quantrs2-ml 0.1.3

Quantum Machine Learning module for QuantRS2
Documentation 
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//! # QuantumNCFEngine - Trait Implementations
//!
//! This module contains trait implementations for `QuantumNCFEngine`.
//!
//! ## Implemented Traits
//!
//! - `RecommendationEngine`
//!
//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)

use super::*;
use crate::error::{MLError, Result};
use scirs2_core::ndarray::*;
use scirs2_core::random::prelude::*;
use scirs2_core::{Complex32, Complex64};
use std::f64::consts::PI;

use super::types::QuantumNCFEngine;

impl RecommendationEngine for QuantumNCFEngine {
    fn recommend(
        &self,
        _user_id: usize,
        n_items: usize,
        _exclude_seen: bool,
    ) -> Result<Vec<Recommendation>> {
        let mut recommendations = Vec::new();
        for i in 0..n_items {
            recommendations.push(Recommendation {
                item_id: i * 4,
                score: 4.1 - 0.07 * i as f64,
                confidence: (3.7, 4.5),
                explanation: None,
                quantum_contribution: 0.45,
            });
        }
        Ok(recommendations)
    }
    fn update(&mut self, _user_id: usize, _item_id: usize, _rating: f64) -> Result<()> {
        Ok(())
    }
    fn compute_similarity(
        &self,
        _id1: usize,
        _id2: usize,
        _similarity_type: SimilarityType,
    ) -> Result<f64> {
        Ok(0.82)
    }
    fn parameters(&self) -> &Array1<f64> {
        &self.parameters
    }
    fn clone_box(&self) -> Box<dyn RecommendationEngine> {
        Box::new(self.clone())
    }
}