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)
