def test_scenario2(self):
"""
Scenario: Successfully building test predictions from source
Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
And I create BigML resources using source to find centroids for "<test>" and log predictions in "<output>"
And I check that the dataset has been created
And I check that the cluster has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
|scenario | kwargs | test | output |predictions_file |
| scenario_c_1| {"data": "../data/diabetes.csv", "output": "./scenario_c_1/centroids.csv", "test": "../data/diabetes.csv"} | ../data/diabetes.csv | ./scenario_c_2/centroids.csv | ./check_files/centroids_diabetes.csv |
"""
print self.test_scenario2.__doc__
examples = [
['scenario_c_1', '{"data": "data/diabetes.csv", "output": "scenario_c_1/centroids.csv", "test": "data/diabetes.csv"}', 'data/diabetes.csv', 'scenario_c_2/centroids.csv', 'check_files/centroids_diabetes.csv']]
for example in examples:
print "\nTesting with:\n", example
test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
test_cluster.i_create_cluster_resources_from_source(self, test=example[2], output=example[3])
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[4])
def test_scenario2(self):
"""
Scenario: Successfully building remote test centroid predictions from scratch to dataset:
Given I create BigML resources uploading train "<data>" file to find centroids for "<test>" remotely to dataset with no CSV 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 cluster has been created
And I check that the source has been created from the test file
And I check that the dataset has been created from the test file
And I check that the batch centroid prediction has been created
Then I check that the batch centroids dataset exists
And no local CSV file is created
Examples:
| data | test | output_dir |
| ../data/grades.csv | ../data/test_grades.csv | ./scenario_cb_2 |
"""
print self.test_scenario2.__doc__
examples = [
['data/grades.csv', 'data/test_grades.csv', 'scenario_cb_2']]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources_to_dataset(self, data=example[0], test=example[1], output_dir=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_pred.i_check_create_test_source(self)
test_pred.i_check_create_test_dataset(self)
batch_pred.i_check_create_batch_centroid(self)
batch_pred.i_check_create_batch_centroids_dataset(self)
test_anomaly.i_check_no_local_CSV(self)
def test_scenario1(self):
"""
Scenario: Successfully building test centroids from scratch:
Given I create BigML resources uploading train "<data>" file to create centroids for "<test>" and log predictions 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 cluster has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
| data | test | output |predictions_file |
| ../data/grades.csv | ../data/grades.csv | ./scenario_c_1_r/centroids.csv | ./check_files/centroids_grades.csv |
| ../data/diabetes.csv | ../data/diabetes.csv | ./scenario_c_1/centroids.csv | ./check_files/centroids_diabetes.csv |
"""
print self.test_scenario1.__doc__
examples = [
['data/grades.csv', 'data/grades.csv', 'scenario_c_1_r/centroids.csv', 'check_files/centroids_grades.csv'],
['data/diabetes.csv', 'data/diabetes.csv', 'scenario_c_1/centroids.csv', 'check_files/centroids_diabetes.csv']]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources(self, data=example[0], test=example[1], output=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[3])
def test_scenario8(self):
"""
Scenario: Successfully building a cluster 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 cluster with params "<params>" from dataset in "<output_dir>"
And I check that the cluster has been created
And the cluster params are "<params_json>"
Examples:
|data |output_dir | params | params_json
|../data/iris.csv | ./scenario_d_8 | "--sample-rate 0.2 --replacement" | {"sample-rate": 0.2, "replacement": true}
"""
print self.test_scenario8.__doc__
examples = [[
'data/iris.csv', 'scenario_d_8', '--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_cluster_with_params_from_dataset( \
self, cluster_params=example[2], output_dir=example[1])
test_pred.i_check_create_cluster(self)
dataset_adv.i_check_cluster_params(self, params_json=example[3])
def test_scenario1(self):
"""
Scenario: Successfully building test centroid predictions from scratch:
Given I create BigML resources uploading train "<data>" file to find centroids for "<test>" remotely with mapping file "<fields_map>" and log predictions 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 cluster has been created
And I check that the source has been created from the test file
And I check that the dataset has been created from the test file
And I check that the batch centroid prediction has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
| data | test | fields_map | output |predictions_file |
| ../data/grades.csv | ../data/grades_perm.csv | ../data/grades_fields_map_perm.csv | ./scenario_cb_1_r/centroids.csv | ./check_files/centroids_grades.csv |
"""
print self.test_scenario1.__doc__
examples = [
['data/grades.csv', 'data/grades_perm.csv', 'data/grades_fields_map_perm.csv', 'scenario_cb_1_r/centroids.csv', 'check_files/centroids_grades.csv']]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources_with_mapping(self, data=example[0], test=example[1], fields_map=example[2], output=example[3])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_pred.i_check_create_test_source(self)
test_pred.i_check_create_test_dataset(self)
batch_pred.i_check_create_batch_centroid(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[4])
def test_scenario9(self):
"""
Scenario: Successfully building test predictions from dataset with summary fields
Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
And I create BigML cluster using dataset and summary fields "<summary_fields>" and log resources in "<output_dir>"
And I check that the cluster has been created
Then the cluster has summary fields "<summary_fields>"
Examples:
|scenario | kwargs | output-dir |summary_fields |
| scenario_c_1| {"data": "../data/diabetes.csv", "output": "./scenario_c_1/centroids.csv", "test": "../data/diabetes.csv"} | scenario_c_9/ | diabetes,age
"""
print self.test_scenario9.__doc__
examples = [[
'scenario_c_1',
'{"data": "data/diabetes.csv", "output": "scenario_c_1/centroids.csv", "test": "data/diabetes.csv"}',
'scenario_c_9', '000008,000007'
]]
for example in examples:
print "\nTesting with:\n", example
test_pred.i_have_previous_scenario_or_reproduce_it(
self, example[0], example[1])
test_cluster.i_create_cluster_from_dataset_with_summary_fields(
self, summary_fields=example[3], output_dir=example[2])
test_pred.i_check_create_cluster(self)
test_cluster.i_check_cluster_has_summary_fields(self, example[3])
def test_scenario2(self):
"""
Scenario: Successfully building test predictions from source
Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
And I create BigML resources using source to find centroids for "<test>" and log predictions in "<output>"
And I check that the dataset has been created
And I check that the cluster has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
|scenario | kwargs | test | output |predictions_file |
| scenario_c_1| {"data": "../data/diabetes.csv", "output": "./scenario_c_1/centroids.csv", "test": "../data/diabetes.csv"} | ../data/diabetes.csv | ./scenario_c_2/centroids.csv | ./check_files/centroids_diabetes.csv |
"""
print self.test_scenario2.__doc__
examples = [[
'scenario_c_1',
'{"data": "data/diabetes.csv", "output": "scenario_c_1/centroids.csv", "test": "data/diabetes.csv"}',
'data/diabetes.csv', 'scenario_c_2/centroids.csv',
'check_files/centroids_diabetes.csv'
]]
for example in examples:
print "\nTesting with:\n", example
test_pred.i_have_previous_scenario_or_reproduce_it(
self, example[0], example[1])
test_cluster.i_create_cluster_resources_from_source(
self, test=example[2], output=example[3])
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[4])
def test_scenario2(self):
"""
Scenario: Successfully building remote test centroid predictions from scratch to dataset:
Given I create BigML resources uploading train "<data>" file to find centroids for "<test>" remotely to dataset with no CSV 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 cluster has been created
And I check that the source has been created from the test file
And I check that the dataset has been created from the test file
And I check that the batch centroid prediction has been created
Then I check that the batch centroids dataset exists
And no local CSV file is created
Examples:
| data | test | output_dir |
| ../data/grades.csv | ../data/test_grades.csv | ./scenario_cb_2 |
"""
print self.test_scenario2.__doc__
examples = [[
'data/grades.csv', 'data/test_grades.csv', 'scenario_cb_2'
]]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources_to_dataset(
self, data=example[0], test=example[1], output_dir=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_pred.i_check_create_test_source(self)
test_pred.i_check_create_test_dataset(self)
batch_pred.i_check_create_batch_centroid(self)
batch_pred.i_check_create_batch_centroids_dataset(self)
test_anomaly.i_check_no_local_CSV(self)
def test_scenario8(self):
"""
Scenario: Successfully building a cluster 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 cluster with params "<params>" from dataset in "<output_dir>"
And I check that the cluster has been created
And the cluster params are "<params_json>"
Examples:
|data |output_dir | params | params_json
|../data/iris.csv | ./scenario_d_8 | "--sample-rate 0.2 --replacement" | {"sample-rate": 0.2, "replacement": true}
"""
print self.test_scenario8.__doc__
examples = [
['data/iris.csv', 'scenario_d_8',
'--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_cluster_with_params_from_dataset( \
self, cluster_params=example[2], output_dir=example[1])
test_pred.i_check_create_cluster(self)
dataset_adv.i_check_cluster_params(self, params_json=example[3])
def test_scenario1(self):
"""
Scenario: Successfully building test centroid predictions from scratch:
Given I create BigML resources uploading train "<data>" file to find centroids for "<test>" remotely with mapping file "<fields_map>" and log predictions 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 cluster has been created
And I check that the source has been created from the test file
And I check that the dataset has been created from the test file
And I check that the batch centroid prediction has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
| data | test | fields_map | output |predictions_file |
| ../data/grades.csv | ../data/grades_perm.csv | ../data/grades_fields_map_perm.csv | ./scenario_cb_1_r/centroids.csv | ./check_files/centroids_grades.csv |
"""
print self.test_scenario1.__doc__
examples = [
['data/grades.csv', 'data/grades_perm.csv', 'data/grades_fields_map_perm.csv', 'scenario_cb_1_r/centroids.csv', 'check_files/centroids_grades.csv']]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources_with_mapping(self, data=example[0], test=example[1], fields_map=example[2], output=example[3])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_pred.i_check_create_test_source(self)
test_pred.i_check_create_test_dataset(self)
batch_pred.i_check_create_batch_centroid(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[4])
def test_scenario9(self):
"""
Scenario: Successfully building test predictions from dataset with summary fields
Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
And I create BigML cluster using dataset and summary fields "<summary_fields>" and log resources in "<output_dir>"
And I check that the cluster has been created
Then the cluster has summary fields "<summary_fields>"
Examples:
|scenario | kwargs | output-dir |summary_fields |
| scenario_c_1| {"data": "../data/diabetes.csv", "output": "./scenario_c_1/centroids.csv", "test": "../data/diabetes.csv"} | scenario_c_9/ | diabetes,age
"""
print self.test_scenario9.__doc__
examples = [
['scenario_c_1', '{"data": "data/diabetes.csv", "output": "scenario_c_1/centroids.csv", "test": "data/diabetes.csv"}', 'scenario_c_9', '000008,000007']]
for example in examples:
print "\nTesting with:\n", example
test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
test_cluster.i_create_cluster_from_dataset_with_summary_fields(self, summary_fields=example[3], output_dir=example[2])
test_pred.i_check_create_cluster(self)
test_cluster.i_check_cluster_has_summary_fields(self, example[3])
def test_scenario1(self):
"""
Scenario: Successfully building test centroids from scratch:
Given I create BigML resources uploading train "<data>" file to create centroids for "<test>" and log predictions 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 cluster has been created
And I check that the centroids are ready
Then the local centroids file is like "<predictions_file>"
Examples:
| data | test | output |predictions_file |
| ../data/grades.csv | ../data/grades.csv | ./scenario_c_1_r/centroids.csv | ./check_files/centroids_grades.csv |
| ../data/diabetes.csv | ../data/diabetes.csv | ./scenario_c_1/centroids.csv | ./check_files/centroids_diabetes.csv |
"""
print self.test_scenario1.__doc__
examples = [[
'data/grades.csv', 'data/grades.csv',
'scenario_c_1_r/centroids.csv', 'check_files/centroids_grades.csv'
],
[
'data/diabetes.csv', 'data/diabetes.csv',
'scenario_c_1/centroids.csv',
'check_files/centroids_diabetes.csv'
]]
for example in examples:
print "\nTesting with:\n", example
test_cluster.i_create_all_cluster_resources(self,
data=example[0],
test=example[1],
output=example[2])
test_pred.i_check_create_source(self)
test_pred.i_check_create_dataset(self, suffix=None)
test_pred.i_check_create_cluster(self)
test_cluster.i_check_create_centroids(self)
test_pred.i_check_predictions(self, example[3])