main.py

import hmm as HiddenMarkov
import gc 
import utils as utls
import sys


datasetFile = "dataset.txt";
outFile = "out.txt";
testDataSize = 200;

datasetFile = sys.argv[1];
outFile = sys.argv[2];

print("initializing hmm...");
hiddenMarkovModel = HiddenMarkov.HMM(datasetFile);


print("Correcting the sentences...")
results = list();
data = hiddenMarkovModel.errorFullDataSet[:testDataSize];
dataLength = len(data);
for i in range(dataLength):
    temp = hiddenMarkovModel.viterbi(data[i]);
    results.append(temp);
    if not (i%100):
        gc.collect()

#evaluation
correctEstimatedWordCount = 0;
wrongTypedWordCount = 0;
for i in range(dataLength):
    counts = utls.evaluateSentence(data[i], results[i]);
    correctEstimatedWordCount = correctEstimatedWordCount + counts[1];
    wrongTypedWordCount = wrongTypedWordCount + counts[0];


print(wrongTypedWordCount);
print(correctEstimatedWordCount);
acc = correctEstimatedWordCount/wrongTypedWordCount;

out = open(outFile,'w');
out.write("------- Evaluation -------\n");
out.write("Accuracy : " + str(acc));
out.write("\nTotal miss typed word count is : "+ str(wrongTypedWordCount));
out.write("\nTotal correct estimated word count is : "+ str(correctEstimatedWordCount));
out.write("\n\nSentences after viterbi:");
for result in results:
    out.write("\n" + result);
    

out.write("\n----EOF----");
out.close()