Analysis#

class gammapy.analysis.Analysis(config)[source]#

Bases: object

Config-driven high level analysis interface.

It is initialized by default with a set of configuration parameters and values declared in an internal high level interface model, though the user can also provide configuration parameters passed as a nested dictionary at the moment of instantiation. In that case these parameters will overwrite the default values of those present in the configuration file.

Parameters:

configdict or AnalysisConfig: Configuration options following AnalysisConfig schema.

Attributes Summary

`config`	Analysis configuration as an `AnalysisConfig` object.
`models`

Methods Summary

`get_datasets`()	Produce reduced datasets.
`get_excess_map`()	Calculate excess map with respect to the current model.
`get_flux_points`()	Calculate flux points for a specific model component.
`get_light_curve`()	Calculate light curve for a specific model component.
`get_observations`()	Fetch observations from the data store according to criteria defined in the configuration.
`read_datasets`()	Read datasets from YAML file.
`read_models`(path[, extend])	Read models from YAML file.
`run_fit`()	Fitting reduced datasets to model.
`set_models`(models[, extend])	Set models on datasets.
`update_config`(config)	Update the configuration.
`write_datasets`([overwrite, write_covariance])	Write datasets to YAML file.
`write_models`([overwrite, write_covariance])	Write models to YAML file.

Attributes Documentation

config#: Analysis configuration as an AnalysisConfig object.

models#

Methods Documentation

get_datasets()[source]#

Produce reduced datasets.

Notes

The progress bar can be displayed for this function.

get_excess_map()[source]#: Calculate excess map with respect to the current model.

get_flux_points()[source]#: Calculate flux points for a specific model component.

get_light_curve()[source]#: Calculate light curve for a specific model component.

get_observations()[source]#: Fetch observations from the data store according to criteria defined in the configuration.

read_datasets()[source]#

Read datasets from YAML file.

File names are taken from the configuration file.

read_models(path, extend=True)[source]#

Read models from YAML file.

Parameters:

pathstr: Path to the model file.
extendbool, optional: Extend the exiting models on the datasets or replace them. Default is True.

run_fit()[source]#: Fitting reduced datasets to model.

set_models(models, extend=True)[source]#

Set models on datasets.

Adds FoVBackgroundModel if not present already

Parameters:

modelsModels or str: Models object or YAML models string.
extendbool, optional: Extend the exiting models on the datasets or replace them. Default is True.

update_config(config)[source]#: Update the configuration.

write_datasets(overwrite=True, write_covariance=True)[source]#

Write datasets to YAML file.

File names are taken from the configuration file.

Parameters:

overwritebool, optional: Overwrite existing file. Default is True.
write_covariancebool, optional: Save covariance or not. Default is True.

write_models(overwrite=True, write_covariance=True)[source]#

Write models to YAML file.

File name is taken from the configuration file.