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218
pyground/sugar/targetScoreGenerator.py
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218
pyground/sugar/targetScoreGenerator.py
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from time import time
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import json
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import random
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from typing import List, Dict, Tuple, Optional
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import time
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from SugarRush1000 import SugarRush1000
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class SugarRushSimulator:
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def __init__(self, buy_type: Optional[str] = None):
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self.buy_type = buy_type
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self.f = open(
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f"simulator_log_{'normal' if buy_type is None else buy_type}_{time.time()}.log",
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"w",
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)
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def check_target_score(self, score, target_scores):
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for i in range(len(target_scores)):
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if score[i] < target_scores[i][2]:
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return False
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return True
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def getIndex(self, score, target_scores):
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for i in range(len(target_scores)):
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if score > target_scores[i][0] and score <= target_scores[i][1]:
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return i
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return -1
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def simulate_batch(
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self, weights, scotter_counts_weights, target_scores: List[Tuple[int, int, int]]
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) -> Dict:
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"""
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模拟指定次数的旋转
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:param target_scores: 模拟目标分数范围
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:param buy_type: None=普通混合模式, 'standard'=只测买普通, 'super'=只测买超级
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:return: 统计结果
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"""
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begin_balance = 1_0000_0000
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game = SugarRush1000(
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balance=begin_balance,
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weights=weights,
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scotter_counts_weights=scotter_counts_weights,
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)
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total_bet = 0.0
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total_win = 0.0
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game_spins = []
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index = 0
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real_score_counts = [0 for _ in target_scores]
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while True:
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if self.check_target_score(real_score_counts, target_scores):
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break
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spin = {
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"gid": index + 1,
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"score": 0,
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"count": 0,
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"feature": "normal" if self.buy_type is None else self.buy_type,
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"extra_free": 0,
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"steps": [],
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}
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bet = 0
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if self.buy_type and self.buy_type != "normal":
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r = game.buy_free_spins(self.buy_type)
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bet = r["cost"]
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can_spins = 1
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free_spind_id = 0
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aes = 0
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while can_spins > 0:
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can_spins -= 1
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res = game.doSpin()
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game.mock_grid = None
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if res["error"]:
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raise Exception("模拟器异常", res["error"])
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if res["free_spins_remaining"] >= 0:
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can_spins = res["free_spins_remaining"]
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actual_cost = res["actual_bet"]
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if actual_cost > 0:
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bet = actual_cost
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free_spind_id += 1
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for step in res["steps"]:
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step["gid"] = spin["gid"]
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step["free_spin_id"] = free_spind_id
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step["aes"] = aes
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aes += 1
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spin["steps"].append(step)
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if res["extra_free"]:
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spin["extra_free"] += 1
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spin["score"] = res["spin_total_win"]
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spin["count"] = len(spin["steps"])
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range_index = self.getIndex(spin["score"], target_scores)
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if (
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range_index < 0
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or real_score_counts[range_index] >= target_scores[range_index][2]
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):
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continue
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real_score_counts[range_index] += 1
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total_win += spin["score"]
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total_bet += bet
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game_spins.append(spin)
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if len(game_spins) >= 100:
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self.write_log(game_spins)
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game_spins = []
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index += 1
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if len(game_spins) > 0:
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self.write_log(game_spins)
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game_spins = []
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print(f"旋转{index} 次，RTP {(total_win / total_bet) * 100}")
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return {}
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def write_log(self, games):
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buf = ""
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for game in games:
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buf += json.dumps(game, ensure_ascii=False) + "\n"
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self.f.write(buf)
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self.f.flush()
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if __name__ == "__main__":
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scotter_count_weights = {
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"3": 7.26421894353717,
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"4": 4.1724734692682395,
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"5": 0.8119106579617028,
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"6": 0.20313929837878217,
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"7": 0.04857599989214818,
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}
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batchs = [
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# {
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# "buy_type": "normal",
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# "weights": {
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# "A": 16.559326336631095,
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# "B": 17.242437197138468,
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# "C": 23.794844051571708,
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# "D": 24.480364769888073,
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# "E": 31.29327382410323,
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# "F": 38.17160528628571,
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# "G": 17.242437197138468,
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# "S": 2.2546844695944754,
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# },
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# "target_score": [(0,1, 500),
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# (1,5, 500),
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# (5,10, 500),
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# (10,20, 500)],
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# "scotter_count_weights": scotter_count_weights,
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# },
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# {
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# "buy_type": "standard",
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# "weights": {
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# "A": 18.92167765262542,
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# "B": 21.106974838197058,
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# "C": 31.250953223681833,
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# "D": 34.54623003651251,
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# "E": 47.52175529241897,
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# "F": 62.474728710698884,
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# "G": 21.106974838197058,
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# "S": 2.666109542063759,
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# },
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# "scotter_count_weights": scotter_count_weights,
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# "target_score": [(20, 30, 500),
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# (30, 50, 500),
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# (50, 100, 500),
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# (100, 200, 500),
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# (200, 300, 500),
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# (300, 400, 500),
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# (400, 500, 500),
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# ],
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# },
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{
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"buy_type": "super",
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"weights": {
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"A": 19.015957779792195,
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"B": 21.291015318701493,
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"C": 31.66660200727613,
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"D": 35.193596023259865,
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"E": 48.7122724047052,
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"F": 64.49005324700025,
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"G": 21.291015318701493,
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"S": 2.6840958157151236,
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},
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"scotter_count_weights": scotter_count_weights,
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"target_score": [
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(80, 120, 500),
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(120, 200, 500),
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(200, 400, 500),
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(400, 600, 500),
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(800, 1000, 500),
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(1000, 1200, 500),
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(1200, 1400, 200),
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(1400, 1600, 200),
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(1600, 1800, 200),
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(1800, 2000, 200),
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],
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},
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]
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for batch in batchs:
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sim = SugarRushSimulator(buy_type=batch["buy_type"])
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sim.simulate_batch(
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batch["weights"], batch["scotter_count_weights"], batch["target_score"]
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)
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