caf_ignoring_runs_sequential.py

 
 
import basf2 as b2
 
import os
import sys
 
from caf.framework import Calibration, CAF
from caf.utils import ExpRun, IoV
from caf.strategies import SequentialRunByRun
from caf.backends import Local
 
b2.set_log_level(b2.LogLevel.INFO)
 
 
def main(argv):
    if len(argv) == 1:
        data_dir = argv[0]
    else:
        print("Usage: python3 caf_ignoring_runs.py <data directory>")
        sys.exit(1)
 
    
    input_files_test = [os.path.join(os.path.abspath(data_dir), '*.root')]
 
    
 
    # Make a bunch of test calibrations
    col_test = b2.register_module('CaTest')
    # Specific parameter to our test collector, proportional to the probability of algorithm requesting iteration.
    col_test.param('spread', 15)
 
    from ROOT import Belle2  # noqa: make the Belle2 namespace available
    from ROOT.Belle2 import TestCalibrationAlgorithm
    alg_test = TestCalibrationAlgorithm()
    # We want to see what happens when c_NotEnoughData is returned
    alg_test.setMinEntries(10000)
 
    cal_test = Calibration(name='TestCalibration',
                           collector=col_test,
                           algorithms=alg_test,
                           input_files=input_files_test)
 
    # We don't want to run collector jobs on these runs (if possible) and we don't want the algorithm to use data from
    # these runs. However, the algorithm strategy may also merge IoVs across the gaps left by the ignored runs.
    # What the strategy does with missing runs depends on the AlgorithmStrategy and any configuration you have made.
    cal_test.ignored_runs = [ExpRun(0, 2), ExpRun(0, 3)]
 
    # We use a different algorithm strategy for every algorithm (only one) in this Calibration
    cal_test.strategies = SequentialRunByRun
 
    # This parameter is used by SequentialRunByRun to define a total IoV that the combination of all IoVs defines.
    # It must be strictly larger than the IoV of all input data, OR the IoV in cal_fw.run(iov=...) if defined.
    # This allows us to define a larger total IoV so that the first payload IoV MUST START at the ExpRun(exp_low, run_low)
    # and the final IoV MUST END at ExpRun(exp_high, run_high) e.g.
    #
    # Here we define iov_coverage = IoV(0, 1, 0, 15). This means that the first payload created will be of the form
    # IoV(0, 1, ?, ?) where we don't yet know what the highest (exp,run) will be as it depends on the data.
    # The last payload we create must have the form IoV(?, ?, 0, 15) but we can't yet know the lowest (exp,run)
    #
    # It is entirely possible that in the final database there will be only one payload of IoV(0, 1, 0, 15), or
    # several such as [IoV(0, 1, 0, 5), IoV(0, 6, 0, 10), IoV(0, 11, 0, 15)]
    cal_test.algorithms[0].params["iov_coverage"] = IoV(0, 1, 0, 15)
 
    # This parameter defines the step size of the SequentialRunByRun strategy i.e. how many runs of data we add
    # each time we execute.
    # So initially an execution of the algorithm will use this many runs-worth of data (if possible).
    # If c_NotEnoughData is returned on this execution, we will add the next 'step_size' number of runs and execute again.
    # Then repeat until we get c_Iterate or c_OK.
    #
    # The default value is 1.
    cal_test.algorithms[0].params["step_size"] = 1
 
    cal_test.max_files_per_collector_job = 1
 
    
    cal_fw = CAF()
 
    # You could alternatively set the same ignored_runs for every Calibration by setting it here.
    # Note that setting cal_test.ignored_runs will override the value set from here.
 
    # cal_fw = CAF(calibration_defaults={'ignored_runs':[ExpRun(0,2), ExpRun(0, 3)])
 
    cal_fw.add_calibration(cal_test)
    cal_fw.backend = Local(max_processes=4)
 
    # The iov value here allows you to set an IoV that all your input files/executed runs must overlap.
    # Any input files not overlapping this IoV will be ignored.
    # HOWEVER, if you have an input file containing multiple runs the file IoV may overlap this IoV. But it may still
    # contain runs outside of it.
    # In this case the CAF will still use the file in collector jobs, BUT any runs collected will not be used in the
    # algorithm step if they exist outside of this IoV.
    #
    # To explicitly prevent certain runs from within this IoV being used, you should use the ignored_runs
    # attribute of the Calibration. Or make sure that the input data files do not contain data from those runs at all.
    cal_fw.run(iov=IoV(0, 3, 0, 11))
    print("End of CAF processing.")
 
 
if __name__ == "__main__":
    main(sys.argv[1:])