FluxPointsDataset

class gammapy.spectrum.FluxPointsDataset(model, data, mask=None, likelihood='chi2')

Bases: gammapy.utils.fitting.Dataset

Fit a set of flux points with a parametric model.

Parameters:

model : SpectralModel

Spectral model

data : FluxPoints

Flux points.

mask : numpy.ndarray

Mask to apply to the likelihood.

likelihood : {“chi2”, “chi2assym”}

Likelihood function to use for the fit.

Examples

Load flux points from file and fit with a power-law model:

from astropy import units as u
from gammapy.spectrum import FluxPoints, FluxPointsDataset
form gammapy.utils.fitting import Fit
from gammapy.spectrum.models import PowerLaw

filename = '$GAMMAPY_DATA/tests/spectrum/flux_points/diff_flux_points.fits'
flux_points = FluxPoints.read(filename)

model = PowerLaw()

dataset = FluxPointsDataset(model, flux_points)
fit = Fit(dataset)
result = fit.run()
print(result)
print(result.model)

Methods Summary

data_shape()	Shape of the flux points data
flux_pred()	Compute predicted flux.
likelihood(parameters[, mask])	Total likelihood given the current model parameters.
likelihood_per_bin()	Likelihood per bin given the current model parameters

Methods Documentation

data_shape()

Shape of the flux points data

flux_pred()

Compute predicted flux.

likelihood(parameters, mask=None)

Total likelihood given the current model parameters.

Parameters:

mask : ndarray

Mask to be combined with the dataset mask.

likelihood_per_bin()

Likelihood per bin given the current model parameters