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FluxPointsDataset

class gammapy.spectrum.FluxPointsDataset(model, data, mask_fit=None, likelihood='chi2', mask_safe=None)[source]

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_fit : numpy.ndarray

Mask to apply to the likelihood for fitting.

likelihood : {“chi2”, “chi2assym”}

Likelihood function to use for the fit.

mask_safe : numpy.ndarray

Mask defining the safe data range.

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
from 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.parameters.to_table())

Attributes Summary

mask Combined fit and safe mask

Methods Summary

copy(self) A deep copy.
data_shape(self) Shape of the flux points data
flux_pred(self) Compute predicted flux.
likelihood(self) Total likelihood given the current model parameters.
likelihood_per_bin(self) Likelihood per bin given the current model parameters
peek(self, \*\*kwargs) Plot flux points, best fit model and residuals.
plot_residuals(self[, ax]) Plot flux point residuals.
plot_spectrum(self[, ax, fp_kwargs, …]) Plot spectrum including flux points and model.
residuals(self) Compute flux point residuals

Attributes Documentation

mask

Combined fit and safe mask

Methods Documentation

copy(self)

A deep copy.

data_shape(self)[source]

Shape of the flux points data

flux_pred(self)[source]

Compute predicted flux.

likelihood(self)

Total likelihood given the current model parameters.

likelihood_per_bin(self)[source]

Likelihood per bin given the current model parameters

peek(self, **kwargs)[source]

Plot flux points, best fit model and residuals.

plot_residuals(self, ax=None, **kwargs)[source]

Plot flux point residuals.

Parameters:
ax : Axes

Axes object.

**kwargs : dict

Keyword arguments passed to errorbar.

Returns:
ax : Axes

Axes object.

plot_spectrum(self, ax=None, fp_kwargs=None, model_kwargs=None)[source]

Plot spectrum including flux points and model.

Parameters:
ax : Axes

Axes object.

fp_kwargs : dict

Keyword arguments passed to FluxPoints.plot.

model_kwargs : dict

Keywords passed to SpectralModel.plot and SpectralModel.plot_error

Returns:
ax : Axes

Axes object.

residuals(self)[source]

Compute flux point residuals

Defined as (data - model) / model.

Returns:
residuals : ndarray

Flux point residuals