//! Least Angle Regression (LARS) algorithms for dictionary learning

use scirs2_core::ndarray::{Array1, Array2};
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
use sklears_core::{error::Result, types::Float};

/// Configuration for LARS algorithm
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LARSConfig {
    /// Maximum number of active variables
    pub max_iter: usize,
    /// Regularization parameter
    pub alpha: Float,
}

impl Default for LARSConfig {
    fn default() -> Self {
        Self {
            max_iter: 500,
            alpha: 1.0,
        }
    }
}

/// LARS algorithm result
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LARSResult {
    /// Path coefficients
    pub coefficients: Array2<Float>,
    /// Active set indices
    pub active_set: Vec<usize>,
    /// Number of iterations
    pub n_iter: usize,
}

/// LARS direction computation
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LARSDirection {
    pub direction: Array1<Float>,
    pub correlation: Float,
}

/// LARS step size computation
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LARSStepSize {
    pub step_size: Float,
    pub next_variable: Option<usize>,
}

/// LARS algorithm encoder
#[derive(Debug, Clone)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub struct LARSEncoder {
    config: LARSConfig,
}

impl LARSEncoder {
    pub fn new(config: LARSConfig) -> Self {
        Self { config }
    }

    /// Perform LARS algorithm
    pub fn encode(
        &self,
        dictionary: &Array2<Float>,
        _signal: &Array1<Float>,
    ) -> Result<LARSResult> {
        let n_atoms = dictionary.nrows();

        // Placeholder implementation
        let coefficients = Array2::zeros((1, n_atoms));
        let active_set = Vec::new();

        Ok(LARSResult {
            coefficients,
            active_set,
            n_iter: 0,
        })
    }
}
