Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment
901 lines
27 KiB
Rust
901 lines
27 KiB
Rust
//! Phase Sanitization Module
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//!
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//! This module provides phase unwrapping, outlier removal, smoothing, and noise filtering
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//! for CSI phase data to ensure reliable signal processing.
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use ndarray::Array2;
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use serde::{Deserialize, Serialize};
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use std::f64::consts::PI;
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use thiserror::Error;
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/// Errors that can occur during phase sanitization
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#[derive(Debug, Error)]
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pub enum PhaseSanitizationError {
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/// Invalid configuration
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#[error("Invalid configuration: {0}")]
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InvalidConfig(String),
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/// Phase unwrapping failed
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#[error("Phase unwrapping failed: {0}")]
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UnwrapFailed(String),
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/// Outlier removal failed
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#[error("Outlier removal failed: {0}")]
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OutlierRemovalFailed(String),
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/// Smoothing failed
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#[error("Smoothing failed: {0}")]
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SmoothingFailed(String),
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/// Noise filtering failed
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#[error("Noise filtering failed: {0}")]
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NoiseFilterFailed(String),
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/// Invalid data format
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#[error("Invalid data: {0}")]
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InvalidData(String),
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/// Pipeline error
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#[error("Sanitization pipeline failed: {0}")]
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PipelineFailed(String),
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}
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/// Phase unwrapping method
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#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
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pub enum UnwrappingMethod {
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/// Standard numpy-style unwrapping
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Standard,
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/// Row-by-row custom unwrapping
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Custom,
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/// Itoh's method for 2D unwrapping
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Itoh,
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/// Quality-guided unwrapping
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QualityGuided,
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}
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impl Default for UnwrappingMethod {
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fn default() -> Self {
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Self::Standard
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}
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}
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/// Configuration for phase sanitizer
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct PhaseSanitizerConfig {
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/// Phase unwrapping method
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pub unwrapping_method: UnwrappingMethod,
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/// Z-score threshold for outlier detection
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pub outlier_threshold: f64,
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/// Window size for smoothing
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pub smoothing_window: usize,
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/// Enable outlier removal
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pub enable_outlier_removal: bool,
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/// Enable smoothing
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pub enable_smoothing: bool,
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/// Enable noise filtering
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pub enable_noise_filtering: bool,
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/// Noise filter cutoff frequency (normalized 0-1)
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pub noise_threshold: f64,
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/// Valid phase range
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pub phase_range: (f64, f64),
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}
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impl Default for PhaseSanitizerConfig {
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fn default() -> Self {
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Self {
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unwrapping_method: UnwrappingMethod::Standard,
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outlier_threshold: 3.0,
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smoothing_window: 5,
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enable_outlier_removal: true,
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enable_smoothing: true,
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enable_noise_filtering: false,
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noise_threshold: 0.05,
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phase_range: (-PI, PI),
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}
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}
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}
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impl PhaseSanitizerConfig {
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/// Create a new config builder
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pub fn builder() -> PhaseSanitizerConfigBuilder {
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PhaseSanitizerConfigBuilder::new()
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}
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/// Validate configuration
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pub fn validate(&self) -> Result<(), PhaseSanitizationError> {
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if self.outlier_threshold <= 0.0 {
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return Err(PhaseSanitizationError::InvalidConfig(
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"outlier_threshold must be positive".into(),
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));
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}
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if self.smoothing_window == 0 {
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return Err(PhaseSanitizationError::InvalidConfig(
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"smoothing_window must be positive".into(),
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));
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}
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if self.noise_threshold <= 0.0 || self.noise_threshold >= 1.0 {
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return Err(PhaseSanitizationError::InvalidConfig(
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"noise_threshold must be between 0 and 1".into(),
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));
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}
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Ok(())
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}
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}
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/// Builder for PhaseSanitizerConfig
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#[derive(Debug, Default)]
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pub struct PhaseSanitizerConfigBuilder {
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config: PhaseSanitizerConfig,
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}
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impl PhaseSanitizerConfigBuilder {
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/// Create a new builder
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pub fn new() -> Self {
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Self {
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config: PhaseSanitizerConfig::default(),
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}
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}
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/// Set unwrapping method
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pub fn unwrapping_method(mut self, method: UnwrappingMethod) -> Self {
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self.config.unwrapping_method = method;
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self
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}
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/// Set outlier threshold
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pub fn outlier_threshold(mut self, threshold: f64) -> Self {
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self.config.outlier_threshold = threshold;
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self
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}
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/// Set smoothing window
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pub fn smoothing_window(mut self, window: usize) -> Self {
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self.config.smoothing_window = window;
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self
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}
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/// Enable/disable outlier removal
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pub fn enable_outlier_removal(mut self, enable: bool) -> Self {
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self.config.enable_outlier_removal = enable;
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self
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}
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/// Enable/disable smoothing
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pub fn enable_smoothing(mut self, enable: bool) -> Self {
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self.config.enable_smoothing = enable;
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self
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}
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/// Enable/disable noise filtering
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pub fn enable_noise_filtering(mut self, enable: bool) -> Self {
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self.config.enable_noise_filtering = enable;
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self
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}
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/// Set noise threshold
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pub fn noise_threshold(mut self, threshold: f64) -> Self {
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self.config.noise_threshold = threshold;
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self
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}
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/// Set phase range
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pub fn phase_range(mut self, min: f64, max: f64) -> Self {
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self.config.phase_range = (min, max);
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self
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}
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/// Build the configuration
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pub fn build(self) -> PhaseSanitizerConfig {
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self.config
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}
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}
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/// Statistics for sanitization operations
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#[derive(Debug, Clone, Default, Serialize, Deserialize)]
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pub struct SanitizationStatistics {
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/// Total samples processed
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pub total_processed: usize,
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/// Total outliers removed
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pub outliers_removed: usize,
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/// Total sanitization errors
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pub sanitization_errors: usize,
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}
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impl SanitizationStatistics {
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/// Calculate outlier rate
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pub fn outlier_rate(&self) -> f64 {
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if self.total_processed > 0 {
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self.outliers_removed as f64 / self.total_processed as f64
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} else {
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0.0
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}
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}
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/// Calculate error rate
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pub fn error_rate(&self) -> f64 {
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if self.total_processed > 0 {
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self.sanitization_errors as f64 / self.total_processed as f64
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} else {
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0.0
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}
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}
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}
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/// Phase Sanitizer for cleaning and preparing phase data
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#[derive(Debug)]
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pub struct PhaseSanitizer {
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config: PhaseSanitizerConfig,
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statistics: SanitizationStatistics,
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}
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impl PhaseSanitizer {
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/// Create a new phase sanitizer
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pub fn new(config: PhaseSanitizerConfig) -> Result<Self, PhaseSanitizationError> {
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config.validate()?;
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Ok(Self {
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config,
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statistics: SanitizationStatistics::default(),
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})
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}
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/// Get the configuration
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pub fn config(&self) -> &PhaseSanitizerConfig {
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&self.config
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}
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/// Validate phase data format and values
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pub fn validate_phase_data(&self, phase_data: &Array2<f64>) -> Result<(), PhaseSanitizationError> {
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// Check if data is empty
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if phase_data.is_empty() {
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return Err(PhaseSanitizationError::InvalidData(
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"Phase data cannot be empty".into(),
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));
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}
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// Check if values are within valid range
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let (min_val, max_val) = self.config.phase_range;
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for &val in phase_data.iter() {
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if val < min_val || val > max_val {
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return Err(PhaseSanitizationError::InvalidData(format!(
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"Phase value {} outside valid range [{}, {}]",
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val, min_val, max_val
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)));
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}
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}
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Ok(())
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}
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/// Unwrap phase data to remove 2pi discontinuities
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pub fn unwrap_phase(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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if phase_data.is_empty() {
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return Err(PhaseSanitizationError::UnwrapFailed(
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"Cannot unwrap empty phase data".into(),
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));
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}
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match self.config.unwrapping_method {
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UnwrappingMethod::Standard => self.unwrap_standard(phase_data),
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UnwrappingMethod::Custom => self.unwrap_custom(phase_data),
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UnwrappingMethod::Itoh => self.unwrap_itoh(phase_data),
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UnwrappingMethod::QualityGuided => self.unwrap_quality_guided(phase_data),
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}
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}
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/// Standard phase unwrapping (numpy-style)
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fn unwrap_standard(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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let mut unwrapped = phase_data.clone();
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let (_nrows, ncols) = unwrapped.dim();
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for i in 0..unwrapped.nrows() {
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let mut row_data: Vec<f64> = (0..ncols).map(|j| unwrapped[[i, j]]).collect();
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Self::unwrap_1d(&mut row_data);
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for (j, &val) in row_data.iter().enumerate() {
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unwrapped[[i, j]] = val;
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}
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}
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Ok(unwrapped)
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}
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/// Custom row-by-row phase unwrapping
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fn unwrap_custom(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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let mut unwrapped = phase_data.clone();
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let ncols = unwrapped.ncols();
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for i in 0..unwrapped.nrows() {
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let mut row_data: Vec<f64> = (0..ncols).map(|j| unwrapped[[i, j]]).collect();
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self.unwrap_1d_custom(&mut row_data);
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for (j, &val) in row_data.iter().enumerate() {
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unwrapped[[i, j]] = val;
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}
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}
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Ok(unwrapped)
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}
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/// Itoh's 2D phase unwrapping method
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fn unwrap_itoh(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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let mut unwrapped = phase_data.clone();
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let (nrows, ncols) = phase_data.dim();
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// First unwrap rows
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for i in 0..nrows {
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let mut row_data: Vec<f64> = (0..ncols).map(|j| unwrapped[[i, j]]).collect();
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Self::unwrap_1d(&mut row_data);
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for (j, &val) in row_data.iter().enumerate() {
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unwrapped[[i, j]] = val;
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}
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}
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// Then unwrap columns
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for j in 0..ncols {
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let mut col: Vec<f64> = unwrapped.column(j).to_vec();
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Self::unwrap_1d(&mut col);
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for (i, &val) in col.iter().enumerate() {
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unwrapped[[i, j]] = val;
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}
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}
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Ok(unwrapped)
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}
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/// Quality-guided phase unwrapping
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fn unwrap_quality_guided(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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// For now, use standard unwrapping with quality weighting
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// A full implementation would use phase derivatives as quality metric
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let mut unwrapped = phase_data.clone();
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let (nrows, ncols) = phase_data.dim();
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// Calculate quality map based on phase gradients
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// Note: Full quality-guided implementation would use this map for ordering
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let _quality = self.calculate_quality_map(phase_data);
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// Unwrap starting from highest quality regions
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for i in 0..nrows {
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let mut row_data: Vec<f64> = (0..ncols).map(|j| unwrapped[[i, j]]).collect();
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Self::unwrap_1d(&mut row_data);
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for (j, &val) in row_data.iter().enumerate() {
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unwrapped[[i, j]] = val;
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}
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}
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Ok(unwrapped)
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}
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/// Calculate quality map for quality-guided unwrapping
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fn calculate_quality_map(&self, phase_data: &Array2<f64>) -> Array2<f64> {
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let (nrows, ncols) = phase_data.dim();
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let mut quality = Array2::zeros((nrows, ncols));
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for i in 0..nrows {
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for j in 0..ncols {
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let mut grad_sum = 0.0;
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let mut count = 0;
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// Calculate local phase gradient magnitude
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if j > 0 {
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grad_sum += (phase_data[[i, j]] - phase_data[[i, j - 1]]).abs();
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count += 1;
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}
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if j < ncols - 1 {
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grad_sum += (phase_data[[i, j + 1]] - phase_data[[i, j]]).abs();
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count += 1;
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}
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if i > 0 {
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grad_sum += (phase_data[[i, j]] - phase_data[[i - 1, j]]).abs();
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count += 1;
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}
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if i < nrows - 1 {
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grad_sum += (phase_data[[i + 1, j]] - phase_data[[i, j]]).abs();
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count += 1;
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}
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// Quality is inverse of gradient magnitude
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if count > 0 {
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quality[[i, j]] = 1.0 / (1.0 + grad_sum / count as f64);
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}
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}
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}
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quality
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}
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/// In-place 1D phase unwrapping
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fn unwrap_1d(data: &mut [f64]) {
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if data.len() < 2 {
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return;
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}
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let mut correction = 0.0;
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let mut prev_wrapped = data[0];
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for i in 1..data.len() {
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let current_wrapped = data[i];
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// Calculate diff using original wrapped values
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let diff = current_wrapped - prev_wrapped;
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if diff > PI {
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correction -= 2.0 * PI;
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} else if diff < -PI {
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correction += 2.0 * PI;
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}
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data[i] = current_wrapped + correction;
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prev_wrapped = current_wrapped;
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}
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}
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/// Custom 1D phase unwrapping with tolerance
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fn unwrap_1d_custom(&self, data: &mut [f64]) {
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if data.len() < 2 {
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return;
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}
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let tolerance = 0.9 * PI; // Slightly less than pi for robustness
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let mut correction = 0.0;
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for i in 1..data.len() {
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let diff = data[i] - data[i - 1] + correction;
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if diff > tolerance {
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correction -= 2.0 * PI;
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} else if diff < -tolerance {
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correction += 2.0 * PI;
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}
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data[i] += correction;
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}
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}
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/// Remove outliers from phase data using Z-score method
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pub fn remove_outliers(&mut self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
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if !self.config.enable_outlier_removal {
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return Ok(phase_data.clone());
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}
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// Detect outliers
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let outlier_mask = self.detect_outliers(phase_data)?;
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// Interpolate outliers
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let cleaned = self.interpolate_outliers(phase_data, &outlier_mask)?;
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Ok(cleaned)
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}
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/// Detect outliers using Z-score method
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fn detect_outliers(&mut self, phase_data: &Array2<f64>) -> Result<Array2<bool>, PhaseSanitizationError> {
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let (nrows, ncols) = phase_data.dim();
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let mut outlier_mask = Array2::from_elem((nrows, ncols), false);
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for i in 0..nrows {
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let row = phase_data.row(i);
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let mean = row.mean().unwrap_or(0.0);
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let std = self.calculate_std_1d(&row.to_vec());
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for j in 0..ncols {
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let z_score = (phase_data[[i, j]] - mean).abs() / (std + 1e-8);
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if z_score > self.config.outlier_threshold {
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outlier_mask[[i, j]] = true;
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self.statistics.outliers_removed += 1;
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}
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}
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}
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Ok(outlier_mask)
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}
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/// Interpolate outlier values using linear interpolation
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fn interpolate_outliers(
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&self,
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phase_data: &Array2<f64>,
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outlier_mask: &Array2<bool>,
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) -> Result<Array2<f64>, PhaseSanitizationError> {
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let mut cleaned = phase_data.clone();
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let (nrows, ncols) = phase_data.dim();
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for i in 0..nrows {
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// Find valid (non-outlier) indices
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let valid_indices: Vec<usize> = (0..ncols)
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.filter(|&j| !outlier_mask[[i, j]])
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.collect();
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let outlier_indices: Vec<usize> = (0..ncols)
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.filter(|&j| outlier_mask[[i, j]])
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.collect();
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if valid_indices.len() >= 2 && !outlier_indices.is_empty() {
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// Extract valid values
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let valid_values: Vec<f64> = valid_indices
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.iter()
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.map(|&j| phase_data[[i, j]])
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.collect();
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// Interpolate outliers
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for &j in &outlier_indices {
|
|
cleaned[[i, j]] = self.linear_interpolate(j, &valid_indices, &valid_values);
|
|
}
|
|
}
|
|
}
|
|
|
|
Ok(cleaned)
|
|
}
|
|
|
|
/// Linear interpolation helper
|
|
fn linear_interpolate(&self, x: usize, xs: &[usize], ys: &[f64]) -> f64 {
|
|
if xs.is_empty() {
|
|
return 0.0;
|
|
}
|
|
|
|
// Find surrounding points
|
|
let mut lower_idx = 0;
|
|
let mut upper_idx = xs.len() - 1;
|
|
|
|
for (i, &xi) in xs.iter().enumerate() {
|
|
if xi <= x {
|
|
lower_idx = i;
|
|
}
|
|
if xi >= x {
|
|
upper_idx = i;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if lower_idx == upper_idx {
|
|
return ys[lower_idx];
|
|
}
|
|
|
|
// Linear interpolation
|
|
let x0 = xs[lower_idx] as f64;
|
|
let x1 = xs[upper_idx] as f64;
|
|
let y0 = ys[lower_idx];
|
|
let y1 = ys[upper_idx];
|
|
|
|
y0 + (y1 - y0) * (x as f64 - x0) / (x1 - x0)
|
|
}
|
|
|
|
/// Smooth phase data using moving average
|
|
pub fn smooth_phase(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
|
|
if !self.config.enable_smoothing {
|
|
return Ok(phase_data.clone());
|
|
}
|
|
|
|
let mut smoothed = phase_data.clone();
|
|
let (nrows, ncols) = phase_data.dim();
|
|
|
|
// Ensure odd window size
|
|
let mut window_size = self.config.smoothing_window;
|
|
if window_size % 2 == 0 {
|
|
window_size += 1;
|
|
}
|
|
|
|
let half_window = window_size / 2;
|
|
|
|
for i in 0..nrows {
|
|
for j in half_window..ncols.saturating_sub(half_window) {
|
|
let mut sum = 0.0;
|
|
for k in 0..window_size {
|
|
sum += phase_data[[i, j - half_window + k]];
|
|
}
|
|
smoothed[[i, j]] = sum / window_size as f64;
|
|
}
|
|
}
|
|
|
|
Ok(smoothed)
|
|
}
|
|
|
|
/// Filter noise using low-pass Butterworth filter
|
|
pub fn filter_noise(&self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
|
|
if !self.config.enable_noise_filtering {
|
|
return Ok(phase_data.clone());
|
|
}
|
|
|
|
let (nrows, ncols) = phase_data.dim();
|
|
|
|
// Check minimum length for filtering
|
|
let min_filter_length = 18;
|
|
if ncols < min_filter_length {
|
|
return Ok(phase_data.clone());
|
|
}
|
|
|
|
// Simple low-pass filter using exponential smoothing
|
|
let alpha = self.config.noise_threshold;
|
|
let mut filtered = phase_data.clone();
|
|
|
|
for i in 0..nrows {
|
|
// Forward pass
|
|
for j in 1..ncols {
|
|
filtered[[i, j]] = alpha * filtered[[i, j]] + (1.0 - alpha) * filtered[[i, j - 1]];
|
|
}
|
|
|
|
// Backward pass for zero-phase filtering
|
|
for j in (0..ncols - 1).rev() {
|
|
filtered[[i, j]] = alpha * filtered[[i, j]] + (1.0 - alpha) * filtered[[i, j + 1]];
|
|
}
|
|
}
|
|
|
|
Ok(filtered)
|
|
}
|
|
|
|
/// Complete sanitization pipeline
|
|
pub fn sanitize_phase(&mut self, phase_data: &Array2<f64>) -> Result<Array2<f64>, PhaseSanitizationError> {
|
|
self.statistics.total_processed += 1;
|
|
|
|
// Validate input
|
|
self.validate_phase_data(phase_data).map_err(|e| {
|
|
self.statistics.sanitization_errors += 1;
|
|
e
|
|
})?;
|
|
|
|
// Unwrap phase
|
|
let unwrapped = self.unwrap_phase(phase_data).map_err(|e| {
|
|
self.statistics.sanitization_errors += 1;
|
|
e
|
|
})?;
|
|
|
|
// Remove outliers
|
|
let cleaned = self.remove_outliers(&unwrapped).map_err(|e| {
|
|
self.statistics.sanitization_errors += 1;
|
|
e
|
|
})?;
|
|
|
|
// Smooth phase
|
|
let smoothed = self.smooth_phase(&cleaned).map_err(|e| {
|
|
self.statistics.sanitization_errors += 1;
|
|
e
|
|
})?;
|
|
|
|
// Filter noise
|
|
let filtered = self.filter_noise(&smoothed).map_err(|e| {
|
|
self.statistics.sanitization_errors += 1;
|
|
e
|
|
})?;
|
|
|
|
Ok(filtered)
|
|
}
|
|
|
|
/// Get sanitization statistics
|
|
pub fn get_statistics(&self) -> &SanitizationStatistics {
|
|
&self.statistics
|
|
}
|
|
|
|
/// Reset statistics
|
|
pub fn reset_statistics(&mut self) {
|
|
self.statistics = SanitizationStatistics::default();
|
|
}
|
|
|
|
/// Calculate standard deviation for 1D slice
|
|
fn calculate_std_1d(&self, data: &[f64]) -> f64 {
|
|
if data.is_empty() {
|
|
return 0.0;
|
|
}
|
|
|
|
let mean: f64 = data.iter().sum::<f64>() / data.len() as f64;
|
|
let variance: f64 = data.iter().map(|x| (x - mean).powi(2)).sum::<f64>() / data.len() as f64;
|
|
variance.sqrt()
|
|
}
|
|
}
|
|
|
|
#[cfg(test)]
|
|
mod tests {
|
|
use super::*;
|
|
use std::f64::consts::PI;
|
|
|
|
fn create_test_phase_data() -> Array2<f64> {
|
|
// Create phase data with some simulated wrapping
|
|
Array2::from_shape_fn((4, 64), |(i, j)| {
|
|
let base = (j as f64 * 0.05).sin() * (PI / 2.0);
|
|
base + (i as f64 * 0.1)
|
|
})
|
|
}
|
|
|
|
fn create_wrapped_phase_data() -> Array2<f64> {
|
|
// Create phase data that will need unwrapping
|
|
// Generate a linearly increasing phase that wraps at +/- pi boundaries
|
|
Array2::from_shape_fn((2, 20), |(i, j)| {
|
|
let unwrapped = j as f64 * 0.4 + i as f64 * 0.2;
|
|
// Proper wrap to [-pi, pi]
|
|
let mut wrapped = unwrapped;
|
|
while wrapped > PI {
|
|
wrapped -= 2.0 * PI;
|
|
}
|
|
while wrapped < -PI {
|
|
wrapped += 2.0 * PI;
|
|
}
|
|
wrapped
|
|
})
|
|
}
|
|
|
|
#[test]
|
|
fn test_config_validation() {
|
|
let config = PhaseSanitizerConfig::default();
|
|
assert!(config.validate().is_ok());
|
|
}
|
|
|
|
#[test]
|
|
fn test_invalid_config() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.outlier_threshold(-1.0)
|
|
.build();
|
|
assert!(config.validate().is_err());
|
|
}
|
|
|
|
#[test]
|
|
fn test_sanitizer_creation() {
|
|
let config = PhaseSanitizerConfig::default();
|
|
let sanitizer = PhaseSanitizer::new(config);
|
|
assert!(sanitizer.is_ok());
|
|
}
|
|
|
|
#[test]
|
|
fn test_phase_validation() {
|
|
let config = PhaseSanitizerConfig::default();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let valid_data = create_test_phase_data();
|
|
assert!(sanitizer.validate_phase_data(&valid_data).is_ok());
|
|
|
|
// Test with out-of-range values
|
|
let invalid_data = Array2::from_elem((2, 10), 10.0);
|
|
assert!(sanitizer.validate_phase_data(&invalid_data).is_err());
|
|
}
|
|
|
|
#[test]
|
|
fn test_phase_unwrapping() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.unwrapping_method(UnwrappingMethod::Standard)
|
|
.build();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let wrapped = create_wrapped_phase_data();
|
|
let unwrapped = sanitizer.unwrap_phase(&wrapped);
|
|
assert!(unwrapped.is_ok());
|
|
|
|
// Verify that differences are now smooth (no jumps > pi)
|
|
let unwrapped = unwrapped.unwrap();
|
|
let ncols = unwrapped.ncols();
|
|
for i in 0..unwrapped.nrows() {
|
|
for j in 1..ncols {
|
|
let diff = (unwrapped[[i, j]] - unwrapped[[i, j - 1]]).abs();
|
|
assert!(diff < PI + 0.1, "Jump detected: {}", diff);
|
|
}
|
|
}
|
|
}
|
|
|
|
#[test]
|
|
fn test_outlier_removal() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.outlier_threshold(2.0)
|
|
.enable_outlier_removal(true)
|
|
.build();
|
|
let mut sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let mut data = create_test_phase_data();
|
|
// Insert an outlier
|
|
data[[0, 10]] = 100.0 * data[[0, 10]];
|
|
|
|
// Need to use data within valid range
|
|
let data = Array2::from_shape_fn((4, 64), |(i, j)| {
|
|
if i == 0 && j == 10 {
|
|
PI * 0.9 // Near boundary but valid
|
|
} else {
|
|
0.1 * (j as f64 * 0.1).sin()
|
|
}
|
|
});
|
|
|
|
let cleaned = sanitizer.remove_outliers(&data);
|
|
assert!(cleaned.is_ok());
|
|
}
|
|
|
|
#[test]
|
|
fn test_phase_smoothing() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.smoothing_window(5)
|
|
.enable_smoothing(true)
|
|
.build();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let noisy_data = Array2::from_shape_fn((2, 20), |(_, j)| {
|
|
(j as f64 * 0.2).sin() + 0.1 * ((j * 7) as f64).sin()
|
|
});
|
|
|
|
let smoothed = sanitizer.smooth_phase(&noisy_data);
|
|
assert!(smoothed.is_ok());
|
|
}
|
|
|
|
#[test]
|
|
fn test_noise_filtering() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.noise_threshold(0.1)
|
|
.enable_noise_filtering(true)
|
|
.build();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let data = create_test_phase_data();
|
|
let filtered = sanitizer.filter_noise(&data);
|
|
assert!(filtered.is_ok());
|
|
}
|
|
|
|
#[test]
|
|
fn test_complete_pipeline() {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.unwrapping_method(UnwrappingMethod::Standard)
|
|
.outlier_threshold(3.0)
|
|
.smoothing_window(3)
|
|
.enable_outlier_removal(true)
|
|
.enable_smoothing(true)
|
|
.enable_noise_filtering(false)
|
|
.build();
|
|
let mut sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let data = create_test_phase_data();
|
|
let sanitized = sanitizer.sanitize_phase(&data);
|
|
assert!(sanitized.is_ok());
|
|
|
|
let stats = sanitizer.get_statistics();
|
|
assert_eq!(stats.total_processed, 1);
|
|
}
|
|
|
|
#[test]
|
|
fn test_different_unwrapping_methods() {
|
|
let methods = vec![
|
|
UnwrappingMethod::Standard,
|
|
UnwrappingMethod::Custom,
|
|
UnwrappingMethod::Itoh,
|
|
UnwrappingMethod::QualityGuided,
|
|
];
|
|
|
|
let wrapped = create_wrapped_phase_data();
|
|
|
|
for method in methods {
|
|
let config = PhaseSanitizerConfig::builder()
|
|
.unwrapping_method(method)
|
|
.build();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let result = sanitizer.unwrap_phase(&wrapped);
|
|
assert!(result.is_ok(), "Failed for method {:?}", method);
|
|
}
|
|
}
|
|
|
|
#[test]
|
|
fn test_empty_data_handling() {
|
|
let config = PhaseSanitizerConfig::default();
|
|
let sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let empty = Array2::<f64>::zeros((0, 0));
|
|
assert!(sanitizer.validate_phase_data(&empty).is_err());
|
|
assert!(sanitizer.unwrap_phase(&empty).is_err());
|
|
}
|
|
|
|
#[test]
|
|
fn test_statistics() {
|
|
let config = PhaseSanitizerConfig::default();
|
|
let mut sanitizer = PhaseSanitizer::new(config).unwrap();
|
|
|
|
let data = create_test_phase_data();
|
|
let _ = sanitizer.sanitize_phase(&data);
|
|
let _ = sanitizer.sanitize_phase(&data);
|
|
|
|
let stats = sanitizer.get_statistics();
|
|
assert_eq!(stats.total_processed, 2);
|
|
|
|
sanitizer.reset_statistics();
|
|
let stats = sanitizer.get_statistics();
|
|
assert_eq!(stats.total_processed, 0);
|
|
}
|
|
}
|