Struct proptest::num::f64::Any

#[must_use = "strategies do nothing unless used"]pub struct Any(_);

Strategies which produce floating-point values from particular classes. See the various Any-typed constants in this module.

Note that this usage is fairly advanced and primarily useful to implementors of algorithms that need to handle wild values in a particular way. For testing things like graphics processing or game physics, simply using ranges (e.g., -1.0..2.0) will often be more practical.

Any can be OR'ed to combine multiple classes. For example, POSITIVE | INFINITE will generate arbitrary positive, non-NaN floats, including positive infinity (but not negative infinity, of course).

If neither POSITIVE nor NEGATIVE has been OR'ed into an Any but a type to be generated requires a sign, POSITIVE is assumed. If no classes are OR'ed into an Any (i.e., only POSITIVE and/or NEGATIVE are given), NORMAL is assumed.

The various float classes are assigned fixed weights for generation which are believed to be reasonable for most applications. Roughly:

• If POSITIVE | NEGATIVE, the sign is evenly distributed between both options.

• Classes are weighted as follows, in descending order: NORMAL > ZERO > SUBNORMAL > INFINITE > QUIET_NAN = SIGNALING_NAN.

Trait Implementations

impl BitOr<Any> for Any

type Output = Self

The resulting type after applying the | operator.

fn bitor(self, rhs: Self) -> Self

Performs the | operation.

impl BitOrAssign<Any> for Any

fn bitor_assign(&mut self, rhs: Self)

Performs the |= operation.

impl Clone for Any

fn clone(&self) -> Any

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Copy for Any

impl Debug for Any

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Strategy for Any

type Tree = BinarySearch

The value tree generated by this Strategy.

type Value = f64

The type of value used by functions under test generated by this Strategy.

fn new_tree(&self, runner: &mut TestRunner) -> NewTree<Self>

Generate a new value tree from the given runner.

fn prop_map<O: Debug, F: Fn(Self::Value) -> O>(self, fun: F) -> Map<Self, F> where
    Self: Sized, 

Returns a strategy which produces values transformed by the function fun.

fn prop_map_into<O: Debug>(self) -> MapInto<Self, O> where
    Self: Sized,
    Self::Value: Into<O>, 

Returns a strategy which produces values of type O by transforming Self with Into<O>.

fn prop_perturb<O: Debug, F: Fn(Self::Value, TestRng) -> O>(
    self,
    fun: F
) -> Perturb<Self, F> where
    Self: Sized, 

Returns a strategy which produces values transformed by the function fun, which is additionally given a random number generator.

fn prop_flat_map<S: Strategy, F: Fn(Self::Value) -> S>(
    self,
    fun: F
) -> Flatten<Map<Self, F>> where
    Self: Sized, 

Maps values produced by this strategy into new strategies and picks values from those strategies.

fn prop_ind_flat_map<S: Strategy, F: Fn(Self::Value) -> S>(
    self,
    fun: F
) -> IndFlatten<Map<Self, F>> where
    Self: Sized, 

Maps values produced by this strategy into new strategies and picks values from those strategies while considering the new strategies to be independent.

fn prop_ind_flat_map2<S: Strategy, F: Fn(Self::Value) -> S>(
    self,
    fun: F
) -> IndFlattenMap<Self, F> where
    Self: Sized, 

Similar to prop_ind_flat_map(), but produces 2-tuples with the input generated from self in slot 0 and the derived strategy in slot 1.

fn prop_filter<R: Into<Reason>, F: Fn(&Self::Value) -> bool>(
    self,
    whence: R,
    fun: F
) -> Filter<Self, F> where
    Self: Sized, 

Returns a strategy which only produces values accepted by fun.

fn prop_filter_map<F: Fn(Self::Value) -> Option<O>, O: Debug>(
    self,
    whence: impl Into<Reason>,
    fun: F
) -> FilterMap<Self, F> where
    Self: Sized, 

Returns a strategy which only produces transformed values where fun returns Some(value) and rejects those where fun returns None.

fn prop_union(self, other: Self) -> Union<Self> where
    Self: Sized, 

Returns a strategy which picks uniformly from self and other.

fn prop_recursive<R: Strategy<Value = Self::Value> + 'static, F: Fn(BoxedStrategy<Self::Value>) -> R>(
    self,
    depth: u32,
    desired_size: u32,
    expected_branch_size: u32,
    recurse: F
) -> Recursive<Self::Value, F> where
    Self: Sized + 'static, 

Generate a recursive structure with self items as leaves.

fn prop_shuffle(self) -> Shuffle<Self> where
    Self: Sized,
    Self::Value: Shuffleable, 

Shuffle the contents of the values produced by this strategy.

fn boxed(self) -> BoxedStrategy<Self::Value> where
    Self: Sized + 'static, 

Erases the type of this Strategy so it can be passed around as a simple trait object.

fn sboxed(self) -> SBoxedStrategy<Self::Value> where
    Self: Sized + Send + Sync + 'static, 

Erases the type of this Strategy so it can be passed around as a simple trait object.

fn no_shrink(self) -> NoShrink<Self> where
    Self: Sized, 

Wraps this strategy to prevent values from being subject to shrinking.