import json
from datetime import datetime

class LotteryPredictorV6:
    def __init__(self, stats_path):
        with open(stats_path, 'r', encoding='utf-8') as f:
            self.stats = json.load(f)
        # self.result_weights = {'time': 0.83, 'week': 0.14, 'date': 0.03}
        self.result_weights = {'time': 0.9, 'week': 0.05, 'date': 0.05}
        self.result_detail_weights = {'time': 0.9, 'week': 0.05, 'date': 0.05}
        self.winner_weights = {'time': 0.9, 'week': 0.05, 'date': 0.05}
        self.gd_weights = {'time': 0.9, 'week': 0.05, 'date': 0.05}
        self.glh_weights = {'time': 0.9, 'week': 0.05, 'date': 0.05}

    def predict(self, date_str, time_str):
        dt = datetime.strptime(date_str, '%Y-%m-%d')
        day_of_month = str(dt.day)
        day_of_week = str(dt.weekday())

        t_stats = self.stats['by_time'].get(time_str, {})
        d_stats = self.stats['by_date'].get(day_of_month, {})
        w_stats = self.stats['by_week'].get(day_of_week, {})

        raw_probs = {
            'digital_pos': {},
            'pos_detail': {},
            'winner_prob': {},
            'direct_gd1': {},
            'direct_gd2': {},
            'glh_pos': {}
        }

        # 1. 数字位置概率
        for i in range(10):
            pos_key = f'pos_{i}'
            combined = {}
            for val in range(1, 11):
                v = str(val)
                p = (t_stats.get('result_pos_prob', {}).get(pos_key, {}).get(v, 0) * self.result_weights['time'] +
                     w_stats.get('result_pos_prob', {}).get(pos_key, {}).get(v, 0) * self.result_weights['week'] +
                     d_stats.get('result_pos_prob', {}).get(pos_key, {}).get(v, 0) * self.result_weights['date'])
                combined[v] = p
            raw_probs['digital_pos'][pos_key] = combined

        # 2. 位置详情 (单双大小)
        for i in range(10):
            pos_key = f'pos_{i}'
            raw_probs['pos_detail'][pos_key] = {'big_small': {}, 'odd_even': {}}
            for cat in ['big_small', 'odd_even']:
                options = ['大', '小'] if cat == 'big_small' else ['单', '双']
                for opt in options:
                    p = (t_stats.get('result_pos_detail_prob', {}).get(pos_key, {}).get(cat, {}).get(opt, 0) * self.result_detail_weights['time'] +
                         w_stats.get('result_pos_detail_prob', {}).get(pos_key, {}).get(cat, {}).get(opt, 0) * self.result_detail_weights['week'] +
                         d_stats.get('result_pos_detail_prob', {}).get(pos_key, {}).get(cat, {}).get(opt, 0) * self.result_detail_weights['date'])
                    raw_probs['pos_detail'][pos_key][cat][opt] = p

        # 3. 冠亚和
        for val in range(3, 20):
            v = str(val)
            p = (t_stats.get('winner_prob', {}).get(v, 0) * self.winner_weights['time'] +
                 w_stats.get('winner_prob', {}).get(v, 0) * self.winner_weights['week'] +
                 d_stats.get('winner_prob', {}).get(v, 0) * self.winner_weights['date'])
            raw_probs['winner_prob'][v] = p

        # 4. GD1 & GD2
        for cat, opts in [('direct_gd1', ['冠亚大', '冠亚小']), ('direct_gd2', ['冠亚单', '冠亚双'])]:
            stat_key = 'GD1_prob' if cat == 'direct_gd1' else 'GD2_prob'
            for opt in opts:
                p = (t_stats.get(stat_key, {}).get(opt, 0) * self.gd_weights['time'] +
                     w_stats.get(stat_key, {}).get(opt, 0) * self.gd_weights['week'] +
                     d_stats.get(stat_key, {}).get(opt, 0) * self.gd_weights['date'])
                raw_probs[cat][opt] = p

        # 5. 龙虎
        for i in range(5):
            pos_key = f'pos_{i}'
            raw_probs['glh_pos'][pos_key] = {}
            for opt in ['龙', '虎']:
                p = (t_stats.get('GLH_pos_prob', {}).get(pos_key, {}).get(opt, 0) * self.glh_weights['time'] +
                     w_stats.get('GLH_pos_prob', {}).get(pos_key, {}).get(opt, 0) * self.glh_weights['week'] +
                     d_stats.get('GLH_pos_prob', {}).get(pos_key, {}).get(opt, 0) * self.glh_weights['date'])
                raw_probs['glh_pos'][pos_key][opt] = p

        return raw_probs