def testStellarPhotometryIndices(self):
"""
A test to make sure that stellar photometry still calculates the right values
even when it is not calculating all of the magnitudes in the getter
"""
baselineDtype = numpy.dtype([('id',int),
('raObserved', float), ('decObserved', float),
('magNorm', float),
('cartoon_u', float), ('cartoon_g',float),
('cartoon_r', float), ('cartoon_i', float),
('cartoon_z', float)])
baselineCatName = 'stellarBaselineCatalog.txt'
testDtype = numpy.dtype([('id',int),
('raObserved',float), ('decObserved',float),
('cartoon_i',float)])
testCatName = 'stellarTestCatalog.txt'
obs_metadata_pointed=ObservationMetaData(mjd=2013.23,
boundType='circle',unrefractedRA=200.0,unrefractedDec=-30.0,
boundLength=1.0)
baseline_cat=cartoonStars(self.star,obs_metadata=obs_metadata_pointed)
baseline_cat.write_catalog(baselineCatName)
baselineData = numpy.genfromtxt(baselineCatName, dtype=baselineDtype, delimiter=',')
test_cat=cartoonStarsOnlyI(self.star, obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = numpy.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
ct = 0
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
ct+=1
self.assertTrue(ct>0)
testDtype = numpy.dtype([('id',int),
('raObserved',float), ('decObserved',float),
('cartoon_i',float), ('cartoon_z',float)])
test_cat=cartoonStarsIZ(self.star, obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = numpy.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
ct = 0
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
self.assertAlmostEqual(b['cartoon_z'], t['cartoon_z'], 10)
ct+=1
self.assertTrue(ct>0)
if os.path.exists(testCatName):
os.unlink(testCatName)
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
def testStellarPhotometryIndices(self):
"""
A test to make sure that stellar photometry still calculates the right values
even when it is not calculating all of the magnitudes in the getter
"""
baselineDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('magNorm', float),
('cartoon_u', float), ('cartoon_g', float),
('cartoon_r', float), ('cartoon_i', float),
('cartoon_z', float)])
testDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('cartoon_i', float)])
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0,
pointingDec=-30.0,
boundLength=1.0)
baseline_cat = cartoonStars(self.star,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as baselineCatName:
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName,
dtype=baselineDtype,
delimiter=',')
self.assertGreater(len(baselineData), 0)
test_cat = cartoonStarsOnlyI(self.star,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName,
dtype=testDtype,
delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
testDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('cartoon_i', float),
('cartoon_z', float)])
test_cat = cartoonStarsIZ(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName,
dtype=testDtype,
delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
self.assertAlmostEqual(b['cartoon_z'], t['cartoon_z'], 10)
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0,
pointingDec=-30.0,
boundLength=1.0)
test_cat = cartoonStars(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
with open(catName, 'r') as input_file:
lines = input_file.readlines()
self.assertGreater(len(lines), 1)
cartoonDir = os.path.join(getPackageDir('sims_photUtils'), 'tests',
'cartoonSedTestData')
testBandPasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
bplist = []
for kk in keys:
testBandPasses[kk] = Bandpass()
testBandPasses[kk].readThroughput(
os.path.join(cartoonDir, "test_bandpass_%s.dat" % kk))
bplist.append(testBandPasses[kk])
sedObj = Sed()
phiArray, waveLenStep = sedObj.setupPhiArray(bplist)
i = 0
# since all of the SEDs in the cartoon database are the same, just test on the first
# if we ever include more SEDs, this can be something like
# for ss in test_cata.sedMasterList:
ss = test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match=bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5 * np.log10(
np.sum(phiArray * ss.fnu, axis=1) * waveLenStep) - ss.zp
self.assertEqual(len(mags), len(test_cat.cartoonBandpassDict))
self.assertGreater(len(mags), 0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j], test_cat.magnitudeMasterList[i][j],
4)
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0, pointingDec=-30.0,
boundLength=1.0)
test_cat = cartoonStars(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
with open(catName, 'r') as input_file:
lines = input_file.readlines()
self.assertGreater(len(lines), 1)
cartoonDir = os.path.join(getPackageDir('sims_photUtils'), 'tests', 'cartoonSedTestData')
testBandPasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
bplist = []
for kk in keys:
testBandPasses[kk] = Bandpass()
testBandPasses[kk].readThroughput(os.path.join(cartoonDir, "test_bandpass_%s.dat" % kk))
bplist.append(testBandPasses[kk])
sedObj = Sed()
phiArray, waveLenStep = sedObj.setupPhiArray(bplist)
i = 0
# since all of the SEDs in the cartoon database are the same, just test on the first
# if we ever include more SEDs, this can be something like
# for ss in test_cata.sedMasterList:
ss = test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*np.log10(np.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
self.assertEqual(len(mags), len(test_cat.cartoonBandpassDict))
self.assertGreater(len(mags), 0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j], test_cat.magnitudeMasterList[i][j], 4)
def testStellarPhotometryIndices(self):
"""
A test to make sure that stellar photometry still calculates the right values
even when it is not calculating all of the magnitudes in the getter
"""
baselineDtype = np.dtype([('id', int),
('raObserved', float), ('decObserved', float),
('magNorm', float),
('cartoon_u', float), ('cartoon_g', float),
('cartoon_r', float), ('cartoon_i', float),
('cartoon_z', float)])
testDtype = np.dtype([('id', int),
('raObserved', float), ('decObserved', float),
('cartoon_i', float)])
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0, pointingDec=-30.0,
boundLength=1.0)
baseline_cat = cartoonStars(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as baselineCatName:
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName, dtype=baselineDtype, delimiter=',')
self.assertGreater(len(baselineData), 0)
test_cat = cartoonStarsOnlyI(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
testDtype = np.dtype([('id', int),
('raObserved', float), ('decObserved', float),
('cartoon_i', float), ('cartoon_z', float)])
test_cat = cartoonStarsIZ(self.star, obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as testCatName:
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
self.assertAlmostEqual(b['cartoon_z'], t['cartoon_z'], 10)
def testAlternateBandpassesStars(self):
"""
This will test our ability to do photometry using non-LSST bandpasses.
It will first calculate the magnitudes using the getters in cartoonPhotometryStars.
It will then load the alternate bandpass files 'by hand' and re-calculate the magnitudes
and make sure that the magnitude values agree. This is guarding against the possibility
that some default value did not change and the code actually ended up loading the
LSST bandpasses.
"""
obs_metadata_pointed=ObservationMetaData(mjd=2013.23,
boundType='circle',unrefractedRA=200.0,unrefractedDec=-30.0,
boundLength=1.0)
test_cat=cartoonStars(self.star,obs_metadata=obs_metadata_pointed)
test_cat.write_catalog("testStarsCartoon.txt")
cartoonDir = os.getenv('SIMS_PHOTUTILS_DIR')+'/tests/cartoonSedTestData/'
testBandPasses = {}
keys = ['u','g','r','i','z']
bplist = []
for kk in keys:
testBandPasses[kk] = Bandpass()
testBandPasses[kk].readThroughput(os.path.join(cartoonDir,"test_bandpass_%s.dat" % kk))
bplist.append(testBandPasses[kk])
sedObj = Sed()
phiArray, waveLenStep = sedObj.setupPhiArray(bplist)
i = 0
#since all of the SEDs in the cartoon database are the same, just test on the first
#if we ever include more SEDs, this can be something like
#for ss in test_cata.sedMasterList:
#
ss=test_cat.sedMasterList[0]
ss.resampleSED(wavelen_match = bplist[0].wavelen)
ss.flambdaTofnu()
mags = -2.5*numpy.log10(numpy.sum(phiArray*ss.fnu, axis=1)*waveLenStep) - ss.zp
self.assertTrue(len(mags)==len(test_cat.bandpassDict))
self.assertTrue(len(mags)>0)
for j in range(len(mags)):
self.assertAlmostEqual(mags[j],test_cat.magnitudeMasterList[i][j],10)
i += 1
os.unlink("testStarsCartoon.txt")
def testStellarPhotometryIndices(self):
"""
A test to make sure that stellar photometry still calculates the right values
even when it is not calculating all of the magnitudes in the getter
"""
baselineDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('magNorm', float),
('cartoon_u', float), ('cartoon_g', float),
('cartoon_r', float), ('cartoon_i', float),
('cartoon_z', float)])
baselineCatName = os.path.join(
getPackageDir('sims_catUtils'), 'tests', 'scratchSpace',
'testPhotMix_testStellarIndices_stellarBaselineCatalog.txt')
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
testDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('cartoon_i', float)])
testCatName = os.path.join(
getPackageDir('sims_catUtils'), 'tests', 'scratchSpace',
'testPhotMix_testStellarIndices_stellarTestCatalog.txt')
if os.path.exists(testCatName):
os.unlink(testCatName)
obs_metadata_pointed = ObservationMetaData(mjd=2013.23,
boundType='circle',
pointingRA=200.0,
pointingDec=-30.0,
boundLength=1.0)
baseline_cat = cartoonStars(self.star,
obs_metadata=obs_metadata_pointed)
baseline_cat.write_catalog(baselineCatName)
baselineData = np.genfromtxt(baselineCatName,
dtype=baselineDtype,
delimiter=',')
self.assertGreater(len(baselineData), 0)
test_cat = cartoonStarsOnlyI(self.star,
obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
testDtype = np.dtype([('id', int), ('raObserved', float),
('decObserved', float), ('cartoon_i', float),
('cartoon_z', float)])
test_cat = cartoonStarsIZ(self.star, obs_metadata=obs_metadata_pointed)
test_cat.write_catalog(testCatName)
testData = np.genfromtxt(testCatName, dtype=testDtype, delimiter=',')
self.assertGreater(len(testData), 0)
for b, t in zip(baselineData, testData):
self.assertAlmostEqual(b['cartoon_i'], t['cartoon_i'], 10)
self.assertAlmostEqual(b['cartoon_z'], t['cartoon_z'], 10)
if os.path.exists(testCatName):
os.unlink(testCatName)
if os.path.exists(baselineCatName):
os.unlink(baselineCatName)
