287 lines
9.2 KiB
Python
287 lines
9.2 KiB
Python
"""
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SM-15 接口兼容实现, 基于 SM-15 算法的逆向工程
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全局状态保存在文件中, 项目状态通过 algodata 字典传递
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基于: https://github.com/slaypni/sm.js
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原始 CoffeeScript 代码: (c) 2014 Kazuaki Tanida
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MIT 许可证
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"""
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import datetime
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import json
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import os
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import pathlib
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from typing import TypedDict
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from heurams.context import config_var
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from heurams.kernel.algorithms.sm15m_calc import (MAX_AF, MIN_AF, NOTCH_AF,
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RANGE_AF, RANGE_REPETITION,
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SM, THRESHOLD_RECALL, Item)
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# 全局状态文件路径
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_GLOBAL_STATE_FILE = os.path.expanduser(
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pathlib.Path(config_var.get()["paths"]["global_dir"]) / "sm15m_global_state.json"
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)
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def _get_global_sm():
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"""获取全局 SM 实例, 从文件加载或创建新的"""
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if os.path.exists(_GLOBAL_STATE_FILE):
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try:
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with open(_GLOBAL_STATE_FILE, "r", encoding="utf-8") as f:
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data = json.load(f)
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sm_instance = SM.load(data)
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return sm_instance
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except Exception:
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# 如果加载失败, 创建新的实例
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pass
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# 创建新的 SM 实例
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sm_instance = SM()
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# 保存初始状态
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_save_global_sm(sm_instance)
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return sm_instance
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def _save_global_sm(sm_instance):
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"""保存全局 SM 实例到文件"""
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try:
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data = sm_instance.data()
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with open(_GLOBAL_STATE_FILE, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2)
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except Exception:
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# 忽略保存错误
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pass
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class SM15MAlgorithm:
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algo_name = "SM-15M"
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class AlgodataDict(TypedDict):
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efactor: float
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real_rept: int
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rept: int
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interval: int
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last_date: int
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next_date: int
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is_activated: int
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last_modify: float
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defaults = {
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"efactor": 2.5,
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"real_rept": 0,
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"rept": 0,
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"interval": 0,
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"last_date": 0,
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"next_date": 0,
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"is_activated": 0,
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"last_modify": 0.0,
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}
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@classmethod
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def _get_timestamp(cls):
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"""获取当前时间戳(秒)"""
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return datetime.datetime.now().timestamp()
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@classmethod
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def _get_daystamp(cls):
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"""获取当前天数戳(从某个纪元开始的天数)"""
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# 使用与原始 SM-2 相同的纪元：1970-01-01
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now = datetime.datetime.now()
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epoch = datetime.datetime(1970, 1, 1)
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delta = now - epoch
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return delta.days
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@classmethod
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def _algodata_to_item(cls, algodata, sm_instance):
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"""将 algodata 转换为 Item 实例"""
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# 从 algodata 获取 SM-2 数据
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sm15_data = algodata.get(cls.algo_name, cls.defaults.copy())
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# 创建 Item 实例
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item = Item(sm_instance)
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# 映射字段
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# efactor -> A-Factor (需要转换)
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efactor = sm15_data.get("efactor", 2.5)
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# SM-2 的 efactor 范围 [1.3, 2.5+], SM-15 的 A-Factor 范围 [1.2, 6.9]
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# 简单线性映射：af = (efactor - 1.3) * (MAX_AF - MIN_AF) / (2.5 - 1.3) + MIN_AF
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# 但 efactor 可能大于 2.5, 所以需要限制
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af = max(MIN_AF, min(MAX_AF, efactor * 2.0)) # 粗略映射
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# 调试
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# print(f"DEBUG: efactor={efactor}, af before set={af}")
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item.af(af)
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# print(f"DEBUG: item.af() after set={item.af()}")
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# rept -> repetition (成功回忆次数)
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rept = sm15_data.get("rept", 0)
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item.repetition = (
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rept - 1 if rept > 0 else -1
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) # SM-15 中 repetition=-1 表示新项目
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# real_rept -> lapse? 或者忽略
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real_rept = sm15_data.get("real_rept", 0)
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# 可以存储在 value 中或忽略
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# interval -> optimum_interval (需要从天数转换为毫秒)
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interval_days = sm15_data.get("interval", 0)
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if interval_days == 0:
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item.optimum_interval = sm_instance.interval_base
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else:
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item.optimum_interval = interval_days * 24 * 60 * 60 * 1000 # 天转毫秒
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# last_date -> previous_date
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last_date_days = sm15_data.get("last_date", 0)
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if last_date_days > 0:
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epoch = datetime.datetime(1970, 1, 1)
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item.previous_date = epoch + datetime.timedelta(days=last_date_days)
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# next_date -> due_date
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next_date_days = sm15_data.get("next_date", 0)
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if next_date_days > 0:
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epoch = datetime.datetime(1970, 1, 1)
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item.due_date = epoch + datetime.timedelta(days=next_date_days)
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# is_activated 和 last_modify 忽略
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# 将原始 algodata 保存在 value 中以便恢复
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item.value = {
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"front": "SM-15 item",
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"back": "SM-15 item",
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"_sm15_data": sm15_data,
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}
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return item
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@classmethod
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def _item_to_algodata(cls, item, algodata):
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"""将 Item 实例状态写回 algodata"""
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if cls.algo_name not in algodata:
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algodata[cls.algo_name] = cls.defaults.copy()
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sm15_data = algodata[cls.algo_name]
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# A-Factor -> efactor (反向映射)
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af = item.af()
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if af is None:
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af = MIN_AF
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# 反向粗略映射
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efactor = max(1.3, min(af / 2.0, 10.0)) # 限制范围
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# 调试
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# print(f"DEBUG: item.af()={af}, computed efactor={efactor}")
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sm15_data["efactor"] = efactor
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# repetition -> rept
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rept = item.repetition + 1 if item.repetition >= 0 else 0
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sm15_data["rept"] = rept
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# real_rept: 递增在 revisor 中处理, 这里保持不变
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# 但如果没有 real_rept 字段, 则初始化为0
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if "real_rept" not in sm15_data:
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sm15_data["real_rept"] = 0
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# optimum_interval -> interval (毫秒转天)
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interval_ms = item.optimum_interval
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if interval_ms == item.sm.interval_base:
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sm15_data["interval"] = 0
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else:
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interval_days = max(0, round(interval_ms / (24 * 60 * 60 * 1000)))
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sm15_data["interval"] = interval_days
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# previous_date -> last_date
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if item.previous_date:
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epoch = datetime.datetime(1970, 1, 1)
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last_date_days = (item.previous_date - epoch).days
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sm15_data["last_date"] = last_date_days
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else:
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sm15_data["last_date"] = 0
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# due_date -> next_date
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if item.due_date:
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epoch = datetime.datetime(1970, 1, 1)
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next_date_days = (item.due_date - epoch).days
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sm15_data["next_date"] = next_date_days
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else:
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sm15_data["next_date"] = 0
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# is_activated: 保持不变或设为1
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if "is_activated" not in sm15_data:
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sm15_data["is_activated"] = 1
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# last_modify: 更新时间戳
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sm15_data["last_modify"] = cls._get_timestamp()
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return algodata
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@classmethod
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def revisor(
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cls, algodata: dict, feedback: int = 5, is_new_activation: bool = False
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):
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"""SM-15 算法迭代决策机制实现"""
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# 获取全局 SM 实例
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sm_instance = _get_global_sm()
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# 将 algodata 转换为 Item
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item = cls._algodata_to_item(algodata, sm_instance)
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# 处理 is_new_activation
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if is_new_activation:
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# 重置为初始状态
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item.repetition = -1
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item.lapse = 0
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item.optimum_interval = sm_instance.interval_base
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item.previous_date = None
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item.due_date = datetime.datetime.fromtimestamp(0)
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item.af(2.5) # 重置 efactor
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# 将项目临时添加到 SM 实例(以便 answer 更新共享状态)
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sm_instance.q.append(item)
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# 处理反馈(评分)
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# SM-2 的 feedback 是 0-5, SM-15 的 grade 也是 0-5
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grade = feedback
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now = datetime.datetime.now()
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# 调用 answer 方法
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item.answer(grade, now)
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# 更新共享状态(FI-Graph, ForgettingCurves, OFM)
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if item.repetition >= 0:
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sm_instance.forgetting_curves.register_point(grade, item, now)
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sm_instance.ofm.update()
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sm_instance.fi_g.update(grade, item, now)
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# 从队列中移除项目
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sm_instance.q.remove(item)
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# 保存全局状态
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_save_global_sm(sm_instance)
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# 将更新后的 Item 状态写回 algodata
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cls._item_to_algodata(item, algodata)
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# 更新 real_rept(总复习次数)
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algodata[cls.algo_name]["real_rept"] += 1
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@classmethod
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def is_due(cls, algodata):
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"""检查项目是否到期"""
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sm15_data = algodata.get(cls.algo_name, cls.defaults.copy())
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next_date_days = sm15_data.get("next_date", 0)
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current_daystamp = cls._get_daystamp()
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return next_date_days <= current_daystamp
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@classmethod
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def rate(cls, algodata):
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"""获取项目的评分(返回 efactor 字符串)"""
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sm15_data = algodata.get(cls.algo_name, cls.defaults.copy())
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efactor = sm15_data.get("efactor", 2.5)
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return str(efactor)
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@classmethod
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def nextdate(cls, algodata) -> int:
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"""获取下次复习日期(天数戳)"""
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sm15_data = algodata.get(cls.algo_name, cls.defaults.copy())
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next_date_days = sm15_data.get("next_date", 0)
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return next_date_days
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