Exemple #1
0
    def setup_scenario02(self):
        """
        Scenario: Successfully building test projections from start:
            Given I create BigML PCA resources uploading train "<data>" file to test "<test>" and log projections in "<output>"
            And I check that the source has been created
            And I check that the dataset has been created
            And I check that the model has been created
            And I check that the projections are ready
            Then the local projection file is like "<projections_file>"

            Examples:
            | data               | test                    | output                        |projections_file           |
            | ../data/grades.csv   | ../data/test_grades.csv   | ./scenario1_pca/projections.csv   | ./check_files/projections_grades_pca.csv   |
        """
        print self.setup_scenario02.__doc__
        examples = [[
            'data/grades.csv', 'data/test_grades_no_missings.csv',
            'scenario1_pca/projections.csv',
            'check_files/projections_grades_pca.csv'
        ]]
        for example in examples:
            print "\nTesting with:\n", example
            pca_proj.i_create_all_pca_resources(self, example[0], example[1],
                                                example[2])
            test_pred.i_check_create_source(self)
            test_pred.i_check_create_dataset(self, suffix=None)
            pca_proj.i_check_create_pca_model(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[3])
Exemple #2
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    def test_scenario06(self):
        """
        Scenario: Successfully building batch test projections from model
            Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
            And I create BigML linear regression resources using model to test "<test>" as a batch projection and log projections in "<output>"
            And I check that the projections are ready
            Then the local projection file is like "<projections_file>"

            Examples:
            |scenario    | kwargs                                                  | test                    | output                        |projections_file           |


        """
        print self.test_scenario06.__doc__
        examples = [[
            'scenario1_pca',
            '{"data": "data/grades.csv", "output": "scenario1_pca/projections.csv", "test": "data/test_grades_no_missings.csv"}',
            'data/test_grades_no_missings.csv',
            'scenario5_pca/projections.csv',
            'check_files/projections_grades_pca.csv'
        ]]
        for example in examples:
            print "\nTesting with:\n", example
            test_pred.i_have_previous_scenario_or_reproduce_it(
                self, example[0], example[1])
            pca_proj.i_create_pca_resources_from_model_remote(
                self, test=example[2], output=example[3])
            batch_pred.i_check_create_batch_projection(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[4])
Exemple #3
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    def test_scenario03(self):
        """
        Scenario: Successfully building test projections from source
            Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
            And I create BigML linear regression resources using source to test "<test>" and log projections in "<output>"
            And I check that the dataset has been created
            And I check that the model has been created
            And I check that the projections are ready
            Then the local projections file is like "<projections_file>"

            Examples:
            |scenario    | kwargs                                                  | test                    | output                        |projections_file           |
            | scenario1| {"data": "../data/grades.csv", "output": "./scenario1_lrr/projections.csv", "test": "../data/test_grades.csv"}   | ../data/test_grades.csv   | ./scenario2/projections.csv   | ./check_files/projections_grades.csv   |
        """
        print self.test_scenario03.__doc__
        examples = [[
            'scenario1_pca',
            '{"data": "data/grades.csv", "output": "scenario1_pca/projections.csv", "test": "data/test_grades_no_missings.csv"}',
            'data/test_grades_no_missings.csv',
            'scenario2_pca/projections.csv',
            'check_files/projections_grades_pca.csv'
        ]]
        for example in examples:
            print "\nTesting with:\n", example
            test_pred.i_have_previous_scenario_or_reproduce_it(
                self, example[0], example[1])
            pca_proj.i_create_pca_resources_from_source(self,
                                                        test=example[2],
                                                        output=example[3])
            test_pred.i_check_create_dataset(self, suffix=None)
            pca_proj.i_check_create_pca_model(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[4])
Exemple #4
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    def setup_scenario02(self):
        """
        Scenario: Successfully building test projections from start:
            Given I create BigML PCA resources uploading train "<data>" file to test "<test>" and log projections in "<output>"
            And I check that the source has been created
            And I check that the dataset has been created
            And I check that the model has been created
            And I check that the projections are ready
            Then the local projection file is like "<projections_file>"

            Examples:
            | data               | test                    | output                        |projections_file           |
            | ../data/grades.csv   | ../data/test_grades.csv   | ./scenario1_pca/projections.csv   | ./check_files/projections_grades_pca.csv   |
        """
        print self.setup_scenario02.__doc__
        examples = [
            ['data/grades.csv', 'data/test_grades_no_missings.csv', 'scenario1_pca/projections.csv', 'check_files/projections_grades_pca.csv']]
        for example in examples:
            print "\nTesting with:\n", example
            pca_proj.i_create_all_pca_resources(self, example[0], example[1], example[2])
            test_pred.i_check_create_source(self)
            test_pred.i_check_create_dataset(self, suffix=None)
            pca_proj.i_check_create_pca_model(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[3])
Exemple #5
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    def test_scenario03(self):
        """
        Scenario: Successfully building test projections from source
            Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
            And I create BigML linear regression resources using source to test "<test>" and log projections in "<output>"
            And I check that the dataset has been created
            And I check that the model has been created
            And I check that the projections are ready
            Then the local projections file is like "<projections_file>"

            Examples:
            |scenario    | kwargs                                                  | test                    | output                        |projections_file           |
            | scenario1| {"data": "../data/grades.csv", "output": "./scenario1_lrr/projections.csv", "test": "../data/test_grades.csv"}   | ../data/test_grades.csv   | ./scenario2/projections.csv   | ./check_files/projections_grades.csv   |
        """
        print self.test_scenario03.__doc__
        examples = [
            ['scenario1_pca', '{"data": "data/grades.csv", "output": "scenario1_pca/projections.csv", "test": "data/test_grades_no_missings.csv"}', 'data/test_grades_no_missings.csv', 'scenario2_pca/projections.csv', 'check_files/projections_grades_pca.csv']]
        for example in examples:
            print "\nTesting with:\n", example
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            pca_proj.i_create_pca_resources_from_source(self, test=example[2], output=example[3])
            test_pred.i_check_create_dataset(self, suffix=None)
            pca_proj.i_check_create_pca_model(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[4])
Exemple #6
0
    def test_scenario06(self):
        """
        Scenario: Successfully building batch test projections from model
            Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
            And I create BigML linear regression resources using model to test "<test>" as a batch projection and log projections in "<output>"
            And I check that the projections are ready
            Then the local projection file is like "<projections_file>"

            Examples:
            |scenario    | kwargs                                                  | test                    | output                        |projections_file           |


        """
        print self.test_scenario06.__doc__
        examples = [
            ['scenario1_pca', '{"data": "data/grades.csv", "output": "scenario1_pca/projections.csv", "test": "data/test_grades_no_missings.csv"}', 'data/test_grades_no_missings.csv', 'scenario5_pca/projections.csv', 'check_files/projections_grades_pca.csv']]
        for example in examples:
            print "\nTesting with:\n", example
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            pca_proj.i_create_pca_resources_from_model_remote(self, test=example[2], output=example[3])
            batch_pred.i_check_create_batch_projection(self)
            test_pred.i_check_create_projections(self)
            test_pred.i_check_projections(self, example[4])