Primitive Type f32
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.
This also affects the sign of the NaN: checking
is_sign_positive
oris_sign_negative
on a NaN is the most common way to run into these surprising results. (Checkingx >= 0.0
orx <= 0.0
avoids those surprises, but also how negative/positive zero are treated.) See the section below for what exactly is guaranteed about the bit pattern of a NaN.
- 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.
See also the std::f32::consts
module.
§NaN bit patterns
This section defines the possible NaN bit patterns returned by floating-point operations.
The bit pattern of a floating-point NaN value is defined by:
- a sign bit.
- a quiet/signaling bit. Rust assumes that the quiet/signaling bit being set to
1
indicates a quiet NaN (QNaN), and a value of0
indicates a signaling NaN (SNaN). In the following we will hence just call it the “quiet bit”. - a payload, which makes up the rest of the significand (i.e., the mantissa) except for the quiet bit.
The rules for NaN values differ between arithmetic and non-arithmetic (or “bitwise”)
operations. The non-arithmetic operations are unary -
, abs
, copysign
, signum
,
{to,from}_bits
, {to,from}_{be,le,ne}_bytes
and is_sign_{positive,negative}
. These
operations are guaranteed to exactly preserve the bit pattern of their input except for possibly
changing the sign bit.
The following rules apply when a NaN value is returned from an arithmetic operation:
-
The result has a non-deterministic sign.
-
The quiet bit and payload are non-deterministically chosen from the following set of options:
- Preferred NaN: The quiet bit is set and the payload is all-zero.
- Quieting NaN propagation: The quiet bit is set and the payload is copied from any input
operand that is a NaN. If the inputs and outputs do not have the same payload size (i.e., for
as
casts), then- If the output is smaller than the input, low-order bits of the payload get dropped.
- If the output is larger than the input, the payload gets filled up with 0s in the low-order bits.
- Unchanged NaN propagation: The quiet bit and payload are copied from any input operand
that is a NaN. If the inputs and outputs do not have the same size (i.e., for
as
casts), the same rules as for “quieting NaN propagation” apply, with one caveat: if the output is smaller than the input, droppig the low-order bits may result in a payload of 0; a payload of 0 is not possible with a signaling NaN (the all-0 significand encodes an infinity) so unchanged NaN propagation cannot occur with some inputs. - Target-specific NaN: The quiet bit is set and the payload is picked from a target-specific set of “extra” possible NaN payloads. The set can depend on the input operand values. See the table below for the concrete NaNs this set contains on various targets.
In particular, if all input NaNs are quiet (or if there are no input NaNs), then the output NaN is definitely quiet. Signaling NaN outputs can only occur if they are provided as an input value. Similarly, if all input NaNs are preferred (or if there are no input NaNs) and the target does not have any “extra” NaN payloads, then the output NaN is guaranteed to be preferred.
The non-deterministic choice happens when the operation is executed; i.e., the result of a NaN-producing floating-point operation is a stable bit pattern (looking at these bits multiple times will yield consistent results), but running the same operation twice with the same inputs can produce different results.
These guarantees are neither stronger nor weaker than those of IEEE 754: IEEE 754 guarantees
that an operation never returns a signaling NaN, whereas it is possible for operations like
SNAN * 1.0
to return a signaling NaN in Rust. Conversely, IEEE 754 makes no statement at all
about which quiet NaN is returned, whereas Rust restricts the set of possible results to the
ones listed above.
Unless noted otherwise, the same rules also apply to NaNs returned by other library functions
(e.g. min
, minimum
, max
, maximum
); other aspects of their semantics and which IEEE 754
operation they correspond to are documented with the respective functions.
When an arithmetic floating-point operation is executed in const
context, the same rules
apply: no guarantee is made about which of the NaN bit patterns described above will be
returned. The result does not have to match what happens when executing the same code at
runtime, and the result can vary depending on factors such as compiler version and flags.
§Target-specific “extra” NaN values
target_arch | Extra payloads possible on this platform |
---|---|
x86 , x86_64 , arm , aarch64 , riscv32 , riscv64 | None |
sparc , sparc64 | The all-one payload |
wasm32 , wasm64 | If all input NaNs are quiet with all-zero payload: None. Otherwise: all possible payloads. |
For targets not in this table, all payloads are possible.
Implementations§
source§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 (−∞).
1.0.0 (const: 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.
1.53.0 (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());
1.0.0 (const: 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());
1.0.0 (const: 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.
1.0.0 (const: 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 or non-portable result. See the specification
of NaN bit patterns for more info. Use self.signum() == 1.0
if you need fully portable behavior (will return false
for all NaNs).
1.0.0 (const: 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 or non-portable result. See the specification
of NaN bit patterns for more info. Use self.signum() == -1.0
if you need fully portable behavior (will return false
for all NaNs).
sourcepub const fn next_up(self) -> Self
🔬This is a nightly-only experimental API. (float_next_up_down
#91399)
pub const fn next_up(self) -> Self
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.
sourcepub const fn next_down(self) -> Self
🔬This is a nightly-only experimental API. (float_next_up_down
#91399)
pub const fn next_down(self) -> Self
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.
1.7.0 · sourcepub fn to_degrees(self) -> f32
pub fn to_degrees(self) -> f32
1.7.0 · sourcepub fn to_radians(self) -> f32
pub fn to_radians(self) -> f32
1.0.0 · sourcepub 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.
1.0.0 · sourcepub 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.
sourcepub 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());
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.
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());
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.
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)Calculates the middle point of self
and rhs
.
This returns NaN when either argument is NaN or if a combination of +inf and -inf is provided as arguments.
§Examples
1.44.0 · sourcepub unsafe fn to_int_unchecked<Int>(self) -> Intwhere
Self: FloatToInt<Int>,
pub unsafe fn to_int_unchecked<Int>(self) -> Intwhere
Self: 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);
§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) · sourcepub const fn to_bits(self) -> u32
pub const 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
1.20.0 (const: 1.83.0) · sourcepub const fn from_bits(v: u32) -> Self
pub const fn from_bits(v: u32) -> Self
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
1.40.0 (const: 1.83.0) · sourcepub const fn to_be_bytes(self) -> [u8; 4]
pub const fn to_be_bytes(self) -> [u8; 4]
1.40.0 (const: 1.83.0) · sourcepub const fn to_le_bytes(self) -> [u8; 4]
pub const fn to_le_bytes(self) -> [u8; 4]
1.40.0 (const: 1.83.0) · sourcepub const fn to_ne_bytes(self) -> [u8; 4]
pub const fn to_ne_bytes(self) -> [u8; 4]
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
1.40.0 (const: 1.83.0) · sourcepub const fn from_be_bytes(bytes: [u8; 4]) -> Self
pub const fn from_be_bytes(bytes: [u8; 4]) -> Self
1.40.0 (const: 1.83.0) · sourcepub const fn from_le_bytes(bytes: [u8; 4]) -> Self
pub const fn from_le_bytes(bytes: [u8; 4]) -> Self
1.40.0 (const: 1.83.0) · sourcepub const fn from_ne_bytes(bytes: [u8; 4]) -> Self
pub const fn from_ne_bytes(bytes: [u8; 4]) -> Self
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
1.62.0 · sourcepub fn total_cmp(&self, other: &Self) -> Ordering
pub fn total_cmp(&self, other: &Self) -> Ordering
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 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()))
}
1.50.0 · 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
Trait 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 more1.0.0 · source§impl FromStr for f32
impl FromStr for f32
source§fn from_str(src: &str) -> Result<Self, ParseFloatError>
fn from_str(src: &str) -> Result<Self, 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).
source§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 more1.0.0 · source§impl PartialOrd for f32
impl PartialOrd for f32
1.0.0 · source§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
1.22.0 · 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