def test_level2(sourceword,target): bestoutfn = "../L2output/{0}.{1}.best".format(sourceword, target) oofoutfn = "../L2output/{0}.{1}.oof".format(sourceword, target) bestoutfile = open(bestoutfn,'w') oofoutfile = open(oofoutfn,'w') level2_classifier = util_run_experiment.get_pickled_classifier(sourceword,target,'level2') frd1,frd2,frd3,frd4 = sorted(list(get_four_friends(target))) ##Need 4 more features from level1. classfrd1,classfrd2,classfrd3,classfrd4 = get_level1_classifiers(frd1,frd2,frd3,frd4,sourceword) # finaldir = "../trialdata/alltrials/" finaldir = "../finaltest" problems = util_run_experiment.get_test_instances(finaldir, sourceword) for problem in problems: level1_features = features.extract(problem) answer_frd1 = classfrd1.classify(level1_features) answer_frd2 = classfrd2.classify(level1_features) answer_frd3 = classfrd3.classify(level1_features) answer_frd4 = classfrd4.classify(level1_features) level2_features = train_extracted_level2.extend_features(level1_features,(answer_frd1,answer_frd2,answer_frd3,answer_frd4),frd1,frd2,frd3,frd4) level2_answer = level2_classifier.classify(level2_features) level2_dist = level2_classifier.prob_classify(level2_features) oof_answers = util_run_experiment.topfive(level2_dist) print(output_one_best(problem, target, level2_answer), file=bestoutfile) print(output_five_best(problem, target, oof_answers), file=oofoutfile)
def main(): parser = util_run_experiment.get_argparser() args = parser.parse_args() assert args.targetlang in all_target_languages assert args.sourceword in all_words targetlang = args.targetlang sourceword = args.sourceword trialdir = args.trialdir stanford.taggerhome = args.taggerhome print("Loading and tagging test problems...") problems = util_run_experiment.get_test_instances(trialdir, sourceword) print("OK loaded and tagged.") ## classifier = get_maxent_classifier(sourceword, targetlang) classifier = get_pickled_classifier(sourceword, targetlang, "level1") if not classifier: print("Couldn't load pickled L1 classifier?") return print("Loaded pickled L1 classifier!") bestoutfn = "../L1output/{0}.{1}.best".format(sourceword, targetlang) oofoutfn = "../L1output/{0}.{1}.oof".format(sourceword, targetlang) with open(bestoutfn, "w") as bestoutfile, \ open(oofoutfn, "w") as oofoutfile: for problem in problems: featureset = features.extract(problem) answer = classifier.classify(featureset) dist = classifier.prob_classify(featureset) oof_answers = util_run_experiment.topfive(dist) print(output_one_best(problem, targetlang, answer), file=bestoutfile) print(output_five_best(problem, targetlang, oof_answers), file=oofoutfile)