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127 lines
4.3 KiB
Python
127 lines
4.3 KiB
Python
#!/usr/bin/env python3
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import pathlib
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import toml
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import time
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import heurams.services.timer as timer
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class Electron:
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"""电子: 记忆分析元数据及算法"""
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algorithm = "SM-2" # 暂时使用 SM-2 算法进行记忆拟合, 考虑 SM-15 替代
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def __init__(self, content: str, metadata: dict):
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self.content = content
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self.metadata = metadata
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if metadata == {}:
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# print("NULL")
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self._default_init()
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def _default_init(self):
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defaults = {
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'efactor': 2.5, # 易度系数, 越大越简单, 最大为5
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'real_rept': 0, # (实际)重复次数
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'rept': 0, # (有效)重复次数
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'interval': 0, # 最佳间隔
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'last_date': 0, # 上一次复习的时间戳
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'next_date': 0, # 将要复习的时间戳
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'is_activated': 0, # 激活状态
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# *NOTE: 此处"时间戳"是以天为单位的整数, 即 UNIX 时间戳除以一天的秒数取整
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'last_modify': time.time() # 最后修改时间戳(此处是UNIX时间戳)
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}
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self.metadata = defaults
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def activate(self):
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self.metadata['is_activated'] = 1
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self.metadata['last_modify'] = time.time()
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def modify(self, var: str, value):
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if var in self.metadata:
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self.metadata[var] = value
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self.metadata['last_modify'] = time.time()
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else:
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print(f"警告: '{var}' 非已知元数据字段")
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def revisor(self, quality: int = 5, is_new_activation: bool = False):
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"""SM-2 算法迭代决策机制实现
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根据 quality(0 ~ 5) 进行参数迭代最佳间隔
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quality 由主程序评估
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Args:
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quality (int): 记忆保留率量化参数
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"""
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print(f"REVISOR: {quality}, {is_new_activation}")
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if quality == -1:
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return -1
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self.metadata['efactor'] = self.metadata['efactor'] + (
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0.1 - (5 - quality) * (0.08 + (5 - quality) * 0.02)
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)
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self.metadata['efactor'] = max(1.3, self.metadata['efactor'])
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if quality < 3:
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# 若保留率低于 3，重置重复次数
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self.metadata['rept'] = 0
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self.metadata['interval'] = 0 # 设为0，以便下面重新计算 I(1)
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else:
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self.metadata['rept'] += 1
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self.metadata['real_rept'] += 1
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if is_new_activation: # 初次激活
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self.metadata['rept'] = 0
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self.metadata['efactor'] = 2.5
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if self.metadata['rept'] == 0: # 刚被重置或初次激活后复习
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self.metadata['interval'] = 1 # I(1)
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elif self.metadata['rept'] == 1:
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self.metadata['interval'] = 6 # I(2) 经验公式
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else:
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self.metadata['interval'] = round(
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self.metadata['interval'] * self.metadata['efactor']
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)
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self.metadata['last_date'] = timer.get_daystamp()
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self.metadata['next_date'] = timer.get_daystamp() + self.metadata['interval']
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self.metadata['last_modify'] = time.time()
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def __str__(self):
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return (
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f"记忆单元预览 \n"
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f"内容: '{self.content}' \n"
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f"易度系数: {self.metadata['efactor']:.2f} \n"
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f"已经重复的次数: {self.metadata['rept']} \n"
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f"下次间隔: {self.metadata['interval']} 天 \n"
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f"下次复习日期时间戳: {self.metadata['next_date']}"
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)
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def __eq__(self, other):
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if self.content == other.content:
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return True
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return False
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def __hash__(self):
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return hash(self.content)
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def __getitem__(self, key):
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if key == "content":
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return self.content
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if key in self.metadata:
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return self.metadata[key]
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else:
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raise KeyError(f"Key '{key}' not found in metadata.")
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def __setitem__(self, key, value):
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if key == "content":
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raise AttributeError("content 应为只读")
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self.metadata[key] = value
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self.metadata['last_modify'] = time.time()
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def __iter__(self):
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yield from self.metadata.keys()
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def __len__(self):
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return len(self.metadata)
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@staticmethod
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def placeholder():
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return Electron("电子对象样例内容", {})
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