old_contents: #print a confidence set of gene family origination points based on LLs
  from __future__ import division
  
  import re, sys
  from decimal import Decimal
  import numpy as np
  
  oriLL = {}
  oriP = {}
  
  total_probs = np.array([])
  
  inh = open(sys.argv[1]) #uml_rec file
  for line in inh:
      fields = re.split("\t", line.rstrip())
      if fields[0].startswith("S_"):
          oriLL[fields[1]] = float(fields[-1])
          oriP[fields[1]] = np.exp(Decimal(fields[-1])) 
          total_probs = np.append(total_probs, np.exp(Decimal(fields[-1])))
  inh.close()
  
  total = np.sum(total_probs)
  
  for k in sorted(oriP, key=oriP.get, reverse=True):
      norm_prob = Decimal(oriP[k]) / total
      print(k + "\t" + str(oriP[k]) + "\t" + str(norm_prob))
  
  
  
new_contents: #print the probability that a gene family originated on each branch of the species tree, based on origination LLs
  from __future__ import division
  
  import re, sys
  from decimal import Decimal
  import numpy as np
  
  oriLL = {}
  oriP = {}
  
  total_probs = np.array([])
  
  inh = open(sys.argv[1]) #uml_rec file
  for line in inh:
      fields = re.split("\t", line.rstrip())
      if fields[0].startswith("S_"):
          oriLL[fields[1]] = float(fields[-1])
          oriP[fields[1]] = np.exp(Decimal(fields[-1])) 
          total_probs = np.append(total_probs, np.exp(Decimal(fields[-1])))
  inh.close()
  
  total = np.sum(total_probs)
  
  for k in sorted(oriP, key=oriP.get, reverse=True):
      norm_prob = Decimal(oriP[k]) / total
      print(k + "\t" + str(oriP[k]) + "\t" + str(norm_prob))
  
  
  
subject: Update confidence_set_origination.py