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)
