history

Former-commit-id: c078eab42975bcbc5fd98aae28228937b5694d19

ch340.py

@@ -79,7 +79,7 @@ if OFFLINE_DEBUG:
         def pull(self,speed=None,t=None,vol=None):
             self._prepare(speed,t,vol)
             self.start = time.time()
-            time.sleep(self._get_time())
+            time.sleep(self._get_time()/4)
         
         def push_async(self,speed=None,t=None,vol=None):
             self._prepare(speed,t,vol)

main.py

@@ -5,7 +5,7 @@ import numpy as np
 import ch340
 import atexit
 import utils
-from utils import State
+from utils import State, History
 
 
 class MAT:
@@ -26,7 +26,7 @@ class MAT:
         self.state = State(bounce_time, end_bounce_time)
         
         atexit.register(self.ch340.stop)
-        self.history = []
+        self.history = History(max(bounce_time, end_bounce_time))
         self.colored_volume = None
         self.colored_time = None
         self.colored_im = None
@@ -53,7 +53,7 @@ class MAT:
         r = now - st
         ret = self.total_volume - (1-r) * self.speeds[self.state.mode.value]
         if value_only:
-                    return ret
+            return ret
         else:
             self.total_volume = ret
 
@@ -71,16 +71,18 @@ class MAT:
         ret, rate = self.predictor(im)
         if ret is None:
             return None
-        
         now = time.time()
         val = self.process_left(now, value_only=True)
         
-        # 更新滑动窗口历史记录 - 维护最近end_bounce_time内的状态
-        self.history.append((now, ret, val, im))
-        while self.history and self.history[0][0] < now - self.state.end_bounce_time:
-            self.history.pop(0)
+        # 确保val不为None
+        if val is None:
+            self.control_logger.warning("体积计算返回None，跳过本次记录")
+            return ret
         
-        if not self.history:
+        # 更新滑动窗口历史记录 - 维护最近end_bounce_time内的状态
+        self.history.add_record(now, ret,rate, val, im)
+        
+        if self.history.is_empty():
             self.control_logger.error("未预期的没有可用的历史记录")
             return ret
         
@@ -111,18 +113,15 @@ class MAT:
                     self.colored_time = now
                     self.colored_im = im.copy()
                 self.endpoint_logger.info(f"检测到colored，开始end检查，记录体积: {val:.2f} ml")
-        
-        # === 状态检查逻辑 ===
+          # === 状态检查逻辑 ===
         
         # middle检查: 进入middle的bounce_time后，在最近bounce_time内middle比例<70%返回fast状态
         if self.state.should_check_middle_exit(now):
             # 计算最近bounce_time内的middle比例
-            bounce_start_time = now - self.state.bounce_time
-            recent_history = [(t, state, v, i) for t, state, v, i in self.history if t >= bounce_start_time]
+            recent_records = self.history.get_recent_records(self.state.bounce_time, now)
             
-            if recent_history:
-                trans_count = sum(1 for _, state, _, _ in recent_history if state == "transport")
-                trans_ratio = trans_count / len(recent_history)
+            if recent_records:
+                trans_ratio = self.history.get_state_ratio("transport", recent_records)
                 
                 if trans_ratio > 0.3:
                     self.process_left(now)
@@ -133,27 +132,25 @@ class MAT:
         
         # end检查: 进入end之后的end_bounce_time，如果end比例<80%，则重置；否则终止实验
         if self.state.should_check_end_result(now):
-            colored_count = sum(1 for _, state, _, _ in self.history if state == "colored")
-            colored_ratio = colored_count / len(self.history)
+            colored_ratio = self.history.get_state_ratio("colored", self.history.get_recent_records(self.state.end_bounce_time, now))
             
             if colored_ratio < 0.8:
                 # end比例<80%，从history中找到第二个end并继续check逻辑
                 self.endpoint_logger.warning(f"colored比例{colored_ratio:.2%}<80%，寻找下一个colored点")
                 
                 # 寻找历史中倒数第二个colored状态
-                colored_times = [t for t, state, _, _ in self.history if state == "colored"]
+                colored_times = self.history.get_states_by_type("colored")
                 if len(colored_times) >= 2:
                     # 使用倒数第二个colored时间重新开始检查
                     second_last_colored_time = colored_times[1]
                     self.state.end_detected_time = second_last_colored_time
                     
                     # 更新colored记录为对应的体积
-                    for t, state, vol, img in self.history:
-                        if t == second_last_colored_time and state == "colored":
-                            self.colored_volume = vol
-                            self.colored_time = t
-                            self.colored_im = img.copy()
-                            break
+                    record = self.history.find_record_by_timestamp(second_last_colored_time)
+                    if record:
+                        self.colored_volume = record.volume
+                        self.colored_time = record.timestamp
+                        self.colored_im = record.image.copy()
                     
                     self.endpoint_logger.info(f"重置到第二个colored点: {self.colored_volume:.2f} ml")
                 else:
@@ -170,7 +167,8 @@ class MAT:
                 if self.colored_im is not None:
                     cv2.imwrite(f"colored_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg", self.colored_im)
                 return "colored"
-          # 显示状态信息
+        
+        # 显示状态信息
         self._display_status(im, ret, rate, val)
         return ret
     
@@ -199,14 +197,20 @@ class MAT:
         tot = mask.shape[0]*mask.shape[1]
         val = np.sum(mask)
         rate = val/tot
-        if rate < 0.02:
-            return "transport",rate
-        elif rate <0.2:
-            return "middle",rate
-        elif rate < 0.35:
-            return "about",rate
+        if self.history.base is not None:
+            base = self.history.base
+            thr = (base*5, base*10, base*30)
+            if rate < thr[0]:
+                return "transport",rate
+            elif rate <thr[1]:
+                return "middle",rate
+            elif rate < thr[2]:
+                return "about",rate
+            else:
+                return "colored",rate
         else:
-            return "colored",rate
+            return "transport",rate
+        
 
     def __del__(self):
         self.cap.release()
@@ -236,11 +240,11 @@ class MAT:
         self.system_logger.info("实验参数:")
         for key, value in experiment_params.items():
             self.system_logger.info(f"  {key}: {value}")
-        
         fps = int(self.cap.get(cv2.CAP_PROP_FPS)) or 30
         width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
         height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-          # 初始化视频录制器
+        
+        # 初始化视频录制器
         if vid_name != "Disabled":
             fourcc = cv2.VideoWriter.fourcc(*'x264')  # 使用更兼容的编码器
             self.capFile = cv2.VideoWriter(vid_name, fourcc, fps, (width, height))
@@ -302,14 +306,14 @@ if __name__ == "__main__":
     mat = MAT(
         videoSourceIndex = 1, 
         bounce_time=3,
-        end_bounce_time=15
+        end_bounce_time=0.01
     )
     
     mat.run(
         slow_speed = 0.05,
         quick_speed = 0.15,
-        end_time= 2
-        # cap_dir=None
+        end_time= 2,
+        cap_dir=None
     )
 
 

utils.py

@@ -2,6 +2,106 @@ import logging
 import os
 from datetime import datetime
 from enum import Enum
+from dataclasses import dataclass
+from typing import List, Tuple, Optional
+import numpy as np
+import time
+
+@dataclass
+class HistoryRecord:
+    """历史记录的单个条目"""
+    timestamp: float
+    state: str  # 'transport', 'middle', 'about', 'colored'
+    rate: float
+    volume: float
+    image: np.ndarray
+
+
+class History:
+    """滑动窗口历史记录管理类"""
+    
+    def __init__(self, max_window_size: float = 5.0, base_time = 5.0):
+        """
+        初始化历史记录管理器
+        
+        Args:
+            max_window_size: 最大窗口时间长度（秒）
+        """
+        if base_time > max_window_size:
+            max_window_size = base_time+0.2
+            # raise ValueError("Base time must be less than or equal to max window size.")
+        self.records: List[HistoryRecord] = []
+        self.max_window_size = max_window_size
+        self.fulled = False
+        self.base = None
+        self._base_time = base_time 
+    
+    def add_record(self, timestamp: float, state: str, rate: float, volume: float, image: np.ndarray):
+        """添加新的历史记录"""
+        record = HistoryRecord(timestamp, state,rate, volume, image)
+        self.records.append(record)
+        self._cleanup_old_records(timestamp)
+        if self.base is None and (timestamp-self._base_time)>= self.records[0].timestamp: 
+            base_records = self.get_recent_records(self._base_time, timestamp)
+            self.base = sum([rec.rate for rec in base_records]) / len(base_records)
+            get_endpoint_logger().info("Base rate calculated: %.2f", self.base)
+    
+    def _cleanup_old_records(self, current_time: float):
+        """清理过期的历史记录"""
+        cutoff_time = current_time - self.max_window_size
+        if not self.records and self.records[0].timestamp < cutoff_time:
+            return False
+        while self.records and self.records[0].timestamp < cutoff_time:
+            self.records.pop(0)
+        return True
+    
+    def get_records_in_timespan(self, start_time: float, end_time: Optional[float] = None) -> List[HistoryRecord]:
+        """获取指定时间段内的记录"""
+        if end_time is None:
+            return [record for record in self.records if record.timestamp >= start_time]
+        else:
+            return [record for record in self.records 
+                   if start_time <= record.timestamp <= end_time]
+    
+    def get_recent_records(self, duration: float, current_time: float) -> List[HistoryRecord]:
+        """获取最近指定时间长度内的记录"""
+        start_time = current_time - duration
+        return self.get_records_in_timespan(start_time, current_time)
+    
+    def get_state_ratio(self, target_state: str, records: Optional[List[HistoryRecord]] = None) -> float:
+        """计算指定状态在记录中的比例"""
+        if records is None:
+            records = self.records
+        
+        if not records:
+            return 0.0
+        
+        target_count = sum(1 for record in records if record.state == target_state)
+        return target_count / len(records)
+    
+    def get_states_by_type(self, target_state: str) -> List[float]:
+        """获取所有指定状态的时间戳"""
+        return [record.timestamp for record in self.records if record.state == target_state]
+    
+    def find_record_by_timestamp(self, target_timestamp: float) -> Optional[HistoryRecord]:
+        """根据时间戳查找记录"""
+        for record in self.records:
+            if record.timestamp == target_timestamp:
+                return record
+        return None
+    
+    def is_empty(self) -> bool:
+        """检查历史记录是否为空"""
+        return len(self.records) == 0
+    
+    def __len__(self) -> int:
+        """返回历史记录的数量"""
+        return len(self.records)
+    
+    def clear(self):
+        """清空所有历史记录"""
+        self.records.clear()
+
 
 class State:
     """滴定状态管理类"""