resulting type after applying the * operator.

Performs the * operation. Read more

The resulting type after applying the * operator.

Performs the * operation. Read more

The resulting type after applying the * operator.

Performs the * operation. Read more

The resulting type after applying the * operator.

Performs the * operation. Read more

Performs the *= operation. Read more

Performs the *= operation. Read more

The resulting type after applying the - operator.

Performs the unary - operation. Read more

The resulting type after applying the - operator.

Performs the unary - operation. Read more

This method tests for self and other values to be equal, and is used by ==. Read more

This method tests for !=.

This method returns an ordering between self and other values if one exists. Read more

This method tests less than (for self and other) and is used by the < operator. Read more

This method tests less than or equal to (for self and other) and is used by the <= operator. Read more

This method tests greater than or equal to (for self and other) and is used by the >= operator. Read more

This method tests greater than (for self and other) and is used by the > operator. Read more

Method which takes an iterator and generates Self from the elements by multiplying the items. Read more

Method which takes an iterator and generates Self from the elements by multiplying the items. Read more

The resulting type after applying the % operator.

Performs the % operation. Read more

The resulting type after applying the % operator.

Performs the % operation. Read more

The resulting type after applying the % operator.

Performs the % operation. Read more

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);
Run

The resulting type after applying the % operator.

Performs the % operation. Read more

Performs the %= operation. Read more

Performs the %= operation. Read more

The resulting type after applying the - operator.

Performs the - operation. Read more

The resulting type after applying the - operator.

Performs the - operation. Read more

The resulting type after applying the - operator.

Performs the - operation. Read more

The resulting type after applying the - operator.

Performs the - operation. Read more

Performs the -= operation. Read more

Performs the -= operation. Read more

Method which takes an iterator and generates Self from the elements by “summing up” the items. Read more

Method which takes an iterator and generates Self from the elements by “summing up” the items. Read more

Formats the value using the given formatter.

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Performs the conversion.

Performs the conversion.

The resulting type after obtaining ownership.

Creates owned data from borrowed data, usually by cloning. Read more

🔬 This is a nightly-only experimental API. (toowned_clone_into #41263)

recently added

Uses borrowed data to replace owned data, usually by cloning. Read more

Converts the given value to a String. Read more

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.