Class PCAResult

src/memory/processing/dimred/pca/mod.rs:105–117

Results from Principal Component Analysis. Contains all the essential outputs from PCA analysis including the transformed data, variance explained by each component, and feature importance scores. ## Fields - `transformed`: Cell embeddings in the principal component space (cells × components) - `explained_variance_ratio`: Fraction of total variance explained by each component - `cumulative_expl

/// let pc1_loadings = pca_result.feature_importance.column(0);
/// ```
pub struct PCAResult<T>
where
    T: FloatOpsTS,
{
    /// Transformed data: cell embeddings in principal component space (n_cells × n_components)
    pub transformed: Array2<T>,
    /// Fraction of variance explained by each principal component
    pub explained_variance_ratio: Array1<T>,
    /// Cumulative fraction of variance explained up to each component
    pub cumulative_explained_variance_ratio: Array1<T>,
    /// Feature loadings/importance for each component (n_features × n_components)
    pub feature_importance: Array2<T>,
}

/// Perform Principal Component Analysis on sparse single-cell expression data.
///