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crates/specialized/rtx-neuro-inverse/src/lib.rs

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+//! Inverse solutions for MEG/EEG source localization.
+//!
+//! This crate provides algorithms to estimate brain source activity from
+//! MEG/EEG sensor measurements.
+//!
+//! ## Available Methods
+//!
+//! - **MNE** (Minimum Norm Estimate): Basic L2-regularized inverse
+//! - **dSPM** (Dynamic Statistical Parametric Mapping): Noise-normalized MNE
+//! - **sLORETA** (Standardized LORETA): Resolution-matrix normalized
+//! - **eLORETA** (Exact LORETA): Zero localization error inverse
+//! - **LCMV** (Linearly Constrained Minimum Variance): Beamformer approach
+//! - **DICS** (Dynamic Imaging of Coherent Sources): Frequency-domain beamformer
+//! - **Dipole Fitting**: Equivalent current dipole fitting with optimization
+//!
+//! ## Usage
+//!
+//! ```rust,ignore
+//! use rtx_neuro_inverse::{MneInverse, InverseMethod, Covariance};
+//!
+//! // Compute inverse operator
+//! let inverse = MneInverse::make_inverse(
+//!     &forward,
+//!     &noise_cov,
+//!     InverseMethod::Dspm,
+//!     0.1, // loose
+//!     0.8, // depth
+//! )?;
+//!
+//! // Apply to evoked data
+//! let stc = inverse.apply(&evoked, 1.0 / 9.0)?; // lambda^2 = 1/SNR^2
+//! ```
+
+#![warn(missing_docs)]
+
+pub mod beamformer;
+pub mod covariance;
+pub mod dipole;
+pub mod loreta;
+pub mod mne;
+pub mod source_estimate;
+
+pub use beamformer::{
+    CrossSpectralDensity, DicsBeamformer, DicsConfig, LcmvBeamformer, PickOrientation,
+};
+pub use covariance::{Covariance, CovarianceType};
+pub use dipole::{DipoleConfig, DipoleFit, DipoleFitSequence, DipoleFitter};
+pub use loreta::{EloretaConfig, EloretaInverse};
+pub use mne::{InverseMethod, MneInverse};
+pub use source_estimate::SourceEstimate;
+
+/// Errors in inverse modeling
+#[derive(Debug, thiserror::Error)]
+pub enum InverseError {
+    /// Invalid parameters
+    #[error("Invalid parameter: {0}")]
+    InvalidParameter(String),
+
+    /// Dimension mismatch
+    #[error("Dimension mismatch: {0}")]
+    DimensionMismatch(String),
+
+    /// Computation error (e.g., singular matrix)
+    #[error("Computation error: {0}")]
+    ComputationError(String),
+
+    /// Forward model error
+    #[error("Forward model error: {0}")]
+    ForwardError(#[from] rtx_neuro_forward::ForwardError),
+
+    /// No inverse operator computed
+    #[error("Inverse operator not computed: {0}")]
+    NoInverse(String),
+}
+
+/// Result type for inverse operations
+pub type InverseResult<T> = Result<T, InverseError>;
+
+#[cfg(test)]
+mod tests {
+    #[test]
+    fn test_error_display() {
+        let err = super::InverseError::InvalidParameter("test".to_string());
+        assert!(err.to_string().contains("test"));
+    }
+}