def setUpClass(cls):
"""For setup, ensure db does not exist."""
cls.config = CompleteTestConfig()
cls.dbfile = cls.config.db
remove_db(cls.dbfile)
pipeline = Phenoscoring(cls.config)
pipeline.build()
class RemoveModelsTests(unittest.TestCase):
"""Test cases for updating a non-empty phenoscoring db with more models"""
def setUp(self):
"""For setup, ensure db does not exist, then build a new one"""
config = CompleteTestConfig()
self.dbfile = config.db
remove_db(self.dbfile)
self.pipeline = Phenoscoring(config)
self.pipeline.build()
impc = Phenoscoring(IMPCTestConfig())
impc.update()
# handles for models
self.desctab = ModelDescriptionTable(self.dbfile)
self.phenstab = ModelPhenotypeTable(self.dbfile)
self.scoretab = ModelScoreTable(self.dbfile)
def tearDown(self):
"""At end, ensure test db is deleted."""
remove_db(self.dbfile)
def test_clear_models(self):
"""can remove all models at once."""
# ensure that db is non empty
self.assertGreater(self.desctab.count_rows(), 0)
self.assertGreater(self.phenstab.count_rows(), 0)
self.assertGreater(self.scoretab.count_rows(), 0)
# attempt to clear everything
impc = Phenoscoring(IMPCTestConfig())
impc.clearmodels()
self.assertEqual(self.desctab.count_rows(), 0)
self.assertEqual(self.phenstab.count_rows(), 0)
self.assertEqual(self.scoretab.count_rows(), 0)
def test_remove_models(self):
"""can remove a partial set of data"""
# get an initial set of database row counts
num_desc = self.desctab.count_rows()
num_phens = self.phenstab.count_rows()
num_score = self.scoretab.count_rows()
# run a model removal using a small descriptions file
config = IMPCTestConfig()
config.model_descriptions = "prep-IMPC-descriptions-update.tsv"
config.model_phenotypes = None
impc = Phenoscoring(config)
impc.remove()
# the number of rows in tables should decrease
self.assertLess(self.desctab.count_rows(), num_desc,
"number of models should decrease")
self.assertLess(self.phenstab.count_rows(), num_phens,
"number of phenotypes should decrease")
self.assertLess(self.scoretab.count_rows(), num_score,
"number of score entries should decrease")
def setUpClass(cls):
"""For setup, ensure db does not exist."""
cls.config = CompleteTestConfig()
cls.dbfile = cls.config.db
cls.k = cls.config.reference_neighbors_k
remove_db(cls.dbfile)
pipeline = Phenoscoring(cls.config)
pipeline.build()
cls.neighbors = get_reference_neighbors(cls.dbfile, cls.k)
def setUp(self):
"""For setup, ensure db does not exist."""
self.config = CompleteTestConfig()
self.dbfile = self.config.db
remove_db(self.dbfile)
pipeline = Phenoscoring(CompleteTestConfig())
pipeline.build()
# add something into the db
self.desctab = ModelDescriptionTable(self.dbfile)
self.desctab.add(id="a", category="test")
self.desctab.save()
def test_reset_build(self):
"""stops processing if build() called a second time."""
# make sure to start the db has something
self.assertGreater(self.desctab.count_rows(), 0)
# rebuild
config = CompleteTestConfig()
config.reset = True
pipeline = Phenoscoring(config)
pipeline.build()
# the tables should now be cleared in the build
self.assertEqual(self.desctab.count_rows(), 0)
def test_can_avoid_rebuild(self):
"""stops processing if build() called a second time."""
# make sure to start the db has something
self.assertGreater(self.desctab.count_rows(), 0)
# attempt rebuild
config = CompleteTestConfig()
config.reset = False
pipeline = Phenoscoring(config)
pipeline.build()
# the tables should still be non-empty
self.assertGreater(self.desctab.count_rows(), 0)
class AddModelsTests(unittest.TestCase):
"""Test cases for adding models to an empty phenoscoring db"""
@classmethod
def setUpClass(self):
"""For setup, ensure db does not exist, then build a new one"""
config = CompleteTestConfig()
self.dbfile = config.db
remove_db(self.dbfile)
self.pipeline = Phenoscoring(config)
self.pipeline.build()
@classmethod
def tearDownClass(self):
"""At end, ensure test db is deleted."""
remove_db(self.dbfile)
def setUp(self):
"""At beginning of each test, make sure there are no models."""
self.pipeline.clearmodels()
def test_build_impc(self):
"""can build a phenoscoring database using only IMPC data"""
impc = Phenoscoring(IMPCTestConfig())
impc.update()
# in contrast to complete build, this db should have IMPC-only rows
desctab = ModelDescriptionTable(self.dbfile)
self.assertEqual(desctab.count_rows(), 8)
modeltab = ModelPhenotypeTable(self.dbfile)
self.assertEqual(modeltab.count_rows(), 14)
def test_build_mgi(self):
"""can build a phenoscoring database using only MGI data"""
mgi = Phenoscoring(MGITestConfig())
mgi.update()
# in contrast to complete config, this db should have fewer rows
desctab = ModelDescriptionTable(self.dbfile)
self.assertEqual(desctab.count_rows(), 6)
modeltab = ModelPhenotypeTable(self.dbfile)
self.assertEqual(modeltab.count_rows(), 9)
def test_build_both(self):
"""can update database sequentially with MGI and IMPC"""
mgi = Phenoscoring(MGITestConfig())
mgi.update()
impc = Phenoscoring(IMPCTestConfig())
impc.update()
desctab = ModelDescriptionTable(self.dbfile)
self.assertEqual(desctab.count_rows(), 14, "8 IMPC, 6 MGI")
modeltab = ModelPhenotypeTable(self.dbfile)
self.assertEqual(modeltab.count_rows(), 23, "9 MGI, 14 IMPC")
scoretab = ModelScoreTable(self.dbfile)
self.assertGreater(scoretab.count_rows(), 0,
"score table is non-empty")
help="reference for detailed calculation log")
# inputs for exporting tables
parser.add_argument("--table", action="store", help="name of table to export")
# ##################################################################
# Execute the program if module is used as an executable
if __name__ == "__main__":
config = parser.parse_args()
pipeline = Phenoscoring(config)
if config.action == "build":
# create a new sqlite database with references
pipeline.build()
if config.action == "clearmodels":
# remove all models and model scores from the database
pipeline.clearmodels()
if config.action == "update":
# add new or update existing model defintions/phenotypes
pipeline.update()
if config.action == "remove":
# remove a subset of models from the database
pipeline.remove()
if config.action == "recompute":
# remove all scores and re-generate them from scratch