def ansChecker(trial):
trial_bag = sanitize.bag_of_words(trial)
scores = []
for i in range(len(bags)):
scores.append(score(bags[i], trial_bag))
sorter = sorted(range(len(scores)), key=lambda k: scores[k])
sorter = sorter[::-1]
bestGuess = []
bestGuess.append(responses[sorter[0]])
bestGuess.append(responses[sorter[1]])
bestGuess.append(responses[sorter[2]])
bestGuessScores = []
bestGuessScores.append(grades[sorter[0]])
bestGuessScores.append(grades[sorter[1]])
bestGuessScores.append(grades[sorter[2]])
return (bestGuess, bestGuessScores)
#run(host="0.0.0.0", port=8090)
#we use:
import sanitize
from bow_classifier import score
responses = []
grades = []
f = open('responses.txt')
for line in f:
s = line.split(':')
grades.append(int(s[0]))
responses.append(s[1])
f.close()
bags = [sanitize.bag_of_words(response) for response in responses]
def ansChecker(trial):
trial_bag = sanitize.bag_of_words(trial)
scores = []
for i in range(len(bags)):
scores.append(score(bags[i], trial_bag))
sorter = sorted(range(len(scores)), key=lambda k: scores[k])
sorter = sorter[::-1]
bestGuess = []
bestGuess.append(responses[sorter[0]])
bestGuess.append(responses[sorter[1]])
bestGuess.append(responses[sorter[2]])
bestGuessScores = []
bestGuessScores.append(grades[sorter[0]])
import sanitize
from bow_classifier import score
responses = []
grades = []
f = open('responses.txt')
for line in f:
s = line.split(':')
grades.append(int(s[0]))
responses.append(s[1])
f.close()
print grades
bags = [sanitize.bag_of_words(response) for response in responses]
print "What is entropy?"
trial = raw_input()
print
print
trial_bag = sanitize.bag_of_words(trial)
print trial_bag
print
scores = []
for i in range(len(bags)):
scores.append(score(bags[i], trial_bag))
sorter = sorted(range(len(scores)), key=lambda k: scores[k])
sorter = sorter[::-1]
for i in range(len(bags)):
print scores[sorter[i]], ": ", responses[sorter[i]]