def test_scenario3(self):
        """

            Scenario3: Successfully creating an evaluation for a logistic regression:
                Given I create a data source uploading a "<data>" file
                And I wait until the source is ready less than <time_1> secs
                And I create a dataset
                And I wait until the dataset is ready less than <time_2> secs
                And I create a logistic regression
                And I wait until the logistic regression is ready less than <time_3> secs
                When I create an evaluation for the logistic regression with the dataset
                And I wait until the evaluation is ready less than <time_4> secs
                Then the measured "<measure>" is <value>

                Examples:
                | data             | time_1  | time_2 | time_3 | time_4 | measure       | value  |
                | ../data/iris.csv | 30      | 30     | 50     | 30     | average_phi   | 0.94107   |
        """
        print self.test_scenario3.__doc__
        examples = [
            ['data/iris.csv', '50', '50', '800', '80', 'average_phi', '0.89054']]
        for example in examples:
            print "\nTesting with:\n", example
            source_create.i_upload_a_file(self, example[0])
            source_create.the_source_is_finished(self, example[1])
            dataset_create.i_create_a_dataset(self)
            dataset_create.the_dataset_is_finished_in_less_than(self, example[2])
            model_create.i_create_a_logistic_model(self)
            model_create.the_logistic_model_is_finished_in_less_than(self, example[3])
            evaluation_create.i_create_an_evaluation_logistic(self)
            evaluation_create.the_evaluation_is_finished_in_less_than(self, example[4])
            evaluation_create.the_measured_measure_is_value(self, example[5], example[6])
    def test_scenario3(self):
        """

            Scenario3: Successfully creating an evaluation for a logistic regression:
                Given I create a data source uploading a "<data>" file
                And I wait until the source is ready less than <time_1> secs
                And I create a dataset
                And I wait until the dataset is ready less than <time_2> secs
                And I create a logistic regression
                And I wait until the logistic regression is ready less than <time_3> secs
                When I create an evaluation for the logistic regression with the dataset
                And I wait until the evaluation is ready less than <time_4> secs
                Then the measured "<measure>" is <value>

                Examples:
                | data             | time_1  | time_2 | time_3 | time_4 | measure       | value  |
                | ../data/iris.csv | 30      | 30     | 50     | 30     | average_phi   | 0.94107   |
        """
        print self.test_scenario3.__doc__
        examples = [
            ['data/iris.csv', '50', '50', '800', '80', 'average_phi', '0.89054']]
        for example in examples:
            print "\nTesting with:\n", example
            source_create.i_upload_a_file(self, example[0])
            source_create.the_source_is_finished(self, example[1])
            dataset_create.i_create_a_dataset(self)
            dataset_create.the_dataset_is_finished_in_less_than(self, example[2])
            model_create.i_create_a_logistic_model(self)
            model_create.the_logistic_model_is_finished_in_less_than(self, example[3])
            evaluation_create.i_create_an_evaluation_logistic(self)
            evaluation_create.the_evaluation_is_finished_in_less_than(self, example[4])
            evaluation_create.the_measured_measure_is_value(self, example[5], example[6])