ease/feature_extractor.py
def gen_prompt_feats(self, e_set):
        """
        Generates prompt based features from an essay set object and internal prompt variable.
        Generally called internally by gen_feats
        Returns an array of prompt features
        e_set - EssaySet object
        """
        prompt_toks = nltk.word_tokenize(e_set._prompt)
        expand_syns = []
        for word in prompt_toks:
            synonyms = util_functions.get_wordnet_syns(word)
            expand_syns.append(synonyms)
        expand_syns = list(chain.from_iterable(expand_syns))
        prompt_overlap = []
        prompt_overlap_prop = []
        for j in e_set._tokens:
            tok_length=len(j)
            if(tok_length==0):
                tok_length=1
            prompt_overlap.append(len([i for i in j if i in prompt_toks]))
            prompt_overlap_prop.append(prompt_overlap[len(prompt_overlap) - 1] / float(tok_length))
        expand_overlap = []
        expand_overlap_prop = []
        for j in e_set._tokens:
            tok_length=len(j)
            if(tok_length==0):
                tok_length=1
            expand_overlap.append(len([i for i in j if i in expand_syns]))
            expand_overlap_prop.append(expand_overlap[len(expand_overlap) - 1] / float(tok_length))

        prompt_arr = numpy.array((prompt_overlap, prompt_overlap_prop, expand_overlap, expand_overlap_prop)).transpose()

        return prompt_arr.copy()
def gen_prompt_feats(self, e_set):
        """
        Generates prompt based features from an essay set object and internal prompt variable.
        Generally called internally by gen_feats
        Returns an array of prompt features
        e_set - EssaySet object
        """
        prompt_toks = nltk.word_tokenize(e_set._prompt)
        expand_syns = []
        for word in prompt_toks:
            synonyms = util_functions.get_wordnet_syns(word)
            expand_syns.append(synonyms)
        expand_syns = list(chain.from_iterable(expand_syns))
        prompt_overlap = []
        prompt_overlap_prop = []
        for j in e_set._tokens:
            tok_length=len(j)
            if(tok_length==0):
                tok_length=1
            prompt_overlap.append(len([i for i in j if i in prompt_toks]))
            prompt_overlap_prop.append(prompt_overlap[len(prompt_overlap) - 1] / float(tok_length))
        expand_overlap = []
        expand_overlap_prop = []
        for j in e_set._tokens:
            tok_length=len(j)
            if(tok_length==0):
                tok_length=1
            expand_overlap.append(len([i for i in j if i in expand_syns]))
            expand_overlap_prop.append(expand_overlap[len(expand_overlap) - 1] / float(tok_length))

        prompt_arr = numpy.array((prompt_overlap, prompt_overlap_prop, expand_overlap, expand_overlap_prop)).transpose()

        return prompt_arr.copy()
Generates prompt based features from an essay set object and internal prompt variable.
        Generally called internally by gen_feats
        Returns an array of prompt features
        e_set - EssaySet object