def testall(directory, pred_file=None, label_file=None, out_path=None): folders = os.listdir(directory) networks = [] for folder in folders: if os.path.isfile(directory+folder+"/network.cfg") and os.path.exists(directory+folder+"/results"): networks.append(folder) config_file = directory+networks[0]+"/network.cfg" config = ConfigParser.ConfigParser() config.read(config_file) test_data = LoadData(directory = config.get('Testing Data', 'folders').split(','), data_file_name = config.get('Testing Data', 'data_file'), label_file_name = config.get('Testing Data', 'label_file'), seg_file_name = config.get('Testing Data', 'seg_file')) res = Analyzer(raw = test_data.get_data()[0], target = test_data.get_labels()[0]) for net in networks: config_file = directory+net+"/network.cfg" config = ConfigParser.ConfigParser() config.read(config_file) res.add_results(results_folder = config.get('General','directory'), name = net, prediction_file = config.get('Testing', 'prediction_file')+'_0', learning_curve_file = 'learning_curve') res.analyze(-1, pred_file=pred_file, label_file=label_file, out_path=out_path) return res
def test_analyze_judgement_weight(self): """ Testing the value order of arbitrary tweets """ ana = Analyzer() assert ana.analyze("i am so happy, great day :D") > ana.analyze("i am so happy :D") assert ana.analyze("so sad, feeling depressed :'(") < ana.analyze("so depressed :'(")
def test_analyze_empty(self): """ Testing empty tweets and tweets including words not in the dictionary """ ana = Analyzer() assert ana.analyze("") == 0.5 assert ana.analyze("hzoehfsdl") == 0.5
def test_analyze_empty(self): """ Testing empty tweets and tweets including words not in the dictionary """ ana = Analyzer() assert ana.analyze("") == 0.5 assert ana.analyze("hzoehfsdl") == 0.5
def test_analyze_judgement(self): """ Testing the proper judgement of the sentiment analysis: * positive and negative * best and worse tweet values """ ana = Analyzer() assert ana.analyze(":)") > 0.5 and ana.analyze(":'(") < 0.5 assert ana.analyze("yahoo yahoo yahoo") == 1.0 assert ana.analyze("zzz zzz zzz zzz zzz") == 0.0
def test_analyze_judgement_weight(self): """ Testing the value order of arbitrary tweets """ ana = Analyzer() assert ana.analyze("i am so happy, great day :D") > ana.analyze( "i am so happy :D") assert ana.analyze("so sad, feeling depressed :'(") < ana.analyze( "so depressed :'(")
def test_analyze_judgement(self): """ Testing the proper judgement of the sentiment analysis: * positive and negative * best and worse tweet values """ ana = Analyzer() assert ana.analyze(":)") > 0.5 and ana.analyze(":'(") < 0.5 assert ana.analyze("yahoo yahoo yahoo") == 1.0 assert ana.analyze("zzz zzz zzz zzz zzz") == 0.0
def test_analyze_bounds(self): """ Testing the bounds of the tweets values """ ana = Analyzer() assert ana.analyze("this is a test neutral tweet") <= 1.0 assert ana.analyze("this is a test neutral tweet") >= 0.0
def test_analyze_bounds(self): """ Testing the bounds of the tweets values """ ana = Analyzer() assert ana.analyze("this is a test neutral tweet") <= 1.0 assert ana.analyze("this is a test neutral tweet") >= 0.0
def testprediction(config_file, pred_file=None, label_file=None, out_path=None): config = ConfigParser.ConfigParser() config.read(config_file) test_data = LoadData(directory = config.get('Testing Data', 'folders').split(','), data_file_name = config.get('Testing Data', 'data_file'), label_file_name = config.get('Testing Data', 'label_file'), seg_file_name = config.get('Testing Data', 'seg_file')) res = Analyzer(raw = test_data.get_data()[0], target = test_data.get_labels()[0]) res.add_results(results_folder = config.get('General','directory'), name = config_file.split('/')[-3], prediction_file = config.get('Testing', 'prediction_file')+'_0', learning_curve_file = 'learning_curve') res.analyze(-1, pred_file=pred_file, label_file=label_file, out_path=out_path) return res