kratsg · February 25, 2023 13:23 · Feb 25, 2023
diff --git a/outputtxt2json.py b/outputtxt2json.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-,
+
+# __future__ imports must occur at beginning of file
+# redirect python output using the newer print function with file description
+#   print(string, f=fd)
+from __future__ import print_function
+
+# import the rest of the stuff
+import argparse
+import os
+import sys
+import csv
+import collections
+import json
+
+def get_scaleFactor(weights, did):
+  weight = weights.get(did, None)
+  if weight is None:
+    return 1.0
+  scaleFactor = 1.0
+  cutflow = weight.get('num events')
+  if cutflow == 0:
+    raise ValueError('Num events = 0!')
+  scaleFactor /= cutflow
+  scaleFactor *= weight.get('cross section', 1.0)
+  scaleFactor *= weight.get('filter efficiency', 1.0)
+  scaleFactor *= weight.get('k-factor', 1.0)
+  return scaleFactor
+
+if __name__ == "__main__":
+
+  # if we want multiple custom formatters, use inheriting
+  class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter):
+    pass
+
+  parser = argparse.ArgumentParser(description='Convert from the txt outputs to an output json combining all information',
+                                   usage='\033[93m%(prog)s\033[0m files [options]',
+                                   formatter_class=lambda prog: CustomFormatter(prog, max_help_position=30))
+  parser.add_argument('files', type=str, nargs='+', help='Files to Convert')
+  parser.add_argument('--analysis', type=str, required=True, help='Name of the analysis to strip off')
+  parser.add_argument('--weights', metavar='weights.json', type=str, help='Weights file to weight all weighted and errs by')
+
+  args = parser.parse_args()
+
+  yields = collections.defaultdict(lambda: collections.defaultdict(lambda: collections.defaultdict(float)))
+  weights = {}
+  if args.weights:
+    weights = json.load(file(args.weights))
+
+  header_map = {"events": "raw", "acceptance": "weighted", "err": "err"}
+
+  for fname in args.files:
+    did = os.path.splitext(os.path.basename(fname))[0]
+    sf = get_scaleFactor(weights, did)
+    print("Reading in DID#{0:s} with SF {1:20.10f}".format(did, sf))
+    with open(fname, 'r') as csvfile:
+      reader = csv.reader(csvfile)
+      headers = next(reader)
+      headers[0] = None
+      for row in reader:
+        region = None
+        for h, v in zip(headers, row):
+          #if region in ['All']: continue
+          if h is None:
+            region = v.replace('{0:s}__'.format(args.analysis),'')
+            print(h,'|', v, '|', region)
+          else:
+            val = float(v)
+            if header_map[h] in ['weighted', 'err']:
+              val*= sf
+            yields[region][did][header_map[h]] += val
+
+  with open('truth_dids.json', 'w+') as outfile:
+    json.dump(yields, outfile, sort_keys=True, indent=4)
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