caf_hotpixel_sequential.py

#!/usr/bin/env python3
 
 
 
# This steering file computes PXD hotpixel and deadpixel masks from root formatted raw data
# running the CAF
#
# Before running, you have to put a file to IoV mapping called 'file_iov_map.pkl' in your
# working directory. You can create such a map file by using the tool b2caf-filemap.
# See also the option --help.
#
# b2caf-filemap -m raw  -p "/hsm/belle2/bdata/Data/Raw/e0003/r*/**/*.root"
#
# This will try to compute hot pixel masks, dead pixel masks and occupancy maps for each run
# in the given IoV range.
#
# The results will be collected in a folder 'pxd_calibration_results_range_XY'. In order to complete the
# process, the check and uploads the outputdbs to a global tag (GT).
#
# b2conditionsdb upload Calibration_Offline_Development ./database.txt
#
# The option --help provides extensive help for the b2conditionsdb tool.
 
import argparse
from caf.strategies import SequentialRunByRun
from caf.utils import ExpRun, IoV
from caf import backends
from caf.framework import Calibration, CAF
from ROOT.Belle2 import PXDHotPixelMaskCalibrationAlgorithm
import pickle
import basf2 as b2
b2.set_log_level(b2.LogLevel.INFO)
 
 
parser = argparse.ArgumentParser(
    description="Compute hot pixel masks for PXD from rawhit occupancy")
parser.add_argument(
    '--runLow',
    default=0,
    type=int,
    help='Compute mask for specific IoV')
parser.add_argument('--runHigh', default=-1, type=int,
                    help='Compute mask for specific IoV')
parser.add_argument(
    '--expNo',
    default=3,
    type=int,
    help='Compute mask for specific IoV')
parser.add_argument('--maxSubRuns', default=20, type=int,
                    help='Maximum number of subruns to use')
args = parser.parse_args()
 
 
# Ignoring runs
pxd_ignore_run_list = [ExpRun(3, 484), ExpRun(3, 485), ExpRun(3, 486), ExpRun(3, 524)]
 
# Set the IoV range for this calibration
iov_to_calibrate = IoV(
    exp_low=args.expNo,
    run_low=args.runLow,
    exp_high=args.expNo,
    run_high=args.runHigh)
 
map_file_path = "file_iov_map.pkl"
with open(map_file_path, 'br') as map_file:
    files_to_iovs = pickle.load(map_file)
 
 
input_file_iov_set = set(files_to_iovs.values())
print(f'Number of distinct iovs {len(input_file_iov_set)}')
 
 
input_files = []
 
for file_iov in input_file_iov_set:
    if iov_to_calibrate.contains(file_iov):
        subruns = [k for k, v in files_to_iovs.items() if v == file_iov]
        input_files.extend(subruns[:args.maxSubRuns])
 
 
print(f'Number selected input files:  {len(input_files)}')
 
# Create and configure the collector and its pre collector path
hotpixelcollector = b2.register_module("PXDRawHotPixelMaskCollector")
hotpixelcollector.param("granularity", "run")
 
# The pre collector path must contain geometry and unpacker
gearbox = b2.register_module('Gearbox')
gearbox.param('fileName', 'geometry/Beast2_phase2.xml')
geometry = b2.register_module('Geometry')
geometry.param('components', ['PXD'])
pre_collector_path = b2.create_path()
pre_collector_path.add_module(gearbox)
pre_collector_path.add_module(geometry)
pre_collector_path.add_module('PXDUnpacker')
 
 
# Create and configure the calibration algorithm
# Getting a calibration algorithm instance
hotpixelkiller = PXDHotPixelMaskCalibrationAlgorithm()
# We can play around with hotpixelkiller parameters
# Continue masking even when few/no events were collected
hotpixelkiller.forceContinueMasking = False
# Minimum number of collected events for masking
hotpixelkiller.minEvents = 30000
# Only consider dead pixel masking when median number of hits per pixel is
# higher
hotpixelkiller.minHits = 15
# Occupancy threshold is median occupancy x multiplier
hotpixelkiller.pixelMultiplier = 7
# Set True to allow masking of hot drain lines
hotpixelkiller.maskDrains = True
# Occupancy threshold is median occupancy x multiplier
hotpixelkiller.drainMultiplier = 7
# Set True to allow masking of hot rows
hotpixelkiller.maskRows = True
# Occupancy threshold is median occupancy x multiplier
hotpixelkiller.rowMultiplier = 7
# We want to use a specific collector collecting from raw hits
hotpixelkiller.setPrefix("PXDRawHotPixelMaskCollector")
 
# Create a calibration
cal = Calibration(
    name="PXDHotPixelMaskCalibrationAlgorithm",
    collector=hotpixelcollector,
    algorithms=hotpixelkiller,
    input_files=input_files)
cal.pre_collector_path = pre_collector_path
 
# Apply the map to this calibration, now the CAF doesn't have to do it
cal.files_to_iovs = files_to_iovs
 
# The SequentialRunByRun strategy executes your algorithm over runs
# individually to give you payloads for each one (if successful)
cal.strategies = SequentialRunByRun
 
cal.ignored_runs = pxd_ignore_run_list
cal.algorithms[0].params["iov_coverage"] = iov_to_calibrate
 
cal.max_files_per_collector_job = 1
 
# Create a CAF instance and add the calibration to it.
cal_fw = CAF()
cal_fw.add_calibration(cal)
# cal_fw.backend = backends.LSF()
cal_fw.backend = backends.Local(max_processes=20)
# Time between polling checks to the CAF to see if a step (algorithm,
# collector jobs) is complete
cal_fw.heartbeat = 30
# Can change where your calibration runs
cal_fw.output_dir = f'calibration_results_range_{args.runLow}_{args.runHigh}'
cal_fw.run(iov=iov_to_calibrate)
# Should have created a directory called 'calibration_results'