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archive/source/sim_agents/traits.py

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+import pandas as pd
+import numpy as np
+from dataclasses import dataclass
+
+
+grades = {
+    "Kindergarden":np.array(
+        [31.43,5.65,1.21,0.24]
+        ),
+    "Grade 1":np.array(
+        [32.57,6.27,1.35,0.26]
+        ),
+    "Grade 2":np.array(
+        [34.43,6.80,1.42,0.28]
+        ),
+    "Grade 3":np.array(
+        [35.43,5.19,1.48,0.23]
+        ),
+    "Grade 4":np.array(
+        [34.86,6.77,1.58,0.26]
+        ),
+    "Grade 5":np.array(
+        [36.71,7.09,1.59,0.24]
+        ),
+    "Grade 6":np.array(
+        [37.71,6.99,1.65,0.24]
+        ),
+    "Grade 7":np.array(
+        [40.43,6.02,1.61,0.25]
+        ),
+    "Grade 8":np.array(
+        [40.43,5.50,1.66,0.24]
+        ),
+    "Grade 9":np.array(
+        [44.14,4.85,1.60,0.24]
+        ),
+    "Grade 10":np.array(
+        [46.29,6.29,1.57,0.23]
+        ),
+    "Grade 11":np.array(
+        [48.29,3.30,1.51,0.22]
+        ),
+    "Grade 12":np.array(
+        [43.71,6.02,1.54,0.23]
+    )}
+
+df_srs_data=pd.DataFrame({
+    "Grade Level":(
+        list(grades.keys())),
+    "Pop Mean":[
+        grades[j][0] for j in grades],
+    "Pop Std Dev":[
+        grades[j][1] for j in grades],
+    "Speed Mean":[
+        grades[j][2] for j in grades],
+    "Speed Std Dev":[
+        grades[j][3] for j in grades]})
+
+@dataclass
+class AgentConfig:
+    id:int
+    grade:str
+    door:str
+    speed:float
+    radius:float
+    
+    
+    
+    
+    
+    
+