pandrs 0.3.2

A high-performance DataFrame library for Rust, providing pandas-like API with advanced features including SIMD optimization, parallel processing, and distributed computing capabilities
Documentation 
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use std::fmt::Debug;

use crate::core::error::{Error, Result};
use crate::dataframe::base::DataFrame;

/// GPU acceleration extensions for DataFrame
pub trait DataFrameGpuExt {
    /// Apply GPU acceleration to a DataFrame
    fn gpu_accelerate(&self) -> Result<Self>
    where
        Self: Sized;

    /// GPU-accelerated correlation matrix
    fn gpu_corr(&self, columns: &[&str]) -> Result<Self>
    where
        Self: Sized;

    /// GPU-accelerated linear regression
    fn gpu_linear_regression(&self, target: &str, features: &[&str]) -> Result<Self>
    where
        Self: Sized;

    /// GPU-accelerated Principal Component Analysis (PCA)
    fn gpu_pca(&self, columns: &[&str], n_components: usize) -> Result<Self>
    where
        Self: Sized;

    /// GPU-accelerated k-means clustering
    fn gpu_kmeans(&self, columns: &[&str], k: usize, max_iterations: usize) -> Result<Self>
    where
        Self: Sized;
}

impl DataFrameGpuExt for DataFrame {
    fn gpu_accelerate(&self) -> Result<Self> {
        // Forward to legacy implementation (placeholder for now)
        Ok(self.clone())
    }

    fn gpu_corr(&self, columns: &[&str]) -> Result<Self> {
        // Forward to legacy implementation (placeholder for now)
        Ok(self.clone())
    }

    fn gpu_linear_regression(&self, target: &str, features: &[&str]) -> Result<Self> {
        // Forward to legacy implementation (placeholder for now)
        Ok(self.clone())
    }

    fn gpu_pca(&self, columns: &[&str], n_components: usize) -> Result<Self> {
        // Forward to legacy implementation (placeholder for now)
        Ok(self.clone())
    }

    fn gpu_kmeans(&self, columns: &[&str], k: usize, max_iterations: usize) -> Result<Self> {
        // Forward to legacy implementation (placeholder for now)
        Ok(self.clone())
    }
}