package service

import (
	"context"
	"encoding/json"
	"fmt"
	"math"
	"sort"

	"bugulma/backend/internal/domain"
)

// FacilityLocationOptimizer provides optimal facility location recommendations
type FacilityLocationOptimizer struct {
	geoRepo            domain.GeographicalFeatureRepository
	siteRepo           domain.SiteRepository
	geospatialSvc      *GeospatialService
	spatialMatcher     *SpatialResourceMatcher
	environmentalSvc   *EnvironmentalImpactService
	transportSvc       *TransportationService
}

// NewFacilityLocationOptimizer creates a new facility location optimizer
func NewFacilityLocationOptimizer(
	geoRepo domain.GeographicalFeatureRepository,
	siteRepo domain.SiteRepository,
	geospatialSvc *GeospatialService,
	spatialMatcher *SpatialResourceMatcher,
	environmentalSvc *EnvironmentalImpactService,
	transportSvc *TransportationService,
) *FacilityLocationOptimizer {
	return &FacilityLocationOptimizer{
		geoRepo:          geoRepo,
		siteRepo:         siteRepo,
		geospatialSvc:    geospatialSvc,
		spatialMatcher:   spatialMatcher,
		environmentalSvc: environmentalSvc,
		transportSvc:     transportSvc,
	}
}

// LocationCriteria defines the requirements for optimal facility location
type LocationCriteria struct {
	// Required resources/facilities nearby
	RequiredResources    []domain.ResourceType `json:"required_resources"`
	ResourceRadiusKm     float64               `json:"resource_radius_km"`

	// Transportation preferences
	PreferredTransport   domain.TransportMode  `json:"preferred_transport"`
	MaxTransportCost     float64               `json:"max_transport_cost_eur_month"`

	// Environmental constraints
	MinEnvironmentalScore float64              `json:"min_environmental_score"`
	EnvironmentalWeight   float64              `json:"environmental_weight"`

	// Infrastructure requirements
	RequiredUtilities    []string             `json:"required_utilities"`
	MinFloorAreaM2       float64              `json:"min_floor_area_m2"`

	// Cost constraints
	MaxDevelopmentCost   float64              `json:"max_development_cost_eur"`
	BudgetWeight         float64              `json:"budget_weight"`

	// Strategic factors
	ProximityToExistingSites bool               `json:"proximity_to_existing_sites"`
	ClusterFormationBonus    float64            `json:"cluster_formation_bonus"`

	// Result limits
	MaxResults           int                  `json:"max_results"`

	// Scoring weights (should sum to 1.0)
	Weights              LocationWeights      `json:"weights"`
}

// LocationWeights defines how different factors are weighted in scoring
type LocationWeights struct {
	Transportation  float64 `json:"transportation"`
	Environmental  float64 `json:"environmental"`
	Infrastructure float64 `json:"infrastructure"`
	Cost           float64 `json:"cost"`
	Strategic      float64 `json:"strategic"`
}

// DefaultWeights provides balanced default scoring weights
var DefaultWeights = LocationWeights{
	Transportation: 0.30,
	Environmental:  0.25,
	Infrastructure: 0.20,
	Cost:          0.15,
	Strategic:     0.10,
}

// OptimalLocation represents a potential facility location with comprehensive analysis
type OptimalLocation struct {
	Location          *LocationCandidate `json:"location"`
	Score             *LocationScore     `json:"score"`
	ResourceAccess    []*ResourceAccess  `json:"resource_access"`
	TransportOptions  []*domain.TransportOption `json:"transport_options"`
	EnvironmentalData *EnvironmentalScore `json:"environmental_data"`
	DevelopmentCost   *CostEstimate      `json:"development_cost"`
}

// LocationCandidate represents a potential location
type LocationCandidate struct {
	Latitude         float64 `json:"latitude"`
	Longitude        float64 `json:"longitude"`
	Name             string  `json:"name"`
	Description      string  `json:"description"`
	ExistingSite     *domain.Site `json:"existing_site,omitempty"` // If based on existing site
}

// LocationScore provides detailed scoring breakdown
type LocationScore struct {
	TransportationScore float64 `json:"transportation_score"`
	EnvironmentalScore  float64 `json:"environmental_score"`
	InfrastructureScore float64 `json:"infrastructure_score"`
	CostScore          float64 `json:"cost_score"`
	StrategicScore     float64 `json:"strategic_score"`
	OverallScore       float64 `json:"overall_score"`
	Confidence         float64 `json:"confidence"` // 0-100, how reliable the scoring is
}

// ResourceAccess describes access to required resources
type ResourceAccess struct {
	ResourceType    domain.ResourceType `json:"resource_type"`
	DistanceKm      float64            `json:"distance_km"`
	TransportCost   float64            `json:"transport_cost_eur_month"`
	Availability    float64            `json:"availability_score"` // 0-10
	ProviderCount   int                `json:"provider_count"`
}

// CostEstimate provides development cost breakdown
type CostEstimate struct {
	LandAcquisition float64 `json:"land_acquisition_eur"`
	Infrastructure  float64 `json:"infrastructure_eur"`
	Utilities       float64 `json:"utilities_eur"`
	Environmental   float64 `json:"environmental_mitigation_eur"`
	Total           float64 `json:"total_eur"`
	TimeMonths      int     `json:"time_months"`
}

// FindOptimalLocations finds the best facility locations based on criteria
func (f *FacilityLocationOptimizer) FindOptimalLocations(
	ctx context.Context,
	criteria LocationCriteria,
) ([]*OptimalLocation, error) {

	// Set default weights if not provided
	if criteria.Weights == (LocationWeights{}) {
		criteria.Weights = DefaultWeights
	}

	// Generate candidate locations
	candidates, err := f.generateLocationCandidates(ctx, criteria)
	if err != nil {
		return nil, fmt.Errorf("failed to generate candidates: %w", err)
	}

	var optimalLocations []*OptimalLocation

	for _, candidate := range candidates {
		// Analyze each candidate comprehensively
		location, err := f.analyzeLocationCandidate(ctx, candidate, criteria)
		if err != nil {
			// Log error but continue with other candidates
			continue
		}

		// Apply minimum criteria filters
		if f.meetsMinimumCriteria(location, criteria) {
			optimalLocations = append(optimalLocations, location)
		}
	}

	// Sort by overall score (highest first)
	sort.Slice(optimalLocations, func(i, j int) bool {
		return optimalLocations[i].Score.OverallScore > optimalLocations[j].Score.OverallScore
	})

	// Limit results
	if len(optimalLocations) > criteria.MaxResults {
		optimalLocations = optimalLocations[:criteria.MaxResults]
	}

	return optimalLocations, nil
}

// generateLocationCandidates creates potential location options
func (f *FacilityLocationOptimizer) generateLocationCandidates(
	ctx context.Context,
	criteria LocationCriteria,
) ([]*LocationCandidate, error) {

	var candidates []*LocationCandidate

	// Strategy 1: Use existing industrial sites as starting points
	if criteria.ProximityToExistingSites {
		existingSites, err := f.siteRepo.GetBySiteType(ctx, domain.SiteTypeIndustrial)
		if err == nil {
			for _, site := range existingSites {
				// Generate variations around existing sites
				candidates = append(candidates, &LocationCandidate{
					Latitude:     site.Latitude + (math.Mod(float64(len(candidates)), 0.01) - 0.005),
					Longitude:    site.Longitude + (math.Mod(float64(len(candidates)), 0.01) - 0.005),
					Name:         fmt.Sprintf("Near %s", site.Name),
					Description:  "Location near existing industrial facility",
					ExistingSite: site,
				})
			}
		}
	}

	// Strategy 2: Generate grid-based candidates in industrial areas
	// Focus on Bugulma's industrial zones
	industrialZones := []struct {
		name string
		lat  float64
		lng  float64
		radius float64
	}{
		{"Bugulma Industrial District", 54.538, 52.802, 2.0},
		{"Northern Industrial Zone", 54.550, 52.790, 1.5},
		{"Southern Logistics Hub", 54.520, 52.810, 1.5},
	}

	for _, zone := range industrialZones {
		// Generate 5-10 candidates per zone
		for i := 0; i < 8; i++ {
			// Random distribution within zone
			angle := (float64(i) / 8.0) * 2 * math.Pi
			distance := zone.radius * math.Sqrt(math.Mod(float64(i+1), 1.0))

			lat := zone.lat + (distance/111.0)*math.Cos(angle) // ~111km per degree latitude
			lng := zone.lng + (distance/111.0)*math.Sin(angle) / math.Cos(zone.lat*math.Pi/180.0)

			candidates = append(candidates, &LocationCandidate{
				Latitude:    lat,
				Longitude:   lng,
				Name:        fmt.Sprintf("%s Site %d", zone.name, i+1),
				Description: fmt.Sprintf("Generated location in %s", zone.name),
			})
		}
	}

	return candidates, nil
}

// analyzeLocationCandidate performs comprehensive analysis of a location
func (f *FacilityLocationOptimizer) analyzeLocationCandidate(
	ctx context.Context,
	candidate *LocationCandidate,
	criteria LocationCriteria,
) (*OptimalLocation, error) {

	location := &OptimalLocation{
		Location: candidate,
		Score:    &LocationScore{},
	}

	// Analyze resource access
	resourceAccess, transportScore, err := f.analyzeResourceAccess(ctx, candidate, criteria)
	if err != nil {
		return nil, fmt.Errorf("resource access analysis failed: %w", err)
	}
	location.ResourceAccess = resourceAccess
	location.Score.TransportationScore = transportScore

	// Analyze environmental factors
	envData, envScore, err := f.analyzeEnvironmentalFactors(ctx, candidate, criteria)
	if err != nil {
		return nil, fmt.Errorf("environmental analysis failed: %w", err)
	}
	location.EnvironmentalData = envData
	location.Score.EnvironmentalScore = envScore

	// Analyze infrastructure
	infraScore := f.analyzeInfrastructure(ctx, candidate, criteria)
	location.Score.InfrastructureScore = infraScore

	// Estimate costs
	costEstimate, costScore := f.estimateDevelopmentCost(candidate, criteria)
	location.DevelopmentCost = costEstimate
	location.Score.CostScore = costScore

	// Calculate strategic score
	strategicScore := f.calculateStrategicScore(candidate, criteria)
	location.Score.StrategicScore = strategicScore

	// Calculate overall score
	location.Score.OverallScore = f.calculateOverallScore(location.Score, criteria.Weights)

	// Estimate confidence in scoring
	location.Score.Confidence = f.estimateScoringConfidence(location)

	// Get transport options
	transportOptions, err := f.transportSvc.FindOptimalTransportRoutes(
		candidate.Latitude, candidate.Longitude, 54.538, 52.802, 50.0, // To city center
	)
	if err == nil && len(transportOptions) > 0 {
		location.TransportOptions = transportOptions[:min(3, len(transportOptions))] // Top 3 options
	}

	return location, nil
}

// analyzeResourceAccess evaluates access to required resources
func (f *FacilityLocationOptimizer) analyzeResourceAccess(
	ctx context.Context,
	candidate *LocationCandidate,
	criteria LocationCriteria,
) ([]*ResourceAccess, float64, error) {

	var resourceAccess []*ResourceAccess
	totalTransportScore := 0.0

	for _, resourceType := range criteria.RequiredResources {
		// Find nearby providers
		results, err := f.spatialMatcher.FindNearbyResourceProviders(
			ctx, resourceType, candidate.Latitude, candidate.Longitude, criteria.ResourceRadiusKm, criteria.PreferredTransport,
		)
		if err != nil {
			continue
		}

		access := &ResourceAccess{
			ResourceType:  resourceType,
			ProviderCount: len(results),
			Availability:  math.Min(float64(len(results)), 10.0), // Cap at 10
		}

		if len(results) > 0 {
			// Use the best match for distance/cost
			bestMatch := results[0]
			access.DistanceKm = bestMatch.SpatialMetrics.StraightLineDistance
			access.TransportCost = bestMatch.SpatialMetrics.TransportCost

			// Add to transport score
			distanceScore := math.Max(0, 1.0-(access.DistanceKm/criteria.ResourceRadiusKm))
			costScore := math.Max(0, 1.0-(access.TransportCost/criteria.MaxTransportCost))
			totalTransportScore += (distanceScore + costScore) / 2.0
		}

		resourceAccess = append(resourceAccess, access)
	}

	// Average transport score across all resources
	if len(criteria.RequiredResources) > 0 {
		totalTransportScore /= float64(len(criteria.RequiredResources))
		totalTransportScore *= 10.0 // Scale to 0-10
	}

	return resourceAccess, totalTransportScore, nil
}

// analyzeEnvironmentalFactors evaluates environmental suitability
func (f *FacilityLocationOptimizer) analyzeEnvironmentalFactors(
	ctx context.Context,
	candidate *LocationCandidate,
	criteria LocationCriteria,
) (*EnvironmentalScore, float64, error) {

	envScore, err := f.environmentalSvc.CalculateFacilityEnvironmentalScore(
		ctx, candidate.Latitude, candidate.Longitude,
	)
	if err != nil {
		return nil, 0, err
	}

	// Convert to 0-10 scale for consistency
	scaledScore := envScore.OverallScore

	return envScore, scaledScore, nil
}

// analyzeInfrastructure evaluates infrastructure availability
func (f *FacilityLocationOptimizer) analyzeInfrastructure(
	ctx context.Context,
	candidate *LocationCandidate,
	criteria LocationCriteria,
) float64 {

	score := 0.0

	// If based on existing site, use its infrastructure
	if candidate.ExistingSite != nil {
		site := candidate.ExistingSite

		// Utilities scoring
		for _, required := range criteria.RequiredUtilities {
			if f.siteHasUtility(site, required) {
				score += 2.0
			}
		}

		// Floor area
		if site.FloorAreaM2 >= criteria.MinFloorAreaM2 {
			score += 2.0
		}

		// Loading and parking
		if site.LoadingDocks > 0 {
			score += 1.0
		}
		if site.ParkingSpaces > 0 {
			score += 1.0
		}
	} else {
		// For generated locations, estimate based on proximity to infrastructure
		// Simplified scoring - in production, would check actual infrastructure data
		score = 5.0 // Neutral score for generated locations
	}

	return math.Min(score, 10.0)
}

// estimateDevelopmentCost provides cost estimation
func (f *FacilityLocationOptimizer) estimateDevelopmentCost(
	candidate *LocationCandidate,
	criteria LocationCriteria,
) (*CostEstimate, float64) {

	estimate := &CostEstimate{
		TimeMonths: 12, // Default 12 months
	}

	if candidate.ExistingSite != nil {
		// Renovation costs for existing site
		site := candidate.ExistingSite
		estimate.LandAcquisition = 0 // Already owned

		// Infrastructure upgrades
		estimate.Infrastructure = site.FloorAreaM2 * 100.0 // €100/m² renovation

		// Utilities connection
		estimate.Utilities = 50000.0 // €50k for utility connections

		// Environmental mitigation
		estimate.Environmental = 25000.0 // €25k for environmental compliance
	} else {
		// New construction costs
		estimate.LandAcquisition = 100000.0 // €100k for land
		estimate.Infrastructure = criteria.MinFloorAreaM2 * 200.0 // €200/m² construction
		estimate.Utilities = 75000.0 // €75k for new utilities
		estimate.Environmental = 50000.0 // €50k for environmental impact
	}

	estimate.Total = estimate.LandAcquisition + estimate.Infrastructure +
		estimate.Utilities + estimate.Environmental

	// Cost score (higher is better/cheaper)
	costScore := 10.0
	if criteria.MaxDevelopmentCost > 0 {
		costScore = math.Max(0, 10.0-(estimate.Total/criteria.MaxDevelopmentCost)*10.0)
	}

	return estimate, costScore
}

// calculateStrategicScore evaluates long-term strategic value
func (f *FacilityLocationOptimizer) calculateStrategicScore(
	candidate *LocationCandidate,
	criteria LocationCriteria,
) float64 {

	score := 0.0

	// Proximity to existing industrial sites (cluster formation)
	if criteria.ProximityToExistingSites && candidate.ExistingSite != nil {
		score += criteria.ClusterFormationBonus
	}

	// Future expansion potential
	score += 2.0 // Baseline strategic value

	return math.Min(score, 10.0)
}

// calculateOverallScore computes weighted final score
func (f *FacilityLocationOptimizer) calculateOverallScore(
	score *LocationScore,
	weights LocationWeights,
) float64 {

	return (score.TransportationScore * weights.Transportation) +
		(score.EnvironmentalScore * weights.Environmental) +
		(score.InfrastructureScore * weights.Infrastructure) +
		(score.CostScore * weights.Cost) +
		(score.StrategicScore * weights.Strategic)
}

// estimateScoringConfidence provides confidence level in the scoring
func (f *FacilityLocationOptimizer) estimateScoringConfidence(location *OptimalLocation) float64 {
	// Base confidence
	confidence := 70.0

	// Increase confidence with more data
	if location.EnvironmentalData != nil {
		confidence += 10.0
	}
	if len(location.ResourceAccess) > 0 {
		confidence += 10.0
	}
	if len(location.TransportOptions) > 0 {
		confidence += 5.0
	}
	if location.DevelopmentCost != nil {
		confidence += 5.0
	}

	return math.Min(confidence, 100.0)
}

// meetsMinimumCriteria checks if location meets basic requirements
func (f *FacilityLocationOptimizer) meetsMinimumCriteria(location *OptimalLocation, criteria LocationCriteria) bool {
	// Environmental minimum
	if criteria.MinEnvironmentalScore > 0 &&
		location.Score.EnvironmentalScore < criteria.MinEnvironmentalScore {
		return false
	}

	// Cost maximum
	if criteria.MaxDevelopmentCost > 0 &&
		location.DevelopmentCost != nil &&
		location.DevelopmentCost.Total > criteria.MaxDevelopmentCost {
		return false
	}

	// Transport cost maximum
	if criteria.MaxTransportCost > 0 {
		for _, resource := range location.ResourceAccess {
			if resource.TransportCost > criteria.MaxTransportCost {
				return false
			}
		}
	}

	return true
}

// Helper functions

func min(a, b int) int {
	if a < b {
		return a
	}
	return b
}

// siteHasUtility checks if a site has a specific utility available
func (f *FacilityLocationOptimizer) siteHasUtility(site *domain.Site, utility string) bool {
	if len(site.AvailableUtilities) == 0 {
		return false
	}

	var utilities []string
	if err := json.Unmarshal(site.AvailableUtilities, &utilities); err != nil {
		return false
	}

	for _, u := range utilities {
		if u == utility {
			return true
		}
	}

	return false
}