def run_and_evaluate(self):
dai.set_project_path(self.project.path)
sys.path.append(self.project.path)
for a in self.cfg.approaches:
self.logger.info('Running Approach ' + a['name'])
self.webservice and self.webservice.update_approach_status(
a, "TRAINING")
# Run and evaluate the approach
self._run_approach(a)
self.logger.info('Generating evaluations file for ' + a['name'])
evaluations_df = self._evaluate_approach(a)
# Upload the results
self.logger.debug('Uploading evaluation file to coordinator')
self.webservice and self.webservice.upload_evaluations(
evaluations_df, a)
# Set approach done
self.logger.debug('Done')
self.webservice and self.webservice.update_approach_status(
a, "TRAINED")
sys.path.remove(self.project.path)
def setUp(self):
set_project_path(testenv.MOCK_PROJECT_PATH)
self.path_to_dataset = testenv.IRIS_DATASET
self.path_to_test_dir = testenv.TEST_PATH
self.aux_project_name = testenv.MOCK_PROJECT_NAME
self.path_to_auxproj = testenv.MOCK_PROJECT_PATH
self.project_default_name = testenv.DEFAULT_PROJECT_NAME
# Generate a project
self.p = Project(path=self.path_to_test_dir,
name=self.aux_project_name)
# Add a dataset
self.ds = Dataset.read_file(path=self.path_to_dataset, )
self.ds.save()
# Generate subdataset
self.sbds = SubDataset(self.ds, method="k_fold", by=5)
self.sbds.save()
# set apporach
self.approach = Approach(self.p,
"decision_tree",
self.sbds,
path=str(Path(testenv.TEST_PATH, "dt")))
shutil.copyfile(testenv.IRIS_APPROACH, str(self.approach.script_path))
self.approach.save()
# generate runs
import_from("test.dt.decision_tree", "DecisionTreeApproach")().run()
def setUp(self):
set_project_path(testenv.MOCK_PROJECT_PATH)
self.path_to_dataset = testenv.MOCK_DATASET
self.path_to_test_dir = testenv.TEST_PATH
self.aux_project_name = testenv.MOCK_PROJECT_NAME
self.path_to_auxproj = testenv.MOCK_PROJECT_PATH
self.project_default_name = testenv.DEFAULT_PROJECT_NAME
# Generate a project
self.p = Project(path=self.path_to_test_dir,
name=self.aux_project_name)
# Add a dataset
self.ds = Dataset.read_file(path=self.path_to_dataset)
self.ds.save()
# Generate subdataset
self.sbds = SubDataset(self.ds, method="k_fold", by=5)
self.sbds.save()
# set apporach
self.approach = Approach(self.p,
"logistic_regression",
self.sbds,
path=str(Path(testenv.TEST_PATH, "lr")))
shutil.copyfile(testenv.APPROACH_EXAMPLE,
str(self.approach.script_path))
self.approach.save()
# generate runs
import_from("test.lr.logistic_regression",
"LogisticRegressionApproach")().run()
def setUp(self):
set_project_path(testenv.MOCK_PROJECT_PATH)
self.path_to_dataset = testenv.MOCK_DATASET
self.path_to_test_dir = testenv.TEST_PATH
self.aux_project_name = testenv.MOCK_PROJECT_NAME
self.path_to_auxproj = testenv.MOCK_PROJECT_PATH
self.project_default_name = "untitled_driftai_project"
def setUp(self):
"""
Sets a defalut path to dataset
"""
set_project_path(testenv.MOCK_PROJECT_PATH)
self.path_to_dataset = testenv.MOCK_DATASET
self.path_to_test_dir = testenv.TEST_PATH
self.aux_project_name = testenv.MOCK_PROJECT_NAME
self.path_to_auxproj = testenv.MOCK_PROJECT_PATH
self.project_default_name = testenv.DEFAULT_PROJECT_NAME
def test_load_project_from_non_project_dir(self):
"""
Loads a project from a directory that is not a project
Asserts
-------
- Raises the proper exception
"""
set_project_path('no_exists')
with self.assertRaises(FileNotFoundError):
Project.load()
def test_create_new_project_without_name(self):
"""
Creates a new Project given a path to the local file system without the project name
Asserts
-------
- The project path is created
"""
p = Project(path=self.path_to_test_dir)
set_project_path(p.path)
path_to_noname_project = Path(self.path_to_test_dir, self.project_default_name)
self.assertEqual(p.path, str(path_to_noname_project))
def test_create_two_projects_with_same_name(self):
"""
Creates a new Project given a path to the local file system and then creates a new
Project with the same name. The expected behaviour is that the second project creation raises and Exception.
Asserts
-------
- The first project path is created
- The second project generates an Exception
"""
set_project_path(testenv.MOCK_PROJECT_PATH)
p1 = Project(path=self.path_to_test_dir, name=self.project_name)
with self.assertRaises(OptAppProjectNameExistsException):
Project(path=self.path_to_test_dir, name=p1.name)
def generate(self):
# Generate the project
self.logger.info('Creating DriftAI project {}'\
.format(self.cfg.project_name))
project = dai.Project(name=self.cfg.project_name,
path=str(self.PROJECTS_PATH))
dai.set_project_path(project.path)
# Add the datasets to project
self.logger.info('Adding datasets...')
for d in self.cfg.datasets:
self.logger.info('Creating dataset ' + str(d['id']))
if d['custom']:
self.logger.debug('Copying custom {} files'.format(d['id']))
self._add_custom_datasource(project, d)
sys.path.append(project.path)
if not Path(d['path']).is_absolute():
d['path'] = str(self.src_files.joinpath(d['path']))
ds = d['factory'](path=d['path'])
ds.save()
# Generate the subdatasets
for sbds in self.cfg.subdatasets:
self.logger.info('Creating SubDataset' + sbds['id'])
self.logger.debug('With method ' + sbds['method'])
dataset = sbds['dataset_factory']()
subdataset = sbds['factory'](dataset=dataset)
subdataset.save()
# Generate approaches
for a in self.cfg.approaches:
self.logger.info('Creating Approach ' + a['name'])
subdataset = a['sbds_factory']()
approach = a['factory'](subdataset=subdataset, project=project)
approach.save()
self.webservice and self.webservice.create_approach(a)
src_approach = self.src_files.joinpath(a['path'],
a['name'] + '.py')
shutil.copy(str(src_approach), str(approach.script_path))
return project
def test_create_new_project_with_name(self):
"""
Creates a new Project given a path to the local file system and the project name
Asserts
-------
- The project path is created
- Exists property is true
"""
set_project_path(testenv.MOCK_PROJECT_PATH)
p = Project(name=self.project_name,
path=self.path_to_test_dir)
self.assertEqual(p.path, self.path_to_project)
self.assertTrue(p.exists())
def setUp(self):
set_project_path(testenv.MOCK_PROJECT_PATH)
self.p = Project(path=testenv.TEST_PATH,
name=testenv.MOCK_PROJECT_NAME)
self.ds = Dataset.read_file(path=testenv.MOCK_DATASET,
first_line_heading=False)
self.ds.save()
self.sbds = SubDataset(self.ds, method="k_fold", by=5)
self.sbds.save()
self.approach = Approach(self.p,
"logistic_regression",
self.sbds,
path=str(Path(testenv.TEST_PATH, "lr")))
shutil.copyfile(testenv.APPROACH_EXAMPLE,
str(self.approach.script_path))
self.approach.save()
def test_create_two_projects_without_name(self):
"""
Creates a new Project given a path to the local file system without the project name and then creates a new
Project without name. The expected behaviour is that Projects generates a new name.
Asserts
-------
- The first project path is created using the default name when no name is provided
- The second project generates a new default name
"""
p1 = Project(path=self.path_to_test_dir)
p2 = Project(path=self.path_to_test_dir)
set_project_path(p1.path)
path_to_noname_project1 = Path(self.path_to_test_dir, self.project_default_name)
path_to_noname_project2 = Path(self.path_to_test_dir, "{}_{}".format(self.project_default_name, 1))
self.assertEqual(p1.path, str(path_to_noname_project1))
self.assertEqual(p2.path, str(path_to_noname_project2))
def setUp(self):
set_project_path(testenv.MOCK_PROJECT_PATH)
self.path_to_dataset = testenv.MOCK_DATASET
self.path_to_test_dir = testenv.TEST_PATH
self.aux_project_name = testenv.MOCK_PROJECT_NAME
self.path_to_auxproj = testenv.MOCK_PROJECT_PATH
self.project_default_name = testenv.DEFAULT_PROJECT_NAME
self.p = Project(path=self.path_to_test_dir,
name=self.aux_project_name)
self.ds = Dataset.read_file(path=self.path_to_dataset)
self.ds.save()
self.sbds = SubDataset(self.ds, method="k_fold", by=5)
self.sbds.save()
self.approach = Approach(self.p, "test_approach", self.sbds)
shutil.copyfile(testenv.APPROACH_EXAMPLE,
str(self.approach.script_path))
self.approach.save()
from driftai.project import Project
from driftai.approach import Approach
from driftai import set_project_path
ds = Dataset.from_dir(
r"C:\cygwin64\home\fcgr\code\driftai\examples\mnst_digit_classification_old\data"
)
proj_path = r"C:\cygwin64\home\fcgr\code\driftai\test\my_tests"
proj_name = "a"
if Path("{}\{}".format(proj_path, proj_name)).exists():
shutil.rmtree(str(Path("{}\{}".format(proj_path, proj_name)).absolute()))
p = Project(name="a", path=r"C:\cygwin64\home\fcgr\code\driftai\test\my_tests")
set_project_path(p.path)
info = ds.get_info()
ds.save()
sbs = ds.generate_subdataset(method="k_fold", by=5)
sbs.save()
from PIL import Image
import numpy as np
#tr_data = sbs.get_train_data("A", loader=lambda x: np.asarray(Image.open(x)).reshape(-1))
#ts_data = sbs.get_test_data("A", loader=lambda x: np.asarray(Image.open(x)))
a = Approach(project=p, name="my_approach", subdataset=sbs)
a.save()
