Struct elastic::types::prelude::Float [] [src]

pub struct Float<M> where
    M: FloatMapping
{ /* fields omitted */ }

Number type with a given mapping.

Methods

impl<M> Float<M> where
    M: FloatMapping
[src]

Creates a new number with the given mapping.

Change the mapping of this number.

Methods from Deref<Target = f32>

Returns true if this value is NaN and false otherwise.

use std::f32;

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

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

Returns true if this value is positive infinity or negative infinity and false otherwise.

use std::f32;

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());

Returns true if this number is neither infinite nor NaN.

use std::f32;

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());

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

use std::f32;

let min = f32::MIN_POSITIVE; // 1.17549435e-38f32
let max = f32::MAX;
let lower_than_min = 1.0e-40_f32;
let zero = 0.0_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());

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;
use std::f32;

let num = 12.4_f32;
let inf = f32::INFINITY;

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

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

let f = 3.99_f32;
let g = 3.0_f32;

assert_eq!(f.floor(), 3.0);
assert_eq!(g.floor(), 3.0);

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

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

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

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

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

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

Returns the integer part of a number.

let f = 3.3_f32;
let g = -3.7_f32;

assert_eq!(f.trunc(), 3.0);
assert_eq!(g.trunc(), -3.0);

Returns the fractional part of a number.

use std::f32;

let x = 3.5_f32;
let y = -3.5_f32;
let abs_difference_x = (x.fract() - 0.5).abs();
let abs_difference_y = (y.fract() - (-0.5)).abs();

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

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

use std::f32;

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());

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
use std::f32;

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());

Returns true if self's sign bit is positive, including +0.0 and INFINITY.

use std::f32;

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

assert!(f.is_sign_positive());
assert!(!g.is_sign_positive());
// Requires both tests to determine if is `NaN`
assert!(!nan.is_sign_positive() && !nan.is_sign_negative());

Returns true if self's sign is negative, including -0.0 and NEG_INFINITY.

use std::f32;

let nan = f32::NAN;
let f = 7.0f32;
let g = -7.0f32;

assert!(!f.is_sign_negative());
assert!(g.is_sign_negative());
// Requires both tests to determine if is `NaN`.
assert!(!nan.is_sign_positive() && !nan.is_sign_negative());

Fused multiply-add. Computes (self * a) + b with only one rounding error. This produces a more accurate result with better performance than a separate multiplication operation followed by an add.

use std::f32;

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);

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

use std::f32;

let x = 2.0_f32;
let abs_difference = (x.recip() - (1.0/x)).abs();

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

Raises a number to an integer power.

Using this function is generally faster than using powf

use std::f32;

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

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

Raises a number to a floating point power.

use std::f32;

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

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

Takes the square root of a number.

Returns NaN if self is a negative number.

use std::f32;

let positive = 4.0_f32;
let negative = -4.0_f32;

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

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

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

use std::f32;

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);

Returns 2^(self).

use std::f32;

let f = 2.0f32;

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

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

Returns the natural logarithm of the number.

use std::f32;

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);

Returns the logarithm of the number with respect to an arbitrary base.

use std::f32;

let ten = 10.0f32;
let two = 2.0f32;

// log10(10) - 1 == 0
let abs_difference_10 = (ten.log(10.0) - 1.0).abs();

// log2(2) - 1 == 0
let abs_difference_2 = (two.log(2.0) - 1.0).abs();

assert!(abs_difference_10 <= f32::EPSILON);
assert!(abs_difference_2 <= f32::EPSILON);

Returns the base 2 logarithm of the number.

use std::f32;

let two = 2.0f32;

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

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

Returns the base 10 logarithm of the number.

use std::f32;

let ten = 10.0f32;

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

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

Converts radians to degrees.

use std::f32::{self, consts};

let angle = consts::PI;

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

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

Converts degrees to radians.

use std::f32::{self, consts};

let angle = 180.0f32;

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

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

Returns the maximum of the two numbers.

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

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

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);

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

Deprecated since 1.10.0

: you probably meant (self - other).abs(): this operation is (self - other).max(0.0) (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
use std::f32;

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);

Takes the cubic root of a number.

use std::f32;

let x = 8.0f32;

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

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

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

use std::f32;

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);

Computes the sine of a number (in radians).

use std::f32;

let x = f32::consts::PI/2.0;

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

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

Computes the cosine of a number (in radians).

use std::f32;

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

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

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

Computes the tangent of a number (in radians).

use std::f32;

let x = f32::consts::PI / 4.0;
let abs_difference = (x.tan() - 1.0).abs();

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

Computes the arcsine of a number. Return value is in radians in the range [-pi/2, pi/2] or NaN if the number is outside the range [-1, 1].

use std::f32;

let f = f32::consts::PI / 2.0;

// asin(sin(pi/2))
let abs_difference = (f.sin().asin() - f32::consts::PI / 2.0).abs();

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

Computes the arccosine of a number. Return value is in radians in the range [0, pi] or NaN if the number is outside the range [-1, 1].

use std::f32;

let f = f32::consts::PI / 4.0;

// acos(cos(pi/4))
let abs_difference = (f.cos().acos() - f32::consts::PI / 4.0).abs();

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

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

use std::f32;

let f = 1.0f32;

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

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

Computes the four quadrant arctangent of self (y) and other (x).

  • x = 0, y = 0: 0
  • x >= 0: arctan(y/x) -> [-pi/2, pi/2]
  • y >= 0: arctan(y/x) + pi -> (pi/2, pi]
  • y < 0: arctan(y/x) - pi -> (-pi, -pi/2)
use std::f32;

let pi = f32::consts::PI;
// All angles from horizontal right (+x)
// 45 deg counter-clockwise
let x1 = 3.0f32;
let y1 = -3.0f32;

// 135 deg clockwise
let x2 = -3.0f32;
let y2 = 3.0f32;

let abs_difference_1 = (y1.atan2(x1) - (-pi/4.0)).abs();
let abs_difference_2 = (y2.atan2(x2) - 3.0*pi/4.0).abs();

assert!(abs_difference_1 <= f32::EPSILON);
assert!(abs_difference_2 <= f32::EPSILON);

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

use std::f32;

let x = f32::consts::PI/4.0;
let f = x.sin_cos();

let abs_difference_0 = (f.0 - x.sin()).abs();
let abs_difference_1 = (f.1 - x.cos()).abs();

assert!(abs_difference_0 <= f32::EPSILON);
assert!(abs_difference_1 <= f32::EPSILON);

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

use std::f32;

let x = 6.0f32;

// e^(ln(6)) - 1
let abs_difference = (x.ln().exp_m1() - 5.0).abs();

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

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

use std::f32;

let x = f32::consts::E - 1.0;

// ln(1 + (e - 1)) == ln(e) == 1
let abs_difference = (x.ln_1p() - 1.0).abs();

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

Hyperbolic sine function.

use std::f32;

let e = 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);

Hyperbolic cosine function.

use std::f32;

let e = 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);

Hyperbolic tangent function.

use std::f32;

let e = 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);

Inverse hyperbolic sine function.

use std::f32;

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

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

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

Inverse hyperbolic cosine function.

use std::f32;

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

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

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

Inverse hyperbolic tangent function.

use std::f32;

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

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

assert!(abs_difference <= 1e-5);

🔬 This is a nightly-only experimental API. (float_bits_conv)

recently added

Raw transmutation to u32.

Converts the f32 into its raw memory representation, similar to the transmute function.

Note that this function is distinct from casting.

Examples

#![feature(float_bits_conv)]
assert_ne!((1f32).to_bits(), 1f32 as u32); // to_bits() is not casting!
assert_eq!((12.5f32).to_bits(), 0x41480000);

Trait Implementations

impl<M> Default for Float<M> where
    M: Default + FloatMapping
[src]

impl<M> AsRef<f32> for Float<M> where
    M: FloatMapping
[src]

impl<M> PartialEq<Float<M>> for Float<M> where
    M: PartialEq<M> + FloatMapping
[src]

impl<M> PartialEq<f32> for Float<M> where
    M: FloatMapping
[src]

impl<M> Serialize for Float<M> where
    M: FloatMapping
[src]

Serialize this value into the given Serde serializer. Read more

impl<'de, M> Deserialize<'de> for Float<M> where
    M: FloatMapping
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impl<M> From<f32> for Float<M> where
    M: FloatMapping
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Performs the conversion.

impl<M> Deref for Float<M> where
    M: FloatMapping
[src]

The resulting type after dereferencing

The method called to dereference a value

impl<M> FloatFieldType<M> for Float<M> where
    M: FloatMapping
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impl<M> Debug for Float<M> where
    M: Debug + FloatMapping
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Formats the value using the given formatter.

impl<M> Clone for Float<M> where
    M: Clone + FloatMapping
[src]