lines = []

for s in sources:

with open(s) as f:

lines.extend(f.readlines())

text = "".join(lines)

cv = CountVectorizer(min_df=1, decode_error="ignore",

stop_words="english", max_features=200)

counts = cv.fit_transform([text]).toarray().ravel()

words = np.array(cv.get_feature_names())

# throw away some words, normalize

words = words[counts > 1]

counts = counts[counts > 1]

with tempfile.NamedTemporaryFile(suffix='.png') as tmp:

temp_filename = tmp.name

counts = wordcloud.make_wordcloud(words, counts, temp_filename, font_path='/Library/Fonts/Georgia.ttf',width=800, height=800, ranks_only=False)

image_file = cbook.get_sample_data(temp_filename)

image = plt.imread(image_file)

fig, ax = plt.subplots()

im = ax.imshow(image)

plt.axis('off')