view experiments/scripts/cnbh-syllables/results_plotting/gen_results.py @ 610:01986636257a

Second check-in of Alex Brandmeyer's C++ implementation of CARFAC. Addressed style issues and completed implementation of remaining functions. Still needs proper testing of the output stages against the MATLAB version, and runtime functions need improvements in efficiency.

#!/usr/bin/env python
# encoding: utf-8
"""
gen_results.py

Created by Thomas Walters on 2010-09-12.
"""

import sys
import getopt
import re


help_message = '''
Write out all the results for a run of the
syllable recognition experiment. Expected input is a 'misclassificaions'
file of the type generated by run_test_instance.sh, along with the locations
of files containing the training talkers and all the talkers that the system
was tested on.

Arguments:
-i --input_file
-t --train_talkers
-s --test_talkers
-c --value_count
-p --spoke_pattern
'''

class Usage(Exception):
  def __init__(self, msg):
    self.msg = msg


def main(argv=None):
  if argv is None:
    argv = sys.argv
  try:
    try:
      opts, args = getopt.getopt(argv[1:], "hi:t:s:o:c:p:v",
                                 ["help", "input_file=", "train_talkers=",
                                  "test_talkers=",
                                  "value_count=", "spoke_pattern="])
    except getopt.error, msg:
      raise Usage(msg)
  
    # defaults
    input_file = "misclassified_syllables_iteration_15"
    train_talkers = "training_talkers"
    test_talkers = "testing_talkers"
    output_filename = "results.txt"
    total_value_count = 185
    spoke_pattern_file = "spoke_pattern.txt"
    
    # option processing
    for option, value in opts:
      if option == "-v":
        verbose = True
      if option in ("-h", "--help"):
        raise Usage(help_message)
      if option in ("-i", "--input_file"):
        input_file = value
      if option in ("-t", "--train_talkers"):
        train_talkers = value
      if option in ("-s", "--test_talkers"):
        test_talkers = value
      if option in ("-c", "--value_count"):
        total_value_count = int(value)
      if option in ("-p", "--spoke_pattern"):
        spoke_pattern_file = value
  
  except Usage, err:
    print >> sys.stderr, sys.argv[0].split("/")[-1] + ": " + str(err.msg)
    print >> sys.stderr, "\t for help use --help"
    return 2
    
  results = dict()
  f = open(input_file, 'r')
  for line in f:
    values = line.strip().split(' ')
    results[values[1]]=100*(1-float(values[0])/total_value_count)
 	
  f = open(test_talkers, 'r')
  test_talkers_list = f.readlines()
  f.close()

  f = open(train_talkers, 'r')
  train_talkers_list = f.readlines()
  f.close()

  spoke_pattern = []
  f = open(spoke_pattern_file, 'r')
  for line in f:
	spoke_pattern.append(line.strip().split(' '))

  all_talkers_list = []
  all_talkers_list.extend(train_talkers_list)
  all_talkers_list.extend(test_talkers_list)

  # Here I make the rather rash assumption that the model was tested on all talkers
  # this should be true if the training and testing was done using my scripts.
  for t in all_talkers_list:
	results.setdefault(t.strip(), 100.0)

  total_score = 0.0
  element_count = 0
  for t in train_talkers_list:
	total_score += results[t.strip()]
	element_count += 1
  score = total_score / element_count
  print ("# Score on training talkers: %.1f%%" % score)

  total_score = 0.0
  element_count = 0
  for t in all_talkers_list:
	total_score += results[t.strip()]
	element_count += 1
  score = total_score / element_count
  print ("# Score on all talkers: %.1f%%" % score)

  total_score = 0.0
  element_count = 0
  for t in test_talkers_list:
	total_score += results[t.strip()]
	element_count += 1
  score = total_score / element_count
  print ("# Score on test talkers: %.1f%%" % score)

  score = results[spoke_pattern[0][0]]
  print ("# Score on central talker: %.1f" % score)

  for s in xrange(1,9):
	print ("# Results for spoke %d" % s)
	for p in xrange(0, 7):
	  score = results[spoke_pattern[s][p]]
	  m = re.match('(.*)p(.*)s', spoke_pattern[s][p])
	  gpr = m.group(1)
	  vtl=m.group(2)
	  print ("%s %s %s" % (gpr, vtl, score))

if __name__ == "__main__":
  sys.exit(main())