def parseActorsAndMovies():
Actor.unpickleActors()
if(not Actor.total):
print "Reading all actor data from dataset..."
inputFile = open("../dataset/actor_movies.txt")
lineString = inputFile.readline()
while(lineString):
actor_name = ""
parsedLineArray = lineString.split("\t\t")
for i in range(0,len(parsedLineArray)):
if(i == 0):
actor_name = parsedLineArray[0].strip()
actor = Actor(actor_name)
else:
if(parsedLineArray[i].strip() != ""):
(movieTitle,movieYear) = Movie.separateTitleAndYear(parsedLineArray[i].strip())
movieActedIn = Movie.hashByTitle[movieTitle]
#Set actor's movie list
actor.movieList.append(movieActedIn)
#Update actor's movieVector for current movie
actor.moviesVector[0][movieActedIn.id] = 1
#Append current movie's actor list with current actor
movieActedIn.actors.append(actor)
lineString = inputFile.readline()
print actor
#Append actor's moviesVector to the actorMovieMatrix
if(Actor.total == 1):
Actor.actorMovieAdjacencyMatrix = np.append(np.zeros((0,Movie.total)),actor.moviesVector,axis=0)
else:
Actor.actorMovieAdjacencyMatrix = np.append(Actor.actorMovieAdjacencyMatrix,actor.moviesVector,axis=0)
Actor.pickleActors()
def parseMoviesAndRatings():
inputFile = open("../dataset/movie_rating.txt")
lineString = inputFile.readline()
movieRatingVector = np.zeros(0)
global missing_count
while(lineString):
(movie_title,movie_year) = Movie.separateTitleAndYear(lineString.split("\t\t")[0].strip())
movie_rating = float(lineString.split("\t\t")[1].strip())
if(not movie_title in Movie.hashByTitle):
movie = Movie(movie_title,rating=movie_rating)
missing_count = missing_count + 1
else:
movie = Movie.hashByTitle[movie_title]
movie.rating = movie_rating
movieRatingVector = np.append(movieRatingVector,movie_rating)
lineString = inputFile.readline()
if(movie.id%100000 == 0):
print movie
arrayToSave = np.asarray(movieRatingVector)
np.savetxt("./movie_rating_vector.csv", arrayToSave, delimiter=",")
