KLMAlignment Class Reference

Inheritance diagram for KLMAlignment:

Collaboration diagram for KLMAlignment:

Public Member Functions
def	__init__ (self, algorithm)
def	apply_experiment_settings (self, algorithm, experiment)

Public Attributes
	millepede_entries
	Number of Millepede entries.
	millepede_entries_exp7
	Number of Millepede entries for experiment 7.

Static Public Attributes
dictionary	usable_params
	The params that you could set on the Algorithm object which this Strategy would use. More...
list	allowed_granularities = ["run"]
	Granularity of collector that can be run by this algorithm properly.

Detailed Description

Custom stragery for KLM alignment. Based on SequentialRunByRun strategy,
but requires custom experiment-dependent settings.

Definition at line 17 of file klm_alignment.py.

Constructor & Destructor Documentation

__init__()

def __init__	(		self,
			algorithm
	)

Definition at line 35 of file klm_alignment.py.

    def __init__(self, algorithm):
        """
        """
        super().__init__(algorithm)
        
        self.millepede_entries = 0
        
        self.millepede_entries_exp7 = 0
 

Member Function Documentation

apply_experiment_settings()

def apply_experiment_settings	(		self,
			algorithm,
			experiment
	)

Apply experiment-dependent settings.

Definition at line 44 of file klm_alignment.py.

Member Data Documentation

usable_params

dictionary usable_params

static

Initial value:

=  {
        "has_experiment_settings": bool,  # Used in SequentialRunByRun.
        "iov_coverage": IoV,              # Used in SequentialRunByRun.
        "millepede_entries": int,
        "millepede_entries_exp7": int,
        "step_size": int                  # Used in SequentialRunByRun.
    }

The params that you could set on the Algorithm object which this Strategy would use.

Just here for documentation reasons.

Definition at line 24 of file klm_alignment.py.

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The documentation for this class was generated from the following file:

• klm/calibration/scripts/klm_alignment.py