def test_scenario11(self): """ Scenario: Successfully building association from a sampled 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 association with params "<params>" from dataset in "<output_dir>" And I check that the association has been created And the association params are "<params_json>" Examples: |data |output_dir | params | params_json |../data/iris.csv | ./scenario_d_11 | "--sample-rate 0.2 --replacement" | {"sample-rate": 0.2, "replacement": true} """ print self.test_scenario11.__doc__ examples = [[ 'data/iris.csv', 'scenario_d_11', '--sample-rate 0.2 --replacement', '{"sample_rate": 0.2, "replacement": true}' ]] 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_association_with_params_from_dataset( \ self, params=example[2], output_dir=example[1]) test_pred.i_check_create_association(self) dataset_adv.i_check_association_params(self, params_json=example[3])
def test_scenario11(self): """ Scenario: Successfully building association from a sampled 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 association with params "<params>" from dataset in "<output_dir>" And I check that the association has been created And the association params are "<params_json>" Examples: |data |output_dir | params | params_json |../data/iris.csv | ./scenario_d_11 | "--sample-rate 0.2 --replacement" | {"sample-rate": 0.2, "replacement": true} """ print self.test_scenario11.__doc__ examples = [ ['data/iris.csv', 'scenario_d_11', '--sample-rate 0.2 --replacement', '{"sample_rate": 0.2, "replacement": true}']] 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_association_with_params_from_dataset( \ self, params=example[2], output_dir=example[1]) test_pred.i_check_create_association(self) dataset_adv.i_check_association_params(self, params_json=example[3])
def test_scenario2(self): """ Scenario: Successfully building association from source Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs> And I create BigML association using source and log resources in "<output_dir>" And I check that the dataset has been created And I check that the association has been created Examples: |scenario | kwargs | output_dir | scenario_ass_1| {"data": "../data/iris.csv", "output_dir": "./scenario_ass_1/} | ./scenario_ass_2 | """ print self.test_scenario2.__doc__ examples = [[ 'scenario_ass_1', '{"data": "data/iris.csv", "output_dir": "scenario_ass_1"}', 'scenario_ass_2' ]] for example in examples: print "\nTesting with:\n", example test_pred.i_have_previous_scenario_or_reproduce_it( self, example[0], example[1]) test_association.i_create_association_from_source( self, output_dir=example[2]) test_pred.i_check_create_dataset(self, suffix=None) test_pred.i_check_create_association(self)
def test_scenario1(self): """ Scenario: Successfully building association from scratch: Given I create BigML association uploading train "<data>" file and log resources 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 association has been created Examples: | data | output_dir | ../data/grades.csv | ./scenario_ass_1_r | ../data/diabetes.csv | ./scenario_ass_1 """ print self.test_scenario1.__doc__ examples = [['data/spam.csv', 'scenario_ass_1_r'], ['data/movies.csv', 'scenario_ass_1_i'], ['data/iris.csv', 'scenario_ass_1']] for example in examples: print "\nTesting with:\n", example test_association.i_create_association(self, data=example[0], output_dir=example[1]) test_pred.i_check_create_source(self) test_pred.i_check_create_dataset(self, suffix=None) test_pred.i_check_create_association(self)
def test_scenario3(self): """ Scenario: Successfully building test predictions from dataset Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs> And I create BigML association using dataset and log predictions in "<output_dir>" And I check that the association has been created Examples: |scenario | kwargs | test | output |predictions_file | | scenario_ass_1| {"data": "../data/iris.csv", "output_dir": "./scenario_c_1"} | ../data/diabetes.csv | ./scenario_c_3/centroids.csv | ./check_files/centroids_diabetes.csv | """ print self.test_scenario3.__doc__ examples = [[ 'scenario_ass_1', '{"data": "data/iris.csv", "output_dir": "scenario_ass_1"}', 'scenario_ass_3' ]] for example in examples: print "\nTesting with:\n", example test_pred.i_have_previous_scenario_or_reproduce_it( self, example[0], example[1]) test_association.i_create_association_from_dataset( self, output_dir=example[2]) test_pred.i_check_create_association(self)
def test_scenario3(self): """ Scenario: Successfully building test predictions from dataset Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs> And I create BigML association using dataset and log predictions in "<output_dir>" And I check that the association has been created Examples: |scenario | kwargs | test | output |predictions_file | | scenario_ass_1| {"data": "../data/iris.csv", "output_dir": "./scenario_c_1"} | ../data/diabetes.csv | ./scenario_c_3/centroids.csv | ./check_files/centroids_diabetes.csv | """ print self.test_scenario3.__doc__ examples = [ ['scenario_ass_1', '{"data": "data/iris.csv", "output_dir": "scenario_ass_1"}', 'scenario_ass_3']] for example in examples: print "\nTesting with:\n", example test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1]) test_association.i_create_association_from_dataset(self, output_dir=example[2]) test_pred.i_check_create_association(self)
def test_scenario2(self): """ Scenario: Successfully building association from source Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs> And I create BigML association using source and log resources in "<output_dir>" And I check that the dataset has been created And I check that the association has been created Examples: |scenario | kwargs | output_dir | scenario_ass_1| {"data": "../data/iris.csv", "output_dir": "./scenario_ass_1/} | ./scenario_ass_2 | """ print self.test_scenario2.__doc__ examples = [ ['scenario_ass_1', '{"data": "data/iris.csv", "output_dir": "scenario_ass_1"}', 'scenario_ass_2']] for example in examples: print "\nTesting with:\n", example test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1]) test_association.i_create_association_from_source(self, output_dir=example[2]) test_pred.i_check_create_dataset(self, suffix=None) test_pred.i_check_create_association(self)
def test_scenario1(self): """ Scenario: Successfully building association from scratch: Given I create BigML association uploading train "<data>" file and log resources 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 association has been created Examples: | data | output_dir | ../data/grades.csv | ./scenario_ass_1_r | ../data/diabetes.csv | ./scenario_ass_1 """ print self.test_scenario1.__doc__ examples = [ ['data/spam.csv', 'scenario_ass_1_r'], ['data/movies.csv', 'scenario_ass_1_i'], ['data/iris.csv', 'scenario_ass_1']] for example in examples: print "\nTesting with:\n", example test_association.i_create_association(self, data=example[0], output_dir=example[1]) test_pred.i_check_create_source(self) test_pred.i_check_create_dataset(self, suffix=None) test_pred.i_check_create_association(self)