def setUpClass(cls): cls.root = testUtils.makeTestTempDir( os.path.abspath(os.path.dirname(__file__))) cls.addClassCleanup(testUtils.removeTestTempDir, cls.root) # Can't use in-memory datastore because JobReporter creates a # new Butler from scratch. cls.repo = dafButler.Butler(dafButler.Butler.makeRepo(cls.root), writeable=True) # White-box testing: must use real metrics, and provide datasets of # type metricvalue_*_*. butlerTests.addDataIdValue(cls.repo, "instrument", "NotACam") butlerTests.addDataIdValue(cls.repo, "detector", 101) # physical_filter needed for well-behaved visits butlerTests.addDataIdValue(cls.repo, "physical_filter", "k2021", band="k") butlerTests.addDataIdValue(cls.repo, "visit", 42) # Dependency on verify_metrics, but not on the code for computing # these metrics. butlerTests.addDatasetType( cls.repo, "metricvalue_pipe_tasks_CharacterizeImageTime", {"instrument", "visit", "detector"}, "MetricValue")
def setUp(self): self.root = makeTestTempDir(TESTDIR) self.testRepo = MetricTestRepo(self.root, configFile=os.path.join( TESTDIR, "config/basic/butler.yaml")) self.runner = LogCliRunner()
def testRegisterMetricsExampleChained(self): """Regression test for registerMetricsExample having no effect on ChainedDatastore. """ temp = makeTestTempDir(TESTDIR) try: config = lsst.daf.butler.Config() config[ "datastore", "cls"] = "lsst.daf.butler.datastores.chainedDatastore.ChainedDatastore" config["datastore", "datastores"] = [{ "cls": "lsst.daf.butler.datastores.fileDatastore.FileDatastore", }] repo = lsst.daf.butler.Butler.makeRepo(temp, config=config) butler = lsst.daf.butler.Butler(repo, run="chainedExample") registerMetricsExample(butler) addDatasetType(butler, "DummyType", {}, "StructuredDataNoComponents") data = MetricsExample(summary={}) # Should not raise butler.put(data, "DummyType") finally: shutil.rmtree(temp, ignore_errors=True)
def setUp(self): self.root = makeTestTempDir(TESTDIR) Butler.makeRepo(self.root) ints = [1, 2, 3] names = ['one', 'two', 'three'] transcendentals = [3.14, 2.718, 0.643] self.table = Table([ints, names, transcendentals], names=['ints', 'names', 'transcendentals'])
def setUp(self): self.root = makeTestTempDir(TESTDIR) Butler.makeRepo(self.root) self.hspMap = hsp.HealSparseMap.make_empty(nside_coverage=32, nside_sparse=4096, dtype=np.float32) self.hspMap[0:10000] = 1.0 self.hspMap[100000:110000] = 2.0 self.hspMap[500000:510000] = 3.0
def setUp(self): """Create a new butler root for each test.""" self.root = makeTestTempDir(TESTDIR) Butler.makeRepo(self.root) self.butler = Butler(self.root, run="test_run") # No dimensions in dataset type so we don't have to worry about # inserting dimension data or defining data IDs. self.datasetType = DatasetType("data", dimensions=(), storageClass="DataFrame", universe=self.butler.registry.dimensions) self.butler.registry.registerDatasetType(self.datasetType)
def setUp(self): # Local test directory self.tmpdir = makeTestTempDir(TESTDIR) # set up some fake credentials if they do not exist self.usingDummyCredentials = setAwsEnvCredentials() # MOTO needs to know that we expect Bucket bucketname to exist s3 = boto3.resource("s3") s3.create_bucket(Bucket=self.bucketName)
def setUpClass(cls): # Repository should be re-created for each test case, but # this has a prohibitive run-time cost at present cls.root = makeTestTempDir(TESTDIR) dataIds = { "instrument": ["notACam", "dummyCam"], "physical_filter": ["k2020", "l2019"], "visit": [101, 102], "detector": [5] } cls.creatorButler = makeTestRepo(cls.root, dataIds) registerMetricsExample(cls.creatorButler) addDatasetType(cls.creatorButler, "DataType1", {"instrument"}, "StructuredDataNoComponents") addDatasetType(cls.creatorButler, "DataType2", {"instrument", "visit"}, "StructuredData")
def setUpClass(cls): # Repository should be re-created for each test case, but # this has a prohibitive run-time cost at present cls.root = makeTestTempDir(TESTDIR) cls.creatorButler = makeTestRepo(cls.root) addDataIdValue(cls.creatorButler, "instrument", "notACam") addDataIdValue(cls.creatorButler, "instrument", "dummyCam") addDataIdValue(cls.creatorButler, "physical_filter", "k2020", band="k", instrument="notACam") addDataIdValue(cls.creatorButler, "physical_filter", "l2019", instrument="dummyCam") addDataIdValue(cls.creatorButler, "visit", 101, instrument="notACam", physical_filter="k2020") addDataIdValue(cls.creatorButler, "visit", 102, instrument="notACam", physical_filter="k2020") addDataIdValue(cls.creatorButler, "detector", 5) # Leave skymap/patch/tract undefined so that tests can assume # they're missing. registerMetricsExample(cls.creatorButler) addDatasetType(cls.creatorButler, "DataType1", {"instrument"}, "StructuredDataNoComponents") addDatasetType(cls.creatorButler, "DataType2", {"instrument", "visit"}, "StructuredData")
def setUp(self): self.root = makeTestTempDir(TESTDIR)
def setUp(self): self.root = makeTestTempDir(TESTDIR) Butler.makeRepo(self.root) # Create a random image for testing self.rng = Random(self.RANDOM_SEED)
def setUp(self): # Use a local tempdir because on macOS the temp dirs use symlinks # so relsymlink gets quite confused. self.tmpdir = makeTestTempDir(TESTDIR)
def setUp(self): self.tmpdir = makeTestTempDir(TESTDIR)
def setUpClass(cls): cls.root = makeTestTempDir(TESTDIR) cls.server = _startServer(cls.root)
def setUp(self): self.root = makeTestTempDir(TESTDIR) self.testRepo = MetricTestRepo(self.root, configFile=self.configFile)