def test_validate_date_is_false_words(self):
"""
Test the validate date function
:return: True
"""
v = Validator()
result = v.validate_date("02-March-1991")
self.assertFalse(result, 'invalid Date format')
def get_url(self):
while 1:
url = raw_input("Please insert URL to API :")
validator = Validator()
if validator.validate_url(url):
self.api_url = url
return 0
def test_validate_salary_is_false_negative_value(self):
"""
Test the validate salary function
:return: True
"""
v = Validator()
result = v.validate_salary("-20")
self.assertFalse(result, 'invalid Salary')
def test_validate_salary_is_false_too_small(self):
"""
Test the validate salary function
:return:
"""
v = Validator()
result = v.validate_salary('8')
self.assertFalse(result, 'invalid SALARY')
def test_validate_salary_is_true_3_digit(self):
"""
Test the validate salary function
:return: True
"""
v = Validator()
result = v.validate_salary("200")
self.assertTrue(result, 'valid Salary')
def test_validate_salary_is_false_words(self):
"""
Test the validate salary function
:return: True
"""
v = Validator()
result = v.validate_salary("seventy thousand")
self.assertFalse(result, 'valid Salary')
def __init__(self):
self.modes = {
'AUTHENTICATION': self.process_token,
'VOTING': self.vote,
'FEEDBACK': self.send_feedback,
self.confirm: 'CONFIRMATION'
}
self.key_val = Validator(KEYS_FILE)
def __init__(self, hps, device):
self.hps = hps
self.device = device
# load validator
# when paired validation data is available, we also calculate bleu
if hps.paired_valid_data is not None:
self.bleu_validator = Validator(hps.paired_valid_data, device)
def representation():
is_validation_pass, flash_message = Validator(
request, request.files['file']).get_results()
if not is_validation_pass:
flash(flash_message)
return render_template('index.html')
return render_template('representation.html')
def test_validate_method_name_is_false2(self):
validator = Validator()
result_1 = validator.validate_method_name("Name")
result_2 = validator.validate_method_name("get_Name")
result_3 = validator.validate_method_name("1_get")
self.assertFalse(result_1)
self.assertFalse(result_2)
self.assertFalse(result_3)
def validate_text(self):
brackets = self.inputBracketsLineEdit.text()
if len(brackets) % 2 != 0 or brackets == '':
QMessageBox.warning(self, 'Alarm', 'Incorrect number of brackets')
validator = Validator(brackets)
self.inputTextEdit.setText(
validator.validate(self.inputTextEdit.toPlainText()))
def test_validate_salary_is_true_small_but_includes_zero(self):
"""
Test the validate salary function
:return:
"""
v = Validator()
result = v.validate_salary('008')
self.assertTrue(result, 'valid SALARY')
def test_validate_date_is_true(self):
"""
Test the validate date function
:return: True
"""
v = Validator()
result = v.validate_date("02-03-1990")
self.assertTrue(result, 'valid Date')
def test_09_validate_bmi_is_true(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi("Normal")
self.assertTrue(result, "Valide BMI")
def test_validate_date_is_false_invalid_format(self):
"""
Test the validate date function
:return:
"""
v = Validator()
result = v.validate_date('01/08/1991')
self.assertFalse(result, 'invalid date, wrong format')
def test_11_validate_bmi_is_false_notEqualN(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi("N")
self.assertNotEqual(result, 'Normal', "Invaid BMI")
def test_10_validate_bmi_is_false_space(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi(" ")
self.assertFalse(result, "Invalid BMI")
def test_14_validate_bmi_is_false_notequal_over(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi("OVERWEIGHT")
self.assertNotEqual(result, 'Overweight', "Invaid BMI")
def test_12_validate_bmi_is_false_notEqualO(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi("OBESITY")
self.assertNotEqual(result, 'Obesity', "Invaid BMI")
def test_validate_age_is_false_negative_num(self):
"""
Test the validate age function
:return:
"""
v = Validator()
result = v.validate_age('-20')
self.assertFalse(result, 'invalid AGE')
def test_15_validate_bmi_is_false_notequal_under(self):
"""
Test the validate bmi true function
:return:
"""
v = Validator()
result = v.validate_bmi("U")
self.assertNotEqual(result, 'Underweight', "Invaid BMI")
def test_validate_age_is_true(self):
"""
Test the validate age function
:return: True
"""
v = Validator()
result = v.validate_age("20")
self.assertTrue(result, 'valid AGE')
def test_validate_date_is_false_invalid_date(self):
"""
Test the validate date function
:return:
"""
v = Validator()
result = v.validate_date('89/13/1991')
self.assertFalse(result, 'invalid date, date doesnt exist')
def test_check_field_bmi(self):
v = Validator()
self.assertTrue(v.check_field('BMI', 'Normal'))
self.assertTrue(v.check_field('BMI', 'Overweight'))
self.assertTrue(v.check_field('BMI', 'Obesity'))
self.assertTrue(v.check_field('BMI', 'Underweight'))
self.assertFalse(v.check_field('BMI', 21))
self.assertFalse(v.check_field('BMI', 'A0501'))
def test_validate_regex(self):
row = OrderedDict([('Product Number', 'P-10001'), ('__row_number', 1)])
validations = {'Product Number': [{'method': 'regex', 'kwargs': {'pattern': '\\d+'}}]}
with self.assertLogs(level='ERROR') as log_output:
# A failing regex match should log a ValueError on Row 1
is_valid = Validator(validations=validations).validate_row(row)
self.assertFalse(is_valid)
self.assertTrue('ERROR on ROW 1' in log_output.output[0])
self.assertTrue('ValueError' in log_output.output[0])
error_logs_count = len(log_output)
# Test same row value against a valid regex
validations = {'Product Number': [{'method': 'regex', 'kwargs': {'pattern': '[A-Z]+-\\d+'}}]}
is_valid = Validator(validations=validations).validate_row(row)
self.assertTrue(is_valid)
# No more error logs should have been produced
self.assertEqual(error_logs_count, len(log_output))
def val_thread(port):
val = Validator(port=port)
val.create_connections()
while True:
val.receive()
if len(val.mempool) == 5:
blk = val.create_block(0, 5)
print(blk)
break
def setUp(self):
"""
Create a validator and add one note to it.
Note(delay=100, height=15, duration=100)
"""
self.the_note = Note(delay=100, height=15, duration=100)
score = Score([self.the_note])
self.validator = Validator(score, margin=10)
self.validator.add_reference_note(self.the_note)
def get_consequent_atoms(self):
if not self.consequent_atoms:
atoms = []
validate = Validator()
for token in self.get_consequent():
if validate.is_fact(token):
atoms.append(token)
self.consequent_atoms = atoms
return self.consequent_atoms
def main():
# Check if the number of command line arguments is correct
if len(sys.argv) < 6:
print(
"-- python --|-- main.py --|-- L --|-- K --|-- training_set.csv --|-- validation_set.csv --|-- test_set.csv --|"
)
sys.exit(1)
# The program takes two integer L and K as input to prune the decision tree
L = int(sys.argv[1])
K = int(sys.argv[2])
# Get the file path of the training data, validation data and test data
dataDir = './data1/'
training_set = dataDir + sys.argv[3]
validation_set = dataDir + sys.argv[4]
test_set = dataDir + sys.argv[5]
# Build a decision tree on training data
decisionTree = DecisionTree(training_set)
#############################################
# decisionTree.exportTree('tree.txt')
# print decisionTree
#############################################
# Create a validator using test data to calculate the prediction accuracy of a given decision tree
validator = Validator(test_set)
# Calculate the prediction accuracy of the original decision tree on test data
validator.calculateAccuracy(decisionTree.root)
# Display the prediction accuracy before pruning
print("\nA decision tree is fully grown to fit the training data.")
validator.displayAccuracy()
# Post pruning the decision tree
print("\nPost prunning", '.' * 30)
print("L =", L, ", K =", K, ", the pruned decision tree is:\n")
# Prune the original decision tree using L, K and validation data as inputs
decisionTree.pruneTree(L, K, validation_set)
##############################################
# decisionTree.exportTree('pruned_tree.txt')
##############################################
# print the decision tree to standard output
print(decisionTree) # Override the __str__ method in DecisionTree class
# Calculate the prediction accuracy of the pruned decision tree on test data
validator.calculateAccuracy(decisionTree.root)
# Display the prediction accuracy after pruning
validator.displayAccuracy()
def setUp(self):
view = CmdView()
data_vis = DataVis()
validator = Validator()
format = Format()
pickle = Pickle()
db = Database('company.db')
self.con = Controller(view, data_vis, validator, format, pickle, db)
view.controller_set(self.con)
