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()
def gen_prompt_feats ( self , e_set ) : 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
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