EnergyDependentTablePSF¶

class gammapy.irf.EnergyDependentTablePSF(energy, rad, exposure=None, psf_value=None, interp_kwargs=None)[source]¶

Energy-dependent radially-symmetric table PSF (gtpsf format).

TODO: add references and explanations.

Parameters:	energy : `Quantity` Energy (1-dim) rad : `Quantity` with angle units Offset angle wrt source position (1-dim) exposure : `Quantity` Exposure (1-dim) psf_value : `Quantity` PSF (2-dim with axes: psf[energy_index, offset_index] interp_kwargs : dict Interpolation keyword arguments pass to `ScaledRegularGridInterpolator`.

Methods Summary

`containment`(energy, rad_max)	Compute containment of the PSF.
`containment_radius`(energy[, fraction])	Containment radius.
`evaluate`([energy, rad, method])	Evaluate the PSF at a given energy and offset
`from_fits`(hdu_list)	Create `EnergyDependentTablePSF` from `gtpsf` format HDU list.
`info`()	Print basic info
`plot_containment_vs_energy`([ax, fractions])	Plot containment versus energy.
`plot_exposure_vs_energy`()	Plot exposure versus energy.
`plot_psf_vs_rad`([energies, ax])	Plot PSF vs radius.
`read`(filename)	Create `EnergyDependentTablePSF` from `gtpsf`-format FITS file.
`stack`(psf)	Stack two EnergyDependentTablePSF objects.s
`table_psf_at_energy`(energy[, method])	Create `TablePSF` at one given energy.
`table_psf_in_energy_band`(energy_band[, …])	Average PSF in a given energy band.
`to_fits`()	Convert to FITS HDU list format.
`write`(args, *kwargs)	Write to FITS file.

Methods Documentation

containment(energy, rad_max)[source]¶

Compute containment of the PSF.

Parameters:	energy : `Quantity` Energy rad_max : `Angle` Maximum offset angle.
Returns:	fraction : array_like Containment fraction (in range 0 .. 1)

containment_radius(energy, fraction=0.68)[source]¶

Containment radius.

Parameters:	energy : `Quantity` Energy fraction : float Containment fraction.
Returns:	rad : `Quantity` Containment radius in deg

evaluate(energy=None, rad=None, method='linear')[source]¶

Evaluate the PSF at a given energy and offset

Parameters:	energy : `Quantity` Energy value rad : `Angle` Offset wrt source position method : {“linear”, “nearest”} Linear or nearest neighbour interpolation.
Returns:	values : `Quantity` Interpolated value

classmethod from_fits(hdu_list)[source]¶

Create EnergyDependentTablePSF from gtpsf format HDU list.

Parameters:	hdu_list : `HDUList` HDU list with `THETA` and `PSF` extensions.

plot_containment_vs_energy(ax=None, fractions=[0.68, 0.8, 0.95], **kwargs)[source]¶: Plot containment versus energy.

plot_psf_vs_rad(energies=None, ax=None, **kwargs)[source]¶

Plot PSF vs radius.

Parameters:	energy : `Quantity` Energies where to plot the PSF. **kwargs : dict Keyword arguments pass to `plot`.

classmethod read(filename)[source]¶

Create EnergyDependentTablePSF from gtpsf-format FITS file.

Parameters:	filename : str File name

stack(psf)[source]¶

Stack two EnergyDependentTablePSF objects.s

Parameters:	psf : `EnergyDependentTablePSF` PSF to stack.
Returns:	stacked_psf : `EnergyDependentTablePSF` Stacked PSF.

table_psf_at_energy(energy, method='linear', **kwargs)[source]¶

Create TablePSF at one given energy.

Parameters:	energy : `Quantity` Energy method : {“linear”, “nearest”} Linear or nearest neighbour interpolation.
Returns:	psf : `TablePSF` Table PSF

table_psf_in_energy_band(energy_band, spectrum=None, n_bins=11, **kwargs)[source]¶

Average PSF in a given energy band.

Expected counts in sub energy bands given the given exposure and spectrum are used as weights.

Parameters:	energy_band : `Quantity` Energy band spectrum : `SpectralModel` Spectral model used for weighting the PSF. Default is a power law with index=2. n_bins : int Number of energy points in the energy band, used to compute the weigthed PSF.
Returns:	psf : `TablePSF` Table PSF

to_fits()[source]¶

Convert to FITS HDU list format.

Returns:	hdu_list : `HDUList` PSF in HDU list format.

write(*args, **kwargs)[source]¶

Write to FITS file.

Calls writeto, forwarding all arguments.