feat: FAST-0 特殊算法

src/heurams/kernel/algorithms/__init__.py

@@ -1,15 +1,18 @@
 from .base import BaseAlgorithm
 from .sm2 import SM2Algorithm
 from .sm15m import SM15MAlgorithm
+from .fast0 import FAST0Algorithm
 
 __all__ = [
     "SM2Algorithm",
     "BaseAlgorithm",
     "SM15MAlgorithm",
+    "FAST0Algorithm",
 ]
 
 algorithms = {
     "SM-2": SM2Algorithm,
+    "FAST-0": FAST0Algorithm,
     "SM-15M": SM15MAlgorithm,
     "Base": BaseAlgorithm,
 }

src/heurams/kernel/algorithms/fast0.py

@@ -0,0 +1,91 @@
+from typing import TypedDict
+
+import heurams.services.timer as timer
+from heurams.services.logger import get_logger
+
+from .base import BaseAlgorithm
+
+logger = get_logger(__name__)
+
+
+class FAST0Algorithm(BaseAlgorithm):
+    algo_name = "FAST-0"
+
+    class AlgodataDict(TypedDict):
+        real_rept: int
+        rept: int
+        interval: int
+        important: int
+        last_date: int
+        next_date: int
+        is_activated: int
+        last_modify: float
+
+    defaults = {
+        "real_rept": 0,
+        'important': 0,
+        "rept": 0,
+        "interval": 0,
+        "last_date": 0,
+        "next_date": 0,
+        "is_activated": 0,
+        "last_modify": timer.get_timestamp(),
+    }
+
+    @classmethod
+    def revisor(
+        cls, algodata: dict, feedback: int = 5, is_new_activation: bool = False
+    ):
+        """FAST-0 算法迭代决策机制实现
+        根据 quality(0 ~ 5) 进行参数迭代最佳间隔
+        quality 由主程序评估
+
+        Args:
+            quality (int): 记忆保留率量化参数
+        """
+        logger.debug(
+            "FAST0.revisor 开始, feedback: %d, is_new_activation: %s",
+            feedback,
+            is_new_activation,
+        )
+
+        if feedback == -1:
+            logger.debug("feedback 为 -1, 跳过更新")
+            return
+        algodata[cls.algo_name]["interval"] = (1 if feedback <= 3 else float('inf'))
+        algodata[cls.algo_name]["important"] = (1 if feedback <= 3 else algodata[cls.algo_name]["important"])
+        algodata[cls.algo_name]["last_date"] = timer.get_daystamp()
+        algodata[cls.algo_name]["next_date"] = (
+            timer.get_daystamp() + algodata[cls.algo_name]["interval"]
+        )
+        algodata[cls.algo_name]["last_modify"] = timer.get_timestamp()
+
+        logger.debug(
+            "更新日期: last_date=%d, next_date=%d, last_modify=%f",
+            algodata[cls.algo_name]["last_date"],
+            algodata[cls.algo_name]["next_date"],
+            algodata[cls.algo_name]["last_modify"],
+        )
+
+    @classmethod
+    def is_due(cls, algodata):
+        result = algodata[cls.algo_name]["next_date"] <= timer.get_daystamp()
+        logger.debug(
+            "FAST0.is_due: next_date=%d, current_daystamp=%d, result=%s",
+            algodata[cls.algo_name]["next_date"],
+            timer.get_daystamp(),
+            result,
+        )
+        return result
+
+    @classmethod
+    def get_rating(cls, algodata):
+        efactor = algodata[cls.algo_name]["efactor"]
+        logger.debug("FAST0.rate: efactor=%f", efactor)
+        return str(efactor)
+
+    @classmethod
+    def nextdate(cls, algodata) -> int:
+        next_date = algodata[cls.algo_name]["next_date"]
+        logger.debug("FAST0.nextdate: %d", next_date)
+        return next_date