def test_scenario12(self):
        """
            Scenario: Successfully comparing logistic regression predictions with constant fields:

                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 update the dataset with "<params>"
                And I wait until the dataset is ready less than <time_4> secs
                And I create a logistic regression model
                And I wait until the logistic regression model is ready less than <time_3> secs
                And I create a local logistic regression model
                When I create a logistic regression prediction for "<data_input>"
                Then the logistic regression prediction is "<prediction>"
                And I create a local logistic regression prediction for "<data_input>"
                Then the local logistic regression prediction is "<prediction>"

                Examples:
                | data             | time_1  | time_2 | time_3 |time_4| data_input                                 | prediction  | field_id

        """
        examples = [[
            'data/constant_field.csv', '10', '10', '50', '10',
            '{"a": 1, "b": 1, "c": 1}', 'a',
            '{"fields": {"000000": {"preferred": true}}}'
        ]]
        show_doc(self.test_scenario12, examples)

        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])
            dataset_create.i_update_dataset_with(self, example[7])
            dataset_create.the_dataset_is_finished_in_less_than(
                self, example[4])
            model_create.i_create_a_logistic_model(self)
            model_create.the_logistic_model_is_finished_in_less_than(
                self, example[3])
            prediction_compare.i_create_a_local_logistic_model(self)
            prediction_create.i_create_a_logistic_prediction(self, example[5])
            prediction_create.the_logistic_prediction_is(self, example[6])
            prediction_compare.i_create_a_local_prediction(self, example[5])
            prediction_compare.the_local_prediction_is(self, example[6])
    def test_scenario12(self):
        """
            Scenario: Successfully comparing logistic regression predictions with constant fields:

                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 update the dataset with "<params>"
                And I wait until the dataset is ready less than <time_4> secs
                And I create a logistic regression model
                And I wait until the logistic regression model is ready less than <time_3> secs
                And I create a local logistic regression model
                When I create a logistic regression prediction for "<data_input>"
                Then the logistic regression prediction is "<prediction>"
                And I create a local logistic regression prediction for "<data_input>"
                Then the local logistic regression prediction is "<prediction>"

                Examples:
                | data             | time_1  | time_2 | time_3 |time_4| data_input                                 | prediction  | field_id

        """
        examples = [
            ['data/constant_field.csv', '10', '10', '50', '10','{"a": 1, "b": 1, "c": 1}', 'a', '{"fields": {"000000": {"preferred": true}}}']]
        show_doc(self.test_scenario12, examples)

        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])
            dataset_create.i_update_dataset_with(self, example[7])
            dataset_create.the_dataset_is_finished_in_less_than(self, example[4])
            model_create.i_create_a_logistic_model(self)
            model_create.the_logistic_model_is_finished_in_less_than(self, example[3])
            prediction_compare.i_create_a_local_logistic_model(self)
            prediction_create.i_create_a_logistic_prediction(self, example[5])
            prediction_create.the_logistic_prediction_is(self, example[6])
            prediction_compare.i_create_a_local_prediction(self, example[5])
            prediction_compare.the_local_prediction_is(self, example[6])