Struct HashCell 

pub struct HashCell<K, const D: usize>
where
    K: Eq + Hash,
{ /* private fields */ }

Bucket sort points into cubes with HashMap-backed storage

See VecCell for a complete description of the algorithm. Use VecCell for dense, bounded collections of points. Use HashMap for sparse and/or unbounded collections of points.

Examples

The default HashCell set both the nominal and maximum search radii to 1.0.

use hoomd_spatial::HashCell;

let hash_cell = HashCell::<usize, 3>::default();

Use the builder API to set any or all parameters:

use hoomd_spatial::HashCell;

let hash_cell = HashCell::<usize, 3>::builder()
    .nominal_search_radius(2.5.try_into()?)
    .maximum_search_radius(7.5)
    .build();

Implementations

impl<K, const D: usize> HashCell<K, D>

where K: Copy + Eq + Hash,

pub fn shrink_to_fit(&mut self)

Remove excess capacity from dynamically allocated arrays.

pub fn builder() -> HashCellBuilder<K, D>

Construct a HashCell builder.

Use the builder to set any or all parameters and construct a HashCell.

Example

use hoomd_spatial::HashCell;

let hash_cell = HashCell::<usize, 3>::builder()
    .nominal_search_radius(2.5.try_into()?)
    .maximum_search_radius(7.5)
    .build();

Trait Implementations

impl<K, const D: usize> Clone for HashCell<K, D>

where K: Eq + Hash + Clone,

fn clone(&self) -> HashCell<K, D>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<K, const D: usize> Debug for HashCell<K, D>

where K: Eq + Hash + Debug,

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

Formats the value using the given formatter.

impl<K, const D: usize> Default for HashCell<K, D>

where K: Copy + Eq + Hash,

fn default() -> Self

Construct a default HashCell.

The default sets both the nominal and maximum search radii to 1.0.

Example

use hoomd_spatial::HashCell;

let hash_cell = HashCell::<usize, 3>::default();

impl<'de, K, const D: usize> Deserialize<'de> for HashCell<K, D>

where K: Eq + Hash + Deserialize<'de>,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<K, const D: usize> Display for HashCell<K, D>

where K: Eq + Hash,

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

Summarize the contents of the cell list.

This is a slow operation. It is meant to be printed to logs only occasionally, such as at the end of a benchmark or simulation.

Example

use hoomd_spatial::HashCell;
use log::info;

let vec_cell = HashCell::<usize, 3>::default();

info!("{vec_cell}");

impl<K, const D: usize> PointUpdate<Cartesian<D>, K> for HashCell<K, D>

where K: Copy + Eq + Hash,

fn insert(&mut self, key: K, position: Cartesian<D>)

Insert or update a point identified by a key.

Example

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();

hash_cell.insert(0, [1.25, 2.5].into());

fn remove(&mut self, key: &K)

Remove the point with the given key.

Example

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();
hash_cell.insert(0, [1.25, 2.5].into());

hash_cell.remove(&0)

fn len(&self) -> usize

Get the number of points in the spatial data structure.

Example

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();
hash_cell.insert(0, [1.25, 2.5].into());

assert_eq!(hash_cell.len(), 1)

fn is_empty(&self) -> bool

Test if the spatial data structure is empty.

Example

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();

assert!(hash_cell.is_empty());

fn contains_key(&self, key: &K) -> bool

Test if the spatial data structure contains a key.

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();
hash_cell.insert(0, [1.25, 2.5].into());

assert!(hash_cell.contains_key(&0));

fn clear(&mut self)

Remove all points.

Example

use hoomd_spatial::{HashCell, PointUpdate};

let mut hash_cell = HashCell::default();
hash_cell.insert(0, [1.25, 2.5].into());

hash_cell.clear();

impl<const D: usize, K> PointsNearBall<Cartesian<D>, K> for HashCell<K, D>

where K: Copy + Eq + Hash,

fn points_near_ball( &self, position: &Cartesian<D>, radius: f64, ) -> impl Iterator<Item = K>

Find all the points that might be in the given ball.

points_near_ball will iterate over all points in the given ball and possibly others as well. HashCell may iterate over the points in any order.

Example

use hoomd_spatial::{HashCell, PointUpdate, PointsNearBall};

let mut hash_cell = HashCell::default();
hash_cell.insert(0, [1.25, 0.0].into());
hash_cell.insert(1, [3.25, 0.75].into());
hash_cell.insert(2, [-10.0, 12.0].into());

for key in hash_cell.points_near_ball(&[2.0, 0.0].into(), 1.0) {
    println!("{key}");
}

Prints (in any order):

0
1

Panics

Panics when radius is larger than the maximum search radius provided at construction, rounded up to the nearest integer multiple of the nominal search radius.

fn is_all_pairs() -> bool

Is this spatial data structures AllPairs?

impl<K, const D: usize> Serialize for HashCell<K, D>

where K: Eq + Hash + Serialize,

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl<K, const D: usize> WithSearchRadius for HashCell<K, D>

where K: Copy + Eq + Hash,

fn with_search_radius(radius: PositiveReal) -> Self

Construct a HashCell with the given search radius.

Set both the nominal and maximum search radii to radius.

Example

use hoomd_spatial::{HashCell, WithSearchRadius};

let hash_cell = HashCell::<usize, 3>::with_search_radius(2.5.try_into()?);