pep8/pycodestyle fixes for hanging indents in Summarization module

gensim/summarization/__init__.py

@@ -1,4 +1,4 @@
 
 # bring model classes directly into package namespace, to save some typing
 from .summarizer import summarize, summarize_corpus
-from .keywords import keywords
+from .keywords import keywords

gensim/summarization/bm25.py

@@ -40,16 +40,16 @@ def initialize(self):
                 self.df[word] += 1
 
         for word, freq in iteritems(self.df):
-            self.idf[word] = math.log(self.corpus_size-freq+0.5) - math.log(freq+0.5)
+            self.idf[word] = math.log(self.corpus_size - freq + 0.5) - math.log(freq + 0.5)
 
     def get_score(self, document, index, average_idf):
         score = 0
         for word in document:
             if word not in self.f[index]:
                 continue
             idf = self.idf[word] if self.idf[word] >= 0 else EPSILON * average_idf
-            score += (idf*self.f[index][word]*(PARAM_K1+1)
-                      / (self.f[index][word] + PARAM_K1*(1 - PARAM_B+PARAM_B*self.corpus_size / self.avgdl)))
+            score += (idf * self.f[index][word] * (PARAM_K1 + 1)
+                      / (self.f[index][word] + PARAM_K1 * (1 - PARAM_B + PARAM_B * self.corpus_size / self.avgdl)))
         return score
 
     def get_scores(self, document, average_idf):

gensim/summarization/keywords.py

@@ -164,7 +164,7 @@ def _get_combined_keywords(_keywords, split_text):
                 result.append(word)   # appends last word if keyword and doesn't iterate
             for j in xrange(i + 1, len_text):
                 other_word = _strip_word(split_text[j])
-                if other_word in _keywords and other_word == split_text[j] and not other_word in combined_word:
+                if other_word in _keywords and other_word == split_text[j] and other_word not in combined_word:
                     combined_word.append(other_word)
                 else:
                     for keyword in combined_word:

gensim/summarization/summarizer.py

@@ -198,10 +198,10 @@ def summarize(text, ratio=0.2, word_count=None, split=False):
         logger.warning("Input text is empty.")
         return
 
-    # If only one sentence is present, the function raises an error (Avoids ZeroDivisionError). 
+    # If only one sentence is present, the function raises an error (Avoids ZeroDivisionError).
     if len(sentences) == 1:
         raise ValueError("input must have more than one sentence")
-    
+
     # Warns if the text is too short.
     if len(sentences) < INPUT_MIN_LENGTH:
         logger.warning("Input text is expected to have at least " + str(INPUT_MIN_LENGTH) + " sentences.")