fix docs

docs/index.rst

@@ -1,18 +1,26 @@
 .. nagisa documentation master file, created by
-   sphinx-quickstart on Wed Jun 13 00:32:26 2018.
+   sphinx-quickstart on Wed Jun 13 23:53:38 2018.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to nagisa's documentation!
-==================================
+nagisa documentation
+====================
+
+| Nagisa is a python module for Japanese word segmentation/POS-tagging.  
+| It is designed to be a simple and easy-to-use tool.  
+
+This tool has the following features.
+    - Based on recurrent neural networks. 
+    - The word segmentation model uses character- and word-level features.
+    - The POS-tagging model uses tag dictionary information.
 
 .. toctree::
    :maxdepth: 2
    :caption: Contents:
 
+   introduction
    nagisa
 
-
 Indices and tables
 ==================
 

docs/nagisa.rst

@@ -1,33 +1,6 @@
 nagisa package
 ==============
 
-Submodules
-----------
-
-nagisa.mecab\_system\_eval module
----------------------------------
-
-.. automodule:: nagisa.mecab_system_eval
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-nagisa.model module
--------------------
-
-.. automodule:: nagisa.model
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-nagisa.prepro module
---------------------
-
-.. automodule:: nagisa.prepro
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
 nagisa.tagger module
 --------------------
 
@@ -36,27 +9,3 @@ nagisa.tagger module
     :undoc-members:
     :show-inheritance:
 
-nagisa.train module
--------------------
-
-.. automodule:: nagisa.train
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-nagisa.utils module
--------------------
-
-.. automodule:: nagisa.utils
-    :members:
-    :undoc-members:
-    :show-inheritance:
-
-
-Module contents
----------------
-
-.. automodule:: nagisa
-    :members:
-    :undoc-members:
-    :show-inheritance:

nagisa/tagger.py

@@ -16,10 +16,15 @@ class Tagger(object):
     """
     This class has a word segmentation function and a POS-tagging function for Japanese.
     """
-    def __init__(self, vocabs=base+'/data/nagisa_v001.dict',
-                 params=base+'/data/nagisa_v001.model', 
-                 hp=base+'/data/nagisa_v001.hp',
-                 single_word_list=None):
+
+    def __init__(self, vocabs=None, params=None, hp=None, single_word_list=None):
+        if vocabs is None:
+            vocabs = base + '/data/nagisa_v001.dict'
+        if params is None:
+            params = base + '/data/nagisa_v001.model'
+        if hp is None:
+            hp = base + '/data/nagisa_v001.hp'
+
         # Load vocaburary files
         vocabs = utils.load_data(vocabs) 
         self._uni2id, self._bi2id, self._word2id, self._pos2id, self._word2postags = vocabs
@@ -41,10 +46,15 @@ def __init__(self, vocabs=base+'/data/nagisa_v001.dict',
 
 
     def wakati(self, text, lower=False):
-        """
-        Return the words of the given sentence.
-        Input: str (a sentence)
-        Output: the list of the words
+        """Return the words of the given sentence.
+
+        args:
+            - text (str): An input sentence.
+            - lower (bool): If lower is True, all uppercase characters in a list \
+                            of the words are converted into lowercase characters.
+
+        return:
+            - words (list): A list of the words.
         """
         text = utils.preprocess(text)
         lower_text = text.lower()
@@ -87,10 +97,14 @@ def wakati(self, text, lower=False):
 
 
     def tagging(self, text, lower=False):
-        """
-        Return the words with POS-tags of the given sentence.
-        Input: str (a sentence)
-        Output: the object of the words with POS-tags
+        """ Return the words with POS-tags of the given sentence.
+
+        args:
+            - text (str): An input sentence.
+            - lower (bool): If lower is True, all uppercase characters in a list \
+                            of the words are converted into lowercase characters.
+        return:
+            - object : The object of the words with POS-tags.
         """
         words = self.wakati(text, lower)
 
@@ -117,10 +131,17 @@ def tagging(self, text, lower=False):
 
 
     def filter(self, text, lower=False, filter_postags=[]):
-        """
-        Return the filtered words with POS-tags of the given sentence.
-        Input: str (a sentence)
-        Output: the object of the words with POS-tags
+        """Return the filtered words with POS-tags of the given sentence.
+
+        args:
+            - text (str): An input sentence.
+            - lower (bool): If lower is True, all uppercase characters in a list \
+                            of the words are converted into lowercase characters.
+            - filter_postags (list): Filtering the word with the POS-tag in \
+                                     filter_postags from a text.
+
+        return:
+            - object : The object of the words with POS-tags.
         """
         words   = []
         postags = []
@@ -133,10 +154,18 @@ def filter(self, text, lower=False, filter_postags=[]):
 
 
     def extract(self, text, lower=False, extract_postags=[]):
-        """
-        Return the extracted words with POS-tags of the given sentence.
-        Input: str (a sentence)
-        Output: the object of the words with POS-tags
+        """Return the extracted words with POS-tags of the given sentence.
+
+        args:
+            - text (str): An input sentence.
+            - lower (bool): If lower is True, all uppercase characters in a list \
+                            of the words are converted into lowercase characters.
+            - filter_postags (list): Extracting the word with the POS-tag in \
+                                     filter_postags from a text.
+
+        return:
+            - object : The object of the words with POS-tags.
+
         """
         words   = []
         postags = []