def testSumMagnitudes(self):
"""
Test that the method sum_magnitudes in PhotometryGalaxies handles
NaNs correctly. Test it both in the vectorized and non-vectorized form.
"""
mm_0 = 22.0
bulge = 15.0 * np.ones(8)
disk = 15.2 * np.ones(8)
agn = 15.4 * np.ones(8)
bulge[0] = np.NaN
disk[1] = np.NaN
agn[2] = np.NaN
bulge[3] = np.NaN
disk[3] = np.NaN
bulge[4] = np.NaN
agn[4] = np.NaN
disk[5] = np.NaN
agn[5] = np.NaN
bulge[7] = np.NaN
disk[7] = np.NaN
agn[7] = np.NaN
bulge_flux = np.power(10.0, -0.4 * (bulge - mm_0))
disk_flux = np.power(10.0, -0.4 * (disk - mm_0))
agn_flux = np.power(10.0, -0.4 * (agn - mm_0))
answer = np.zeros(8)
answer[0] = -2.5 * np.log10(disk_flux[0] + agn_flux[0]) + mm_0
answer[1] = -2.5 * np.log10(bulge_flux[1] + agn_flux[1]) + mm_0
answer[2] = -2.5 * np.log10(bulge_flux[2] + disk_flux[2]) + mm_0
answer[3] = -2.5 * np.log10(agn_flux[3]) + mm_0
answer[4] = -2.5 * np.log10(disk_flux[4]) + mm_0
answer[5] = -2.5 * np.log10(bulge_flux[5]) + mm_0
answer[6] = -2.5 * np.log10(bulge_flux[6] + disk_flux[6] +
agn_flux[6]) + mm_0
answer[7] = np.NaN
phot = PhotometryGalaxies()
test = phot.sum_magnitudes(bulge=bulge, disk=disk, agn=agn)
np.testing.assert_array_almost_equal(test, answer, decimal=10)
for ix, (bb, dd, aa, truth) in enumerate(zip(bulge, disk, agn,
answer)):
test = phot.sum_magnitudes(bulge=bb, disk=dd, agn=aa)
if ix < 7:
self.assertAlmostEqual(test, truth, 10)
self.assertFalse(np.isnan(test),
msg='test is NaN; should not be')
else:
np.testing.assert_equal(test, np.NaN)
np.testing.assert_equal(truth, np.NaN)
def testGalaxyVariabilityInfrastructure(self):
"""
Test that the variability design was correctly implemented in
the case of galaxies
"""
outputs = [
'id', 'test_u', 'test_g', 'test_r', 'test_i', 'test_z', 'test_y',
'test_bulge_u', 'test_bulge_g', 'test_bulge_r', 'test_bulge_i',
'test_bulge_z', 'test_bulge_y', 'test_disk_u', 'test_disk_g',
'test_disk_r', 'test_disk_i', 'test_disk_z', 'test_disk_y',
'test_agn_u', 'test_agn_g', 'test_agn_r', 'test_agn_i',
'test_agn_z', 'test_agn_y'
]
baseline = GalaxyBaselineCatalogClass(self.galaxyDB,
column_outputs=outputs)
variable = GalaxyVariabilityCatalogClass(self.galaxyDB,
column_outputs=outputs)
phot = PhotometryGalaxies()
variable_indices = [19, 20, 21, 7, 16]
for bb, vv in zip(baseline.iter_catalog(), variable.iter_catalog()):
self.assertEqual(bb[0], vv[0])
# test that the variable components are altered
# the way they ought to be
self.assertAlmostEqual(bb[19] + 1.0, vv[19], 10)
self.assertAlmostEqual(bb[20] + 2.0, vv[20], 10)
self.assertAlmostEqual(bb[21] + 3.0, vv[21], 10)
self.assertAlmostEqual(bb[7] + 4.0, vv[7], 10)
self.assertAlmostEqual(bb[16] + 5.0, vv[16], 10)
# test that the components which do not vary are equal
for ix in range(7, 25):
if ix not in variable_indices:
self.assertAlmostEqual(bb[ix], vv[ix], 10)
# test that the total magnitudes are correctly calculated
for ix in range(6):
self.assertAlmostEqual(
bb[ix + 1],
phot.sum_magnitudes(bulge=bb[7 + ix],
disk=bb[13 + ix],
agn=bb[19 + ix]), 10)
self.assertAlmostEqual(
vv[ix + 1],
phot.sum_magnitudes(bulge=vv[7 + ix],
disk=vv[13 + ix],
agn=vv[19 + ix]), 10)
def testAlternateBandpassesGalaxies(self):
"""
the same as testAlternateBandpassesStars, but for galaxies
"""
obs_metadata_pointed = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0,
pointingDec=0.0,
boundLength=10.0)
dtype = np.dtype([('galid', np.int), ('ra', np.float),
('dec', np.float), ('uTotal', np.float),
('gTotal', np.float), ('rTotal', np.float),
('iTotal', np.float), ('zTotal', np.float),
('uBulge', np.float), ('gBulge', np.float),
('rBulge', np.float), ('iBulge', np.float),
('zBulge', np.float), ('uDisk', np.float),
('gDisk', np.float), ('rDisk', np.float),
('iDisk', np.float), ('zDisk', np.float),
('uAgn', np.float), ('gAgn', np.float),
('rAgn', np.float), ('iAgn', np.float),
('zAgn', np.float), ('bulgeName', str, 200),
('bulgeNorm', np.float), ('bulgeAv', np.float),
('diskName', str, 200), ('diskNorm', np.float),
('diskAv', np.float), ('agnName', str, 200),
('agnNorm', np.float), ('redshift', np.float)])
test_cat = cartoonGalaxies(self.galaxy,
obs_metadata=obs_metadata_pointed)
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
catData = np.genfromtxt(catName, dtype=dtype, delimiter=', ')
self.assertGreater(len(catData), 0)
cartoonDir = getPackageDir('sims_photUtils')
cartoonDir = os.path.join(cartoonDir, 'tests', 'cartoonSedTestData')
sedDir = getPackageDir('sims_sed_library')
testBandpasses = {}
keys = ['u', 'g', 'r', 'i', 'z']
for kk in keys:
testBandpasses[kk] = Bandpass()
testBandpasses[kk].readThroughput(
os.path.join(cartoonDir, "test_bandpass_%s.dat" % kk))
imsimBand = Bandpass()
imsimBand.imsimBandpass()
specMap = defaultSpecMap
ct = 0
for line in catData:
bulgeMagList = []
diskMagList = []
agnMagList = []
if line['bulgeName'] == 'None':
for bp in keys:
np.testing.assert_equal(line['%sBulge' % bp], np.NaN)
bulgeMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['bulgeName']]))
fnorm = dummySed.calcFluxNorm(line['bulgeNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['bulgeAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sBulge' % bpName], 10)
bulgeMagList.append(mag)
if line['diskName'] == 'None':
for bp in keys:
np.assert_equal(line['%sDisk' % bp], np.NaN)
diskMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['diskName']]))
fnorm = dummySed.calcFluxNorm(line['diskNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
a_int, b_int = dummySed.setupCCM_ab()
dummySed.addDust(a_int, b_int, A_v=line['diskAv'])
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sDisk' % bpName], 10)
diskMagList.append(mag)
if line['agnName'] == 'None':
for bp in keys:
np.testing.assert_true(line['%sAgn' % bp], np.NaN)
agnMagList.append(np.NaN)
else:
ct += 1
dummySed = Sed()
dummySed.readSED_flambda(
os.path.join(sedDir, specMap[line['agnName']]))
fnorm = dummySed.calcFluxNorm(line['agnNorm'], imsimBand)
dummySed.multiplyFluxNorm(fnorm)
dummySed.redshiftSED(line['redshift'], dimming=True)
dummySed.resampleSED(wavelen_match=testBandpasses['u'].wavelen)
for bpName in keys:
mag = dummySed.calcMag(testBandpasses[bpName])
self.assertAlmostEqual(mag, line['%sAgn' % bpName], 10)
agnMagList.append(mag)
totalMags = PhotometryGalaxies().sum_magnitudes(
bulge=np.array(bulgeMagList),
disk=np.array(diskMagList),
agn=np.array(agnMagList))
for testMag, bpName in zip(totalMags, keys):
if np.isnan(line['%sTotal' % bpName]):
np.testing.assert_equal(testMag, np.NaN)
else:
self.assertAlmostEqual(testMag, line['%sTotal' % bpName],
10)
self.assertGreater(ct, 0)
def testSumMagnitudesCatalog(self):
"""
test that sum_magnitudes handles NaNs correctly in the context
of a catalog by outputting a catalog of galaxies with NaNs in
different component magnitudes, reading that catalog back in,
and then calculating the summed magnitude by hand and comparing
"""
obs_metadata = ObservationMetaData(mjd=50000.0,
boundType='circle',
pointingRA=0.0,
pointingDec=0.0,
boundLength=10.0)
test_cat = galaxiesWithHoles(self.galaxy, obs_metadata=obs_metadata)
dtype = np.dtype([('raJ2000', np.float), ('decJ2000', np.float),
('u', np.float), ('g', np.float), ('r', np.float),
('i', np.float), ('z', np.float), ('y', np.float),
('ub', np.float), ('gb', np.float), ('rb', np.float),
('ib', np.float), ('zb', np.float), ('yb', np.float),
('ud', np.float), ('gd', np.float), ('rd', np.float),
('id', np.float), ('zd', np.float), ('yd', np.float),
('ua', np.float), ('ga', np.float), ('ra', np.float),
('ia', np.float), ('za', np.float),
('ya', np.float)])
with lsst.utils.tests.getTempFilePath('.txt') as catName:
test_cat.write_catalog(catName)
data = np.genfromtxt(catName, dtype=dtype, delimiter=', ')
self.assertGreater(len(data), 16)
phot = PhotometryGalaxies()
test = phot.sum_magnitudes(bulge=data['ub'],
disk=data['ud'],
agn=data['ua'])
np.testing.assert_array_almost_equal(test, data['u'], decimal=10)
test = phot.sum_magnitudes(bulge=data['gb'],
disk=data['gd'],
agn=data['ga'])
np.testing.assert_array_almost_equal(test, data['g'], decimal=10)
test = phot.sum_magnitudes(bulge=data['rb'],
disk=data['rd'],
agn=data['ra'])
np.testing.assert_array_almost_equal(test, data['r'], decimal=10)
test = phot.sum_magnitudes(bulge=data['ib'],
disk=data['id'],
agn=data['ia'])
np.testing.assert_array_almost_equal(test, data['i'], decimal=10)
test = phot.sum_magnitudes(bulge=data['zb'],
disk=data['zd'],
agn=data['za'])
np.testing.assert_array_almost_equal(test, data['z'], decimal=10)
test = phot.sum_magnitudes(bulge=data['yb'],
disk=data['yd'],
agn=data['ya'])
np.testing.assert_array_almost_equal(test, data['y'], decimal=10)
# make sure that there were some NaNs for our catalog to deal with (but that they were not
# all NaNs
for line in [
data['u'], data['g'], data['r'], data['i'], data['z'],
data['y'], data['ub'], data['gb'], data['rb'], data['ib'],
data['zb'], data['yb'], data['ud'], data['gd'], data['rd'],
data['id'], data['zd'], data['yd'], data['ua'], data['ga'],
data['ra'], data['ia'], data['za'], data['ya']
]:
ctNans = len(np.where(np.isnan(line))[0])
self.assertGreater(ctNans, 0)
self.assertLess(ctNans, len(line))
