def runModel():
print("Model running mode!\n")
print("Collecting 10 tweets to iterate through!")
data.testTweets = tweetstreamer.getTweets(10)
print("Use learning?")
goodinput = 0
while(not goodinput):
inputstring = raw_input("(y/n): ")
if(inputstring == "y"):
useLearning = True
goodinput = 1
elif(inputstring == "n"):
useLearning = False
goodinput = 1
else:
print("Please enter y or n")
# runModel main loop
while(len(data.testTweets) != 0):
print("\n1: Evaluate new tweet\n2: Exit running mode")
inputstring = raw_input("Enter option: ")
if(inputstring == "1"):
newTweet = data.testTweets.pop()
wordsInTweet = re.findall(r'\w+', newTweet.lower())
probTweetFlu = probOfFlu(wordsInTweet)
isTweetFlu = probTweetFlu > data.THRESHOLD
if(isTweetFlu):
data.numFluTweets += 1
try:
print("\nNew tweet: " + str(newTweet))
print("Probability the user has flu: " + str(probTweetFlu))
except UnicodeEncodeError:
print("Codec cannot encode characters in this tweet!")
if(useLearning):
learner.updateProbs(wordsInTweet, isTweetFlu)
elif(inputstring == "2"):
return
else:
print("\nThat is not an option!\n")
print("All test tweets evaluated!!!")
def trainModel():
# Check if probabilities already exist and ask user if they want to use these probs
if(len(data.probabilities) != 0):
print("Saved model already exists.\nUse this model?\n")
while(True):
inputstring = raw_input("(y/n): ")
if(inputstring == "y"):
print("Model trained!")
return
elif(inputstring == "n"):
data.probabilities.clear()
break
elif(inputstring == "q"):
print("Good bye!")
quit()
## TODO EXIT ##
else:
print("Please enter y, n, or q to quit")
# Read tweets and categorization data from files
if(os.path.exists("./tweets.txt")):
tweetsFile = open("./tweets.txt","r")
data.tweetsStored = int(tweetsFile.readline())
tweetsFile.close()
print("Found tweets.txt with " + str(data.tweetsStored) + " tweets in it!")
# Load tweets into memory
readTweetsFromFile()
# Check if training data already exists for these tweets
if(os.path.exists("./trainingdata.txt")):
trainingDataFile = open("./trainingdata.txt")
data.tweetsCategorized = int(trainingDataFile.readline())
trainingDataFile.close()
print("Found trainingdata.txt with " + str(data.tweetsCategorized) + " categorizations in it!")
if(data.tweetsStored < data.tweetsCategorized):
# We have more categorized tweets than tweets themselves. Error
print("Mismatch: more tweets are categorized than exist! Disregarding categorization data.")
data.tweetsCategorized = 0
else:
readCategorizationFromFile()
else:
print("No categorization data exists for these tweets!\n")
# Ask the user how many tweets they would like in the training set
print("Please enter the number of tweets you would like in the training set")
inputstring = raw_input(">> ")
tweetsWanted = int(inputstring)
# If we do not have enough tweets as the user requested
if(data.tweetsStored < tweetsWanted):
print(str(data.tweetsStored) + " tweets already stored.")
print(str(tweetsWanted - data.tweetsStored) + " more tweets needed.")
print("Append more tweets or overwrite and collect new tweets?")
while(True):
inputstring = raw_input("(a/o): ")
if(inputstring == "a"):
data.tweets.append(tweetstreamer.getTweets(tweetsWanted - data.tweetsStored, data.searchterms))
trainer.categorizeTweets()
break
elif(inputstring == "o"):
data.tweetsStored = 0
data.tweetsCategorized = 0
data.tweets = tweetstreamer.getTweets(tweetsWanted - data.tweetsStored, data.searchterms)
trainer.categorizeTweets()
break
elif(inputstring == "q"):
print("Good bye!")
## TODO EXIT ##
else:
print("Please enter a to append, o to overwrite, or q to quit")
# We have more than enough tweets
elif(data.tweetsStored >= tweetsWanted):
print(str(data.tweetsStored) + " tweets already stored.")
print("Use these tweets or overwrite and collect new tweets?")
while(True):
inputstring = raw_input("(u/o): ")
if(inputstring == "u"):
readCategorizationFromFile()
break
elif(inputstring == "o"):
data.tweetsStored = 0
data.tweetsCategorized = 0
data.tweets = tweetstreamer.getTweets(tweetsWanted - data.tweetsStored, data.searchterms)
trainer.categorizeTweets()
break
elif(inputstring == "q"):
print("Good bye!")
quit()
else:
print("Please enter a to append, o to overwrite, or q to quit")
# Now we have the tweets and some categorization or not
# Model is now trained
# Model is stored in probabilities
data.tweetsStored = len(data.tweets)
trainer.calculateProbs()
