Struct Fpie 

pub struct Fpie {
    pub iterations: usize,
    pub object_step: f64,
    pub stability: f64,
    pub batch_size: usize,
    pub epsilon: f64,
    pub loss_type: LossType,
}

Regularized ptychographic iterative-engine reconstruction adapted to FPM.

Method

Fpie performs the same detector-amplitude projection as super::AlternatingProjection, but preconditions each object correction with the rPIE denominator (1 - stability) * |pupil|^2 + stability * max(|pupil|^2). This blends local inverse-pupil weighting with a global power bound, reducing unstable updates where the pupil transfer is weak. The corrected low-resolution spectrum is inserted into the corresponding overlapping patch of the high-resolution object spectrum.

This crate adapts the rPIE update, originally formulated for scanned ptychography, to image-plane Fourier ptychography.

Reference

A. Maiden, D. Johnson, and P. Li, “Further improvements to the ptychographical iterative engine” (2017), Optica 4(7), 736–745.

Fields

iterations: usize

Number of complete passes through the acquisition schedule.

object_step: f64

Relaxation factor applied to each object-spectrum correction.

stability: f64

Blend between local pupil power (0) and maximum pupil power (1) in the rPIE denominator.

batch_size: usize

Number of measured frames supplied to each reconstruction step.

epsilon: f64

Positive numerical floor added to the rPIE denominator.

loss_type: LossType

Loss used for diagnostics; the projection itself always enforces the measured amplitude.

Implementations

impl Fpie

pub fn iterations(self, iterations: usize) -> Self

Sets the number of complete acquisition-schedule passes; validation requires non-zero.

pub fn object_step(self, step: f64) -> Self

Sets the finite positive relaxation applied to object-spectrum corrections.

pub fn stability(self, stability: f64) -> Self

Sets the rPIE pupil-power blend after clamping the value to [0, 1].

Trait Implementations

impl Clone for Fpie

fn clone(&self) -> Fpie

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Fpie

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

Formats the value using the given formatter.

impl Default for Fpie

fn default() -> Self

Returns the “default value” for a type.

impl ReconstructionAlgorithm for Fpie

type IterationMetrics = NoIterationMetrics

Algorithm-specific metrics emitted by each step and appended to the trace.

fn validate(&self) -> Result<()>

Validates solver parameters independently of a reconstruction problem.

fn step<M: MeasurementRead>( &mut self, problem: &ReconstructionProblem<M>, state: &mut ReconstructionState, batch: &Batch, _iteration: usize, ) -> Result<StepOutput<Self::IterationMetrics>>

Updates state for one scheduled batch in zero-based iteration.

fn iterations(&self) -> usize

Returns the requested number of complete schedule passes.

fn batch_size(&self) -> usize

Returns the number of measured frames combined into one step.

fn validate_problem<M: MeasurementRead>( &self, _problem: &ReconstructionProblem<M>, ) -> Result<()>

Validates solver requirements that depend on problem.

fn initialize<M: MeasurementRead>( &self, problem: &ReconstructionProblem<M>, ) -> Result<ReconstructionState>

Creates the default CPU-backed state for problem.

fn initialize_with_backend<M: MeasurementRead>( &self, problem: &ReconstructionProblem<M>, backend: Arc<dyn Backend>, ) -> Result<ReconstructionState>

Creates reconstruction state using the supplied execution backend.

fn canonicalize_state<M: MeasurementRead>( &self, _problem: &ReconstructionProblem<M>, _state: &mut ReconstructionState, ) -> Result<()>

Projects algorithm-owned ambiguities into a stable reported convention.

fn supports_joint_reconstruction(&self) -> bool

Reports whether the algorithm may run inside physical joint calibration.

fn run<M: MeasurementRead>( self, problem: &ReconstructionProblem<M>, ) -> Result<ReconstructionResult>

where Self: Sized,

Runs the algorithm with default sequential scheduling and no callbacks.

fn run_with_callbacks<M: MeasurementRead>( self, problem: &ReconstructionProblem<M>, callbacks: Vec<Box<dyn Callback>>, ) -> Result<ReconstructionResult>

where Self: Sized,

Runs the algorithm and invokes callbacks at their declared hooks.

fn run_from_checkpoint<M: MeasurementRead>( self, problem: &ReconstructionProblem<M>, checkpoint: ReconstructionCheckpoint, ) -> Result<ReconstructionResult>

where Self: Sized,

Resumes a run from a checkpoint after validating it against problem.