import nltk

__author__ = "Sreejith Sreekumar"
__email__ = "sreekumar.s@husky.neu.edu"
__version__ = "0.0.1"

nltk.download('wordnet')
from nltk.corpus import wordnet


#wordnet.synsets('dog')

def calc_sim(vectors, words):

    num = np.dot(vectors[words[0]], vectors[words[1]])
    den = (np.linalg.norm(vectors[words[0]]) * np.linalg.norm(vectors[words[1]]))
    return (num/den)



def alg1(w1, w2):

    wordFromList1 = wordnet.synsets(w1)
    wordFromList2 = wordnet.synsets(w2)

    res = []
    if wordFromList1 and wordFromList2: #Thanks to @alexis' note
        s = wordFromList1[0].wup_similarity(wordFromList2[0])
        res.append(s)
    else:
        res = 0.5

    return res



alg1('planet','moon')