threeML.plugins.FermipyLike module

class threeML.plugins.FermipyLike.FermipyLike(*args, **kwargs)

Bases: PluginPrototype

Plugin for the data of the Fermi Large Area Telescope, based on fermipy (http://fermipy.readthedocs.io/)

property configuration

Returns the loaded configuration

Returns:

a dictionary containing the active configuration

display_model(data_color: str = 'k', model_cmap: str = 'Set1', model_color: str | None = None, total_model_color: str = 'k', background_color: str = 'b', show_data: bool = True, primary_sources: str | List[str] | None = None, show_background_sources: bool = True, shade_fixed_sources: bool = True, shade_secondary_source: bool = False, fixed_sources_color: str = 'grey', secondary_sources_color: str = 'k', show_residuals: bool = True, ratio_residuals: bool = False, show_legend: bool = True, model_label: str | None = None, model_kwargs: Dict[str, Any] | None = None, data_kwargs: Dict[str, Any] | None = None, background_kwargs: Dict[str, Any] | None = None, **kwargs) → ResidualPlot

Plot the current model with or without the data and the residuals. Multiple models can be plotted by supplying a previous axis to ‘model_subplot’.

Example usage:

fig = data.display_model()

fig2 = data2.display_model(model_subplot=fig.axes)

Parameters:

• data_color – the color of the data

• model_color – the color of the model

• show_data – (bool) show_the data with the model

• show_residuals – (bool) shoe the residuals

• ratio_residuals – (bool) use model ratio instead of residuals

• show_legend – (bool) show legend

• model_label – (optional) the label to use for the model default is plugin name

• model_kwargs – plotting kwargs affecting the plotting of the model

• data_kwargs – plotting kwargs affecting the plotting of the data and residuls

• background_kwargs – plotting kwargs affecting the plotting of the background

Returns:

static get_basic_config(evfile, scfile, ra, dec, emin=100.0, emax=100000.0, zmax=100.0, evclass=128, evtype=3, filter='DATA_QUAL>0 && LAT_CONFIG==1', fermipy_verbosity=2, fermitools_chatter=2)

get_log_like()

Return the value of the log-likelihood with the current values for the parameters stored in the ModelManager instance

get_number_of_data_points()

Return the number of spatial/energy bins

Returns:

number of bins

get_observation_duration()

property gta

inner_fit()

This is used for the profile likelihood. Keeping fixed all parameters in the LikelihoodModel, this method minimize the logLike over the remaining nuisance parameters, i.e., the parameters belonging only to the model for this particular detector. If there are no nuisance parameters, simply return the logLike value.

set_inner_minimization(flag: bool) → None

Turn on the minimization of the internal Fermi parameters

Parameters:

flag (bool) – turing on and off the minimization of the Fermipy internal parameters

Returns:

set_model(likelihood_model_instance)

Set the model to be used in the joint minimization. Must be a LikelihoodModel instance.

set_nuisance_parameter_value(paramName, value)