def get_battle_pass_rewards():
_df = tools.read_spec_file('BattlePass', path)
# 免费奖励
_df1 = tools.reset_rewards_to_dict(_df, 'NormalReward')
# 付费奖励
_df2 = tools.reset_rewards_to_dict(_df, 'PaidReward')
_rewards = {}
for _t in rewards_type:
_rewards[_t] = 0
if _t in _df1.columns:
# 将通行证统一处理为45天，免费奖励用1级，付费奖励用5级
_rewards[_t] += int(
_df1.loc[(_df1['PassLevel'] == 1) & (_df1['Level'] <= battle_pass_level), _t].sum() * days / 45)
if is_buy_battle_pass:
_rewards[_t] += int(
_df2.loc[(_df2['PassLevel'] == 5) & (_df2['Level'] <= battle_pass_level), _t].sum() * days / 45)
return _rewards
def get_adventure_rewards():
df = tools.read_spec_file('MapUnit', path)
df = df.drop(df[(df['Id'] > 500000) | (df['Id'] < 100000) |
((df['Type'] != 31) & (df['Type'] != 27))].index)
df = df.reset_index()
df['Adventure'] = df['Id'].apply(get_adventure_id)
df = tools.reset_rewards_to_dict(df, 'Param3')
return get_sum_rewards(df, 'Adventure', adventure)
def get_rank_rewards():
df = tools.read_spec_file('Rank', path)
df = tools.reset_rewards_to_dict(df, 'MissionReward')
_rewards = get_sum_rewards(df, 'Id', 999999)
# 排行榜奖励按天数发放 100天为上限
for _t in _rewards:
_rewards[_t] = int(_rewards[_t] * min(days / 100, 1.0))
return _rewards
def get_seven_day_rewards():
df = tools.read_spec_file('Configs', path)
seven_day_reward = tools.get_specific_property(df, 'value', 'key',
'SevenDaysReward')
_rs = seven_day_reward.split('#S#')
df = pd.DataFrame(_rs, index=range(1, 8), columns=['Reward'])
df['Day'] = range(1, 8)
df = tools.reset_rewards_to_dict(df, 'Reward')
_rewards = get_sum_rewards(df, 'Day', days)
return _rewards
def get_daily_mission_rewards():
_df = tools.read_spec_file('MissionDailyReward', path)
_df = tools.reset_rewards_to_dict(_df, 'Reward')
_rewards = {}
for _t in rewards_type:
_rewards[_t] = 0
if _t in _df.columns:
_rewards[_t] += int(
_df.loc[(_df['DailyType'] == 0) & (_df['ActivityRequire'] <= daily_mission_progress), _t].sum() * days)
_rewards[_t] += int(_df.loc[(_df['DailyType'] == 1) & (
_df['ActivityRequire'] <= weekly_mission_progress), _t].sum() * weeks)
return _rewards
def get_extreme_rewards():
df = tools.read_spec_file('ExtremeSimulation', path)
df = tools.reset_rewards_to_dict(df, 'Reward')
_rewards = {}
for _t in rewards_type:
_rewards[_t] = 0
if _t in df.columns:
_rewards[_t] += df.loc[(df['ExtremeType'] == 11) &
(df['Floor'] < extreme_standard), _t].sum()
_rewards[_t] += df.loc[((df['ExtremeType'] == 1) |
(df['ExtremeType'] == 2) |
(df['ExtremeType'] == 3)
| (df['ExtremeType'] == 4)) &
(df['Floor'] < extreme_race), _t].sum()
return _rewards
def get_commission_rewards():
_df = tools.read_spec_file('Commission', path)
# 将金币奖励改为2小时金币奖励，要奖励结果/7200
_df['coin'] = ';prop,402,'
_df['Reward'] = _df['Reward'] + _df['coin'] + _df['CoinAfkTime'].map(str)
_df = tools.reset_rewards_to_dict(_df, 'Reward')
if 'prop_402' in _df.columns:
_df['prop_402'] /= 7200
# 将统一委托等级下的各种奖励取平均，方便计算
_df = _df.groupby(['CommissionLevel', 'Type']).mean().fillna(0).reset_index() # 计算的结果要除以2，因为要跟金币平分概率
# 通过委托等级表，拆分出各个等级下刷新不同委托任务的权重
_df_lv = tools.read_spec_file('CommissionLevel', path)
_df_lv = tools.reset_dict_str_to_dict(_df_lv, 'CommissionWeight')
_df_lv.drop(_df_lv.columns.difference(['CommissionLevel', 'CommissionWeight', 'CommissionWeightTeam']), axis=1,
inplace=True)
_df_lv = tools.reset_dict_str_to_dict(_df_lv, 'CommissionWeightTeam')
_df_lv.drop(_df_lv.columns.difference(['CommissionLevel', 'CommissionWeight', 'CommissionWeightTeam']), axis=1,
inplace=True)
# 根据不同天数对应的委托等级，计算委托奖励
# 等级与天数对应：5:2;14:3;39,4;89,5;152,6;195,7;99999,8
_rewards = separate_commission(_df, 5, 0, _df_lv['CommissionWeight'][1], _df_lv['CommissionWeightTeam'][1])
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 14, 5, _df_lv['CommissionWeight'][2],
_df_lv['CommissionWeightTeam'][2]))
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 39, 14, _df_lv['CommissionWeight'][3],
_df_lv['CommissionWeightTeam'][3]))
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 89, 39, _df_lv['CommissionWeight'][4],
_df_lv['CommissionWeightTeam'][4]))
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 152, 89, _df_lv['CommissionWeight'][5],
_df_lv['CommissionWeightTeam'][5]))
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 195, 152, _df_lv['CommissionWeight'][6],
_df_lv['CommissionWeightTeam'][6]))
_rewards = tools.combine_dict(_rewards, separate_commission(_df, 999999, 195, _df_lv['CommissionWeight'][7],
_df_lv['CommissionWeightTeam'][7]))
return _rewards
def get_mission_rewards(
): # _stage, _chapter, _extreme, _race_extreme, _days, _arena, _player_lv):
df = tools.read_spec_file('Mission', path)
df = tools.reset_rewards_to_dict(df, 'Reward')
_rewards = {}
for _t in rewards_type:
_rewards[_t] = 0
if _t in df.columns:
# 类型1：通关
_rewards[_t] += df.loc[(df['MissionType'] == 1) &
(df['Target'] < stage), _t].sum()
print(_rewards)
# 类型2：拥有英雄数量
_rewards[_t] += df.loc[(df['MissionType'] == 2) &
(df['Target'] <= cards_count), _t].sum()
print(_rewards)
# 类型3：竞技场历史最大积分
_rewards[_t] += df.loc[(df['MissionType'] == 3) &
(df['Target'] <= arena_max_score),
_t].sum()
print(_rewards)
# 类型4：竞技场胜利场数
_rewards[_t] += df.loc[(df['MissionType'] == 4) &
(df['Target'] <= arena_win_count),
_t].sum()
print(_rewards)
# 类型5：通章
_rewards[_t] += df.loc[(df['MissionType'] == 5) &
(df['Target'] < chapter), _t].sum()
print(_rewards)
# 类型6：通关标准极限试炼
_rewards[_t] += df.loc[(df['MissionType'] == 6) &
(df['Target'] < extreme_standard),
_t].sum()
print(_rewards)
# 类型35：通关类型极限试炼
_rewards[_t] += df.loc[(df['MissionType'] == 35) &
(df['Target'] < extreme_race), _t].sum()
print(_rewards)
# 类型7/ 8/ 10/ 11/ 12/ 14/ 19
# Discord/Facebook/Twitter/Website/JoinGuild/1PurpleHero/OasisAccount
_rewards[_t] += df.loc[(df['MissionType'] == 7) |
(df['MissionType'] == 8) |
(df['MissionType'] == 10)
| (df['MissionType'] == 11) |
(df['MissionType'] == 12) |
(df['MissionType'] == 14)
| (df['MissionType'] == 19), _t].sum()
print(_rewards)
# 类型13：挂机现金总量
_rewards[_t] += df.loc[(df['MissionType'] == 13) &
(df['Target'] <= afk_cash_count), _t].sum()
print(_rewards)
# 类型15：最大英雄等级
_rewards[_t] += df.loc[(df['MissionType'] == 15) &
(df['Target'] <= max_hero_level), _t].sum()
print(_rewards)
# 类型16：通关强者之路次数
_rewards[_t] += df.loc[(df['MissionType'] == 16) & (df['Target'] <=
(days / 2)),
_t].sum()
print(_rewards)
# 类型17：共鸣水晶等级
_rewards[_t] += df.loc[(df['MissionType'] == 17) &
(df['Target'] <= connect_level), _t].sum()
print(_rewards)
# 类型18：共鸣水晶槽数
_rewards[_t] += df.loc[(df['MissionType'] == 18) &
(df['Target'] <= connect_holes), _t].sum()
print(_rewards)
# 类型20：队伍等级
_rewards[_t] += df.loc[(df['MissionType'] == 20) &
(df['Target'] <= player_level), _t].sum()
print(_rewards)
return _rewards
def get_stage_rewards():
df = tools.read_spec_file('Stage', path)
df = tools.reset_rewards_to_dict(df, 'Reward')
return get_sum_rewards(df, 'Id', stage)
def get_mission_newbie_rewards():
df = tools.read_spec_file('MissionNewbie', path)
df = tools.reset_rewards_to_dict(df, 'Reward')
# 默认达到天数即完成
_rewards = get_sum_rewards(df, 'Day', days)
return _rewards
