Spectrum1D¶

class specutils.Spectrum1D(flux=None, spectral_axis=None, wcs=None, velocity_convention=None, rest_value=None, *args, **kwargs)[source]¶

Bases: specutils.spectra.spectrum_mixin.OneDSpectrumMixin, astropy.nddata.NDDataRef

Spectrum container for 1D spectral data.

Parameters

fluxastropy.units.Quantity or astropy.nddata.NDData`-like: The flux data for this spectrum.
spectral_axisastropy.units.Quantity: Dispersion information with the same shape as the last (or only) dimension of flux.
wcsastropy.wcs.WCS or gwcs.wcs.WCS: WCS information object.
velocity_convention{“doppler_relativistic”, “doppler_optical”, “doppler_radio”}: Convention used for velocity conversions.
rest_valueQuantity: Any quantity supported by the standard spectral equivalencies (wavelength, energy, frequency, wave number). Describes the rest value of the spectral axis for use with velocity conversions.
uncertaintyNDUncertainty: Contains uncertainty information along with propagation rules for spectrum arithmetic. Can take a unit, but if none is given, will use the unit defined in the flux.
metadict: Arbitrary container for any user-specific information to be carried around with the spectrum container object.

Attributes Summary

`bin_edges`
`energy`	The energy of the spectral axis as a `Quantity` in units of eV.
`frequency`	The frequency as a `Quantity` in units of GHz
`photon_flux`	The flux density of photons as a `Quantity`, in units of photons per cm^2 per second per spectral_axis unit
`shape`
`wavelength`	The wavelength as a `Quantity` in units of Angstroms

Methods Summary

spectral_resolution(self, true_dispersion, …)

Evaluate the probability distribution of the spectral resolution.

Attributes Documentation

bin_edges¶

energy¶: The energy of the spectral axis as a Quantity in units of eV.

frequency¶: The frequency as a Quantity in units of GHz

photon_flux¶: The flux density of photons as a Quantity, in units of photons per cm^2 per second per spectral_axis unit

shape¶

wavelength¶: The wavelength as a Quantity in units of Angstroms

Methods Documentation

spectral_resolution(self, true_dispersion, delta_dispersion, axis=- 1)[source]¶

Evaluate the probability distribution of the spectral resolution.

Parameters

true_dispersionQuantity: True value(s) of dispersion for which the resolution should be evaluated.
delta_dispersionQuantity: Array of (observed - true) dispersion bin edges to integrate the resolution probability density over.
axisint: Which axis of delta_dispersion contains the strictly increasing dispersion values to interpret as bin edges. The dimension of delta_dispersion along this axis must be at least two.

Returns

numpy array: Array of dimensionless probabilities calculated as the integral of P(observed | true) over each bin in (observed - true). The output shape is the result of broadcasting the input shapes.

Examples

To tabulate a binned resolution function at 6000A covering +/-10A in 0.2A steps:

>>> R = spectrum1d.spectral_resolution(
...     6000 * u.Angstrom, np.linspace(-10, 10, 51) * u.Angstrom)
>>> assert R.shape == (50,)
>>> assert np.allclose(R.sum(), 1.)

To build a sparse resolution matrix for true wavelengths 4000-8000A in 0.1A steps:

>>> R = spectrum1d.spectral_resolution(
...     np.linspace(4000, 8000, 40001)[:, np.newaxis] * u.Angstrom,
...     np.linspace(-10, +10, 201) * u.Angstrom)
>>> assert R.shape == (40000, 200)
>>> assert np.allclose(R.sum(axis=1), 1.)

Navigation

Spectrum1D¶