Struct weird_data::Wdg

pub struct Wdg(/* private fields */);

A weird data generator

Implementations

impl Wdg

pub fn new() -> Self

Create a new Wdg by forking the global Wdg.

If you want to control the initial seed, use [with_seed] instead.

impl Wdg

pub fn with_seed(seed: u64) -> Self

pub fn fork(&mut self) -> Self

pub fn seed(&mut self, seed: u64)

pub fn get_seed(&mut self) -> u64

pub fn nan_f32(&mut self) -> f32

Generates a random f32 NAN value.

There are multiple bit patterns that are equivalent to a NAN. This generator covers all possible NAN values as specified in IEEE-754, even ones that Rust would normally not generate.

pub fn nan_f64(&mut self) -> f64

Generates a random f64 NAN value.

There are multiple bit patterns that are equivalent to a NAN. This generator covers all possible NAN values as specified in IEEE-754, even ones that Rust would normally not generate.

pub fn subnormal_f32(&mut self) -> f32

Generates a random f32 denormal value.

This generator covers all possible denormal values as specified in IEEE-754.

pub fn subnormal_f64(&mut self) -> f64

Generates a random f64 denormal value.

This generator covers all possible denormal values as specified in IEEE-754.

pub fn normal_f32(&mut self) -> f32

Generate a random f32 normal value

pub fn normal_f64(&mut self) -> f64

Generate a random f64 normal value

pub fn special_f32(&mut self) -> f32

Generate a random f32 “special” value

A special value is what I call specific float values that are unique and are pretty much impossible to generate by chance, and have some unusual properties.

pub fn special_f64(&mut self) -> f64

Generate a random f64 “special” value

A special value is what I call specific float values that are unique and are pretty much impossible to generate by chance, and have some unusual properties.

pub fn f32(&mut self) -> f32

Generate a random f32, such that special or problematic values are much more common than normal.

The distribution is not statistically useful, but it ensures that all edge-case values get a fair chance of being generated. This is better than using a regular random number generator, because in the vast majority of cases, a random number generator will generate perfectly regular and well-behaved values, and certain values, like INFINITY and NAN may be impossible to generate.

The distribution is as follows:

• 25% normal values
• 25% subnormal values
• 25% NAN values, including all possible payloads, quiet and signaling NAN.
• 25% “special” values, i.e. unique values with special properties such as INFINITY and -0.0

pub fn f64(&mut self) -> f64

Generate a random f64, such that special or problematic values are much more common than normal.

The distribution is not statistically useful, but it ensures that all edge-case values get a fair chance of being generated. This is better than using a regular random number generator, because in the vast majority of cases, a random number generator will generate perfectly regular and well-behaved values, and certain values, like INFINITY and NAN may be impossible to generate.

The distribution is as follows:

• 25% normal values
• 25% subnormal values
• 25% NAN values, including all possible payloads, quiet and signaling NAN.
• 25% “special” values, i.e. unique values with special properties such as INFINITY and -0.0

Trait Implementations

impl Clone for Wdg

fn clone(&self) -> Wdg

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Default for Wdg

fn default() -> Self

Returns the “default value” for a type.