def display(self, amount):
pygame.init()
screen = pygame.display.set_mode((740, 480))
black = (0, 0, 0)
myfont = pygame.font.SysFont("comicsansms", 35)
p_name = myfont.render('Gross amount', 4, black)
amount = str(amount)
price = myfont.render(amount, 4, black)
Group = pygame.sprite.Group()
f = Probe(530, 400)
Group.add(f)
while True:
screen.fill((255, 255, 255))
screen.blit(p_name, (250, 300))
screen.blit(price, (480, 300))
for event in pygame.event.get():
if event.type == pygame.QUIT:
pygame.quit()
exit(0)
elif event.type == pygame.MOUSEBUTTONDOWN:
if f.rect.collidepoint(pygame.mouse.get_pos()):
import interface
z = interface.display()
z.begin()
Group.draw(screen)
pygame.display.flip()
def fetch(entries):
save = []
for entry in entries:
field = entry[0]
text = entry[1].get()
save.append(text)
if save[0] == 'admin' and save[1] == 'admin':
a = interface.display()
a.login()
def makeCloud(tweetObjs, window):
stopwords = [
"&", "&", "a", "about", "above", "above", "across", "after",
"afterwards", "again", "against", "all", "almost", "alone", "along",
"already", "also", "although", "always", "am", "among", "amongst",
"amoungst", "amount", "an", "and", "another", "any", "anyhow",
"anyone", "anything", "anyway", "anywhere", "are", "around", "as",
"at", "back", "be", "became", "because", "become", "becomes",
"becoming", "been", "before", "beforehand", "behind", "being", "below",
"beside", "besides", "between", "beyond", "bill", "both", "bottom",
"but", "by", "call", "can", "cannot", "cant", "co", "con", "could",
"couldnt", "cry", "de", "describe", "detail", "do", "done", "down",
"due", "during", "each", "eg", "eight", "either", "eleven", "else",
"elsewhere", "empty", "enough", "etc", "even", "ever", "every",
"everyone", "everything", "everywhere", "except", "few", "fifteen",
"fify", "fill", "find", "fire", "first", "five", "for", "former",
"formerly", "forty", "found", "four", "from", "front", "full",
"further", "get", "give", "go", "had", "has", "hasnt", "have", "he",
"hence", "her", "here", "hereafter", "hereby", "herein", "hereupon",
"hers", "herself", "him", "himself", "his", "how", "however",
"hundred", "ie", "if", "in", "inc", "indeed", "interest", "into", "is",
"it", "its", "itself", "keep", "last", "latter", "latterly", "least",
"less", "ltd", "made", "many", "may", "me", "meanwhile", "might",
"mill", "mine", "more", "moreover", "most", "mostly", "move", "much",
"must", "my", "myself", "name", "namely", "neither", "never",
"nevertheless", "next", "nine", "no", "nobody", "none", "noone", "nor",
"not", "nothing", "now", "nowhere", "of", "off", "often", "on", "once",
"one", "only", "onto", "or", "other", "others", "otherwise", "our",
"ours", "ourselves", "out", "over", "own", "part", "per", "perhaps",
"please", "put", "rather", "re", "same", "see", "seem", "seemed",
"seeming", "seems", "serious", "several", "she", "should", "show",
"side", "since", "sincere", "six", "sixty", "so", "some", "somehow",
"someone", "something", "sometime", "sometimes", "somewhere", "still",
"such", "system", "take", "ten", "than", "that", "the", "their",
"them", "themselves", "then", "thence", "there", "thereafter",
"thereby", "therefore", "therein", "thereupon", "these", "they",
"thickv", "thin", "third", "this", "those", "though", "three",
"through", "throughout", "thru", "thus", "to", "together", "too",
"top", "toward", "towards", "twelve", "twenty", "two", "un", "under",
"until", "up", "upon", "us", "very", "via", "was", "we", "well",
"were", "what", "whatever", "when", "whence", "whenever", "where",
"whereafter", "whereas", "whereby", "wherein", "whereupon", "wherever",
"whether", "which", "while", "whither", "who", "whoever", "whole",
"whom", "whose", "why", "will", "with", "within", "without", "would",
"yet", "you", "your", "yours", "yourself", "yourselves", "the"
]
tweets = []
for text in tweetObjs:
tweets.append((str)(text["text"]))
tweetsProcessed = [] #FILTERED TWEETS WITH STUFF LIKE STOPWORDS REMOVED
# Extract the vocabulary of keywords
# and put them into a dictionary
vocab = dict()
for eachTweet in tweets:
filteredTweet = ""
for term in eachTweet.split():
term = term.lower()
#filter removing terms under 2char, in stopwords, and links
if len(term) > 2 and term not in stopwords and not term.startswith(
'http'):
filteredTweet = filteredTweet + ' ' + term
if vocab.has_key(term):
vocab[term] = vocab[term] + 1
else:
vocab[term] = 1
tweetsProcessed.append(filteredTweet)
# Remove terms whose frequencies are less than a threshold (e.g., 15)
vocab = {term: freq for term, freq in vocab.items() if freq > 20}
#sort of like x = x+1; term only gets added if its freq is > # in old vocab.items()
# Generate an id (starting from 0) for each term in vocab
vocab = {term: i for i, (term, freq) in enumerate(vocab.items())}
# Generate X
X = []
#basically, X = list of Ys
#Ys = counts of which words got hit in a single tweet instance
for text in tweets: #iterate through each tweet
x = [0] * len(vocab) #x is now len(vocab) large
#terms = list of terms that >2 in length in a tweet
terms = [term for term in text.split() if len(term) > 2]
for term in terms: # for each term in terms
if vocab.has_key(term):
x[vocab[term]] += 1 #increase that term's id by 1
X.append(x)
################################################################################
numberOfClusters = 5
# K-means clustering
km = KMeans(n_clusters=numberOfClusters,
n_init=100) # try 100 different initial centroids
km.fit(X) #KMeans all those Ys
#make a directory for cluster files (if it doesn't exist already
subDirectory = "wordcloud"
if not os.path.exists(subDirectory):
os.makedirs(subDirectory)
#open cluster files for writing
clusterFilePtr = [] #set up cluster pointer array
for i in range(0, numberOfClusters):
filename = "cluster" + str(i) + "_data.txt"
#put categorized tweets in the subdirectory
clusterFilePtr.append(open(os.path.join(subDirectory, filename), "w"))
counter = [] #counter for each cluster
for i in range(0, numberOfClusters):
counter.append(0)
#write each tweet to the cluster file they belong to
for i, cls in enumerate(km.labels_):
clusterFilePtr[cls].write(tweetsProcessed[i] + "\n")
counter[cls] += 1
#close cluster files
for eachPtr in clusterFilePtr:
eachPtr.close()
print "Number of clusters:", len(counter)
#print count of each cluster
for i in range(0, len(counter)):
print "cluster%d: %d" % (i, counter[i])
#####################################################wordcloud time
# get all the words from each cluster
for i in range(0, numberOfClusters):
filename = "cluster" + str(i) + "_data.txt"
wordball = []
wordball = open(os.path.join(subDirectory, filename)).read()
wc = WordCloud().generate(wordball) #generate wordcloud
picname = "cloud" + str(i) + ".png"
wc.to_file(os.path.join(subDirectory, picname)) # store to file
interface.display(window)
def bill():
import interface
a = interface.display()
a.begin()
return