for sentence in tokenized:

    pos_sentences = st.tag(sentence)

    #print pos_sentences

    tmp = []

    # mapping nltk pos tags to wordnet pos tags

    for tok, pos in pos_sentences:

        lower_pos = pos[0].lower()

        if lower_pos in ['a', 'n', 'v', 'r', 's']:

            res = wordnet.synsets(tok, lower_pos)

            if len(res) > 0:

                a = res[0]

        else:

            a = "[{0}, {1}]".format(tok, pos)


        tmp.append(a)
        #print a

    wordnet_sense.append(tmp)


print wordnet_sense

>>> [['[angry, JJ]'], [Synset('anger.n.01')], [Synset('happiness.n.01')], ['[sad, JJ]']]

for i in wordnet_sense:
    for v in i:

        wna = WNAffect('wordnet-1.6/', 'wn-domains-3.2/')
        emo = wna.get_emotion(v[0], v[1])

        print emo