class TestDataSerializer(TestCase):
def setUp(self):
self.serializer = SpectrumSerializer()
def test_serialize_spectrum(self):
flux = np.arange(1, 200) * units.Jy
wavelength = np.arange(1, 200) * units.Angstrom
spectrum = Spectrum1D(spectral_axis=wavelength, flux=flux)
serialized = self.serializer.serialize(spectrum)
self.assertTrue(isinstance(serialized, str))
serialized = json.loads(serialized)
self.assertTrue(serialized['photon_flux'])
self.assertTrue(serialized['photon_flux_units'])
self.assertTrue(serialized['wavelength'])
self.assertTrue(serialized['wavelength_units'])
def test_serialize_spectrum_invalid(self):
with self.assertRaises(Exception):
self.serializer.serialize({'flux': [1, 2], 'wavelength': [1, 2]})
def test_deserialize_spectrum(self):
serialized_spectrum = json.dumps({
'photon_flux': [1, 2],
'photon_flux_units': 'ph / (Angstrom cm2 s)',
'wavelength': [1, 2],
'wavelength_units': 'Angstrom'
})
deserialized = self.serializer.deserialize(serialized_spectrum)
self.assertTrue(type(deserialized) is Spectrum1D)
self.assertEqual(deserialized.flux.mean().value, 1.5)
self.assertEqual(deserialized.wavelength.mean().value, 1.5)
def test_deserialize_spectrum_invalid(self):
with self.assertRaises(Exception):
self.serializer.deserialize(json.dumps({'invalid_key': 'value'}))
def photon_spectrum_to_energy_spectrum(apps, schema_editor):
reduced_datum = apps.get_model('tom_dataproducts', 'ReducedDatum')
spectrum_serializer = SpectrumSerializer()
for row in reduced_datum.objects.filter(data_type='spectroscopy'):
# In order to avoid a KeyError on already-corrected data or data that has no need to be corrected, we only
# perform the spectroscopy correction on values that have photon_flux/photon_flux_units
if all(k in row.value.keys() for k in ['photon_flux', 'photon_flux_units', 'wavelength', 'wavelength_units']):
photon_counts = Quantity(value=row.value['photon_flux'], unit=row.value['photon_flux_units'])
wavelength = Quantity(value=row.value['wavelength'], unit=row.value['wavelength_units'])
photon_spectrum = Spectrum1D(flux=photon_counts, spectral_axis=wavelength)
energy_spectrum = photon_spectrum.flux * (photon_spectrum.energy / photon)
energy_spectrum_object = Spectrum1D(
spectral_axis=wavelength,
flux=energy_spectrum.to('erg / (s cm2 AA)', spectral_density(wavelength)))
row.value = spectrum_serializer.serialize(energy_spectrum_object)
row.save()
def photon_spectrum_to_energy_spectrum(apps, schema_editor):
reduced_datum = apps.get_model('tom_dataproducts', 'ReducedDatum')
spectrum_serializer = SpectrumSerializer()
for row in reduced_datum.objects.filter(data_type='spectroscopy'):
photon_counts = Quantity(value=row.value['photon_flux'],
unit=row.value['photon_flux_units'])
wavelength = Quantity(value=row.value['wavelength'],
unit=row.value['wavelength_units'])
photon_spectrum = Spectrum1D(flux=photon_counts,
spectral_axis=wavelength)
energy_spectrum = photon_spectrum.flux * (photon_spectrum.energy /
photon)
energy_spectrum_object = Spectrum1D(spectral_axis=wavelength,
flux=energy_spectrum.to(
'erg / (s cm2 AA)',
spectral_density(wavelength)))
row.value = spectrum_serializer.serialize(energy_spectrum_object)
row.save()