caf_algorithmdb_access.py

 
 
import basf2 as b2
 
import os
import sys
 
from caf.framework import Calibration, CAF
from caf import backends
 
 
def main(argv):
    if len(argv) == 1:
        data_dir = argv[0]
    else:
        print("Usage: python3 caf_multiple_options.py <data directory>")
        sys.exit(1)
 
    
    input_files = [os.path.join(os.path.abspath(data_dir), '*.root')]
 
    
    dep_col = b2.register_module('CaTest')
    dep_col.set_name('Dependent')   # Sets the prefix of the collected data in the datastore.
    # Allows us to execute algorithm over input data in a run-by-run way so we can see DB constants from each run.
    dep_col.param('granularity', 'run')
    # Specific parameter to our test collector, proportional to the probability of algorithm requesting iteration.
    dep_col.param('spread', 15)
 
    from ROOT import Belle2  # noqa: make the Belle2 namespace available
    from ROOT.Belle2 import TestDBAccessAlgorithm
    dep_alg = TestDBAccessAlgorithm()
    # Since we're using several instances of the same test algorithm here, we still want the database entries to have
    # different names. TestCalibrationAlgorithm outputs to the database using the prefix name so we change it
    # for each calibration. Not something you'd usually have to do. And you could instead use whatever name you want,
    # we just use the prefix as a handy string.
    dep_alg.setPrefix('Dependent')  # Must be the same as colllector prefix
 
    # Create our Calibration object
    dep_cal = Calibration(name='Dependent_Calibration',
                          collector=dep_col,
                          algorithms=dep_alg,
                          input_files=input_files)
 
    # Let's split up the collector jobs by files
    dep_cal.max_files_per_collector_job = 1
    dep_cal.max_iterations = 5
 
    # This one runs last and picks up the final DB constants from the first one
    last_col = b2.register_module('CaTest')
    last_col.set_name('Last')   # Sets the prefix of the collected data in the datastore.
    # Allows us to execute algorithm over input data in a run-by-run way so we can see DB constants from each run.
    last_col.param('granularity', 'run')
    # Specific parameter to our test collector, proportional to the probability of algorithm requesting iteration.
    last_col.param('spread', 15)
 
    last_alg = TestDBAccessAlgorithm()
    last_alg.setGeneratePayloads(False)
    last_alg.setPrefix('Last')  # Must be the same as colllector prefix
 
    # Create our Calibration object
    last_cal = Calibration(name='Last_Calibration',
                           collector=last_col,
                           algorithms=last_alg,
                           input_files=input_files)
 
    # Let's split up the collector jobs by files
    last_cal.max_files_per_collector_job = 1
    last_cal.max_iterations = 5
 
    # Define dependencies
    last_cal.depends_on(dep_cal)
 
    
    cal_fw = CAF()
    cal_fw.add_calibration(dep_cal)
    cal_fw.add_calibration(last_cal)
    # Subjobs from collector jobs being split over input files can be parallelized.
    # Also Calibrations 1 and 2, can be run at the same time.
    # If you have 4 cores this backend will run them whenever one of the 4 processes becomes available
    # For larger data or more calibrations, consider using the LSF or PBS batch system backends at your site
    cal_fw.backend = backends.Local(max_processes=4)
    # Start her up!
    cal_fw.run()
    print("End of CAF processing.")
 
 
if __name__ == "__main__":
    main(sys.argv[1:])