def word_cloud(self, model: LdaModel, stopwords_path, save_path):
with open(stopwords_path, 'r', encoding='utf8') as f:
words = f.readlines()
stopwords = add_stop_words(words)
print('stop words added')
word_cloud = PersianWordCloud(only_persian=True,
max_words=10,
stopwords=stopwords,
width=800,
height=800,
background_color='black',
min_font_size=1,
max_font_size=300)
topics = model.show_topics(formatted=False)
for i, topic in enumerate(topics):
topic_words = dict(topic[1])
print(topic_words)
new = {}
for word in topic_words.keys():
reshaped = get_display(arabic_reshaper.reshape(word))
new[reshaped] = topic_words[word]
print(new)
word_cloud.generate_from_frequencies(new)
image = word_cloud.to_image()
image.show()
s = save_path + '_topic_' + str(i) + '.png'
print(s)
image.save(s)
def word_cloud_generator(text):
d = path.dirname(__file__)
twitter_mask = np.array(Image.open(path.join(d, "twitter-logo.jpg")))
stopwords = add_stop_words(['کاسپین'])
stopwords |= EN_STOPWORDS
# Generate a word cloud image
wordcloud = PersianWordCloud(only_persian=False,
max_words=200,
stopwords=stopwords,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
random_state=True,
background_color="white",
mask=twitter_mask).generate(text)
image = wordcloud.to_image()
# image.show()
# image.save('en-fa-result.png')
from io import BytesIO
bio = BytesIO()
bio.name = 'image.jpeg'
image.save(bio, 'JPEG')
bio.seek(0)
return bio
def wc_without_removing_stopWords(text, number):
wordcloud = PersianWordCloud(
only_persian=True,
max_words=100,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
background_color="black"
).generate(text)
image = wordcloud.to_image()
image.show()
image.save('../out/%s.jpg'%number)
def draw_cloud(cleantweets):
text = " ".join(str(tweet) for tweet in cleantweets)
tokens = word_tokenize(text)
dic = Counter(tokens)
print(dic.most_common(max_words))
twitter_mask = np.array(Image.open("twitter-logo.jpg"))
wordcloud = PersianWordCloud(only_persian=True,
max_words=max_words,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
background_color="white",
mask=twitter_mask).generate(text)
image = wordcloud.to_image()
wordcloud.to_file(image_file_path)
image.show()
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--txt', help='main text file',type=str, required=True)
parser.add_argument('--mask', help='binary mask(generated by mask_generator.py)', type=str, required=True)
parser.add_argument('--stopwords', help='words you don\'t want',type=str, required=False)
# parser.add_argument('--startwords',help='stopwords that come first',type=str,required=False)
parser.add_argument('--persian',help='language is persian?(True or False)', type=bool, default=True)
parser.add_argument('--maxwords',help='maximum number of words to show in image', type=int, default=1000)
parser.add_argument('--bgcolor',help='background color(black or white)', type=str, default='white')
parser.add_argument('--out',help='image output name', type=str, default='out.png')
parser.add_argument('--cmap',help='output image colormap', type=str, default='plasma')
args = parser.parse_args()
# print(args.output)
stop = read_words(args.stopwords) if args.stopwords else ""
out = args.out if args.out.split('.')[-1] in ['png', 'jpg'] else args.out + '.png'
wordcloud = PersianWordCloud(
only_persian=args.persian,
max_words=args.maxwords,
stopwords=stop,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
random_state=True,
background_color=args.bgcolor,
colormap=args.cmap,
mask=read_img(args.mask)
).generate(read_file(args.txt))
image = wordcloud.to_image()
image.show()
image.save(out)
class TweetCloud(object):
def __init__(self):
self.tweet_cloud = None
self.file_names = []
self.d = path.dirname(__file__)
self.all_tweets_count = None
self.from_date = None
self.from_time = None
self.to_date = None
def generate(self,
from_date=None,
to_date="Today",
from_time=None,
to_time="Now",
max_words=1000):
self.from_time = abs(from_time)
if from_date and to_date:
if from_date == to_date and from_date == "Today":
# Read the whole text.
self.from_date = datetime.date.today() - datetime.timedelta(1)
self.to_date = datetime.date.today()
elif isinstance(from_date, float) and to_date == "Today":
self.from_date = datetime.date.today() + datetime.timedelta(
from_date)
self.to_date = datetime.date.today()
if from_time and to_time:
if isinstance(from_time, float) and to_time == "Now":
self.from_date = datetime.datetime.now() + datetime.timedelta(
hours=from_time)
self.to_date = datetime.datetime.now()
all_tweets = Analysis.objects(
Q(create_date__lt=self.to_date.replace(tzinfo=tz.tzlocal()))
& Q(create_date__gte=self.from_date.replace(tzinfo=tz.tzlocal()))
& Q(user_mentions=[])).all()
self.all_tweets_count = all_tweets.count()
all_words = []
for item in all_tweets:
tw_text = item.clean_text
for sentese in tw_text:
for item, key in sentese:
if key in ['Ne', 'N', 'AJ', 'AJe']:
word = ''
for w in item:
if u'\u0600' <= w <= u'\u06FF':
word += w
all_words.append(word)
text = ' '.join(all_words)
twitter_mask = np.array(
Image.open(path.join(self.d, "image/twitter-logo.jpg")))
# Generate a word cloud image
stopwords = add_stop_words(['توییت', 'رو', 'توییتر'])
self.tweet_cloud = PersianWordCloud(only_persian=True,
max_words=max_words,
stopwords=stopwords,
margin=0,
min_font_size=12,
max_font_size=100,
random_state=1,
background_color="white",
mask=twitter_mask).generate(text)
def send(self):
filename = datetime.datetime.today().strftime('%Y-%m-%d-%H:%m')
image = (path.join(self.d, 'tmp/' + filename + '.png'))
img = self.tweet_cloud.to_image()
img.save(image)
# img.show()
self.file_names.append(path.join(self.d, 'tmp/' + filename + '.png'))
media_ids = []
for file in self.file_names:
res = api.media_upload(file)
media_ids.append(res.media_id)
status_text = "ابر کلمات {} ساعت گذشته \n در تاریخ {} \n از {} توییت".format(
int(self.from_time),
jdatetime.datetime.fromgregorian(
datetime=datetime.datetime.now()).strftime('%H:%m - %m/%d'),
self.all_tweets_count,
)
api.update_status(status=status_text, media_ids=media_ids)
@staticmethod
def send_text_cloud(f_date, f_time, max_words):
command_cloud = TweetCloud()
MessageBoot.send('im going to generate Text CLOUD')
command_cloud.generate(from_date=f_date,
from_time=f_time,
max_words=max_words)
command_cloud.send()
MessageBoot.send('Text Cloud send')
return dict
text = open(path.join(d, 'sohrab.txt'), encoding='utf-8').read()
# Add another stopword
stopwords = add_stop_words(['شاسوسا'])
# add_stop_words
data_s = pickle.load(open("sohrab_data.pkl", "rb"))
data_m = pickle.load(open("moshiri_data.pkl", "rb"))
frequency_data = difference(data_s, data_m)
# Generate a word cloud image
wordcloud = PersianWordCloud(
only_persian=True,
max_words=100,
stopwords=stopwords,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
background_color="black").generate_from_frequencies(
frequencies=frequency_data)
image = wordcloud.to_image()
image.show()
image.save('difference_word_map.png')
background_color="Black",
collocations=False).generate(difference_text)
wordcloud_similarity = PersianWordCloud(
only_persian=True,
max_words=100,
stopwords=stopwords,
margin=0,
width=800,
height=800,
min_font_size=1,
max_font_size=500,
background_color="Black",
collocations=False).generate(similarity_text)
image_difference = wordcloud_difference.to_image()
image_difference.show()
image_difference.save('difference.png')
image_similarity = wordcloud_similarity.to_image()
image_similarity.show()
image_similarity.save('similarity.png')
image_emam = wordcloud_emam.to_image()
image_emam.show()
image_emam.save('emam.png')
image_shah = wordcloud_shah.to_image()
image_shah.show()
image_shah.save('shah.png')