update notebook

clean/ex3.py

 import numpy as np
 import uproot
 
+# Define minimum energy threshold
+emin = 0.005
+#Define sampling fraction constant
+sfc = 0.11
+
 def getData(fname="", procName="Events"):
     """Load data from a ROOT file."""
     file = uproot.open(fname)
@@ -14,47 +19,47 @@ def getData(fname="", procName="Events"):
     return dq_events
 
 def process_event(sample_type="electron", event_number=0):
-    """
-    Process a specific event from the ROOT file.
-
-    Parameters:
-    - sample_type (str): Type of sample ("electron" or "dielectron")
-    - event_number (int): Event number (0–10)
-
-    Returns:
-    - dict: Processed data for the event, including elmID and edep
-    """
-    # Validate event number
     if event_number < 0 or event_number > 10:
-        raise ValueError("Event number must be between 0 and 10")
+        raise ValueError("Event number must be between 0 and 9")
 
-    # Select ROOT file based on sample type
     file_name = f"{sample_type}.root"
     proc_name = f"Events{event_number}"
     
-    # Load event data
     dq_events = getData(file_name, proc_name)
     dq_hits = dq_events["Hits"]
     
-    # Retrieve and filter data
     raw_elmID = dq_hits["elmID"]
     raw_edep = dq_hits["edep"]
     
-    # Apply energy mask
+    # Apply energy threshold mask
     eng_mask = raw_edep >= emin
     elmID = raw_elmID[eng_mask]
     edep = raw_edep[eng_mask]
 
-    # Return the filtered data
     return {
         "elmID": elmID,
         "edep": edep
     }
 
-# Example usage
-sample_type = input("Enter sample type (electron or dielectron): ")
-event_number = int(input("Enter event number (0-10): "))
-result = process_event(sample_type, event_number)
+def get_hit_data():
+    sample_type = input("Enter sample type (electron or dielectron): ").strip()
+    event_number = int(input("Enter event number (0-9): ").strip())
+    
+    event_data = process_event(sample_type, event_number)
+    elmID = event_data["elmID"]
+    edep = event_data["edep"]
+    
+    return elmID, edep
+
 
-# Print the result for debugging
-print("Filtered event data:", result)
+def generate_2d_points(num_clusters=3, points_per_cluster=50, spread=1.0, random_seed=42):
+    np.random.seed(random_seed)
+    data = []
+
+    for i in range(num_clusters):
+        center = np.random.rand(2) * 10
+        cluster_points = center + np.random.randn(points_per_cluster, 2) * spread
+        data.append(cluster_points)
+    
+    data = np.vstack(data)
+    return data