def phrase_ranking(neg_examples,pos_examples,vocab,W1,W2,b1,b2,Wlabel,normalized):
#first loop over neg_examples
phrase_list = []
score_list = []
meaning_list = []
label = np.array([0.0,1.0])
for example in neg_examples:
sub_phrase_list = []
sub_score_list = []
sub_meaning_list = []
N = len(example)
num_nodes = 2*N - 1
tree_stuff = tm.build_tree(example,label,vocab,W1,W2,b1,b2,Wlabel,normalized)
tree_info = tree_stuff[0]
tree_meanings = tree_stuff[1]
for i in range(N):
sub_phrase_list.append([example[i]])
for k in range(N,num_nodes):
left = tree_info[0,k]
right = tree_info[1,k]
phrase = sub_phrase_list[left] + sub_phrase_list[right]
sub_phrase_list.append(phrase)
for j in range(num_nodes):
predicted = tm.make_d(tree_meanings[:,j],Wlabel)
score = math.log(predicted[0]/predicted[1])
sub_score_list.append(score)
sub_meaning_list.append(tree_meanings[:,j])
score_list += sub_score_list
meaning_list += sub_meaning_list
phrase_list += sub_phrase_list
label = np.array([1.0,0.0])
for example in pos_examples:
sub_phrase_list = []
sub_score_list = []
sub_meaning_list = []
N = len(example)
num_nodes = 2*N - 1
tree_stuff = tm.build_tree(example,label,vocab,W1,W2,b1,b2,Wlabel,normalized)
tree_info = tree_stuff[0]
tree_meanings = tree_stuff[1]
for i in range(N):
sub_phrase_list.append([example[i]])
for k in range(N,num_nodes):
left = tree_info[0,k]
right = tree_info[1,k]
phrase = sub_phrase_list[left] + sub_phrase_list[right]
sub_phrase_list.append(phrase)
for j in range(num_nodes):
predicted = tm.make_d(tree_meanings[:,j],Wlabel)
score = math.log(predicted[0]/predicted[1])
sub_score_list.append(score)
sub_meaning_list.append(tree_meanings[:,j])
score_list += sub_score_list
meaning_list += sub_meaning_list
phrase_list += sub_phrase_list
return phrase_list,score_list,meaning_list
def word_ranks(vocab,Wlabel):
v_size = np.shape(vocab)[0]
score_list = []
meaning_list = []
word_list = []
for i in range(1,v_size):
label = tm.make_d(vocab[i,:],Wlabel)
score_list.append(math.log(label[0]/label[1]))
meaning_list.append(vocab[i,:])
word_list.append([i])
return word_list,score_list,meaning_list