Trying something crazy...

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='SPLAT-library',
-    version='0.3.6',
+    version='0.3.7',
     description='Speech Processing & Linguistic Analysis Tool',
     long_description="SPLAT is a command-line application designed to make it easy for linguists (both computer-oriented and non-computer-oriented) to use the Natural Language Tool Kit (NLTK) for analyzing virtually any text file.\n\nSPLAT is designed to help you gather linguistic features from text files and it is assumed that most input files will not be already annotated. In order for SPLAT to function properly, you should ensure that the input files that you provide do not contain any annotations. Because there are so many variations of linguistic annotation schemes, it would simply be impossible to account for all of them in the initial parsing of input files; it is easier for you to remove any existing annotations than it is for me to do so.",
     url='http://splat-library.org',
@@ -23,7 +23,7 @@
         'splat.taggers',
         'splat.tokenizers'
     ],
-    download_url='https://github.com/meyersbs/SPLAT/archive/v0.3.6.tar.gz',
+    download_url='https://github.com/meyersbs/SPLAT/archive/v0.3.7.tar.gz',
     requires=['matplotlib', 'nltk', 'jsonpickle'],
     classifiers=[
         'Development Status :: 3 - Alpha',

splat/SPLAT.py

@@ -59,15 +59,7 @@ class SPLAT:
     # Frequency Distribution Variables
     __freq_dist = None
 
-    # Object Declarations
-    __ngramminator = FullNGramminator()
-    __cleantokenizer = CleanTokenizer()
-    __rawtokenizer = RawTokenizer()
-    __sentenizer = CleanSentenizer()
-    __postagger = NLTKPOSTagger()
-    __treestring_gen = TreeStringParser()
-
-    def __init__(self, text, ngramminator=FullNGramminator(), postagger=NLTKPOSTagger()):
+    def __init__(self, text):
         """
         Creates a SPLAT Object.
         """
@@ -89,23 +81,15 @@ def __init__(self, text, ngramminator=FullNGramminator(), postagger=NLTKPOSTagge
             raise ValueError("WARNING: SPLAT must be of type str or file.")
 
         self.__uttcount = len(self.__utterances)
-        self.__sentences = self.__sentenizer.sentenize(self.__splat)
+        self.__sentences = CleanSentenizer().sentenize(self.__splat)
         if self.__sentences == []: self.__sentences = self.__utterances
         self.__sentcount = len(self.__sentences)
-        self.__rawtokens = self.__rawtokenizer.tokenize(self.__splat)
-        self.__tokens = self.__cleantokenizer.tokenize(self.__splat)
+        self.__rawtokens = RawTokenizer().tokenize(self.__splat)
+        self.__tokens = CleanTokenizer().tokenize(self.__splat)
         self.__rawtypes = Util.typify(self.__rawtokens)
         self.__types = Util.typify(self.__tokens)
         self.__wordcount = Util.wordcount(self.__rawtokens)
         self.__unique_wordcount = Util.wordcount(self.__types)
-        if ngramminator == {}:
-            self.__ngramminator = FullNGramminator()
-        else:
-            self.__ngramminator = ngramminator
-        if postagger == {}:
-            self.__postagger = NLTKPOSTagger()
-        else:
-            self.__postagger = postagger
         self.__ttr = Util.type_token_ratio(self.__types, self.__tokens)
         self.__alu = round(float(self.__wordcount) / float(self.__uttcount), 4) if self.__uttcount != 0 else 0.0
         self.__als = round(float(self.__wordcount) / float(self.__sentcount), 4) if self.__sentcount != 0 else 0.0
@@ -309,23 +293,23 @@ def shortest_words(self):
     def unigrams(self):
         """ Returns a list of unigrams. """
         if self.__unigrams is None:
-            self.__unigrams = self.__ngramminator.unigrams(self.__splat)
+            self.__unigrams = FullNGramminator().unigrams(self.__splat)
             return self.__unigrams
         else:
             return self.__unigrams
 
     def bigrams(self):
         """ Returns a list of bigrams. """
         if self.__bigrams is None:
-            self.__bigrams = self.__ngramminator.bigrams(self.__splat)
+            self.__bigrams = FullNGramminator().bigrams(self.__splat)
             return self.__bigrams
         else:
             return self.__bigrams
 
     def trigrams(self):
         """ Returns a list of trigrams. """
         if self.__trigrams is None:
-            self.__trigrams = self.__ngramminator.trigrams(self.__splat)
+            self.__trigrams = FullNGramminator().trigrams(self.__splat)
             return self.__trigrams
         else:
             return self.__trigrams
@@ -341,14 +325,14 @@ def ngrams(self, n):
         elif n == 3:
             return self.trigrams()
         else:
-            return self.__ngramminator.ngrams(self.__splat, n)
+            return FullNGramminator().ngrams(self.__splat, n)
 
     ##### PART-OF-SPEECH BASED #########################################################################################
 
     def pos(self):
         """ Returns a list of tuple pairs: (word, POS taggers). """
         if self.__pos is None:
-            self.__pos = self.__postagger.tag(self.__splat)
+            self.__pos = NLTKPOSTagger().tag(self.__splat)
         return self.__pos
 
     def content_function_ratio(self):
@@ -392,8 +376,7 @@ def pos_counts(self):
     def treestrings(self):
         """ Returns a list of parsers trees. """
         if self.__treestrings is None:
-            self.__treestring_gen = TreeStringParser()
-            self.__treestrings = self.__treestring_gen.get_parse_trees(self.__utterances)
+            self.__treestrings = TreeStringParser().get_parse_trees(self.__utterances)
         return self.__treestrings
 
     def drawtrees(self):