import { ExperimentConfig } from '../../types';

export interface QuantumSimulationResult {
  id: string;
  experimentId: string;
  timestamp: string;
  quantumMetrics: {
    coherenceTime: number;
    gateErrors: number;
    quantumVolume: number;
    circuitDepth: number;
  };
  optimizationMetrics: {
    convergenceRate: number;
    energyLandscape: number[];
    quantumSpeedup: number;
  };
  results: {
    timepoint: number;
    predictions: {
      trait: string;
      value: number;
      uncertainty: number;
    }[];
  }[];
}

export class QuantumSimulationPipeline {
  static async runSimulation(experiment: ExperimentConfig): Promise<QuantumSimulationResult> {
    // Simulate quantum processing time
    await new Promise(resolve => setTimeout(resolve, 3000));

    const timepoints = Array.from({ length: 5 }, (_, i) => i * 24); // 0h, 24h, 48h, 72h, 96h
    const traits = ['growth_rate', 'stress_tolerance', 'nutrient_efficiency'];

    return {
      id: Math.random().toString(36).substr(2, 9),
      experimentId: experiment.id,
      timestamp: new Date().toISOString(),
      quantumMetrics: {
        coherenceTime: Math.random() * 50 + 50, // 50-100 microseconds
        gateErrors: Math.random() * 0.01, // 0-1% error rate
        quantumVolume: Math.floor(Math.random() * 512) + 512, // 512-1024
        circuitDepth: Math.floor(Math.random() * 100) + 100 // 100-200 gates
      },
      optimizationMetrics: {
        convergenceRate: Math.random() * 0.3 + 0.7, // 70-100% convergence
        energyLandscape: Array(10).fill(0).map(() => Math.random() * -10), // Energy values
        quantumSpeedup: Math.random() * 50 + 50 // 50-100x classical speedup
      },
      results: timepoints.map(timepoint => ({
        timepoint,
        predictions: traits.map(trait => ({
          trait,
          value: Math.random() * 0.5 + 0.5, // 0.5-1.0 normalized values
          uncertainty: Math.random() * 0.1 // 0-10% uncertainty
        }))
      }))
    };
  }
}