def test_scenario5(self):
"""
Scenario: Successfully building a filtered dataset from a dataset
Given I create a BigML dataset from "<data>" and store logs in "<output_dir>"
And I check that the source has been created
And I check that the dataset has been created
And I create a BigML filtered dataset with filter "<filter_exp>" from previous dataset and store logs in "<output_dir>"
And I check that the dataset has been created
And the number of records in the dataset is <filtered_records>
Examples:
|data |output_dir | filtered_records | filter_exp
|../data/iris.csv | ./scenario_d_5 | 50 | (= (f "000004") "Iris-setosa")
"""
print self.test_scenario5.__doc__
examples = [[
'data/iris.csv', 'scenario_d_5', '50',
'(= (f "000004") "Iris-setosa")'
]]
for example in examples:
print "\nTesting with:\n", example
dataset_adv.i_create_dataset(self,
data=example[0],
output_dir=example[1])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
dataset_adv.i_create_filtered_dataset_from_dataset(
self, filter_exp=example[3], output_dir=example[1])
test_pred.i_check_create_dataset(self, suffix='gen ')
test_anomaly.i_check_dataset_lines_number(self, example[2])
def test_scenario7(self):
"""
Scenario: Successfully building anomalous dataset test predictions from anomaly
Given I create BigML anomaly detector from data <data> with options <options> and generate a new dataset of anomalies in "<output_dir>"
And I check that the source has been created
And I check that the dataset has been created
And I check that the anomaly detector has been created
Then I check that the new top anomalies dataset has been created
And the top anomalies in the anomaly detector are <top_anomalies>
And the forest size in the anomaly detector is <forest_size>
And the number of records in the top anomalies dataset is <top_anomalies>
Examples:
| data | options | output_dir | top_anomalies | forest_size |
| data/tiny_kdd.csv" | --top-anomalies 15 --forest-size 40 | scenario_an_7 | 15 | 40 |
"""
print self.test_scenario7.__doc__
examples = [[
'data/tiny_kdd.csv', '--top-n 15 --forest-size 40 ',
'scenario_an_7', '15', '40'
]]
for example in examples:
print "\nTesting with:\n", example
test_anomaly.i_create_anomaly_resources_with_options(
self, example[0], example[1], output_dir=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self)
test_anomaly.i_check_create_anomaly(self)
test_pred.i_check_create_dataset(self, suffix='gen ')
test_anomaly.i_check_top_anomalies(self, example[3])
test_anomaly.i_check_forest_size(self, example[4])
test_anomaly.i_check_dataset_lines_number(self, example[3])
def test_scenario7(self):
"""
Scenario: Successfully building anomalous dataset test predictions from anomaly
Given I create BigML anomaly detector from data <data> with options <options> and generate a new dataset of anomalies in "<output_dir>"
And I check that the source has been created
And I check that the dataset has been created
And I check that the anomaly detector has been created
Then I check that the new top anomalies dataset has been created
And the top anomalies in the anomaly detector are <top_anomalies>
And the forest size in the anomaly detector is <forest_size>
And the number of records in the top anomalies dataset is <top_anomalies>
Examples:
| data | options | output_dir | top_anomalies | forest_size |
| data/tiny_kdd.csv" | --top-anomalies 15 --forest-size 40 | scenario_an_7 | 15 | 40 |
"""
print self.test_scenario7.__doc__
examples = [
['data/tiny_kdd.csv', '--top-n 15 --forest-size 40 ', 'scenario_an_7', '15', '40']]
for example in examples:
print "\nTesting with:\n", example
test_anomaly.i_create_anomaly_resources_with_options(self, example[0], example[1], output_dir=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self)
test_anomaly.i_check_create_anomaly(self)
test_pred.i_check_create_dataset(self, suffix='gen ')
test_anomaly.i_check_top_anomalies(self, example[3])
test_anomaly.i_check_forest_size(self, example[4])
test_anomaly.i_check_dataset_lines_number(self, example[3])
def test_scenario5(self):
"""
Scenario: Successfully building a filtered dataset from a dataset
Given I create a BigML dataset from "<data>" and store logs in "<output_dir>"
And I check that the source has been created
And I check that the dataset has been created
And I create a BigML filtered dataset with filter "<filter_exp>" from previous dataset and store logs in "<output_dir>"
And I check that the dataset has been created
And the number of records in the dataset is <filtered_records>
Examples:
|data |output_dir | filtered_records | filter_exp
|../data/iris.csv | ./scenario_d_5 | 50 | (= (f "000004") "Iris-setosa")
"""
print self.test_scenario5.__doc__
examples = [
['data/iris.csv', 'scenario_d_5', '50', '(= (f "000004") "Iris-setosa")']]
for example in examples:
print "\nTesting with:\n", example
dataset_adv.i_create_dataset(self, data=example[0], output_dir=example[1])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
dataset_adv.i_create_filtered_dataset_from_dataset(self, filter_exp=example[3], output_dir=example[1])
test_pred.i_check_create_dataset(self, suffix='gen ')
test_anomaly.i_check_dataset_lines_number(self, example[2])
