DaVinci

Submodules

Package Contents

Classes

Options

A class that holds the user-specified DaVinci options.

Functions

make_config(options, user_algorithms, *[, public_tools])

make_config(options, user_algorithms, *, public_tools=None)[source]
class Options(/, **data: Any)[source]

Bases: GaudiConf.LbExec.Options

A class that holds the user-specified DaVinci options.

This class inherits from the default GaudiConf.LbExec.Options.

This class also configures several PyConf functions, see the list in the apply_binds method, where their keyword arguments are globally bound to the user-specified values. This way, users do not have to manually configure these functions themselves.

The optional parameters that need to be set are : - input_stream (str): Stream name, internally converted to lowercase. Default is “default”.

(Note: for input_process=Hlt2 the stream must be strictly empty. The default value is overwritten in this case.)

  • lumi (bool): Flag to store luminosity information. Default value is True and if Data the “lumiTree” is written by default. If MC the “lumiTree” is not written, EventAccounting is scheduled instead.

  • write_fsr (bool): Flag to write the file summary record. Requires also output_file != None. Default is False.

  • merge_genfsr (bool): Flag to merge the file summary record. Only applies to simulation. Default is False.

  • metainfo_additional_tags: (list): Additional central tags for PyConf.filecontent_metadata.metainfo_repos. Default is [].

_input_config is an ugly hack so that the configuration can be retrieved in config.py This is needed due to the way DaVinci configures itself, which is kind of not compatible with the PyConf spirit

input_stream: str | None = 'default'
lumi: bool = True
write_fsr: bool = False
merge_genfsr: bool = False
metainfo_additional_tags: list | None = []
_input_config: Any
_stream_default(values)[source]

This is a validator that sets the default “stream” value based on “input_process”

Parameters:

values (dict) – User-specified attributes of the Options object.

Returns:

Modified attributes of the Options object.

Return type:

dict

validate_input_output(values)[source]

Validator for the consistency of the input process and input/output file formats for Sprucing jobs.

Parameters:

values (dict) – User-specified attributes of the Options object.

Returns:

Modified attributes of the Options object.

Return type:

dict

validate_fsr_options(values)[source]

Validator for the consistency of writing FSRs and other settings.

Parameters:

values (dict) – User-specified attributes of the Options object.

Returns:

Modified attributes of the Options object.

Return type:

dict

apply_binds()[source]

This function configures the following PyConf functions, where their keyword arguments are globally bound to the user-specified values: - default_raw_event - reconstruction - tes_root - tes_root_for_tistos This way users do not have to manually configure these functions themselves.