pub struct PopulationState<P, F> {
Show 16 fields pub individual: Option<P>, pub prev_individual: Option<P>, pub best_individual: Option<P>, pub prev_best_individual: Option<P>, pub cost: F, pub prev_cost: F, pub best_cost: F, pub prev_best_cost: F, pub target_cost: F, pub population: Option<Vec<P>>, pub iter: u64, pub last_best_iter: u64, pub max_iters: u64, pub counts: HashMap<String, u64>, pub time: Option<Duration>, pub termination_status: TerminationStatus,
}
Expand description

Maintains the state from iteration to iteration of a population-based solver

This struct is passed from one iteration of an algorithm to the next.

Keeps track of

  • individual of current and previous iteration
  • best individual of current and previous iteration
  • current and previous best cost function value
  • target cost function value
  • population (for population based algorithms)
  • current iteration number
  • iteration number where the last best individual was found
  • maximum number of iterations that will be executed
  • problem function evaluation counts
  • elapsed time
  • termination status

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§individual: Option<P>

Current individual vector

§prev_individual: Option<P>

Previous individual vector

§best_individual: Option<P>

Current best individual vector

§prev_best_individual: Option<P>

Previous best individual vector

§cost: F

Current cost function value

§prev_cost: F

Previous cost function value

§best_cost: F

Current best cost function value

§prev_best_cost: F

Previous best cost function value

§target_cost: F

Target cost function value

§population: Option<Vec<P>>

All members of the population

§iter: u64

Current iteration

§last_best_iter: u64

Iteration number of last best cost

§max_iters: u64

Maximum number of iterations

§counts: HashMap<String, u64>

Evaluation counts

§time: Option<Duration>

Time required so far

§termination_status: TerminationStatus

Status of optimization execution

Implementations§

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impl<P, F> PopulationState<P, F>
where Self: State<Float = F>, F: ArgminFloat,

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pub fn individual(self, individual: P) -> Self

Set best individual of current iteration. This shifts the stored individual to the previous individual.

Example
let state = state.individual(individual);
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pub fn cost(self, cost: F) -> Self

Set the current cost function value. This shifts the stored cost function value to the previous cost function value.

Example
let state = state.cost(cost);
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pub fn target_cost(self, target_cost: F) -> Self

Set target cost.

When this cost is reached, the algorithm will stop. The default is Self::Float::NEG_INFINITY.

Example
let state = state.target_cost(0.0);
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pub fn population(self, population: Vec<P>) -> Self

Set population.

A population is a Vec of individuals.

Example
let state = state.population(vec![individual1, individual2]);
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pub fn max_iters(self, iters: u64) -> Self

Set maximum number of iterations

Example
let state = state.max_iters(1000);
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pub fn get_cost(&self) -> F

Returns the current cost function value

Example
let cost = state.get_cost();
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pub fn get_prev_cost(&self) -> F

Returns the previous cost function value

Example
let prev_cost = state.get_prev_cost();
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pub fn get_best_cost(&self) -> F

Returns the current best cost function value

Example
let best_cost = state.get_best_cost();
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pub fn get_prev_best_cost(&self) -> F

Returns the previous best cost function value

Example
let prev_best_cost = state.get_prev_best_cost();
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pub fn get_target_cost(&self) -> F

Returns the target cost function value

Example
let target_cost = state.get_target_cost();
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pub fn take_individual(&mut self) -> Option<P>

Moves the current individual out and replaces it internally with None

Example
let individual = state.take_individual();  // Option<P>
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pub fn get_prev_individual(&self) -> Option<&P>

Returns a reference to previous individual

Example
let prev_individual = state.get_prev_individual();  // Option<&P>
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pub fn take_prev_individual(&mut self) -> Option<P>

Moves the previous individual out and replaces it internally with None

Example
let prev_individual = state.take_prev_individual();  // Option<P>
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pub fn get_prev_best_individual(&self) -> Option<&P>

Returns a reference to previous best individual

Example
let prev_best_individual = state.get_prev_best_individual();  // Option<&P>
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pub fn take_best_individual(&mut self) -> Option<P>

Moves the best individual out and replaces it internally with None

Example
let best_individual = state.take_best_individual();  // Option<P>
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pub fn take_prev_best_individual(&mut self) -> Option<P>

Moves the previous best individual out and replaces it internally with None

Example
let prev_best_individual = state.take_prev_best_individual();  // Option<P>
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pub fn get_population(&self) -> Option<&Vec<P>>

Returns a reference to the population

Example
let population = state.get_population();
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pub fn take_population(&mut self) -> Option<Vec<P>>

Takes population and replaces it internally with None.

Example
let population = state.get_population();

Trait Implementations§

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impl<P: Clone, F: Clone> Clone for PopulationState<P, F>

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fn clone(&self) -> PopulationState<P, F>

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl<P: Debug, F: Debug> Debug for PopulationState<P, F>

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

Formats the value using the given formatter. Read more
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impl<P: Default, F: Default> Default for PopulationState<P, F>

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fn default() -> PopulationState<P, F>

Returns the “default value” for a type. Read more
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impl<'de, P, F> Deserialize<'de> for PopulationState<P, F>
where P: Deserialize<'de>, F: Deserialize<'de>,

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl<P: PartialEq, F: PartialEq> PartialEq for PopulationState<P, F>

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fn eq(&self, other: &PopulationState<P, F>) -> bool

This method tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl<P, F> Serialize for PopulationState<P, F>
where P: Serialize, F: Serialize,

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more
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impl<O, P, F, R> Solver<O, PopulationState<Particle<P, F>, F>> for ParticleSwarm<P, F, R>
where O: CostFunction<Param = P, Output = F> + SyncAlias, P: Clone + SyncAlias + ArgminAdd<P, P> + ArgminSub<P, P> + ArgminMul<F, P> + ArgminZeroLike + ArgminRandom + ArgminMinMax, F: ArgminFloat, R: Rng,

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fn next_iter( &mut self, problem: &mut Problem<O>, state: PopulationState<Particle<P, F>, F> ) -> Result<(PopulationState<Particle<P, F>, F>, Option<KV>), Error>

Perform one iteration of algorithm

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const NAME: &'static str = "Particle Swarm Optimization"

Name of the solver. Mainly used in Observers.
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fn init( &mut self, problem: &mut Problem<O>, state: PopulationState<Particle<P, F>, F> ) -> Result<(PopulationState<Particle<P, F>, F>, Option<KV>), Error>

Initializes the algorithm. Read more
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fn terminate_internal(&mut self, state: &I) -> TerminationStatus

Checks whether basic termination reasons apply. Read more
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fn terminate(&mut self, _state: &I) -> TerminationStatus

Used to implement stopping criteria, in particular criteria which are not covered by (terminate_internal. Read more
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impl<P, F> State for PopulationState<P, F>
where P: Clone, F: ArgminFloat,

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type Param = P

Type of an individual

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type Float = F

Floating point precision

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fn new() -> Self

Create a new PopulationState instance

Example
let state: PopulationState<Vec<f64>, f64> = PopulationState::new();
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fn update(&mut self)

Checks if the current individual is better than the previous best individual. If a new best individual was found, the state is updated accordingly.

Example
let mut state: PopulationState<Vec<f64>, f64> = PopulationState::new();

// Simulating a new, better individual
state.best_individual = Some(vec![1.0f64]);
state.best_cost = 10.0;
state.individual = Some(vec![2.0f64]);
state.cost = 5.0;

// Calling update
state.update();

// Check if update was successful
assert_eq!(state.best_individual.as_ref().unwrap()[0], 2.0f64);
assert_eq!(state.best_cost.to_ne_bytes(), state.best_cost.to_ne_bytes());
assert!(state.is_best());

For algorithms which do not compute the cost function, every new individual will be the new best:

let mut state: PopulationState<Vec<f64>, f64> = PopulationState::new();

// Simulating a new, better individual
state.best_individual = Some(vec![1.0f64]);
state.individual = Some(vec![2.0f64]);

// Calling update
state.update();

// Check if update was successful
assert_eq!(state.best_individual.as_ref().unwrap()[0], 2.0f64);
assert_eq!(state.best_cost.to_ne_bytes(), state.best_cost.to_ne_bytes());
assert!(state.is_best());
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fn get_param(&self) -> Option<&P>

Returns a reference to the current individual

Example
let individual = state.get_param();  // Option<&P>
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fn get_best_param(&self) -> Option<&P>

Returns a reference to the current best individual

Example
let best_individual = state.get_best_param();  // Option<&P>
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fn terminate_with(self, reason: TerminationReason) -> Self

Sets the termination status to Terminated with the given reason

Example
let state = state.terminate_with(TerminationReason::MaxItersReached);
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fn time(&mut self, time: Option<Duration>) -> &mut Self

Sets the time required so far.

Example
let state = state.time(Some(instant::Duration::new(0, 12)));
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fn get_cost(&self) -> Self::Float

Returns current cost function value.

Example
let cost = state.get_cost();
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fn get_best_cost(&self) -> Self::Float

Returns current best cost function value.

Example
let best_cost = state.get_best_cost();
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fn get_target_cost(&self) -> Self::Float

Returns target cost function value.

Example
let target_cost = state.get_target_cost();
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fn get_iter(&self) -> u64

Returns current number of iterations.

Example
let iter = state.get_iter();
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fn get_last_best_iter(&self) -> u64

Returns iteration number of last best individual

Example
let last_best_iter = state.get_last_best_iter();
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fn get_max_iters(&self) -> u64

Returns the maximum number of iterations.

Example
let max_iters = state.get_max_iters();
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fn get_termination_status(&self) -> &TerminationStatus

Returns the termination reason.

Example
let termination_status = state.get_termination_status();
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fn get_termination_reason(&self) -> Option<&TerminationReason>

Returns the termination reason if terminated, otherwise None.

Example
let termination_reason = state.get_termination_reason();
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fn get_time(&self) -> Option<Duration>

Returns the time elapsed since the start of the optimization.

Example
let time = state.get_time();
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fn increment_iter(&mut self)

Increments the number of iterations by one

Example
state.increment_iter();
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fn func_counts<O>(&mut self, problem: &Problem<O>)

Set all function evaluation counts to the evaluation counts of another Problem.

state.func_counts(&problem);
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fn get_func_counts(&self) -> &HashMap<String, u64>

Returns function evaluation counts

Example
let counts = state.get_func_counts();
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fn is_best(&self) -> bool

Returns whether the current individual is also the best individual found so far.

Example
let is_best = state.is_best();
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fn terminated(&self) -> bool

Return whether the algorithm has terminated or not
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impl<P: Eq, F: Eq> Eq for PopulationState<P, F>

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impl<P, F> StructuralEq for PopulationState<P, F>

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impl<P, F> StructuralPartialEq for PopulationState<P, F>

Auto Trait Implementations§

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impl<P, F> RefUnwindSafe for PopulationState<P, F>

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impl<P, F> Send for PopulationState<P, F>
where F: Send, P: Send,

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impl<P, F> Sync for PopulationState<P, F>
where F: Sync, P: Sync,

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impl<P, F> Unpin for PopulationState<P, F>
where F: Unpin, P: Unpin,

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impl<P, F> UnwindSafe for PopulationState<P, F>
where F: UnwindSafe, P: UnwindSafe,

Blanket Implementations§

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more
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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into<U> for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> Same for T

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type Output = T

Should always be Self
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impl<SS, SP> SupersetOf<SS> for SP
where SS: SubsetOf<SP>,

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fn to_subset(&self) -> Option<SS>

The inverse inclusion map: attempts to construct self from the equivalent element of its superset. Read more
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fn is_in_subset(&self) -> bool

Checks if self is actually part of its subset T (and can be converted to it).
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fn to_subset_unchecked(&self) -> SS

Use with care! Same as self.to_subset but without any property checks. Always succeeds.
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fn from_subset(element: &SS) -> SP

The inclusion map: converts self to the equivalent element of its superset.
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impl<T> ToOwned for T
where T: Clone,

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type Owned = T

The resulting type after obtaining ownership.
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fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more
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fn clone_into(&self, target: &mut T)

Uses borrowed data to replace owned data, usually by cloning. Read more
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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.
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impl<V, T> VZip<V> for T
where V: MultiLane<T>,

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fn vzip(self) -> V

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impl<T> DeserializeOwned for T
where T: for<'de> Deserialize<'de>,

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impl<T> Scalar for T
where T: 'static + Clone + PartialEq + Debug,

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impl<T> SendAlias for T

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impl<T> SyncAlias for T