def checkIdenticals():
old = ptd.getDataWithMeta()
old_2011 = old[old.Publication_year == 2011]
old_2011_wos = old_2011.WOS.tolist()
new = ptd.getUnlabelledData()
print("len of new data: {}".format(len(new)))
new_2011 = new[new.Publication_year == "2011"]
new_2011_wos = new_2011.WOS.tolist()
print("old length 2011: {}".format(len(old_2011_wos)))
print("new length 2011: {}".format(len(new_2011_wos)))
print old_2011_wos[:5]
print new_2011_wos[:5]
identical = []
for wos in new_2011_wos:
for wos2 in old_2011_wos:
if wos == wos2:
print("{}\n{}\n".format(wos, wos2))
identical.append(wos)
print("Number of identical papers = {}".format(len(identical)))
new_data = ptd.getUnlabelledDataAsList()
print ("len of old before: {}".format(len(new_data)))
new_data_after = []
for dic in new_data:
if dic["WOS"] not in identical:
new_data_after.append(dic)
print ("len of old after: {}".format(len(new_data_after)))
none_c = 0
for pred in predictions:
if pred == "AGAINST":
against_c += 1
elif pred == "FAVOR":
favor_c += 1
else:
none_c += 1
print("\nThe distribution of predictions are: ")
print("\tFAVOR: \t{}".format(favor_c))
print("\tAGAINST:\t{}".format(against_c))
print("\tNONE: \t{}".format(none_c))
unique_years = list(set(unlabelled_data.Publication_year.tolist()))
unlabelled_data = ptd.getUnlabelledDataAsList()
for i, dic in enumerate(unlabelled_data):
dic["Stance"] = predictions[i]
for year in unique_years:
favor_c = 0
against_c = 0
none_c = 0
for dic in unlabelled_data:
if dic["Publication_year"] == year:
if dic["Stance"] == "AGAINST":
against_c += 1
elif dic["Stance"] == "FAVOR":
favor_c += 1
else:
