class MatplotlibStorageTestCase(lsst.utils.tests.TestCase):
def setUp(self):
inputDir = os.path.join(ROOT, "data", "input")
self.testDir = tempfile.mkdtemp(dir=os.path.join(ROOT, 'tests'),
prefix=type(self).__name__ + '-')
self.butler = Butler(inputs=inputDir,
outputs={
"root": self.testDir,
"mode": 'rw'
})
def tearDown(self):
del self.butler
if os.path.exists(self.testDir):
shutil.rmtree(self.testDir)
def testWriteFigure(self):
"""Test writing a matpotlib figure to a repository."""
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot
fig = pyplot.figure()
pyplot.plot([0, 1], [0, 1], "k")
self.butler.put(fig, "test_plot", visit=1, filter="g")
self.assertTrue(
self.butler.datasetExists("test_plot", visit=1, filter="g"))
self.assertTrue(
os.path.exists(self.butler.getUri("test_plot", visit=1,
filter="g")))
class MatplotlibStorageTestCase(lsst.utils.tests.TestCase):
def setUp(self):
inputDir = os.path.join(ROOT, "data", "input")
self.testDir = tempfile.mkdtemp(dir=os.path.join(ROOT, 'tests'), prefix=type(self).__name__+'-')
self.butler = Butler(inputs=inputDir, outputs={"root": self.testDir, "mode": 'rw'})
def tearDown(self):
del self.butler
if os.path.exists(self.testDir):
shutil.rmtree(self.testDir)
def testWriteFigure(self):
"""Test writing a matpotlib figure to a repository."""
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot
fig = pyplot.figure()
pyplot.plot([0, 1], [0, 1], "k")
self.butler.put(fig, "test_plot", visit=1, filter="g")
self.assertTrue(self.butler.datasetExists("test_plot", visit=1, filter="g"))
self.assertTrue(os.path.exists(self.butler.getUri("test_plot", visit=1, filter="g")))
def prep(self):
self.prior = bfd.MomentPrior()
priorFiles = []
priorButler = Butler(self.config.priorRerun)
prior_skyMap = priorButler.get('deepCoadd_skyMap')
for tract in self.config.priorTracts:
for patchInfo in prior_skyMap[tract]:
patch = '%d,%d' % patchInfo.getIndex()
if self.config.priorPatches:
if patch not in self.config.priorPatches:
continue
if priorButler.datasetExists('deepCoadd_momentPrior',
tract=tract,
patch=patch,
filter=self.config.priorFilter,
label=self.config.priorLabel):
priorFiles.append(
priorButler.get('deepCoadd_momentPrior_filename',
tract=tract,
patch=patch,
filter=self.config.priorFilter,
label=self.config.priorLabel)[0])
max_file = len(priorFiles)
if self.config.maxPriorFiles > 0:
max_file = self.config.maxPriorFiles
first = True
for file in priorFiles[:max_file]:
if file.find('_parent') > 0:
self.log.info("Skipping %s, from parent" % file)
continue
self.log.info("Adding prior %s" % file)
try:
cat = lsst.afw.table.BaseCatalog.readFits(file)
self.prior.addCatalog(cat, self.config.invariantCovariance,
self.config.sampleFraction,
self.config.sampleSeed)
# Should be same for all prior catalogs
if first:
self.cov = numpy.array(
cat.getTable().getMetadata().getArrayDouble(
'COV')).reshape(6, 6)
first = False
except Exception as e:
print('Failed to read', e)
continue
self.prior.prepare()
self.fluxMin = self.prior.getFluxMin()
self.fluxMax = self.prior.getFluxMax()
self.varMin = self.prior.getVarMin()
self.varMax = self.prior.getVarMax()
selectionPqr = self.prior.selectionProbability(
self.cov.astype(numpy.float32))
deselect = selectionPqr.copy()
deselect[0] = 1 - selectionPqr[0]
for i in range(1, 6):
deselect[i] *= -1.
self.noSelectPqr = deselect
def prep(self):
if self.initialized:
return
self.prior = None
priorFiles = []
priorButler = Butler(self.config.priorRerun)
prior_skyMap = priorButler.get('deepCoadd_skyMap')
for tract in self.config.priorTracts:
for patchInfo in prior_skyMap[tract]:
patch = '%d,%d' % patchInfo.getIndex()
if self.config.priorPatches:
if patch not in self.config.priorPatches:
continue
if priorButler.datasetExists('deepCoadd_prior', tract=tract, patch=patch,
filter=self.config.priorFilter, label=self.config.priorLabel):
priorFiles.append(priorButler.getUri('deepCoadd_prior',
tract=tract, patch=patch,
filter=self.config.priorFilter,
label=self.config.priorLabel))
max_file = len(priorFiles)
if self.config.maxPriorFiles > 0:
max_file = self.config.maxPriorFiles
self.zBin = None
for file in priorFiles[:max_file]:
if file.find('_parent') > 0:
self.log.info("Skipping %s, from parent" % file)
continue
self.log.info("Adding prior %s" % file)
try:
cat = afwTable.BaseCatalog.readFits(file)
md = cat.getTable().getMetadata().toDict()
if self.prior is None:
self.fluxMin = md['FLUXMIN']
self.fluxMax = md['FLUXMAX']
self.varMin = md['VARMIN']
self.varMax = md['VARMAX']
cov_even = np.array(md['COV_EVEN'])
cov_odd = np.array(md['COV_ODD'])
self.zMax = md['ZMAXCUT']
self.zMin = md['ZMINCUT']
self.noiseFactor = md['noiseFactor']
self.priorSigmaCutoff = md['priorSigmaCutoff']
self.priorSigmaStep = md['priorSigmaStep']
self.priorSigmaBuffer = md['priorSigmaBuffer']
self.nSample = md['NSAMPLE']
self.selectionOnly = md['selectionOnly']
self.invariantCovariance = md['invariantCovariance']
covMat = self.bfd.MomentCov(cov_even.reshape(self.n_even, self.n_even),
cov_odd.reshape(self.n_odd, self.n_odd))
self.prior = self.bfd.KDTreePrior(self.fluxMin, self.fluxMax, covMat, self.ud,
self.nSample, self.selectionOnly,
self.noiseFactor, self.priorSigmaStep,
self.priorSigmaCutoff, self.priorSigmaBuffer,
self.invariantCovariance)
else:
fluxMin = md['FLUXMIN']
fluxMax = md['FLUXMAX']
varMin = md['VARMIN']
varMax = md['VARMAX']
cov_even = np.array(md['COV_EVEN'])
cov_odd = np.array(md['COV_ODD'])
zMax = md['ZMAXCUT']
zMin = md['ZMINCUT']
noiseFactor = md['noiseFactor']
priorSigmaCutoff = md['priorSigmaCutoff']
priorSigmaStep = md['priorSigmaStep']
priorSigmaBuffer = md['priorSigmaBuffer']
nSample = md['NSAMPLE']
selectionOnly = md['selectionOnly']
invariantCovariance = md['invariantCovariance']
mismatch = False
if fluxMin != self.fluxMin:
self.log.info('does not match fluxMin')
mismatch = True
if fluxMax != self.fluxMax:
self.log.info('does not match fluxMax')
mismatch = True
if varMin != self.varMin:
self.log.info('does not match varMin')
mismatch = True
if varMax != self.varMax:
self.log.info('does not match varMax')
mismatch = True
if zMin != self.zMin:
self.log.info('does not match zMin')
mismatch = True
if zMax != self.zMax:
self.log.info('does not match zMax')
mismatch = True
if noiseFactor != self.noiseFactor:
self.log.info('does not match fluxMin')
mismatch = True
if priorSigmaBuffer != self.priorSigmaBuffer:
self.log.info('does not match priorSigmaBuffer')
mismatch = True
if priorSigmaStep != self.priorSigmaStep:
self.log.info('does not match priorSigmaStep')
mismatch = True
if priorSigmaCutoff != self.priorSigmaCutoff:
self.log.info('does not match priorSigmaCutoff')
mismatch = True
if nSample != self.nSample:
self.log.info('does not match nSample')
mismatch = True
if selectionOnly != self.selectionOnly:
self.log.info('does not match selectionOnly')
mismatch = True
if invariantCovariance != self.invariantCovariance:
self.log.info('does not match invariantCovariance')
mismatch = True
if mismatch:
self.log.info('Skipping %s' % file)
continue
for s in cat:
ti = self.bfd.TemplateInfo()
ti.m = s.get('m')
ti.dm = s.get('dm').reshape(self.bfd.BFDConfig.MSIZE, self.bfd.BFDConfig.DSIZE)
ti.dxy = s.get('dxy').reshape(self.bfd.BFDConfig.XYSIZE, self.bfd.BFDConfig.DSIZE)
ti.nda = s.get('nda')
ti.id = s.get('bfd_id')
self.prior.addTemplateInfo(ti)
except Exception as e:
print('Failed to read', e)
continue
self.prior.prepare()
self.initialized = True
class ProductionTestCase(lsst.utils.tests.TestCase):
def setUp(self):
self.butler = Butler(
os.path.join(weeklyRerun, "pipeline", self.configuration,
"pipeline"))
self.visits = dict(brn=getBrnVisits,
bmn=getBmnVisits)[self.configuration]()
self.design = PfsDesign.read(1, weeklyRaw)
def tearDown(self):
del self.butler
def testVisitProducts(self):
"""Test that visit products exist"""
for visit in self.visits:
for arm in self.configuration:
self.assertTrue(
self.butler.datasetExists("pfsArm", visit=visit, arm=arm))
self.assertTrue(
self.butler.datasetExists("pfsArmLsf",
visit=visit,
arm=arm))
self.assertTrue(self.butler.datasetExists("pfsMerged",
visit=visit))
self.assertTrue(
self.butler.datasetExists("pfsMergedLsf", visit=visit))
config = self.butler.get("pfsConfig", visit=visit)
for target in config:
if target.catId == -1:
# Not a real target that we've processed
continue
self.assertTrue(
self.butler.datasetExists("pfsSingle",
target.identity,
visit=visit))
self.assertTrue(
self.butler.datasetExists("pfsSingleLsf",
target.identity,
visit=visit))
def testObjectProducts(self):
"""Test that object products exist"""
for target in self.design:
if target.catId == -1:
# Not a real target that we've processed
continue
dataId = target.identity.copy()
dataId["nVisit"] = len(self.visits)
dataId["pfsVisitHash"] = calculatePfsVisitHash(self.visits)
self.assertTrue(self.butler.datasetExists("pfsObject", dataId),
msg=str(dataId))
self.assertTrue(self.butler.datasetExists("pfsObjectLsf", dataId),
msg=str(dataId))
def testSpectra(self):
"""Test that spectra files can be read, and they are reasonable"""
for visit in self.visits:
config = self.butler.get("pfsConfig", visit=visit)
spectra = self.butler.get("pfsMerged", visit=visit)
lsf = self.butler.get("pfsMergedLsf", visit=visit)
badMask = spectra.flags.get("NO_DATA", "BAD_FLAT", "INTRP")
for fiberId, target in zip(config.fiberId, config):
if target.catId == -1:
# Not a real target that we've processed
continue
with self.subTest(visit=visit, fiberId=fiberId):
index = np.where(spectra.fiberId == fiberId)[0]
mask = spectra.mask[index]
select = (mask & badMask) == 0
self.assertGreater(select.sum(), 0.75 * len(mask),
"Too many masked pixels")
self.assertFalse(np.all(spectra.sky[index][select] == 0))
self.assertTrue(
np.all(spectra.variance[index][select] > 0))
self.assertIn(fiberId, lsf)
self.assertIsInstance(lsf[fiberId], Lsf)
def testObjects(self):
"""Test that object files can be read, and they are reasonable"""
for target in self.design:
if target.catId == -1:
# Not a real target that we've processed
continue
with self.subTest(**target.identity):
dataId = target.identity.copy()
dataId.update(nVisit=len(self.visits),
pfsVisitHash=calculatePfsVisitHash(self.visits))
spectrum = self.butler.get("pfsObject", dataId)
lsf = self.butler.get("pfsObjectLsf", dataId)
badMask = spectrum.flags.get("NO_DATA")
select = (spectrum.mask & badMask) == 0
minFrac = dict(brn=0.75, bmn=0.70)[self.configuration]
self.assertGreater(select.sum(), minFrac * len(spectrum),
"Too many masked pixels")
self.assertFalse(np.all(spectrum.sky[select] == 0))
self.assertTrue(np.all(spectrum.variance[select] > 0))
self.assertIsInstance(lsf, Lsf)
def prep(self):
self.prior = bfd.MomentPrior()
priorFiles = []
priorButler = Butler(self.config.priorRerun)
prior_skyMap = priorButler.get('deepCoadd_skyMap')
for tract in self.config.priorTracts:
for patchInfo in prior_skyMap[tract]:
patch = '%d,%d' % patchInfo.getIndex()
if self.config.priorPatches:
if patch not in self.config.priorPatches:
continue
if priorButler.datasetExists('deepCoadd_momentPrior',
tract=tract,
patch=patch,
filter=self.config.priorFilter,
label=self.config.priorLabel):
priorFiles.append(
priorButler.get('deepCoadd_momentPrior_filename',
tract=tract,
patch=patch,
filter=self.config.priorFilter,
label=self.config.priorLabel)[0])
if len(priorFiles) == 0:
raise Exception('No Prior files found')
max_file = len(priorFiles)
if self.config.maxPriorFiles > 0:
max_file = self.config.maxPriorFiles
first = True
self.zBin = None
for file in priorFiles[:max_file]:
if file.find('_parent') > 0:
self.log.info("Skipping %s, from parent" % file)
continue
self.log.info("Adding prior %s" % file)
try:
cat = lsst.afw.table.BaseCatalog.readFits(file)
self.prior.addCatalog(cat, self.config.invariantCovariance,
self.config.sampleFraction,
self.config.sampleSeed)
# Should be same for all prior catalogs
if first:
self.cov = numpy.array(
cat.getTable().getMetadata().getArrayDouble(
'COV')).reshape(6, 6)
self.zBin = cat.getTable().getMetadata().getInt('ZBIN')
self.fluxBin = cat.getTable().getMetadata().getInt(
'NOISEBIN')
first = False
self.log.info('Processing zbin: %d flux: %d' %
(self.zBin, self.fluxBin))
except Exception as e:
print 'Failed to read', e
continue
self.log.info("Building tree from prior")
self.prior.prepare()
self.fluxMin = self.prior.getFluxMin()
self.fluxMax = self.prior.getFluxMax()
self.varMin = self.prior.getVarMin()
self.varMax = self.prior.getVarMax()
if self.config.writeNonSelect:
self.selectionPqr = self.prior.selectionProbability(
self.cov.astype(numpy.float32))
deselect = self.selectionPqr.copy()
deselect[0] = 1 - self.selectionPqr[0]
for i in range(1, 6):
deselect[i] *= -1.
self.noSelectPqr = deselect
self.log.info('Probability of not being selected: %s' %
self.noSelectPqr)
if self.config.readZFile is False:
self.log.info("Reading redshift file")
zFile = pyfits.open(self.config.zFile)[1].data
self.zRedshift = numpy.zeros(len(zFile))
self.zId = zFile[self.config.zId]
if self.config.useXY is False:
zRa = zFile[self.config.zRa] * numpy.pi / 180
zDec = zFile[self.config.zDec] * numpy.pi / 180
if self.config.useAllZ:
mask = zFile['frankenz_photoz_%s_isnull' %
self.config.zField] == False
self.zRedshift[mask] = zFile['frankenz_photoz_%s' %
self.config.zField][mask]
mask = (zFile['mizuki_photoz_%s_isnull' %
self.config.zField]
== False) & (self.zRedshift == 0.0)
self.zRedshift[mask] = zFile['mizuki_photoz_%s' %
self.config.zField][mask]
mask = (zFile['nnpz_photoz_%s_isnull' % self.config.zField]
== False) & (self.zRedshift == 0.0)
self.zRedshift[mask] = zFile['nnpz_photoz_%s' %
self.config.zField][mask]
mask = (zFile['mlz_photoz_%s_isnull' % self.config.zField]
== False) & (self.zRedshift == 0.0)
self.zRedshift[mask] = zFile['mlz_photoz_%s' %
self.config.zField][mask]
else:
mask = zFile['%s_photoz_%s_isnull' %
(self.config.zType,
self.config.zField)] == False
self.zRedshift[mask] = zFile['%s_photoz_%s' %
(self.config.zType,
self.config.zField)][mask]
posRef = numpy.dstack([
numpy.sin(zDec) * numpy.cos(zRa),
numpy.sin(zDec) * numpy.sin(zRa),
numpy.sin(zDec)
])[0]
self.log.info('Building redshift treee')
self.zTree = scipy.spatial.cKDTree(posRef)
else:
zX = zFile[self.config.zRa]
zY = zFile[self.config.zDec]
posRef = numpy.dstack([zX, zY])[0]
self.zTree = scipy.spatial.cKDTree(posRef)
self.zRedshift = zFile[self.config.zField]
