若干改进

particles.py

@@ -2,7 +2,7 @@ import pathlib
 import toml
 import time
 import auxiliary as aux
-
+from typing import List
 
 class Electron:
     """电子: 记忆分析元数据及算法"""
@@ -183,7 +183,7 @@ class NucleonUnion:
                 lst.append(Nucleon(i, all[i]))
             self.keydata = all["keydata"]
             self.testdata = all["testdata"]
-            self.nucleons = lst
+            self.nucleons: List[Nucleon] = lst
             self.nucleons_dict = {i.content: i for i in lst}
 
     def __len__(self):

puzzles.py

@@ -1,11 +1,11 @@
 import random
 
 
-class Puzzle:
+class BasePuzzle:
     pass
 
 
-class BlankPuzzle(Puzzle):
+class BlankPuzzle(BasePuzzle):
     """填空题谜题生成器
     
     Args:
@@ -41,7 +41,7 @@ class BlankPuzzle(Puzzle):
         return f"{self.wording}\n{str(self.answer)}"
 
 
-class SelectionPuzzle(Puzzle):
+class SelectionPuzzle(BasePuzzle):
     """选择题谜题生成器
     
     Args:

reactor_k.py

@@ -0,0 +1,76 @@
+import particles as pt
+import auxiliary as aux
+import time
+from typing import List
+
+class BaseScheduler():
+    "调度器接口"
+    
+    def revisor(self, electron: pt.Electron, quality: int):
+        """由 quality 更新电子的记忆参数"""
+        pass
+    
+    def get_atoms_for_review(self, electron_file: pt.ElectronUnion):
+        """从电子文件中筛选出当前需要复习的所有原子"""
+        pass
+    
+    def get_atoms_for_learning(self, nucleon_file: pt.NucleonUnion, limit: int):
+        """从核子文件中获取待学习的新原子"""
+        pass
+    
+class SM2Scheduler(BaseScheduler):
+    "基于 SM-2 的调度器实现"
+    def revisor(self, electron: pt.Electron, quality: int, is_new_activation):
+        print(f"REVISOR: {quality}, {is_new_activation}")
+        if quality == -1:
+            return -1
+
+        electron.metadata['efactor'] = electron.metadata['efactor'] + (
+            0.1 - (5 - quality) * (0.08 + (5 - quality) * 0.02)
+        )
+        electron.metadata['efactor'] = max(1.3, electron.metadata['efactor'])
+
+        if quality < 3:
+            # 若保留率低于 3，重置重复次数
+            electron.metadata['rept'] = 0
+            electron.metadata['interval'] = 0  # 设为0，以便下面重新计算 I(1)
+        else:
+            electron.metadata['rept'] += 1
+
+        electron.metadata['real_rept'] += 1
+
+        if is_new_activation:  # 初次激活
+            electron.metadata['rept'] = 0
+            electron.metadata['efactor'] = 2.5
+
+        if electron.metadata['rept'] == 0:  # 刚被重置或初次激活后复习
+            electron.metadata['interval'] = 1  # I(1)
+        elif electron.metadata['rept'] == 1:
+            electron.metadata['interval'] = 6  # I(2) 经验公式
+        else:
+            electron.metadata['interval'] = round(
+                electron.metadata['interval'] * electron.metadata['efactor']
+            )
+
+        electron.metadata['last_date'] = aux.get_daystamp()
+        electron.metadata['next_date'] = aux.get_daystamp() + electron.metadata['interval']
+        electron.metadata['last_modify'] = time.time()
+
+    def get_atoms_for_learning(self, nucleon_file: pt.NucleonUnion, limit: int):
+        def electron_dict_get_fallback(key) -> pt.Electron:
+            value = self.electron_dict.get(key)
+            # 如果值不存在，则设置默认值
+            if value is None:
+                value = pt.Electron(key, {})  # 获取默认值
+                self.electron_dict[key] = value  # 将默认值存入字典
+                electron_file.sync()
+            return value  # 返回获取的值（可能是默认值）
+
+        for i in nucleon_file.nucleons:
+            if i.metadata
+
+    def get_atoms_for_review(self, electron_file: pt.ElectronUnion):
+        return super().get_atoms_for_review(electron_file)
+    
+class FSRSScheduler():
+    "基于 FSRS 的调度器实现"