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])
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])
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])
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])
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])
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])