def setUp(self):
# Create a typical photometric data product.
# This product is a combination of imager and LRS, which should
# exercise the flexibility of the data model.
pixar_a2 = 0.136
self.phot_table = \
[('F560W', 'GENERIC', 2.41, 0.26),
('F770W', 'GENERIC', 1.32, 0.013),
('F1000W', 'GENERIC', 1.76, 0.12),
('F1130W', 'GENERIC', 5.76, 0.43),
('F1280W', 'GENERIC', 2.11, 0.16),
('F1500W', 'GENERIC', 1.84, 0.01),
('F1800W', 'GENERIC', 2.68, 0.23),
('F2100W', 'GENERIC', 2.04, 0.15),
('F2550W', 'GENERIC', 4.25, 0.4),
('F2550WR','GENERIC', 4.60, 0.24),
('F1065C', 'GENERIC', 1.37, 0.1),
('F1140C', 'GENERIC', 1.43, 0.11),
('F1550C', 'GENERIC', 1.81, 0.13),
('F2300C', 'GENERIC', 3.65, 0.23),
]
self.dataproduct = MiriPhotometricModel(phot_table=self.phot_table,
pixar_a2=pixar_a2)
self.testfile = "MiriPhotometric_test.fits"
def setUp(self):
# Create a typical photometric data product.
# This product is a combination of imager and LRS, which should
# exercise the flexibility of the data model.
pixar_a2 = 0.136
wavelength = []
relresponse = []
relresperror = []
resp = 0
nelm = 0
for ii in range(300):
wav = float(ii) / 12.0
resp = (resp + 1) % 30
r10 = 0.1 + resp / 35.0
wavelength.append(wav)
relresponse.append(r10)
relresperror.append(0.01)
nelm += 1
for ii in range(300, MAX_NLEM):
wavelength.append(0.0)
relresponse.append(0.0)
relresperror.append(0.0)
self.phot_table = \
[('F560W', 'GENERIC', 2.41, 0.26, 0, wavelength, relresponse, relresperror),
('F770W', 'GENERIC', 1.32, 0.013, 0, wavelength, relresponse, relresperror),
('F1000W', 'GENERIC', 1.76, 0.12, 0, wavelength, relresponse, relresperror),
('F1130W', 'GENERIC', 5.76, 0.43, 0, wavelength, relresponse, relresperror),
('F1280W', 'GENERIC', 2.11, 0.16, 0, wavelength, relresponse, relresperror),
('F1500W', 'GENERIC', 1.84, 0.01, 0, wavelength, relresponse, relresperror),
('F1800W', 'GENERIC', 2.68, 0.23, 0, wavelength, relresponse, relresperror),
('F2100W', 'GENERIC', 2.04, 0.15, 0, wavelength, relresponse, relresperror),
('F2550W', 'GENERIC', 4.25, 0.4, 0, wavelength, relresponse, relresperror),
('F2550WR','GENERIC', 4.60, 0.24, 0, wavelength, relresponse, relresperror),
('F1065C', 'GENERIC', 1.37, 0.1, 0, wavelength, relresponse, relresperror),
('F1140C', 'GENERIC', 1.43, 0.11, 0, wavelength, relresponse, relresperror),
('F1550C', 'GENERIC', 1.81, 0.13, 0, wavelength, relresponse, relresperror),
('F2300C', 'GENERIC', 3.65, 0.23, 0, wavelength, relresponse, relresperror),
('P750L', 'FULL', 1.0, 0.0, nelm, wavelength, relresponse, relresperror),
('P750L', 'SLITLESSPRISM', 0.9, 0.0, nelm, wavelength, relresponse, relresperror)
]
self.dataproduct = MiriPhotometricModel(phot_table=self.phot_table,
pixar_a2=pixar_a2)
self.testfile = "MiriPhotometric_test.fits"
def test_creation(self):
# Check that the field names in the class variable are the same
# as the ones declared in the schema.
class_names = list(MiriPhotometricModel.fieldnames)
schema_names = list(self.dataproduct.get_field_names('phot_table'))
self.assertEqual(class_names, schema_names,
"'fieldnames' class variable does not match schema")
# It must be possible to create an empty data product and fill
# in its contents later. This will generate a warning.
with warnings.catch_warnings():
warnings.simplefilter("ignore")
nulldp = MiriPhotometricModel()
descr1 = str(nulldp)
self.assertIsNotNone(descr1)
nulldp.phot_table = self.phot_table
self.assertIsNotNone(nulldp.phot_table)
descr2 = str(nulldp)
self.assertIsNotNone(descr2)
del nulldp, descr1, descr2
def test_fitsio(self):
# Suppress metadata warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
# Check that the data product can be written to a FITS
# file and read back again without changing the data.
self.dataproduct.save(self.testfile, overwrite=True)
with MiriPhotometricModel(self.testfile) as readback:
self.assertIsNotNone(readback.phot_table)
self.assertEqual(len(self.dataproduct.phot_table),
len(readback.phot_table))
original = np.asarray(self.dataproduct.phot_table)
duplicate = np.asarray(readback.phot_table)
assert_recarray_equal(original, duplicate)
del readback
class TestMiriPhotometricModel(unittest.TestCase):
# Test the MiriImagingFluxconversionModel class.
def setUp(self):
# Create a typical photometric data product.
# This product is a combination of imager and LRS, which should
# exercise the flexibility of the data model.
pixar_a2 = 0.136
wavelength = []
relresponse = []
relresperror = []
resp = 0
nelm = 0
for ii in range(300):
wav = float(ii) / 12.0
resp = (resp + 1) % 30
r10 = 0.1 + resp / 35.0
wavelength.append(wav)
relresponse.append(r10)
relresperror.append(0.01)
nelm += 1
for ii in range(300, MAX_NLEM):
wavelength.append(0.0)
relresponse.append(0.0)
relresperror.append(0.0)
self.phot_table = \
[('F560W', 'GENERIC', 2.41, 0.26, 0, wavelength, relresponse, relresperror),
('F770W', 'GENERIC', 1.32, 0.013, 0, wavelength, relresponse, relresperror),
('F1000W', 'GENERIC', 1.76, 0.12, 0, wavelength, relresponse, relresperror),
('F1130W', 'GENERIC', 5.76, 0.43, 0, wavelength, relresponse, relresperror),
('F1280W', 'GENERIC', 2.11, 0.16, 0, wavelength, relresponse, relresperror),
('F1500W', 'GENERIC', 1.84, 0.01, 0, wavelength, relresponse, relresperror),
('F1800W', 'GENERIC', 2.68, 0.23, 0, wavelength, relresponse, relresperror),
('F2100W', 'GENERIC', 2.04, 0.15, 0, wavelength, relresponse, relresperror),
('F2550W', 'GENERIC', 4.25, 0.4, 0, wavelength, relresponse, relresperror),
('F2550WR','GENERIC', 4.60, 0.24, 0, wavelength, relresponse, relresperror),
('F1065C', 'GENERIC', 1.37, 0.1, 0, wavelength, relresponse, relresperror),
('F1140C', 'GENERIC', 1.43, 0.11, 0, wavelength, relresponse, relresperror),
('F1550C', 'GENERIC', 1.81, 0.13, 0, wavelength, relresponse, relresperror),
('F2300C', 'GENERIC', 3.65, 0.23, 0, wavelength, relresponse, relresperror),
('P750L', 'FULL', 1.0, 0.0, nelm, wavelength, relresponse, relresperror),
('P750L', 'SLITLESSPRISM', 0.9, 0.0, nelm, wavelength, relresponse, relresperror)
]
self.dataproduct = MiriPhotometricModel(phot_table=self.phot_table,
pixar_a2=pixar_a2)
self.testfile = "MiriPhotometric_test.fits"
def tearDown(self):
# Tidy up
del self.dataproduct
del self.phot_table
# Remove temporary file, if able to.
if os.path.isfile(self.testfile):
try:
os.remove(self.testfile)
except Exception as e:
strg = "Could not remove temporary file, " + self.testfile + \
"\n " + str(e)
warnings.warn(strg)
def test_referencefile(self):
# Check that the data product contains the standard
# reference file metadata.
type1 = self.dataproduct.meta.model_type
type2 = self.dataproduct.meta.reftype
self.assertIsNotNone(type1)
self.assertIsNotNone(type2)
pedigree = self.dataproduct.meta.pedigree
self.assertIsNotNone(pedigree)
def test_creation(self):
# Check that the field names in the class variable are the same
# as the ones declared in the schema.
class_names = list(MiriPhotometricModel.fieldnames)
schema_names = list(self.dataproduct.get_field_names('phot_table'))
self.assertEqual(class_names, schema_names,
"'fieldnames' class variable does not match schema")
# It must be possible to create an empty data product and fill
# in its contents later. This will generate a warning.
with warnings.catch_warnings():
warnings.simplefilter("ignore")
nulldp = MiriPhotometricModel()
descr1 = str(nulldp)
self.assertIsNotNone(descr1)
nulldp.phot_table = self.phot_table
self.assertIsNotNone(nulldp.phot_table)
descr2 = str(nulldp)
self.assertIsNotNone(descr2)
del nulldp, descr1, descr2
def test_copy(self):
# Test that a copy can be made of the data product.
# This will generate a warning.
with warnings.catch_warnings():
warnings.simplefilter("ignore")
datacopy = self.dataproduct.copy()
self.assertIsNotNone(datacopy.phot_table)
self.assertEqual(len(self.dataproduct.phot_table),
len(datacopy.phot_table))
table1 = np.asarray(self.dataproduct.phot_table)
table2 = np.asarray(datacopy.phot_table)
assert_recarray_equal(table1, table2)
del datacopy
def test_fitsio(self):
# Suppress metadata warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
# Check that the data product can be written to a FITS
# file and read back again without changing the data.
self.dataproduct.save(self.testfile, overwrite=True)
with MiriPhotometricModel(self.testfile) as readback:
self.assertEqual(self.dataproduct.meta.reftype,
readback.meta.reftype)
self.assertEqual(self.dataproduct.meta.model_type,
readback.meta.model_type)
self.assertIsNotNone(readback.phot_table)
self.assertEqual(len(self.dataproduct.phot_table),
len(readback.phot_table))
original = np.asarray(self.dataproduct.phot_table)
duplicate = np.asarray(readback.phot_table)
assert_recarray_equal(original, duplicate)
del readback
def test_description(self):
# Test that the querying and description functions work.
# For the test to pass these need to run without error
# and generate non-null strings.
descr = str(self.dataproduct)
self.assertIsNotNone(descr)
del descr
descr = repr(self.dataproduct)
self.assertIsNotNone(descr)
del descr
# Attempt to access the flux table through attributes.
descr = str(self.dataproduct.phot_table)
self.assertIsNotNone(descr)
del descr