SpectrumFit

class gammapy.spectrum.SpectrumFit(obs_list, model, stat='wstat', forward_folded=True, fit_range=None, background_model=None, method='sherpa', err_method='sherpa')

Bases: object

Orchestrate a 1D counts spectrum fit.

For usage examples see Spectral Fitting

Parameters:

obs_list : SpectrumObservationList, SpectrumObservation

Observation(s) to fit

model : SpectralModel

Source model. Should return counts if forward_folded is False and a flux otherwise

stat : {‘wstat’, ‘cash’}

Fit statistic

forward_folded : bool, default: True

Fold model with the IRFs given in obs_list

fit_range : tuple of Quantity

Fit range, will be convolved with observation thresholds. If you want to control which bins are taken into account in the fit for each observations, use qualitiy()

background_model : SpectralModel, optional

Background model to be used in cash fits

method : {‘sherpa’}

Optimization backend for the fit

err_method : {‘sherpa’}

Optimization backend for error estimation

Attributes Summary

bins_in_fit_range	Bins participating in the fit for each observation.
fit_range	Fit range.
predicted_counts	Current value of predicted counts.
statval	Current value of statval.
total_stat	Statistic summed over all bins and all observations.
true_fit_range	True fit range for each observation.

Methods Summary

calc_statval()	Calc statistic for all observations.
est_errors()	Estimate parameter errors.
fit()	Run the fit.
likelihood_1d(model, parname, parvals)	Compute likelihood profile.
plot_likelihood_1d([ax])	Plot 1-dim likelihood profile.
predict_counts()	Predict counts for all observations.
run([outdir])	Run all steps and write result to disk.

Attributes Documentation

bins_in_fit_range

Bins participating in the fit for each observation.

fit_range

Fit range.

predicted_counts

Current value of predicted counts.

For each observation a tuple to counts for the on and off region is returned.

statval

Current value of statval.

For each observation the statval per bin is returned.

total_stat

Statistic summed over all bins and all observations.

This is what is used for the fit.

true_fit_range

True fit range for each observation.

True fit range is the fit range set in the SpectrumFit with observation threshold taken into account.

Methods Documentation

calc_statval()

Calc statistic for all observations.

The result is stored as attribute statval, bin outside the fit range are set to 0.

est_errors()

Estimate parameter errors.

fit()

Run the fit.

likelihood_1d(model, parname, parvals)

Compute likelihood profile.

Parameters:

model : SpectralModel

Model to draw likelihood profile for

parname : str

Parameter to calculate profile for

parvals : Quantity

Parameter values

plot_likelihood_1d(ax=None, **kwargs)

Plot 1-dim likelihood profile.

See likelihood_1d()

predict_counts()

Predict counts for all observations.

The result is stored as predicted_counts attribute.

run(outdir=None)

Run all steps and write result to disk.

Parameters:

outdir : Path, str

directory to write results files to (if given)