Struct ConvergenceLoss 

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

Distance to crystal. Zero means crystallized. Combine takes the max (the furthest from crystal dominates).

Implementations

impl ConvergenceLoss

pub fn new(steps: usize) -> Self

Create a new ConvergenceLoss with the given number of steps from crystal.

pub fn steps(&self) -> usize

The number of steps remaining to reach crystal (convergence).

Trait Implementations

impl Clone for ConvergenceLoss

fn clone(&self) -> ConvergenceLoss

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ConvergenceLoss

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

Formats the value using the given formatter.

impl Default for ConvergenceLoss

fn default() -> Self

Returns the “default value” for a type.

impl Display for ConvergenceLoss

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

Formats the value using the given formatter.

impl Loss for ConvergenceLoss

fn zero() -> Self

The identity: no loss occurred. combine(zero(), x) == x.

fn total() -> Self

Total loss: the transformation destroyed everything. Acts as an absorbing element under combine.

fn is_zero(&self) -> bool

Whether this loss is zero (lossless).

fn combine(self, other: Self) -> Self

Accumulate two losses. Associative: a.combine(b).combine(c) == a.combine(b.combine(c)).

impl PartialEq for ConvergenceLoss

fn eq(&self, other: &ConvergenceLoss) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Eq for ConvergenceLoss

impl StructuralPartialEq for ConvergenceLoss