def test_prepare_observed():
def check(spec, obj):
if obj.uncertainty is not None:
if (type(obj.wavelength.value) == float) | (type(obj.wavelength.value) == int):
assert spec.wavelength.value == obj.wavelength.value
assert spec.flux.value == obj.flux.value
assert spec.uncertainty.value == obj.uncertainty.value
else:
for i in range(len(spec.wavelength.value)):
assert spec.wavelength.value[i] == obj.wavelength.value[i]
assert spec.flux.value[i] == obj.flux.value[i]
assert spec.uncertainty.value[i] == obj.uncertainty.value[i]
else:
if (type(obj.wavelength.value) == float) | (type(obj.wavelength.value) == int):
assert spec.wavelength.value == obj.wavelength.value
assert spec.flux.value == obj.flux.value
assert spec.uncertainty is not None
else:
for i in range(len(spec.wavelength.value)):
assert spec.wavelength.value[i] == obj.wavelength.value[i]
assert spec.flux.value[i] == obj.flux.value[i]
assert spec.uncertainty is not None
assert type(spec) == SKSpectrum1D
w = Quantity(1000, 'Angstrom')
f = Quantity(100, 'Jy')
u = Quantity(3, 'Jy')
obj = SKSpectrum1D(w, f, u)
spec = spectral.prepare_observed(obj)
check(spec, obj)
w = Quantity([1000, 1500, 2000], 'Angstrom')
f = Quantity([100, 150, 100], 'Jy')
u = Quantity([2, 5, 1], 'Jy')
obj = SKSpectrum1D(w, f, u)
spec = spectral.prepare_observed(obj)
check(spec, obj)
w = Quantity([1000, 1500, 2000], 'Angstrom')
f = Quantity([100, 150, 100], 'Jy')
obj = SKSpectrum1D(w, f, None)
spec = spectral.prepare_observed(obj)
check(spec, obj)
def _update_observed_spectrum(self, observed):
self.observed = prepare_observed(observed)
self.signal_to_noise = (self.observed.flux.value /
self.observed.uncertainty.value)
self.flux_unit = observed.flux.unit
self._rcond = (len(observed.flux.value) *
np.finfo(observed.flux.dtype).eps)
self._Vp = np.polynomial.polynomial.polyvander(
observed.wavelength.value/observed.wavelength.mean().value - 1., self.npol)
self.domain = u.Quantity([observed.wavelength.min().value,
observed.wavelength.max().value])
self.window = self.domain/observed.wavelength.mean().value - 1.
def _update_observed_spectrum(self, observed):
self.observed = prepare_observed(observed)
self.signal_to_noise = (self.observed.flux.value /
self.observed.uncertainty.value)
self.flux_unit = observed.flux.unit
self._rcond = (len(observed.flux.value) *
np.finfo(observed.flux.dtype).eps)
self._Vp = np.polynomial.polynomial.polyvander(
observed.wavelength.value / observed.wavelength.mean().value - 1.,
self.npol)
self.domain = u.Quantity(
[observed.wavelength.min().value,
observed.wavelength.max().value])
self.window = self.domain / observed.wavelength.mean().value - 1.
def _update_observed_spectrum(self, observed):
self.observed = prepare_observed(observed)
def _update_observed_spectrum(self, observed):
self.observed = prepare_observed(observed)
