Change bad-data-interval parsing to account for more requirements

Apparently the separator can change each line and be part
of the comment message. Hence, simple csv parsing does not work.

(cherry picked from commit e5fb7c3)

Author: sawenzel

MC/bin/o2dpg_sim_workflow_anchored.py

@@ -14,7 +14,6 @@
 import json
 import math
 import pandas as pd
-import csv
 
 # Creates a time anchored MC workflow; positioned within a given run-number (as function of production size etc)
 
@@ -318,17 +317,28 @@ def exclude_timestamp(ts, orbit, run, filename):
     if not os.path.isfile(filename):
        return False
 
-    # Function to detect the delimiter automatically
-    def detect_delimiter(file_path):
-      with open(file_path, 'r') as csvfile:
-        sample = csvfile.read(1024)  # Read a small sample of the file
-        sniffer = csv.Sniffer()
-        delimiter = sniffer.sniff(sample).delimiter
-        return delimiter
-      return ',' # a reasonable default
-
-    # read txt file into a pandas dataframe ---> if this fails catch exception and return
-    df = pd.read_csv(filename, header=None, names=["Run", "From", "To", "Message"], sep=detect_delimiter(filename))
+    def parse_file(filename):
+      parsed_data = []
+      with open(filename, 'r') as file:
+        for line in file:
+            # Split the line into exactly 4 parts (first three numbers + comment)
+            columns = re.split(r'[,\s;\t]+', line.strip(), maxsplit=3)
+
+            if len(columns) < 3:
+                continue  # Skip lines with insufficient columns
+
+            try:
+                # Extract the first three columns as numbers
+                num1, num2, num3 = map(int, columns[:3])  # Assuming integers in the data
+                comment = columns[3] if len(columns) > 3 else ""
+                parsed_data.append({"Run" : num1, "From" : num2, "To" : num3, "Message" : comment})
+            except ValueError:
+                continue  # Skip lines where first three columns are not numeric
+      return parsed_data
+
+    data = parse_file(filename)
+    # print (data)
+    df = pd.DataFrame(data) # convert to data frame for easy handling
 
     # extract data for this run number
     filtered = df[df['Run'] == run]