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
