#!/usr/bin/env python3
from src.TextCorpus import TextCorpus
from src.Text import Text
from src.Network import Network
from src.rule_set import english
import os
current_dir = os.path.dirname(os.path.abspath(__file__))
text_filename = os.path.join(
current_dir,
'datasets/bbc-news/news/tech/call-for-action-on-internet-scam.txt')
print('Analyzing ' + text_filename)
corpus = TextCorpus(os.path.join(current_dir, 'datasets/bbc-news.json'))
text = Text(corpus, open(text_filename, mode='r', encoding='utf-8').read())
print('Text of ' + str(len(text.terms)) + ' terms with average score of ' +
str(text.avg_score))
net = Network(english)
net.merge(text)
net.save_graph('output/test')
net.log_to_html()
print('Graph saved to test-edges.xlsx!')
default=None,
type=float,
help=
'threshold (TF-IDF value) below which concepts will not be included to the graph'
)
args = arg_parser.parse_args()
current_dir = os.path.dirname(os.path.abspath(__file__))
df_filename = os.path.normpath(
os.path.join(current_dir, 'datasets/bbc-news.json'))
texts_path = os.path.normpath(os.path.join(current_dir, 'input'))
print('Loading DF metrics from ')
corpus = TextCorpus(df_filename)
print('Creating English semantic network...')
net = Network(english, args.threshold)
print('Reading texts from ' + texts_path)
for filename in glob.iglob(os.path.join(texts_path, '**/*.*'), recursive=True):
text = Text(corpus,
open(filename, mode='r', encoding='utf-8').read(),
name=re.search('[^\\\/]+$', filename).group(0))
print('Text of ' + str(len(text.terms)) + ' terms with average score of ' +
str(text.avg_score))
net.merge(text)
net.save_graph('output/output')
net.log_to_html()
print('Graph saved to ' + current_dir +
'/output/output-edges.xlsx (output-nodes.xlsx)!')
