Skip to content

Commit

Permalink
Auto merge of #74621 - LukasKalbertodt:float-docs, r=GuillaumeGomez
Browse files Browse the repository at this point in the history
Improve `f32` and `f64` primitive documentation

I noticed that the docs for the primitive floats were fairly short. I first only wanted to add the IEEE specification information (compare [the reference](https://doc.rust-lang.org/reference/types/numeric.html)), but then also added some more beginner-friendly docs. Let me know what you think!

Random doc team assign:
r? @rylev
  • Loading branch information
bors committed Aug 11, 2020
2 parents 7189ca6 + e4d27fa commit a9025c5
Showing 1 changed file with 41 additions and 3 deletions.
44 changes: 41 additions & 3 deletions library/std/src/primitive_docs.rs
Original file line number Diff line number Diff line change
Expand Up @@ -764,19 +764,57 @@ mod prim_str {}
mod prim_tuple {}

#[doc(primitive = "f32")]
/// The 32-bit floating point type.
/// 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
/// (like `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`.
///
/// The precision is better for numbers near 0 and worse for large numbers. For
/// example, above 2<sup>24</sup>, not even all integers are representable.
///
/// Additionally, `f32` can represent a couple of special values:
///
/// - `-0`: this is just due to how floats are encoded. It is semantically
/// equivalent to `0` and `-0.0 == 0.0` results in `true`.
/// - [∞](#associatedconstant.INFINITY) and
/// [-∞](#associatedconstant.NEG_INFINITY): these result from calculations
/// like `1.0 / 0.0`.
/// - [NaN (not a number)](#associatedconstant.NAN): 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][wikipedia].
///
/// *[See also the `std::f32::consts` module](f32/consts/index.html).*
///
/// [wikipedia]: https://en.wikipedia.org/wiki/Single-precision_floating-point_format
#[stable(feature = "rust1", since = "1.0.0")]
mod prim_f32 {}

#[doc(primitive = "f64")]
//
/// The 64-bit floating point type.
/// A 64-bit floating point type (specifically, the "binary64" type defined in IEEE 754-2008).
///
/// This type is very similar to [`f32`](primitive.f32.html), but has increased
/// precision by using twice as many bits. Please see [the documentation for
/// `f32`](primitive.f32.html) or [Wikipedia on double precision
/// values][wikipedia] for more information.
///
/// *[See also the `std::f64::consts` module](f64/consts/index.html).*
///
/// [wikipedia]: https://en.wikipedia.org/wiki/Double-precision_floating-point_format
#[stable(feature = "rust1", since = "1.0.0")]
mod prim_f64 {}

Expand Down

0 comments on commit a9025c5

Please sign in to comment.