增加了HSMO整线优化方法，读取数据增加了供料器部分

base_optimizer/optimizer_common.py

@@ -22,6 +22,7 @@ import pandas as pd
 import matplotlib.pyplot as plt
 import matplotlib
 import traceback
+import openpyxl
 
 matplotlib.use('TkAgg')
 
@@ -67,7 +68,16 @@ t_fix_camera_check = 0.12  # 固定相机检测时间
 T_pp, T_tr, T_nc, T_pl = 2, 5, 25, 0
 
 # 时间参数 （数据拟合获得）
-Fit_cy, Fit_nz, Fit_pu, Fit_pl, Fit_mv = 0.326, 0.870, 0.159, 0.041, 0.001
+# Fit_cy, Fit_nz, Fit_pu, Fit_pl, Fit_mv = 0.326, 0.870, 0.159, 0.041, 0.030
+Fit_cy, Fit_nz, Fit_pu, Fit_pl, Fit_mv = 0.326, 0.870, 0.159, 0.041, 0.035
+
+
+class Point:
+    def __init__(self, _x, _y, _r=0, _h=None):
+        self.x = _x
+        self.y = _y
+        self.r = _r
+        self.h = _h
 
 
 class OptResult:
@@ -108,9 +118,12 @@ class OptInfo:
         print(f'-Pick time: {self.pickup_time: .3f}, Pick distance: {self.pickup_distance: .3f}')
         print(f'-Place time: {self.place_time: .3f}, Place distance: {self.place_distance: .3f}')
         print(
-            f'-Round time: {self.total_time - self.place_time - self.place_time: .3f}, Round distance: '
+            f'-Round time: {self.total_time - self.operation_time - self.pickup_time - self.place_time: .3f}, Round distance: '
             f'{self.total_distance - self.pickup_distance - self.place_distance: .3f}')
 
+        print(f'-Round & place time per cycle: {(self.total_time - self.pickup_time - self.operation_time) * 1000.0 / (self.cycle_counter + 1e-10): .3f}, ', end='')
+        print(f'-Round & place distance per cycle: {(self.total_distance - self.pickup_distance) / (self.cycle_counter + 1e-10): .3f}')
+
         minutes, seconds = int(self.total_time // 60), int(self.total_time) % 60
         millisecond = int((self.total_time - minutes * 60 - seconds) * 60)
 
@@ -856,3 +869,10 @@ def random_division(num, div):
 
 def list_range(start, end=None):
     return list(range(start)) if end is None else list(range(start, end))
+
+
+def kth_indices_partition(num, kth):
+    if len(num) > kth:
+        return np.argpartition(num, kth)
+    else:
+        return np.array(range(len(num)))