def run(self):
print ("Loading input and generating...")
fileload, resolution, format = loadMidi.load('midi/bach_simple.mid')
stringNotes = convert.listToString(fileload)
mc = MarkovChain(1)
mc.add_string(stringNotes)
markovNotes = ' '.join(mc.generate_text(50))
writeMidi.writeList(convert.stringToList(markovNotes), resolution, format)
print ('Process complete, output is in ./rebuilt.mid')
def generate_text(input, output):
if os.path.isfile(args.o):
os.remove(args.o)
num_words = args.n
contents = read_file(input)
wordlist = contents.split(' ')
markov = MarkovChain(wordlist)
with open(output, 'a+') as f:
f.write(markov.generate_text(num_words))
# Get India trending topics on Twitter
trends = api.trends_place(23424848)
data = trends[0]
trending = [trend['name'] for trend in data['trends']]
print("Choosing 10 topics at random...")
shuffle(trending)
topics = sample(trending, 10)
for topic in topics:
print(topic)
# Get tweets about the topic
collector = TweetCollector()
stream = Stream(auth, collector)
stream.filter(track=topics, languages=['en'])
print('Finished collecting tweets')
# Generate "empty" tweets
tweets = collector.get_tweets()
mc_model = MarkovChain(tweets)
mc_model.generate_model()
mt_tweets = []
for i in range(50):
mt_tweets.append(mc_model.generate_text())
# Choose one at random and update status
status = choice(mt_tweets)
print("Tweeting...", status, sep='\n')
api.update_status(status)
