feature_dictionary[language_code]="Tense-aspect prefixes"
if feature_dictionary[language_code]!=wals_value:
output.write(language_code+"\n")
output.write("Our value "+feature_dictionary[language_code]+" WALS "+wals_value+"\n")
for igt in igt_list:
printIGT(igt,output)
print(language_code,prefix_count,suffix_count,affix_count,no_affix_count,wals_value)
print(str(lang_count),"languages classified")
#find the accuracy
possibilities = ["Tense-aspect prefixes","Tense-aspect suffixes","Mixed type","No tense-aspect inflection","Tense-aspect tone"]
confusion_matrix = ConfusionMatrix("Generated and WALS", possibilities)
correct=0
for code in feature_dictionary:
our_value = feature_dictionary[code]
try:
wals_code = wals_dictionary.iso_to_wals[code]
wals_value = wals.feature_dictionary[wals_code]
confusion_matrix.addLabel(wals_value, our_value)
except KeyError:
print("No matching WALS data for language " + code)
print(confusion_matrix.printMatrix())
print("baseline accuracy:"+str(baseline_correct/lang_count))
output.close()
results.close()
