Struct GpuPCA 

pub struct GpuPCA {
    pub n_components: usize,
    pub center: bool,
    pub components: Option<Array2<f64>>,
    pub explained_variance: Option<Array1<f64>>,
    pub mean: Option<Array1<f64>>,
    /* private fields */
}

GPU-accelerated Principal Component Analysis

Fields

n_components: usize

Number of components to compute

center: bool

Whether to center the data

components: Option<Array2<f64>>

Principal components (loading vectors)

explained_variance: Option<Array1<f64>>

Explained variance for each component

mean: Option<Array1<f64>>

Mean values for centering

Implementations

impl GpuPCA

pub fn new(n_components: usize) -> Result<Self>

Create a new GPU PCA instance

Arguments

• n_components - Number of principal components to compute

Returns

Returns a new GpuPCA instance with GPU context initialized

Errors

Returns an error if GPU initialization fails or if n_components is 0

Examples

let pca = GpuPCA::new(5)?;

pub fn fit(&mut self, x: &ArrayView2<'_, f64>) -> Result<()>

Fit the PCA model on GPU

Currently this is a placeholder implementation that will return an error indicating that full GPU PCA support is not yet implemented.

Arguments

• x - Input data matrix with shape (n_samples, n_features)

Errors

Returns an error indicating that GPU PCA is not fully implemented yet

Examples

let mut pca = GpuPCA::new(2)?;
let data = Array2::zeros((100, 5));
// This will return an error indicating GPU PCA is not implemented
pca.fit(&data.view())?;

pub fn transform(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Transform data using the fitted PCA model on GPU

Currently this is a placeholder implementation that will return an error indicating that full GPU PCA support is not yet implemented.

Arguments

• x - Input data matrix with shape (n_samples, n_features)

Returns

Transformed data matrix with shape (n_samples, n_components)

Errors

Returns an error indicating that GPU PCA is not fully implemented yet

pub fn fit_transform(&mut self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Fit the PCA model and transform data in one step

Currently this is a placeholder implementation that will return an error indicating that full GPU PCA support is not yet implemented.

Arguments

• x - Input data matrix with shape (n_samples, n_features)

Returns

Transformed data matrix with shape (n_samples, n_components)

Errors

Returns an error indicating that GPU PCA is not fully implemented yet

pub fn explained_variance_ratio(&self) -> Result<Array1<f64>>

Get the explained variance ratio for each principal component

Returns

Array of explained variance ratios with length n_components

Errors

Returns an error if the model has not been fitted