287 lines
9.2 KiB
Python
287 lines
9.2 KiB
Python
import pathlib
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import toml
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import time
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import auxiliary as aux
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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'] = aux.get_daystamp()
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self.metadata['next_date'] = aux.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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class Nucleon:
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"""核子: 材料元数据"""
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def __init__(self, content: str, data: dict):
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self.metadata = data
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self.content = 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 __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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def __hash__(self):
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return hash(self.content)
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@staticmethod
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def placeholder():
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return Nucleon("核子对象样例内容", {})
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class NucleonUnion:
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"""
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替代原有 NucleonFile 类, 支持复杂逻辑
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Attributes:
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path (Path): 对应于 NucleonUnion 实例的文件路径。
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name (str): 核联对象的显示名称，从文件名中派生。
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nucleons (list): 内部核子对象的列表。
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nucleons_dict (dict): 内部核子对象的字典，以核子内容作为键。
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keydata (dict): 核子对象字典键名的翻译。
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testdata (dict): 记忆测试项目的元数据。
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Parameters:
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path (Path): 包含核子数据的文件路径。
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"""
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def __init__(self, path):
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self.path = path
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self.name = path.name.replace(path.suffix, "")
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with open(path, 'r') as f:
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all = toml.load(f)
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lst = list()
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for i in all.keys():
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if "data" in i:
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continue
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lst.append(Nucleon(i, all[i]))
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self.keydata = all["keydata"]
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self.testdata = all["testdata"]
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self.nucleons = lst
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self.nucleons_dict = {i.content: i for i in lst}
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def __len__(self):
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return len(self.nucleons)
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def save(self):
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with open(self.path, 'w') as f:
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tmp = {i.content: i.metadata for i in self.nucleons}
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toml.dump(tmp, f)
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class ElectronUnion:
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"""取代原有 ElectronFile 类, 以支持复杂逻辑"""
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def __init__(self, path):
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self.path = path
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self.name = path.name.replace(path.suffix, "")
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with open(path, 'r') as f:
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all = toml.load(f)
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lst = list()
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for i in all.keys():
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lst.append(Electron(i, all[i]))
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self.electrons = lst
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self.electrons_dict = {i.content: i for i in lst}
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def sync(self):
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"""同步 electrons_dict 中新增对到 electrons 中"""
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self.electrons = self.electrons_dict.values()
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def save(self):
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# print(1)
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with open(self.path, 'w') as f:
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tmp = {i.content: i.metadata for i in self.electrons}
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# print(tmp)
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toml.dump(tmp, f)
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"""
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class AtomicFile():
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def __init__(self, path, type_="unknown"):
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self.path = path
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self.type_ = type_
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if type_ == "nucleon":
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self.name, self.datalist = Nucleon.import_from_file(pathlib.Path(path))
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if type_ == "electron":
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self.name, self.datalist = Electron.import_from_file(pathlib.Path(path))
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def save(self):
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dictobj = {i.content: i.export_data() for i in self.datalist}
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print(dictobj)
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if self.type_ == "nucleon":
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Nucleon.save_to_file(dictobj, self.path)
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if self.type_ == "electron":
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Electron.save_to_file(dictobj, self.path)
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def get_full_content(self):
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if self.type_ == "nucleon":
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text = ""
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for i in self.datalist:
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text += i.content
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return text
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return ""
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def get_len(self):
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return len(self.datalist)
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"""
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class Atom:
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@staticmethod
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def placeholder():
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return (Electron.placeholder(), Nucleon.placeholder(), {})
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@staticmethod
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def advanced_placeholder():
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return (
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Electron("两只黄鹤鸣翠柳", {}),
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Nucleon(
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"两只黄鹤鸣翠柳",
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{
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"note": [],
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"translation": "臣子李密陈言：我因命运不好，小时候遭遇到了不幸",
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"keyword_note": {
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"险衅": "凶险祸患（这里指命运不好）",
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"夙": "早时，这里指年幼的时候",
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"闵": "通'悯'，指可忧患的事",
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"凶": "不幸，指丧父"
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}
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}
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),
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{
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"keydata": {
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"note": "笔记",
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"keyword_note": "关键词翻译",
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"translation": "语句翻译"
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},
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"testdata": {
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"additional_inf": ["translation", "note", "keyword_note"],
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"fill_blank_test": ["translation"],
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"draw_card_test": ["keyword_note"]
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},
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"is_new_activation": 0
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}
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) |