trainTrackFilter.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
 
 
 
import os
import sys
import os.path
 
 
from tracking.path_utils import add_cdc_track_finding
from tracking.run.event_generation import ReadOrGenerateEventsRun
from trackfindingcdc.run.training import TrainingRunMixin
from tracking.adjustments import adjust_module
 
 
class TrackFilterTrainingRun(TrainingRunMixin, ReadOrGenerateEventsRun):
    """Run to record tracks encountered at the TrackRejecter and retrain its mva method"""
 
    
    n_events = 3000
    
    generator_module = "generic"
    
    bkg_files = os.path.join(os.environ["VO_BELLE2_SW_DIR"], "bkg")
 
    
    truth = "truth"
 
    @property
    def identifier(self):
        """Database identifier of the filter being trained"""
        return "trackfindingcdc_TrackFilter.xml"
 
    def create_path(self):
        """Setup the recording path after the simulation"""
        path = super().create_path()
 
        add_cdc_track_finding(path)
 
        
        if self.tasktask == "train":
            filterName = "recording"
 
        elif self.tasktask == "eval":
            filterName = "eval"
            
            self.truthtruthtruth = "truth_accepted"
 
        elif self.tasktask == "explore":
            # Change me.
            filterName = "recording"
 
        adjust_module(path, "TFCDC_SegmentTrackCombiner",
                      trackFilter=filterName,
                      trackFilterParameters={
                          "rootFileName": self.sample_file_name,
                      })
 
        return path
 
    def postprocess(self):
        """Post-process the results for MC-truth acceptance"""
        if self.tasktask == "eval":
            self.truthtruthtruth = "truth_accept"
        super().postprocess()
 
 
def main():
    run = TrackFilterTrainingRun()
    run.configure_and_execute_from_commandline()
 
 
if __name__ == "__main__":
    import logging
    logging.basicConfig(stream=sys.stdout, level=logging.INFO, format='%(levelname)s:%(message)s')
    main()