import { RideSample, ZoneAnalysis } from './types';
import { assignZone, classifyZoneType } from './clustering';

/**
 * Analyze pricing by geographical zone (2.5km grid).
 * Groups samples into zones and computes per-zone statistics.
 */
export function analyzeByZone(samples: RideSample[]): ZoneAnalysis[] {
  const zoneMap = new Map<string, RideSample[]>();

  for (const s of samples) {
    // Use start location for zone assignment
    const zone = assignZone(s.startLat, s.startLng);
    if (!zoneMap.has(zone)) zoneMap.set(zone, []);
    zoneMap.get(zone)!.push(s);
  }

  const results: ZoneAnalysis[] = [];

  for (const [zoneKey, zoneSamples] of zoneMap) {
    if (zoneSamples.length < 3) continue;

    const ppkValues = zoneSamples.map(s => s.ppk);
    const avgPpk = Math.round(
      (ppkValues.reduce((a, b) => a + b, 0) / ppkValues.length) * 1000
    ) / 1000;

    // Count by tier — thresholds depend on currency scale
    const tierCounts: Record<string, number> = {};
    const sample = zoneSamples[0];
    const isHighDenom = sample.countryCode === 'SY' || sample.countryCode === 'IQ';
    const econThreshold = isHighDenom ? 15 : 0.35;
    const stdThreshold = isHighDenom ? 40 : 0.55;

    for (const s of zoneSamples) {
      const tier =
        s.ppk < econThreshold ? 'economy' :
        s.ppk < stdThreshold  ? 'standard' : 'premium';
      tierCounts[tier] = (tierCounts[tier] || 0) + 1;
    }

    const [latStr, lngStr] = zoneKey.split(',');
    results.push({
      zoneKey,
      centerLat: parseFloat(latStr),
      centerLng: parseFloat(lngStr),
      samples: zoneSamples,
      avgPpk,
      tierDistribution: tierCounts,
    });
  }

  return results.sort((a, b) => a.avgPpk - b.avgPpk);
}

/**
 * Analyze pricing by zone type (centre, mid, suburb, outskirts).
 * Passes countryCode to classifyZoneType so the correct city center is used.
 */
export function analyzeByZoneType(
  samples: RideSample[]
): Array<{ zoneType: string; avgPpk: number; sampleCount: number; avgPrice: number }> {
  const typeMap = new Map<string, number[]>();

  for (const s of samples) {
    // Pass countryCode so we use the correct city center (not always Amman)
    const zoneType = classifyZoneType(s.startLat, s.startLng, s.countryCode);
    if (!typeMap.has(zoneType)) typeMap.set(zoneType, []);
    typeMap.get(zoneType)!.push(s.ppk);
  }

  return Array.from(typeMap.entries())
    .map(([zoneType, ppks]) => ({
      zoneType,
      avgPpk: Math.round(
        (ppks.reduce((a, b) => a + b, 0) / ppks.length) * 1000
      ) / 1000,
      sampleCount: ppks.length,
      avgPrice: 0, // calculated below if needed
    }))
    .sort((a, b) => a.avgPpk - b.avgPpk);
}