threeML.config.config_structure module
- class threeML.config.config_structure.Config(logging: threeML.config.config_structure.Logging = Logging(path='~/.threeml/log', developer='off', usr='on', console='on', level=<LoggingLevel.INFO: 20>, startup_warnings='on'), parallel: threeML.config.config_structure.Parallel = Parallel(profile_name='default', use_parallel=False, use_joblib=False), interface: threeML.config.config_structure.Interface = Interface(progress_bars='on', multi_progress_color='on', multi_progress_cmap='viridis', progress_bar_color='#9C04FF'), plugins: threeML.config.plugin_structure.Plugins = Plugins(ogip=OGIP(fit_plot=BinnedSpectrumPlot(data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, n_colors=5, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, show_background=False, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None), data_plot=DataHistPlot(counts_color='#500472', background_color='#79cbb8', warn_channels_color='#C79BFE', bad_channels_color='#FE3131', masked_channels_color='#566573'), response_cmap=<MPLCmap.viridis: 'viridis'>, response_zero_color='k'), photo=Photo(fit_plot=BinnedSpectrumPlot(data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, n_colors=5, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, show_background=False, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None)), fermipy=Fermipy(fit_plot=FermiSpectrumPlot(total_model_color='k', show_background_sources=True, shade_fixed_sources=True, shade_secondary_sources=False, fixed_sources_color='grey', secondary_sources_color='k', data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None))), time_series: threeML.config.plugin_structure.TimeSeries = TimeSeries(light_curve_color='#05716c', selection_color='#1fbfb8', background_color='#C0392B', background_selection_color='#E74C3C', fit=TimeSeriesFit(fit_poly=True, unbinned=False, bayes=False)), mle: threeML.config.fitting_structure.MLEDefault = MLEDefault(default_minimizer=<Optimizer.minuit: 'minuit'>, default_minimizer_algorithm=None, default_minimizer_callback=None, contour_cmap=<MPLCmap.Pastel1: 'Pastel1'>, contour_background='white', contour_level_1='#ffa372', contour_level_2='#ed6663', contour_level_3='#0f4c81', profile_color='k', profile_level_1='#ffa372', profile_level_2='#ed6663', profile_level_3='#0f4c81'), bayesian: threeML.config.fitting_structure.BayesianDefault = BayesianDefault(use_median_fit=False, default_sampler=<Sampler.emcee: 'emcee'>, emcee_setup={'n_burnin': None, 'n_iterations': 500, 'n_walkers': 50, 'seed': 5123}, multinest_setup={'n_live_points': 400, 'chain_name': 'chains/fit-', 'resume': False, 'importance_nested_sampling': False, 'auto_clean': False}, ultranest_setup={'min_num_live_points': 400, 'dlogz': 0.5, 'dKL': 0.5, 'frac_remain': 0.01, 'Lepsilon': 0.001, 'min_ess': 400, 'update_interval_volume_fraction': 0.8, 'cluster_num_live_points': 40, 'use_mlfriends': True, 'resume': 'overwrite'}, zeus_setup={'n_burnin': None, 'n_iterations': 500, 'n_walkers': 50, 'seed': 5123}, dynesty_nested_setup={'n_live_points': 400, 'maxiter': None, 'maxcall': None, 'dlogz': None, 'logl_max': inf, 'n_effective': None, 'add_live': True, 'print_func': None, 'save_bounds': True, 'bound': 'multi', 'wrapped_params': None, 'sample': 'auto', 'periodic': None, 'reflective': None, 'update_interval': None, 'first_update': None, 'npdim': None, 'rstate': None, 'use_pool': None, 'live_points': None, 'logl_args': None, 'logl_kwargs': None, 'ptform_args': None, 'ptform_kwargs': None, 'gradient': None, 'grad_args': None, 'grad_kwargs': None, 'compute_jac': False, 'enlarge': None, 'bootstrap': 0, 'vol_dec': 0.5, 'vol_check': 2.0, 'walks': 25, 'facc': 0.5, 'slices': 5, 'fmove': 0.9, 'max_move': 100, 'update_func': None}, dynesty_dynmaic_setup={'nlive_init': 500, 'maxiter_init': None, 'maxcall_init': None, 'dlogz_init': 0.01, 'logl_max_init': inf, 'n_effective_init': inf, 'nlive_batch': 500, 'wt_function': None, 'wt_kwargs': None, 'maxiter_batch': None, 'maxcall_batch': None, 'maxiter': None, 'maxcall': None, 'maxbatch': None, 'n_effective': inf, 'stop_function': None, 'stop_kwargs': None, 'use_stop': True, 'save_bounds': True, 'print_func': None, 'live_points': None, 'bound': 'multi', 'wrapped_params': None, 'sample': 'auto', 'periodic': None, 'reflective': None, 'update_interval': None, 'first_update': None, 'npdim': None, 'rstate': None, 'use_pool': None, 'logl_args': None, 'logl_kwargs': None, 'ptform_args': None, 'ptform_kwargs': None, 'gradient': None, 'grad_args': None, 'grad_kwargs': None, 'compute_jac': False, 'enlarge': None, 'bootstrap': 0, 'vol_dec': 0.5, 'vol_check': 2.0, 'walks': 25, 'facc': 0.5, 'slices': 5, 'fmove': 0.9, 'max_move': 100, 'update_func': None}, corner_style=CornerStyle(show_titles=True, smooth=0.9, title_fmt='.2g', bins=25, quantiles=[0.16, 0.5, 0.84], fill_contours=True, cmap=<MPLCmap.viridis: 'viridis'>, extremes='white', contourf_kwargs={'colors': None, 'extend': 'both'}, levels=[0.99, 0.865, 0.393])), plotting: threeML.config.plotting_structure.GenericPlotting = GenericPlotting(use_threeml_style=True, mplstyle='threeml.mplstyle', residual_plot=ResidualPlot(linewidth=1, marker='.', size=3, legend_font_size=6.94)), model_plot: threeML.config.plotting_structure.ModelPlotting = ModelPlotting(point_source_plot=PointSourcePlot(fit_cmap=<MPLCmap.Set1: 'Set1'>, contour_cmap=<MPLCmap.Set1: 'Set1'>, bayes_cmap=<MPLCmap.Set1: 'Set1'>, plot_style=PlotStyle(linestyle='-', linewidth=1.7), contour_style=ContourStyle(alpha=0.4), show_legend=True, legend_style=LegendStyle(loc='best', fancybox=True, shadow=True), flux_unit='1/(keV s cm2)', emin=10.0, emax=10000.0, num_ene=100, ene_unit='keV')), point_source: threeML.config.point_source_structure.PointSourceDefaults = PointSourceDefaults(integrate_flux_method=<IntegrateMethod.trapz: 0>, max_number_samples=5000), LAT: threeML.config.catalog_structure.PublicDataServer = PublicDataServer(public_ftp_location='ftp://heasarc.nasa.gov/fermi/data', public_http_location='https://heasarc.gsfc.nasa.gov/FTP/fermi/data/lat', query_form='https://fermi.gsfc.nasa.gov/cgi-bin/ssc/LAT/LATDataQuery.cgi'), GBM: threeML.config.catalog_structure.PublicDataServer = PublicDataServer(public_ftp_location='ftp://heasarc.nasa.gov/fermi/data', public_http_location='https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm', query_form=None), catalogs: threeML.config.catalog_structure.Catalogs = Catalogs(Fermi=InstrumentCatalog(catalogs={'LAT FGL': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermilpsc&'), 'GBM burst catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermigbrst&'), 'GBM trigger catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermigtrig&'), 'LLE catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermille&')}), Swift=InstrumentCatalog(catalogs={'Swift GRB catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=swiftgrb&')})))[source]
Bases:
object- GBM: PublicDataServer = PublicDataServer(public_ftp_location='ftp://heasarc.nasa.gov/fermi/data', public_http_location='https://heasarc.gsfc.nasa.gov/FTP/fermi/data/gbm', query_form=None)
- LAT: PublicDataServer = PublicDataServer(public_ftp_location='ftp://heasarc.nasa.gov/fermi/data', public_http_location='https://heasarc.gsfc.nasa.gov/FTP/fermi/data/lat', query_form='https://fermi.gsfc.nasa.gov/cgi-bin/ssc/LAT/LATDataQuery.cgi')
- bayesian: BayesianDefault = BayesianDefault(use_median_fit=False, default_sampler=<Sampler.emcee: 'emcee'>, emcee_setup={'n_burnin': None, 'n_iterations': 500, 'n_walkers': 50, 'seed': 5123}, multinest_setup={'n_live_points': 400, 'chain_name': 'chains/fit-', 'resume': False, 'importance_nested_sampling': False, 'auto_clean': False}, ultranest_setup={'min_num_live_points': 400, 'dlogz': 0.5, 'dKL': 0.5, 'frac_remain': 0.01, 'Lepsilon': 0.001, 'min_ess': 400, 'update_interval_volume_fraction': 0.8, 'cluster_num_live_points': 40, 'use_mlfriends': True, 'resume': 'overwrite'}, zeus_setup={'n_burnin': None, 'n_iterations': 500, 'n_walkers': 50, 'seed': 5123}, dynesty_nested_setup={'n_live_points': 400, 'maxiter': None, 'maxcall': None, 'dlogz': None, 'logl_max': inf, 'n_effective': None, 'add_live': True, 'print_func': None, 'save_bounds': True, 'bound': 'multi', 'wrapped_params': None, 'sample': 'auto', 'periodic': None, 'reflective': None, 'update_interval': None, 'first_update': None, 'npdim': None, 'rstate': None, 'use_pool': None, 'live_points': None, 'logl_args': None, 'logl_kwargs': None, 'ptform_args': None, 'ptform_kwargs': None, 'gradient': None, 'grad_args': None, 'grad_kwargs': None, 'compute_jac': False, 'enlarge': None, 'bootstrap': 0, 'vol_dec': 0.5, 'vol_check': 2.0, 'walks': 25, 'facc': 0.5, 'slices': 5, 'fmove': 0.9, 'max_move': 100, 'update_func': None}, dynesty_dynmaic_setup={'nlive_init': 500, 'maxiter_init': None, 'maxcall_init': None, 'dlogz_init': 0.01, 'logl_max_init': inf, 'n_effective_init': inf, 'nlive_batch': 500, 'wt_function': None, 'wt_kwargs': None, 'maxiter_batch': None, 'maxcall_batch': None, 'maxiter': None, 'maxcall': None, 'maxbatch': None, 'n_effective': inf, 'stop_function': None, 'stop_kwargs': None, 'use_stop': True, 'save_bounds': True, 'print_func': None, 'live_points': None, 'bound': 'multi', 'wrapped_params': None, 'sample': 'auto', 'periodic': None, 'reflective': None, 'update_interval': None, 'first_update': None, 'npdim': None, 'rstate': None, 'use_pool': None, 'logl_args': None, 'logl_kwargs': None, 'ptform_args': None, 'ptform_kwargs': None, 'gradient': None, 'grad_args': None, 'grad_kwargs': None, 'compute_jac': False, 'enlarge': None, 'bootstrap': 0, 'vol_dec': 0.5, 'vol_check': 2.0, 'walks': 25, 'facc': 0.5, 'slices': 5, 'fmove': 0.9, 'max_move': 100, 'update_func': None}, corner_style=CornerStyle(show_titles=True, smooth=0.9, title_fmt='.2g', bins=25, quantiles=[0.16, 0.5, 0.84], fill_contours=True, cmap=<MPLCmap.viridis: 'viridis'>, extremes='white', contourf_kwargs={'colors': None, 'extend': 'both'}, levels=[0.99, 0.865, 0.393]))
- catalogs: Catalogs = Catalogs(Fermi=InstrumentCatalog(catalogs={'LAT FGL': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermilpsc&'), 'GBM burst catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermigbrst&'), 'GBM trigger catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermigtrig&'), 'LLE catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=fermille&')}), Swift=InstrumentCatalog(catalogs={'Swift GRB catalog': CatalogServer(url='https://heasarc.gsfc.nasa.gov/cgi-bin/vo/cone/coneGet.pl?table=swiftgrb&')}))
- interface: Interface = Interface(progress_bars='on', multi_progress_color='on', multi_progress_cmap='viridis', progress_bar_color='#9C04FF')
- logging: Logging = Logging(path='~/.threeml/log', developer='off', usr='on', console='on', level=<LoggingLevel.INFO: 20>, startup_warnings='on')
- mle: MLEDefault = MLEDefault(default_minimizer=<Optimizer.minuit: 'minuit'>, default_minimizer_algorithm=None, default_minimizer_callback=None, contour_cmap=<MPLCmap.Pastel1: 'Pastel1'>, contour_background='white', contour_level_1='#ffa372', contour_level_2='#ed6663', contour_level_3='#0f4c81', profile_color='k', profile_level_1='#ffa372', profile_level_2='#ed6663', profile_level_3='#0f4c81')
- model_plot: ModelPlotting = ModelPlotting(point_source_plot=PointSourcePlot(fit_cmap=<MPLCmap.Set1: 'Set1'>, contour_cmap=<MPLCmap.Set1: 'Set1'>, bayes_cmap=<MPLCmap.Set1: 'Set1'>, plot_style=PlotStyle(linestyle='-', linewidth=1.7), contour_style=ContourStyle(alpha=0.4), show_legend=True, legend_style=LegendStyle(loc='best', fancybox=True, shadow=True), flux_unit='1/(keV s cm2)', emin=10.0, emax=10000.0, num_ene=100, ene_unit='keV'))
- plotting: GenericPlotting = GenericPlotting(use_threeml_style=True, mplstyle='threeml.mplstyle', residual_plot=ResidualPlot(linewidth=1, marker='.', size=3, legend_font_size=6.94))
- plugins: Plugins = Plugins(ogip=OGIP(fit_plot=BinnedSpectrumPlot(data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, n_colors=5, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, show_background=False, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None), data_plot=DataHistPlot(counts_color='#500472', background_color='#79cbb8', warn_channels_color='#C79BFE', bad_channels_color='#FE3131', masked_channels_color='#566573'), response_cmap=<MPLCmap.viridis: 'viridis'>, response_zero_color='k'), photo=Photo(fit_plot=BinnedSpectrumPlot(data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, n_colors=5, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, show_background=False, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None)), fermipy=Fermipy(fit_plot=FermiSpectrumPlot(total_model_color='k', show_background_sources=True, shade_fixed_sources=True, shade_secondary_sources=False, fixed_sources_color='grey', secondary_sources_color='k', data_cmap=<MPLCmap.Set1: 'Set1'>, model_cmap=<MPLCmap.Set1: 'Set1'>, background_cmap=<MPLCmap.Set1: 'Set1'>, step=False, show_legend=True, show_residuals=True, data_color=None, model_color=None, background_color=None, data_mpl_kwargs=None, model_mpl_kwargs=None, background_mpl_kwargs=None)))
- point_source: PointSourceDefaults = PointSourceDefaults(integrate_flux_method=<IntegrateMethod.trapz: 0>, max_number_samples=5000)
- time_series: TimeSeries = TimeSeries(light_curve_color='#05716c', selection_color='#1fbfb8', background_color='#C0392B', background_selection_color='#E74C3C', fit=TimeSeriesFit(fit_poly=True, unbinned=False, bayes=False))
- class threeML.config.config_structure.Interface(progress_bars: bool = 'on', multi_progress_color: bool = 'on', multi_progress_cmap: str = 'viridis', progress_bar_color: str = '#9C04FF')[source]
Bases:
object- multi_progress_cmap: str = 'viridis'
- multi_progress_color: bool = 'on'
- progress_bar_color: str = '#9C04FF'
- progress_bars: bool = 'on'
- class threeML.config.config_structure.Logging(path: str = '~/.threeml/log', developer: bool = 'off', usr: bool = 'on', console: bool = 'on', level: threeML.config.config_structure.LoggingLevel = <LoggingLevel.INFO: 20>, startup_warnings: bool = 'on')[source]
Bases:
object- console: bool = 'on'
- developer: bool = 'off'
- level: LoggingLevel = 20
- path: str = '~/.threeml/log'
- startup_warnings: bool = 'on'
- usr: bool = 'on'