f64 - Rust (original) (raw)

Expand description

1.43.0 · Source

The radix or base of the internal representation of f64.

1.43.0 · Source

Number of significant digits in base 2.

Note that the size of the mantissa in the bitwise representation is one smaller than this since the leading 1 is not stored explicitly.

1.43.0 · Source

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 f64 and back without loss.

Equal to floor(log10 2MANTISSA_DIGITS − 1).

1.43.0 · Source

Smallest finite f64 value.

Equal to −MAX.

1.43.0 · Source

Smallest positive normal f64 value.

Equal to 2MIN_EXP − 1.

1.43.0 · Source

One greater than the minimum possible normal power of 2 exponent for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).

This corresponds to the exact minimum possible normal power of 2 exponent for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition). In other words, all normal numbers representable by this type are greater than or equal to 0.5 × 2_MIN_EXP_.

1.43.0 · Source

One greater than the maximum possible power of 2 exponent for a significand bounded by 1 ≤ x < 2 (i.e. the IEEE definition).

This corresponds to the exact maximum possible power of 2 exponent for a significand bounded by 0.5 ≤ x < 1 (i.e. the C definition). In other words, all numbers representable by this type are strictly less than 2_MAX_EXP_.

1.43.0 · Source

Minimum x for which 10_x_ is normal.

Equal to ceil(log10 MIN_POSITIVE).

1.43.0 · Source

Maximum x for which 10_x_ is normal.

Equal to floor(log10 MAX).

1.43.0 · Source

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) and its sign. See the specification of NaN bit patterns for more info.

This constant is guaranteed to be a quiet NaN (on targets that follow the Rust assumptions that the quiet/signaling bit being set to 1 indicates a quiet NaN). Beyond that, nothing is guaranteed about the specific bit pattern chosen here: both payload and sign are arbitrary. The concrete bit pattern may change across Rust versions and target platforms.

1.43.0 · Source

Infinity (∞).

1.43.0 · Source

Negative infinity (−∞).

1.0.0 (const: 1.83.0) · Source

Returns true if this value is NaN.

let nan = f64::NAN;
let f = 7.0_f64;

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

1.0.0 (const: 1.83.0) · Source

Returns true if this value is positive infinity or negative infinity, andfalse otherwise.

let f = 7.0f64;
let inf = f64::INFINITY;
let neg_inf = f64::NEG_INFINITY;
let nan = f64::NAN;

assert!(!f.is_infinite());
assert!(!nan.is_infinite());

assert!(inf.is_infinite());
assert!(neg_inf.is_infinite());

1.0.0 (const: 1.83.0) · Source

Returns true if this number is neither infinite nor NaN.

let f = 7.0f64;
let inf: f64 = f64::INFINITY;
let neg_inf: f64 = f64::NEG_INFINITY;
let nan: f64 = f64::NAN;

assert!(f.is_finite());

assert!(!nan.is_finite());
assert!(!inf.is_finite());
assert!(!neg_inf.is_finite());

1.53.0 (const: 1.83.0) · Source

Returns true if the number is subnormal.

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());

1.0.0 (const: 1.83.0) · Source

Returns true if the number is neither zero, infinite,subnormal, or NaN.

let min = f64::MIN_POSITIVE; // 2.2250738585072014e-308f64
let max = f64::MAX;
let lower_than_min = 1.0e-308_f64;
let zero = 0.0f64;

assert!(min.is_normal());
assert!(max.is_normal());

assert!(!zero.is_normal());
assert!(!f64::NAN.is_normal());
assert!(!f64::INFINITY.is_normal());
// Values between `0` and `min` are Subnormal.
assert!(!lower_than_min.is_normal());

1.0.0 (const: 1.83.0) · Source

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_f64;
let inf = f64::INFINITY;

assert_eq!(num.classify(), FpCategory::Normal);
assert_eq!(inf.classify(), FpCategory::Infinite);

1.0.0 (const: 1.83.0) · Source

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 or non-portable result. See the specification of NaN bit patterns for more info. Use self.signum() == 1.0if you need fully portable behavior (will return false for all NaNs).

let f = 7.0_f64;
let g = -7.0_f64;

assert!(f.is_sign_positive());
assert!(!g.is_sign_positive());

1.0.0 (const: 1.83.0) · Source

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 or non-portable result. See the specification of NaN bit patterns for more info. Use self.signum() == -1.0if you need fully portable behavior (will return false for all NaNs).

let f = 7.0_f64;
let g = -7.0_f64;

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

1.86.0 (const: 1.86.0) · Source

Returns the least number greater than self.

Let TINY be the smallest representable positive f64. Then,

if self.is_nan(), this returns self;
if self is NEG_INFINITY, this returns MIN;
if self is -TINY, this returns -0.0;
if self is -0.0 or +0.0, this returns TINY;
if self is MAX or INFINITY, this returns INFINITY;
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 xis finite x == x.next_up().next_down() also holds.

// f64::EPSILON is the difference between 1.0 and the next number up.
assert_eq!(1.0f64.next_up(), 1.0 + f64::EPSILON);
// But not for most numbers.
assert!(0.1f64.next_up() < 0.1 + f64::EPSILON);
assert_eq!(9007199254740992f64.next_up(), 9007199254740994.0);

This operation corresponds to IEEE-754 nextUp.

1.86.0 (const: 1.86.0) · Source

Returns the greatest number less than self.

Let TINY be the smallest representable positive f64. Then,

if self.is_nan(), this returns self;
if self is INFINITY, this returns MAX;
if self is TINY, this returns 0.0;
if self is -0.0 or +0.0, this returns -TINY;
if self is MIN or NEG_INFINITY, this returns NEG_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 xis finite x == x.next_down().next_up() also holds.

let x = 1.0f64;
// Clamp value into range [0, 1).
let clamped = x.clamp(0.0, 1.0f64.next_down());
assert!(clamped < 1.0);
assert_eq!(clamped.next_up(), 1.0);

This operation corresponds to IEEE-754 nextDown.

1.0.0 (const: 1.85.0) · Source

Takes the reciprocal (inverse) of a number, 1/x.

let x = 2.0_f64;
let abs_difference = (x.recip() - (1.0 / x)).abs();

assert!(abs_difference < 1e-10);

1.0.0 (const: 1.85.0) · Source

Converts radians to degrees.

let angle = std::f64::consts::PI;

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

assert!(abs_difference < 1e-10);

1.0.0 (const: 1.85.0) · Source

Converts degrees to radians.

let angle = 180.0_f64;

let abs_difference = (angle.to_radians() - std::f64::consts::PI).abs();

assert!(abs_difference < 1e-10);

1.0.0 (const: 1.85.0) · Source

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. In particular, if the inputs compare equal (such as for the case of +0.0 and -0.0), either input may be returned non-deterministically.

let x = 1.0_f64;
let y = 2.0_f64;

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

1.0.0 (const: 1.85.0) · Source

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. In particular, if the inputs compare equal (such as for the case of +0.0 and -0.0), either input may be returned non-deterministically.

let x = 1.0_f64;
let y = 2.0_f64;

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

Source

🔬This is a nightly-only experimental API. (float_minimum_maximum #91079)

Returns the maximum of the two numbers, propagating NaN.

This returns NaN when either argument is NaN, as opposed tof64::max which only returns NaN when both arguments are NaN.

#![feature(float_minimum_maximum)]
let x = 1.0_f64;
let y = 2.0_f64;

assert_eq!(x.maximum(y), y);
assert!(x.maximum(f64::NAN).is_nan());

If 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 the specification of NaN bit patterns for more info.

Source

🔬This is a nightly-only experimental API. (float_minimum_maximum #91079)

Returns the minimum of the two numbers, propagating NaN.

This returns NaN when either argument is NaN, as opposed tof64::min which only returns NaN when both arguments are NaN.

#![feature(float_minimum_maximum)]
let x = 1.0_f64;
let y = 2.0_f64;

assert_eq!(x.minimum(y), x);
assert!(x.minimum(f64::NAN).is_nan());

If 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 the specification of NaN bit patterns for more info.

1.85.0 (const: 1.85.0) · Source

Calculates the midpoint (average) between self and rhs.

This returns NaN when either argument is NaN or if a combination of +inf and -inf is provided as arguments.

§Examples

assert_eq!(1f64.midpoint(4.0), 2.5);
assert_eq!((-5.5f64).midpoint(8.0), 1.25);

1.44.0 · Source

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_f64;
let rounded = unsafe { value.to_int_unchecked::<u16>() };
assert_eq!(rounded, 4);

let value = -128.9_f64;
let rounded = unsafe { value.to_int_unchecked::<i8>() };
assert_eq!(rounded, i8::MIN);

§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: 1.83.0) · Source

Raw transmutation to u64.

This is currently identical to transmute::<f64, u64>(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!((1f64).to_bits() != 1f64 as u64); // to_bits() is not casting!
assert_eq!((12.5f64).to_bits(), 0x4029000000000000);

1.20.0 (const: 1.83.0) · Source

Raw transmutation from u64.

This is currently identical to transmute::<u64, f64>(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 signaling-ness (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 = f64::from_bits(0x4029000000000000);
assert_eq!(v, 12.5);

1.40.0 (const: 1.83.0) · Source

Returns 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 = 12.5f64.to_be_bytes();
assert_eq!(bytes, [0x40, 0x29, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]);

1.40.0 (const: 1.83.0) · Source

Returns 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 = 12.5f64.to_le_bytes();
assert_eq!(bytes, [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x29, 0x40]);

1.40.0 (const: 1.83.0) · Source

Returns 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 = 12.5f64.to_ne_bytes();
assert_eq!(
    bytes,
    if cfg!(target_endian = "big") {
        [0x40, 0x29, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
    } else {
        [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x29, 0x40]
    }
);

1.40.0 (const: 1.83.0) · Source

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

See from_bits for some discussion of the portability of this operation (there are almost no issues).

§Examples

let value = f64::from_be_bytes([0x40, 0x29, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]);
assert_eq!(value, 12.5);

1.40.0 (const: 1.83.0) · Source

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

See from_bits for some discussion of the portability of this operation (there are almost no issues).

§Examples

let value = f64::from_le_bytes([0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x29, 0x40]);
assert_eq!(value, 12.5);

1.40.0 (const: 1.83.0) · Source

Creates 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 = f64::from_ne_bytes(if cfg!(target_endian = "big") {
    [0x40, 0x29, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00]
} else {
    [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x29, 0x40]
});
assert_eq!(value, 12.5);

1.62.0 · Source

Returns 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 thePartialOrd and PartialEq implementations of f64. For example, they consider negative and positive zero equal, while total_cmpdoesn’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: f64,
}

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: f64::INFINITY },
    GoodBoy { name: "Abs. Unit".to_owned(), weight: f64::NAN },
    GoodBoy { name: "Floaty".to_owned(), weight: -5.0 },
];

bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));

// `f64::NAN` could be positive or negative, which will affect the sort order.
if f64::NAN.is_sign_negative() {
    assert!(bois.into_iter().map(|b| b.weight)
        .zip([f64::NAN, -5.0, 0.1, 10.0, 99.0, f64::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, f64::INFINITY, f64::NAN].iter())
        .all(|(a, b)| a.to_bits() == b.to_bits()))
}

1.50.0 (const: 1.85.0) · Source

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!((-3.0f64).clamp(-2.0, 1.0) == -2.0);
assert!((0.0f64).clamp(-2.0, 1.0) == 0.0);
assert!((2.0f64).clamp(-2.0, 1.0) == 1.0);
assert!((f64::NAN).clamp(-2.0, 1.0).is_nan());

1.0.0 (const: 1.85.0) · Source

Computes the absolute value of self.

This function always returns the precise result.

§Examples

let x = 3.5_f64;
let y = -3.5_f64;

assert_eq!(x.abs(), x);
assert_eq!(y.abs(), -y);

assert!(f64::NAN.abs().is_nan());

1.0.0 (const: 1.85.0) · Source

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_f64;

assert_eq!(f.signum(), 1.0);
assert_eq!(f64::NEG_INFINITY.signum(), -1.0);

assert!(f64::NAN.signum().is_nan());

1.35.0 (const: 1.85.0) · Source

Returns a number composed of the magnitude of self and the sign ofsign.

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 same payload as self and the sign bit of sign is returned.

If sign is a NaN, then this operation will still carry over its sign into the result. 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 copysign with sign being a NaN might produce an unexpected or non-portable result. See the specification of NaN bit patterns for more info.

§Examples

let f = 3.5_f64;

assert_eq!(f.copysign(0.42), 3.5_f64);
assert_eq!(f.copysign(-0.42), -3.5_f64);
assert_eq!((-f).copysign(0.42), 3.5_f64);
assert_eq!((-f).copysign(-0.42), -3.5_f64);

assert!(f64::NAN.copysign(1.0).is_nan());

Source

🔬This is a nightly-only experimental API. (float_algebraic #136469)

Float addition that allows optimizations based on algebraic rules.

See algebraic operators for more info.

Source

🔬This is a nightly-only experimental API. (float_algebraic #136469)

Float subtraction that allows optimizations based on algebraic rules.

See algebraic operators for more info.

Source

🔬This is a nightly-only experimental API. (float_algebraic #136469)

Float multiplication that allows optimizations based on algebraic rules.

See algebraic operators for more info.