Fix whitespace

spacy/lang/ja/__init__.py

@@ -38,24 +38,20 @@ def resolve_pos(token):
     in the sentence. This function adds information to the POS tag to
     resolve ambiguous mappings.
     """
-
     # TODO: This is a first take. The rules here are crude approximations.
     # For many of these, full dependencies are needed to properly resolve
     # PoS mappings.
-
     if token.pos == "連体詞,*,*,*":
         if re.match(r"[こそあど此其彼]の", token.surface):
             return token.pos + ",DET"
         if re.match(r"[こそあど此其彼]", token.surface):
             return token.pos + ",PRON"
         return token.pos + ",ADJ"
-
     return token.pos
 
 
 def detailed_tokens(tokenizer, text):
     """Format Mecab output into a nice data structure, based on Janome."""
-
     node = tokenizer.parseToNode(text)
     node = node.next  # first node is beginning of sentence and empty, skip it
     words = []
@@ -64,12 +60,10 @@ def detailed_tokens(tokenizer, text):
         base = surface  # a default value. Updated if available later.
         parts = node.feature.split(",")
         pos = ",".join(parts[0:4])
-
         if len(parts) > 7:
             # this information is only available for words in the tokenizer
             # dictionary
             base = parts[7]
-
         words.append(ShortUnitWord(surface, base, pos))
         node = node.next
     return words
@@ -78,29 +72,24 @@ def detailed_tokens(tokenizer, text):
 class JapaneseTokenizer(DummyTokenizer):
     def __init__(self, cls, nlp=None):
         self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
-
         self.tokenizer = try_mecab_import().Tagger()
         self.tokenizer.parseToNode("")  # see #2901
 
     def __call__(self, text):
         dtokens = detailed_tokens(self.tokenizer, text)
-
         words = [x.surface for x in dtokens]
         spaces = [False] * len(words)
         doc = Doc(self.vocab, words=words, spaces=spaces)
-
         for token, dtoken in zip(doc, dtokens):
             token._.mecab_tag = dtoken.pos
             token.tag_ = resolve_pos(dtoken)
             token.lemma_ = dtoken.lemma
-
         return doc
 
 
 class JapaneseDefaults(Language.Defaults):
     lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
     lex_attr_getters[LANG] = lambda _text: "ja"
-
     tag_map = TAG_MAP
 
     @classmethod