package puzzle;

import java.util.*;

/**
 * ThemeGraph - Creates a graph between words and themes for filtering.
 * Uses word embeddings approach: co-occurrence and semantic similarity.
 */
public class ThemeGraph {

    // Predefined theme keywords for Dutch word filtering
    private static final Map<String, Set<String>> THEME_KEYWORDS = new HashMap<>();

    static {
        // News/Politics
        THEME_KEYWORDS.put("nieuws", Set.of(
                "POLITIEK", "VERKIEZING", "MINISTER", "PARLEMENT", "WET", "BELEID",
                "REGERING", "PARTIJ", "STEM", "KAMER", "RAAD", "STAAT"
        ));

        // Technology
        THEME_KEYWORDS.put("technologie", Set.of(
                "COMPUTER", "INTERNET", "SOFTWARE", "APP", "DATA", "CODE",
                "NETWERK", "SYSTEEM", "DIGITAAL", "TECH", "ROBOT", "AI"
        ));

        // Sports
        THEME_KEYWORDS.put("sport", Set.of(
                "VOETBAL", "TENNIS", "WIELREN", "SPELER", "WEDSTRIJD", "TEAM",
                "GOAL", "BAL", "SPEL", "WINNEN", "COACH", "ATLEET"
        ));

        // Weather/Nature
        THEME_KEYWORDS.put("weer", Set.of(
                "REGEN", "ZON", "WIND", "WOLKEN", "STORM", "SNEEUW",
                "WEER", "KLIMAAT", "NATUUR", "LUCHT", "WARMTE", "KOU"
        ));

        // Economy
        THEME_KEYWORDS.put("economie", Set.of(
                "GELD", "EURO", "MARKT", "PRIJS", "KOPEN", "VERKOOP",
                "BEDRIJF", "BANK", "HANDEL", "WINST", "SCHULD", "BUDGET"
        ));

        // Health
        THEME_KEYWORDS.put("gezondheid", Set.of(
                "ZORG", "DOKTER", "MEDICIJN", "PATIENT", "ZIEKENHUIS", "GEZOND",
                "VIRUS", "VACCIN", "THERAPIE", "BEHANDEL", "ARTS", "KLINIEK"
        ));

        // General/Common
        THEME_KEYWORDS.put("algemeen", Set.of(
                "HUIS", "AUTO", "BOOM", "WATER", "MENS", "TIJD",
                "LEVEN", "WERK", "SCHOOL", "FAMILIE", "STAD", "LAND"
        ));
    }

    /**
     * Score a word against a theme (0.0 = no match, 1.0 = perfect match)
     */
    public static double scoreWordTheme(String word, String theme) {
       var keywords = THEME_KEYWORDS.get(theme.toLowerCase());
        if (keywords == null) {
            return 0.5; // unknown theme = neutral score
        }

        word = word.toUpperCase();

        // Direct match
        if (keywords.contains(word)) {
            return 1.0;
        }

        // Substring match (partial relevance)
        for (var kw : keywords) {
            if (word.contains(kw) || kw.contains(word)) {
                return 0.7;
            }
        }

        // Edit distance similarity (for typos/variations)
        for (var kw : keywords) {
           var similarity = editDistanceSimilarity(word, kw);
            if (similarity > 0.8) {
                return similarity * 0.9;
            }
        }

        return 0.0;
    }

    /**
     * Filter word list by theme with minimum score threshold
     */
    public static List<String> filterByTheme(List<String> words, String theme, double minScore) {
        List<String> filtered = new ArrayList<>();
        for (var word : words) {
           var score = scoreWordTheme(word, theme);
            if (score >= minScore) {
                filtered.add(word);
            }
        }
        return filtered;
    }

    /**
     * Get theme suggestions for a word (sorted by score)
     */
    public static List<ThemeScore> getThemesForWord(String word) {
        List<ThemeScore> scores = new ArrayList<>();
        for (var theme : THEME_KEYWORDS.keySet()) {
           var score = scoreWordTheme(word, theme);
            if (score > 0.0) {
                scores.add(new ThemeScore(theme, score));
            }
        }
        scores.sort(Comparator.comparingDouble(ts -> -ts.score));
        return scores;
    }

    /**
     * Auto-detect best theme from a word list
     */
    public static String detectTheme(List<String> words) {
        Map<String, Double> themeScores = new HashMap<>();

        for (var theme : THEME_KEYWORDS.keySet()) {
            double totalScore = 0;
            for (var word : words) {
                totalScore += scoreWordTheme(word, theme);
            }
            themeScores.put(theme, totalScore / words.size());
        }

        return themeScores.entrySet().stream()
                .max(Comparator.comparingDouble(Map.Entry::getValue))
                .map(Map.Entry::getKey)
                .orElse("algemeen");
    }

    /**
     * Simple edit distance similarity (normalized Levenshtein)
     */
    private static double editDistanceSimilarity(String a, String b) {
       var dist   = levenshtein(a, b);
       var maxLen = Math.max(a.length(), b.length());
        if (maxLen == 0) return 1.0;
        return 1.0 - ((double) dist / maxLen);
    }

    private static int levenshtein(String a, String b) {
       var dp = new int[a.length() + 1][b.length() + 1];

        for (var i = 0; i <= a.length(); i++) dp[i][0] = i;
        for (var j = 0; j <= b.length(); j++) dp[0][j] = j;

        for (var i = 1; i <= a.length(); i++) {
            for (var j = 1; j <= b.length(); j++) {
               var cost = (a.charAt(i - 1) == b.charAt(j - 1)) ? 0 : 1;
                dp[i][j] = Math.min(
                        Math.min(dp[i - 1][j] + 1, dp[i][j - 1] + 1),
                        dp[i - 1][j - 1] + cost
                );
            }
        }

        return dp[a.length()][b.length()];
    }
   
   public record ThemeScore(String theme, double score) {
      
      @Override
      public String toString() {
         return String.format("%s: %.2f", theme, score);
      }
   }

    // ---- Main for testing ----
    public static void main(String[] args) {
        System.out.println("=== Theme Graph Test ===\n");

        // Test word scoring
       var testWords = new String[]{ "POLITIEK", "VOETBAL", "COMPUTER", "REGEN", "AUTO" };
        for (var word : testWords) {
            System.out.println("Word: " + word);
           var themes = getThemesForWord(word);
            for (var ts : themes) {
                System.out.println("  " + ts);
            }
            System.out.println();
        }

        // Test theme detection
       var techWords = Arrays.asList("COMPUTER", "INTERNET", "SOFTWARE", "DATA");
       var detected  = detectTheme(techWords);
        System.out.println("Detected theme for tech words: " + detected);

        // Test filtering
       var allWords = Arrays.asList(
                "POLITIEK", "COMPUTER", "AUTO", "VOETBAL", "INTERNET", "BOOM"
                                   );
       var filtered = filterByTheme(allWords, "technologie", 0.5);
        System.out.println("\nFiltered for 'technologie' (min 0.5): " + filtered);
    }
}